NVIDIA's market position in China could see a significant boost following the Trump-Xi meeting, as President Trump hints at discussing 'Blackwell' AI chips for Beijing. NVIDIA's Blackwell AI Chip Will Be a Topic of Discussion Under Trump-Xi Meeting, With a Potential Breakthrough in Sight The Chinese market has been a significant challenge for Jensen Huang since the US-China trade hostilities, and now, it seems like there might be a sigh of relief on the horizon for NVIDIA. According to a report by Bloomberg, President Trump has suggested discussing NVIDIA's Blackwell AI chip with the Chinese counterpart, indicating that chips could […]
Read full article at https://wccftech.com/nvidia-could-receive-approval-for-blackwell-ai-chip-in-china/
The DM's Ark is seamlessly integrated with Discord, it transcribes your sessions, organizes notes, sends detailed recaps, and serves as a living archive of your world. But that’s only the beginning.
YouTube's also changing the name of the 'copyright' tab in YouTube Studio.
Amazon will lay off 2,303 corporate employees in Washington state, primarily in its Seattle and Bellevue offices, according to a filing with the state Employment Security Department that provides the first geographic breakdown of the company’s 14,000 global job cuts.
A detailed list included with the state filing shows a wide array of impacted roles, including software engineers, program managers, product managers, and designers, as well as a significant number of recruiters and human resources staff.
Senior and principal-level roles are among those being cut, aligning with a company-wide push to use the cutbacks to help reduce bureaucracy and operate more efficiently.
Amazon announced the cuts Tuesday morning, part of a larger push by CEO Andy Jassy to streamline the company. Jassy had previously told Amazon employees in June that efficiency gains from AI would likely lead to a smaller corporate workforce over time.
In a memo from HR chief Beth Galetti, the company signaled that further cutbacks will continue into 2026. Reuters reported Monday that the number of layoffs could ultimately total as many as 30,000 people, which is still possible as the layoffs continue into next year.
The post Lilly Blackwell Drug Discovery: A New Era appeared first on StartupHub.ai.
Lilly's new AI factory, powered by NVIDIA Blackwell GPUs, marks a pivotal shift in drug discovery, promising unprecedented speed and scale in pharmaceutical innovation.
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The post NVIDIA AI-RAN: Open Source Rewrites Wireless Innovation appeared first on StartupHub.ai.
NVIDIA's open-sourcing of Aerial software, coupled with DGX Spark, is democratizing AI-native 5G and 6G development, accelerating wireless innovation at an unprecedented pace.
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The post Celestica CEO Mionis: AI is a Must-Have Utility, Not a Bubble appeared first on StartupHub.ai.
“AI right now used to be a nice-to-have. It’s a utility, it’s a must-have.” This declarative statement from Celestica President and CEO Rob Mionis on CNBC’s Mad Money with Jim Cramer cuts directly to the core of the current technological zeitgeist. It frames artificial intelligence not as a speculative fad or a nascent technology still […]
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The era of complex, code-heavy AI development is rapidly giving way to an intuitive, natural language-driven approach, dramatically democratizing creation. At the forefront of this shift is Google AI Studio, a platform designed to accelerate the journey from concept to fully functional AI application in minutes. This new “vibe coding” experience, showcased by Logan Kilpatrick, […]
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NVIDIA and General Atomics have launched an AI-enabled digital twin for fusion reactors, dramatically accelerating the path to commercial AI fusion energy.
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CyberRidge launched with $26 million to develop its optical security system that protects data in fiber-optic networks from eavesdropping.
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MSI GeForce RTX 5050 Shadow 2X 8GB: $249 The GeForce RTX 5050 is the most-affordable graphics card based on NVIDIA's Blackwell architecture that targets mainstream gamers, and is the first RTX XX50 series GPU for the desktop in years. Blackwell Architecture Power Efficient Smaller Form Factor Cool And Quiet DLSS4 And RTX Neural Rendering Latest...
Apple is finally getting ready to introduce OLED displays in a wider range of its products. However, don't expect a broad-based debut soon, especially given the Cupertino giant's tendency to move at a glacial pace when introducing new technology. Apple is gearing up to introduce OLED displays in the future versions of the MacBook Air, iPad Air, and iPad mini, with water resistance added for good measure Bloomberg's legendary tipster, Mark Gurman, is out with another scoop today, focusing on a much-anticipated display overhaul for the MacBook Air, iPad Air, and iPad mini, all of which are now slated to […]
Read full article at https://wccftech.com/apple-is-testing-oled-displays-for-the-macbook-air-ipad-air-and-ipad-mini-with-water-resistance-also-in-the-offing/
In an industry where model size is often seen as a proxy for intelligence, IBM is charting a different course — one that values efficiency over enormity, and accessibility over abstraction.
The 114-year-old tech giant's four new Granite 4.0 Nano models, released today, range from just 350 million to 1.5 billion parameters, a fraction of the size of their server-bound cousins from the likes of OpenAI, Anthropic, and Google.
These models are designed to be highly accessible: the 350M variants can run comfortably on a modern laptop CPU with 8–16GB of RAM, while the 1.5B models typically require a GPU with at least 6–8GB of VRAM for smooth performance — or sufficient system RAM and swap for CPU-only inference. This makes them well-suited for developers building applications on consumer hardware or at the edge, without relying on cloud compute.
In fact, the smallest ones can even run locally on your own web browser, as Joshua Lochner aka Xenova, creator of Transformer.js and a machine learning engineer at Hugging Face, wrote on the social network X.
All the Granite 4.0 Nano models are released under the Apache 2.0 license — perfect for use by researchers and enterprise or indie developers, even for commercial usage.
They are natively compatible with llama.cpp, vLLM, and MLX and are certified under ISO 42001 for responsible AI development — a standard IBM helped pioneer.
But in this case, small doesn't mean less capable — it might just mean smarter design.
These compact models are built not for data centers, but for edge devices, laptops, and local inference, where compute is scarce and latency matters.
And despite their small size, the Nano models are showing benchmark results that rival or even exceed the performance of larger models in the same category.
The release is a signal that a new AI frontier is rapidly forming — one not dominated by sheer scale, but by strategic scaling.
The Granite 4.0 Nano family includes four open-source models now available on Hugging Face:
Granite-4.0-H-1B (~1.5B parameters) – Hybrid-SSM architecture
Granite-4.0-H-350M (~350M parameters) – Hybrid-SSM architecture
Granite-4.0-1B – Transformer-based variant, parameter count closer to 2B
Granite-4.0-350M – Transformer-based variant
The H-series models — Granite-4.0-H-1B and H-350M — use a hybrid state space architecture (SSM) that combines efficiency with strong performance, ideal for low-latency edge environments.
Meanwhile, the standard transformer variants — Granite-4.0-1B and 350M — offer broader compatibility with tools like llama.cpp, designed for use cases where hybrid architecture isn’t yet supported.
In practice, the transformer 1B model is closer to 2B parameters, but aligns performance-wise with its hybrid sibling, offering developers flexibility based on their runtime constraints.
“The hybrid variant is a true 1B model. However, the non-hybrid variant is closer to 2B, but we opted to keep the naming aligned to the hybrid variant to make the connection easily visible,” explained Emma, Product Marketing lead for Granite, during a Reddit "Ask Me Anything" (AMA) session on r/LocalLLaMA.
IBM is entering a crowded and rapidly evolving market of small language models (SLMs), competing with offerings like Qwen3, Google's Gemma, LiquidAI’s LFM2, and even Mistral’s dense models in the sub-2B parameter space.
While OpenAI and Anthropic focus on models that require clusters of GPUs and sophisticated inference optimization, IBM’s Nano family is aimed squarely at developers who want to run performant LLMs on local or constrained hardware.
In benchmark testing, IBM’s new models consistently top the charts in their class. According to data shared on X by David Cox, VP of AI Models at IBM Research:
On IFEval (instruction following), Granite-4.0-H-1B scored 78.5, outperforming Qwen3-1.7B (73.1) and other 1–2B models.
On BFCLv3 (function/tool calling), Granite-4.0-1B led with a score of 54.8, the highest in its size class.
On safety benchmarks (SALAD and AttaQ), the Granite models scored over 90%, surpassing similarly sized competitors.
Overall, the Granite-4.0-1B achieved a leading average benchmark score of 68.3% across general knowledge, math, code, and safety domains.
This performance is especially significant given the hardware constraints these models are designed for.
They require less memory, run faster on CPUs or mobile devices, and don’t need cloud infrastructure or GPU acceleration to deliver usable results.
In the early wave of LLMs, bigger meant better — more parameters translated to better generalization, deeper reasoning, and richer output.
But as transformer research matured, it became clear that architecture, training quality, and task-specific tuning could allow smaller models to punch well above their weight class.
IBM is banking on this evolution. By releasing open, small models that are competitive in real-world tasks, the company is offering an alternative to the monolithic AI APIs that dominate today’s application stack.
In fact, the Nano models address three increasingly important needs:
Deployment flexibility — they run anywhere, from mobile to microservers.
Inference privacy — users can keep data local with no need to call out to cloud APIs.
Openness and auditability — source code and model weights are publicly available under an open license.
IBM’s Granite team didn’t just launch the models and walk away — they took to Reddit’s open source community r/LocalLLaMA to engage directly with developers.
In an AMA-style thread, Emma (Product Marketing, Granite) answered technical questions, addressed concerns about naming conventions, and dropped hints about what’s next.
Notable confirmations from the thread:
A larger Granite 4.0 model is currently in training
Reasoning-focused models ("thinking counterparts") are in the pipeline
IBM will release fine-tuning recipes and a full training paper soon
More tooling and platform compatibility is on the roadmap
Users responded enthusiastically to the models’ capabilities, especially in instruction-following and structured response tasks. One commenter summed it up:
“This is big if true for a 1B model — if quality is nice and it gives consistent outputs. Function-calling tasks, multilingual dialog, FIM completions… this could be a real workhorse.”
Another user remarked:
“The Granite Tiny is already my go-to for web search in LM Studio — better than some Qwen models. Tempted to give Nano a shot.”
IBM’s push into large language models began in earnest in late 2023 with the debut of the Granite foundation model family, starting with models like Granite.13b.instruct and Granite.13b.chat. Released for use within its Watsonx platform, these initial decoder-only models signaled IBM’s ambition to build enterprise-grade AI systems that prioritize transparency, efficiency, and performance. The company open-sourced select Granite code models under the Apache 2.0 license in mid-2024, laying the groundwork for broader adoption and developer experimentation.
The real inflection point came with Granite 3.0 in October 2024 — a fully open-source suite of general-purpose and domain-specialized models ranging from 1B to 8B parameters. These models emphasized efficiency over brute scale, offering capabilities like longer context windows, instruction tuning, and integrated guardrails. IBM positioned Granite 3.0 as a direct competitor to Meta’s Llama, Alibaba’s Qwen, and Google's Gemma — but with a uniquely enterprise-first lens. Later versions, including Granite 3.1 and Granite 3.2, introduced even more enterprise-friendly innovations: embedded hallucination detection, time-series forecasting, document vision models, and conditional reasoning toggles.
The Granite 4.0 family, launched in October 2025, represents IBM’s most technically ambitious release yet. It introduces a hybrid architecture that blends transformer and Mamba-2 layers — aiming to combine the contextual precision of attention mechanisms with the memory efficiency of state-space models. This design allows IBM to significantly reduce memory and latency costs for inference, making Granite models viable on smaller hardware while still outperforming peers in instruction-following and function-calling tasks. The launch also includes ISO 42001 certification, cryptographic model signing, and distribution across platforms like Hugging Face, Docker, LM Studio, Ollama, and watsonx.ai.
Across all iterations, IBM’s focus has been clear: build trustworthy, efficient, and legally unambiguous AI models for enterprise use cases. With a permissive Apache 2.0 license, public benchmarks, and an emphasis on governance, the Granite initiative not only responds to rising concerns over proprietary black-box models but also offers a Western-aligned open alternative to the rapid progress from teams like Alibaba’s Qwen. In doing so, Granite positions IBM as a leading voice in what may be the next phase of open-weight, production-ready AI.
In the end, IBM’s release of Granite 4.0 Nano models reflects a strategic shift in LLM development: from chasing parameter count records to optimizing usability, openness, and deployment reach.
By combining competitive performance, responsible development practices, and deep engagement with the open-source community, IBM is positioning Granite as not just a family of models — but a platform for building the next generation of lightweight, trustworthy AI systems.
For developers and researchers looking for performance without overhead, the Nano release offers a compelling signal: you don’t need 70 billion parameters to build something powerful — just the right ones.
Microsoft is launching a significant expansion of its Copilot AI assistant on Tuesday, introducing tools that let employees build applications, automate workflows, and create specialized AI agents using only conversational prompts — no coding required.
The new capabilities, called App Builder and Workflows, mark Microsoft's most aggressive attempt yet to merge artificial intelligence with software development, enabling the estimated 100 million Microsoft 365 users to create business tools as easily as they currently draft emails or build spreadsheets.
"We really believe that a main part of an AI-forward employee, not just developers, will be to create agents, workflows and apps," Charles Lamanna, Microsoft's president of business and industry Copilot, said in an interview with VentureBeat. "Part of the job will be to build and create these things."
The announcement comes as Microsoft deepens its commitment to AI-powered productivity tools while navigating a complex partnership with OpenAI, the creator of the underlying technology that powers Copilot. On the same day, OpenAI completed its restructuring into a for-profit entity, with Microsoft receiving a 27% ownership stake valued at approximately $135 billion.
The new features transform Copilot from a conversational assistant into what Microsoft envisions as a comprehensive development environment accessible to non-technical workers. Users can now describe an application they need — such as a project tracker with dashboards and task assignments — and Copilot will generate a working app complete with a database backend, user interface, and security controls.
"If you're right inside of Copilot, you can now have a conversation to build an application complete with a backing database and a security model," Lamanna explained. "You can make edit requests and update requests and change requests so you can tune the app to get exactly the experience you want before you share it with other users."
The App Builder stores data in Microsoft Lists, the company's lightweight database system, and allows users to share finished applications via a simple link—similar to sharing a document. The Workflows agent, meanwhile, automates routine tasks across Microsoft's ecosystem of products, including Outlook, Teams, SharePoint, and Planner, by converting natural language descriptions into automated processes.
A third component, a simplified version of Microsoft's Copilot Studio agent-building platform, lets users create specialized AI assistants tailored to specific tasks or knowledge domains, drawing from SharePoint documents, meeting transcripts, emails, and external systems.
All three capabilities are included in the existing $30-per-month Microsoft 365 Copilot subscription at no additional cost — a pricing decision Lamanna characterized as consistent with Microsoft's historical approach of bundling significant value into its productivity suite.
"That's what Microsoft always does. We try to do a huge amount of value at a low price," he said. "If you go look at Office, you think about Excel, Word, PowerPoint, Exchange, all that for like eight bucks a month. That's a pretty good deal."
The new tools represent the culmination of a nine-year effort by Microsoft to democratize software development through its Power Platform — a collection of low-code and no-code development tools that has grown to 56 million monthly active users, according to figures the company disclosed in recent earnings reports.
Lamanna, who has led the Power Platform initiative since its inception, said the integration into Copilot marks a fundamental shift in how these capabilities reach users. Rather than requiring workers to visit a separate website or learn a specialized interface, the development tools now exist within the same conversational window they already use for AI-assisted tasks.
"One of the big things that we're excited about is Copilot — that's a tool for literally every office worker," Lamanna said. "Every office worker, just like they research data, they analyze data, they reason over topics, they also will be creating apps, agents and workflows."
The integration offers significant technical advantages, he argued. Because Copilot already indexes a user's Microsoft 365 content — emails, documents, meetings, and organizational data — it can incorporate that context into the applications and workflows it builds. If a user asks for "an app for Project Spartan," Copilot can draw from existing communications to understand what that project entails and suggest relevant features.
"If you go to those other tools, they have no idea what the heck Project Spartan is," Lamanna said, referencing competing low-code platforms from companies like Google, Salesforce, and ServiceNow. "But if you do it inside of Copilot and inside of the App Builder, it's able to draw from all that information and context."
Microsoft claims the apps created through these tools are "full-stack applications" with proper databases secured through the same identity systems used across its enterprise products — distinguishing them from simpler front-end tools offered by competitors. The company also emphasized that its existing governance, security, and data loss prevention policies automatically apply to apps and workflows created through Copilot.
While Microsoft positions the new capabilities as accessible to all office workers, Lamanna was careful to delineate where professional developers remain essential. His dividing line centers on whether a system interacts with parties outside the organization.
"Anything that leaves the boundaries of your company warrants developer involvement," he said. "If you want to build an agent and put it on your website, you should have developers involved. Or if you want to build an automation which interfaces directly with your customers, or an app or a website which interfaces directly with your customers, you want professionals involved."
The reasoning is risk-based: external-facing systems carry greater potential for data breaches, security vulnerabilities, or business errors. "You don't want people getting refunds they shouldn't," Lamanna noted.
For internal use cases — approval workflows, project tracking, team dashboards — Microsoft believes the new tools can handle the majority of needs without IT department involvement. But the company has built "no cliffs," in Lamanna's terminology, allowing users to migrate simple apps to more sophisticated platforms as needs grow.
Apps created in the conversational App Builder can be opened in Power Apps, Microsoft's full development environment, where they can be connected to Dataverse, the company's enterprise database, or extended with custom code. Similarly, simple workflows can graduate to the full Power Automate platform, and basic agents can be enhanced in the complete Copilot Studio.
"We have this mantra called no cliffs," Lamanna said. "If your app gets too complicated for the App Builder, you can always edit and open it in Power Apps. You can jump over to the richer experience, and if you're really sophisticated, you can even go from those experiences into Azure."
This architecture addresses a problem that has plagued previous generations of easy-to-use development tools: users who outgrow the simplified environment often must rebuild from scratch on professional platforms. "People really do not like easy-to-use development tools if I have to throw everything away and start over," Lamanna said.
The democratization of software development raises questions about governance, maintenance, and organizational complexity — issues Microsoft has worked to address through administrative controls.
IT administrators can view all applications, workflows, and agents created within their organization through a centralized inventory in the Microsoft 365 admin center. They can reassign ownership, disable access at the group level, or "promote" particularly useful employee-created apps to officially supported status.
"We have a bunch of customers who have this approach where it's like, let 1,000 apps bloom, and then the best ones, I go upgrade and make them IT-governed or central," Lamanna said.
The system also includes provisions for when employees leave. Apps and workflows remain accessible for 60 days, during which managers can claim ownership — similar to how OneDrive files are handled when someone departs.
Lamanna argued that most employee-created apps don't warrant significant IT oversight. "It's just not worth inspecting an app that John, Susie, and Bob use to do their job," he said. "It should concern itself with the app that ends up being used by 2,000 people, and that will pop up in that dashboard."
Still, the proliferation of employee-created applications could create challenges. Users have expressed frustration with Microsoft's increasing emphasis on AI features across its products, with some giving the Microsoft 365 mobile app one-star ratings after a recent update prioritized Copilot over traditional file access.
The tools also arrive as enterprises grapple with "shadow IT" — unsanctioned software and systems that employees adopt without official approval. While Microsoft's governance controls aim to provide visibility, the ease of creating new applications could accelerate the pace at which these systems multiply.
Microsoft's ambitions for the technology extend far beyond incremental productivity gains. Lamanna envisions a fundamental transformation of what it means to be an office worker — one where building software becomes as routine as creating spreadsheets.
"Just like how 20 years ago you put on your resume that you could use pivot tables in Excel, people are going to start saying that they can use App Builder and workflow agents, even if they're just in the finance department or the sales department," he said.
The numbers he's targeting are staggering. With 56 million people already using Power Platform, Lamanna believes the integration into Copilot could eventually reach 500 million builders. "Early days still, but I think it's certainly encouraging," he said.
The features are currently available only to customers in Microsoft's Frontier Program — an early access initiative for Microsoft 365 Copilot subscribers. The company has not disclosed how many organizations participate in the program or when the tools will reach general availability.
The announcement fits within Microsoft's larger strategy of embedding AI capabilities throughout its product portfolio, driven by its partnership with OpenAI. Under the restructured agreement announced Tuesday, Microsoft will have access to OpenAI's technology through 2032, including models that achieve artificial general intelligence (AGI) — though such systems do not yet exist. Microsoft has also begun integrating Copilot into its new companion apps for Windows 11, which provide quick access to contacts, files, and calendar information.
The aggressive integration of AI features across Microsoft's ecosystem has drawn mixed reactions. While enterprise customers have shown interest in productivity gains, the rapid pace of change and ubiquity of AI prompts have frustrated some users who prefer traditional workflows.
For Microsoft, however, the calculation is clear: if even a fraction of its user base begins creating applications and automations, it would represent a massive expansion of the effective software development workforce — and further entrench customers in Microsoft's ecosystem. The company is betting that the same natural language interface that made ChatGPT accessible to millions can finally unlock the decades-old promise of empowering everyday workers to build their own tools.
The App Builder and Workflows agents are available starting today through the Microsoft 365 Copilot Agent Store for Frontier Program participants.
Whether that future arrives depends not just on the technology's capabilities, but on a more fundamental question: Do millions of office workers actually want to become part-time software developers? Microsoft is about to find out if the answer is yes — or if some jobs are better left to the professionals.
Also, expanded revenue opportunities via creator subscriptions.
Google DeepMind researchers have developed BlockRank, a new method for ranking and retrieving information more efficiently in large language models (LLMs).
What BlockRank changes. ICR is expensive and slow. Models use a process called “attention,” where every word compares itself to every other word. Ranking hundreds of documents at once gets exponentially harder for LLMs.
How BlockRank works. BlockRank restructures how an LLM “pays attention” to text. Instead of every document attending to every other document, each one focuses only on itself and the shared instructions.
By the numbers. In experiments using Mistral-7B, Google’s team found that BlockRank:
Why we care. BlockRank could change how future AI-driven retrieval and ranking systems work to reward user intent, clarity, and relevance. That means (in theory) clear, focused content that aligns with why a person is searching (not just what they type) should increasingly win.
What’s next. Google/DeepMind researchers are continuing to redefine what it means to “rank” information in the age of generative AI. The future of search is advancing fast – and it’s fascinating to watch it evolve in real time.
An IAB report finds AI speeds discovery but adds steps, sending shoppers to retailers, search, reviews, and forums to verify details before buying.
The post Trust In AI Shopping Is Limited As Shoppers Verify On Websites appeared first on Search Engine Journal.
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NVIDIA's DGX GB300 system is empowering the Naval Postgraduate School with advanced NVIDIA Navy AI training, enabling secure, on-premises generative AI and high-fidelity digital twin simulations for critical defense applications.
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NVIDIA's GTC Washington, D.C., keynote unveiled a strategic blueprint for America's AI future, emphasizing national infrastructure, physical AI, and industry transformation.
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NVIDIA is driving significant AI economic development across the US by partnering with states, cities, and universities to democratize AI access and foster innovation.
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Microsoft’s staggering ten-fold return on its OpenAI investment, now valued at $135 billion, signals a new era where strategic AI stakes redefine corporate power and valuation. This monumental gain, highlighted by CNBC’s MacKenzie Sigalos, follows a significant corporate restructure at OpenAI that redefines its partnership terms with Microsoft, granting the tech giant a 27% equity […]
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The post Desktop Commander raises €1.1M to advance AI desktop automation appeared first on StartupHub.ai.
Desktop Commander raised €1.1 million to develop its AI tool that allows non-technical users to automate computer tasks using natural language.
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The post Grasp raises $7M to advance its multi-agent AI for finance appeared first on StartupHub.ai.
AI startup Grasp raised $7 million to expand its multi-agent platform that automates complex financial analysis and reporting for consultants and investment banks.
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The post SalesPatriot raises $5M to advance AI defence procurement appeared first on StartupHub.ai.
SalesPatriot is developing AI-driven procurement software to help defence and aerospace suppliers automate orders and increase processing speeds.
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Micro-mobility company Dott extended its funding to over $150 million to expand its e-bike fleet and enter new European markets.
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Nvidia is investing $1 billion in Nokia to accelerate the development of AI-powered 5G and 6G telecommunications networks.
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The post Socratix AI raises $4.1M to build autonomous AI coworkers appeared first on StartupHub.ai.
Socratix AI raised $4.1M to build autonomous AI coworkers that automate investigations for fraud and risk teams at financial institutions.
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The post NVIDIA AI Physics Simulation Reshapes Engineering appeared first on StartupHub.ai.
NVIDIA AI physics simulation, powered by the PhysicsNeMo framework, is accelerating engineering design by up to 500x in aerospace and automotive.
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The post Energy as the New Geopolitical Currency in the AI Race appeared first on StartupHub.ai.
“Knowledge used to be power, now power is knowledge.” This stark redefinition, articulated by U.S. Secretary of the Interior Doug Burgum during a CNBC “Power Lunch” interview, cuts to the core of the contemporary global power struggle. Speaking with Brian Sullivan, Burgum outlined a comprehensive strategy for the United States to secure its position in […]
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The post CoreStory raises $32M to advance AI legacy code modernization appeared first on StartupHub.ai.
AI startup CoreStory raised $32 million to help enterprises modernize legacy software with its platform that automatically documents and analyzes old code.
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Windows Server 2025 is currently open to a Remote Code Execution exploit via the Windows Update Service, and at the time of this writing a fix from Microsoft has yet to fully patch the issue. Reports to The Register indicate that Microsoft's attempt to patch the exploit earlier this month didn't stop any active exploitation, contrary to Microsoft's
Reaction to a huge round of layoffs rippled across Amazon and beyond on Tuesday as the Seattle-based tech giant confirmed that it was slashing 14,000 corporate and tech jobs.
We’ve rounded up some of what’s being said online and/or shared with GeekWire:
A megathread on Reddit served as a collection of comments by impacted employees who posted about their level, location, org and years of service at Amazon.
Workers across ads, recruitment, robotics, retail, Prime Video, Amazon Games, business development, North American Stores, finance, devices and services, Amazon Autos, and more used the thread to vent.
Kristi Coulter, author of Exit Interview: The Life and Death of My Ambitious Career, a memoir about what she learned in her 12 years at Amazon, weighed in about the timing of apparent text messages that were sent to impacted employees.
“Wait, I’m sorry: Amazon made people relocate, switch their kids’ schools, and bookend their days with traffic for RTO only to lay them off via a 3 a.m. text? What happened to the vibe and conversations that only being together at the office could allow?” Coulter wrote on LinkedIn.
Some employees shared how they were quickly locked out of work laptops, expressing confusion about whether that was how they were supposed to learn about being terminated.
“I lost access to everything immediately :( ,” one Reddit user said.
Others discussed how they should have found time to transfer important work examples or positive interactions related to their performance over to personal computers.
“One thing I would recommend for everyone is to back up your personal files onto your personal laptop,” one user said on Reddit. “I used to keep all my accolades and praise in a quip file along with all my 2×2 write ups and MBR/QBR write ups cataloging my wins. When I found out I got laid off my head was spinning so I went outside for a walk, by the time I returned I was locked out of my laptop and no longer had access to anything.”
Is this Amazon’s way of saying 100% laid off?
— Aravind Naveen (@MydAravind) October 28, 2025
Any Amazon folks on the timeline – seen this before?#Amazon #layoffs #amazonlayoffs pic.twitter.com/1MCxoXjfHQ
Amazon human resources chief Beth Galetti pinned the layoffs in part on the need to reduce bureaucracy and become more efficient in the new era of artificial intelligence. Others looked for deeper meaning in the cuts.
In a post on LinkedIn, Yahoo! Finance Executive Editor Brian Rozzi said stock price is likely a key consideration when it comes to top execs and the Amazon board signing off on such mass layoffs.
Amazon’s stock was up about 1% on Tuesday to $229 per share.
“If the layoffs keep jacking up the stock price, maybe I can retire instead,” one longtime employee told GeekWire.
Entrepreneur and investor Jason Calacanis posted on X about how AI was coming for middle managers and those with “rote jobs” faster than anyone expected. He encouraged workers to become a founder and do a startup before it’s too late.
Mid-level managers in Amazon’s retail division were heavily impacted by Tuesday’s cuts, according to internal data obtained by Business Insider.
More than 78% of the roles eliminated were held by managers assigned L5 to L7 designations, BI reported. (L5 is typically the starting point for managers at Amazon, with more seniority assigned to higher levels.)
BI also said that U.S.-focused data showed that more than 80% of employees laid off Tuesday worked in Amazon’s retail business, spanning e-commerce, human resources, and logistics.
Bloomberg and others reported that significant cuts are also being felt by Amazon’s video games unit.
Steve Boom, VP of audio, Twitch, and games said in a memo shared with The Verge that “significant role reductions” would be felt at studios in Irvine and San Diego, Calif., as well on Amazon’s central publishing teams.
“We have made the difficult decision to halt a significant amount of our first-party AAA game development work — specifically around MMOs [massively multiplayer online games] — within Amazon Game Studios,” Boom wrote.
Current titles in Amazon’s MMO lineup include “New World: Aeternum,” “Throne and Liberty,” and “Lost Ark.” Amazon also previously announced that it would be developing a “Lord of the Rings” MMO.
Jon Scholes, president and CEO of the Downtown Seattle Association (DSA), has previously praised Amazon for its mandate calling for employees to return to the office five days per week, saying that the foot traffic from thousands of tech workers in the city is a necessary element to helping downtown Seattle rebound from the pandemic.
On Tuesday, Scholes reacted to Amazon’s layoffs in a statement to GeekWire:
“As downtown’s largest employer, a workforce change of this scale has ripple effects throughout the community — on individual employees and families and our small businesses that rely on the weekday foot traffic customer base. In addition, these jobs buttress our tax base that helps fund the city services we all depend on. Employers have options for where they locate jobs, and we want to ensure downtown Seattle is the most attractive place to invest and grow. We must provide vibrancy and a predictable regulatory environment in a competitive landscape because other cities would welcome the jobs currently based in downtown.”
AMD and Nvidia have forced RPCS3 to increase its recommended GPU requirements The team behind RPCS3, the PlayStation 3 emulator, has announced that it has increased its recommended GPU requirements for Windows. This is due to AMD and Nvidia’s decision to drop driver support for older Radeon and GeForce graphics cards. Now, the emulator’s recommended […]
The post RPCS3 GPU recommendations increase due to dropped driver support appeared first on OC3D.
Whatnot, a live shopping platform and marketplace, has closed a $225 million Series F round, more than doubling its valuation to $11.5 billion in less than 10 months.
DST Global and CapitalG co-led the financing, which brings the Los Angeles-based company’s total raised to about $968 million since its 2019 inception. Whatnot had raised $265 million in a Series E round at a nearly $5 billion valuation in January.
New investors Sequoia Capital and Alkeon Capital participated in the Series F, alongside returning backers Greycroft, Andreessen Horowitz, Avra and Bond. Other investors include Y Combinator, Lightspeed Venture Partners and Liquid 2 Ventures.
As part of the latest financing, Whatnot says it will initiate a tender offer where select current investors will buy up to $126 million worth of shares.
Funding to e-commerce startups globally so far this year totals $7.1 billion, per Crunchbase data. That compares to $11.3 billion raised by e-commerce startups globally in all of 2024. This year’s numbers are also down significantly from post-pandemic funding totals, which surged to $93 billion in 2021.
Live commerce is the combination of livestreaming and online shopping. Grant LaFontaine, co-founder and CEO of Whatnot, said in an announcement that his startup is “proving that live shopping is retail’s new normal.”
The company says more than $6 billion worth of items have been sold on its platform in 2025 so far, more than twice its total for all of 2024. Its app facilitates the buying and selling of collectibles like trading cards and toys through live video auctions. It also offers items such as clothing and sneakers. It competes with the likes of eBay, which currently does not offer a livestreaming option. It’s also a competitor to TikTok Shop.
“Whatnot brought the live shopping wave to the US, the UK, and Europe and has turned it into one of the fastest growing marketplaces of all time, Laela Sturdy, Whatnot board member and managing partner at CapitalG, Alphabet’s independent growth fund, said in a release.
The company plans to use its new funds to invest in its platform, roll out new features and “evolve” its policies. It is also accelerating its international expansion, adding to its current 900-person workforce by hiring across multiple departments.
Illustration: Dom Guzman
FurMark is a widely trusted GPU stress test built for enthusiasts, overclockers, and system tuners. It delivers a brutal, sustained load to expose thermal and stability limits, giving you a clear picture of your cooling performance and long-term reliability. Despite its intensity, it stays simple to run and produces repeatable, no-nonsense results.
Google appears to be playing it safe with its upcoming budget offering, the Pixel 10a. If the latest CAD renders are anything to go by, the tech giant is eschewing flashy design changes and opting for a predictable, if somewhat boring, overall design language. Almost nothing appears to have changed between the Pixel 9a and the upcoming Pixel 10a, as per the new CAD renders As per the CAD renders published by the X user OnLeaks on behalf of Android Headlines, the following can be easily concluded: As for the budget offering's rumored specs, the following is known at the […]
Read full article at https://wccftech.com/pixel-10a-cad-renders-show-a-pixel-9a-clone/
Developer and publisher DON'T NOD has published its latest financial release which goes over its half-year results for 2025, which includes a few notable updates from the studio, like how its most recent release, Lost Records: Bloom & Rage performed "below expectations," and that the studio signed a deal with Netflix to make a narrative game based on "a major IP." It's definitely a disappointing result for DON'T NOD, particularly considering the fact that its last major releases last year, Banishers: Ghosts of New Eden and Jusant, also fell below expectations. The studio's total operating revenue took a 5% dip […]
Read full article at https://wccftech.com/lost-records-bloom-and-rage-missed-expectations-dont-nod-signs-deal-with-netflix/
Apple revamped its iPhone 17 lineup this year by introducing ProMotion technology to the base model, making it one of the best decisions it could ever make for its flagship smartphone family. Best of all, it brings a host of other upgrades while retaining that $699 price point, which is probably why the iPhone 17 has garnered immense popularity worldwide, particularly in China. Part of why Apple has been able to keep this price unchanged from the iPhone 16 is by keeping the display costs low. According to the latest report, the OLED panel in the iPhone 17 costs around 42 […]
Read full article at https://wccftech.com/iphone-17-oled-panel-around-42-percent-to-make-than-pro-models/
In the ongoing high-stakes court battle between Oppo and Apple, the former has only a few hours left to complete a transfer of required documents and device forensic reports on an ex-Apple engineer who stands accused of stealing proprietary intellectual property (IP) at the behest of Oppo. Apple accuses Oppo of using its former employee, Chen Shi, to steal Apple Watch secrets Before going further, let's summarize what has happened in this high-stakes saga so far: Apple is asking the court for injunctive relief on four counts: For its part, Oppo maintains that it has conducted a comprehensive search of […]
Read full article at https://wccftech.com/oppo-has-just-a-few-hours-left-to-hand-over-to-apple-evidentiary-documents-on-a-former-engineer-who-stole-apple-watch-secrets/
In a market that is littered with countless options, Sony successfully stands out with its family of wireless headphones that offer comfort, impeccable audio, a boatload of features, and value, though the latter is subjective, especially if you are not on the hunt for the WH-1000XM6, which cost a jaw-dropping $458 on Amazon. Sure, the latter are the crème de la crème of wireless headphones, but if your primary objective is affordability, you will want to pick the WH-1000XM4, which are available at the same online retailer, but at a more affordable $198, or 43 percent off. Despite being two […]
Read full article at https://wccftech.com/sony-wh-1000xm4-wireless-headphones-cost-less-than-half-the-price-of-airpods-max-on-amazon/
A new report from GamesIndustry.Biz, based on data provided by Alinea Analytics, shows that in the lead-up to launch, Call of Duty: Black Ops 7 trails "far behind" the numbers that Battlefield 6 was able to pull. Setting the parameters here: this is based on data from Steam pre-order sales for Battlefield 6 and Call of Duty: Black Ops 7, 18 days ahead of their respective launches. Within that 18-day lead-up period, Battlefield 6 was able to sell close to a million copies in pre-orders. Black Ops 7 has only managed 200K pre-order copies sold. These numbers start to look […]
Read full article at https://wccftech.com/call-of-duty-black-ops-7-far-behind-battlefield-6-pre-order-sales/
After Team Group, now Corsair also claims to have reached 14,900 MB/s of read speeds on its latest PCIe 5.0 SSD. CORSAIR Launches MP700 PRO XT and Compact 2242 Form Factor MP700 MICRO PCIe 5.0 SSDs with Blazing Fast Read/Write Speeds One of the leading hardware and peripheral manufacturers, CORSAIR, has released its two new high-performance PCIe 5.0 SSDs for enthusiasts, offering the best-in-class performance for PC builders. The first SSD is the MP700 PRO XT, which is its flagship offering, delivering up to 14,900 MB/s of sequential Read speeds and up to 14,500 MB/s of sequential Write speeds. If […]
Read full article at https://wccftech.com/corsair-unveils-its-flagship-mp700-pro-xt-pcie-5-0-ssd-offering-up-to-14900-mb-s-of-read-speeds/
With each passing month, artificial intelligence creeps into more industries. That does not exclude the gaming industry, which has long used artificial intelligence to populate its virtual worlds. Still, the generative AI that is taking root everywhere offers much more power, and also much greater risk, compared to what gaming developers were used to. Big companies like Microsoft, Amazon, and EA are already laying off (or thinking about laying off) employees to invest further into artificial intelligence. What do the actual developers think about this artificial intelligence revolution? Their takes, as you would expect, are quite varied. The creator of […]
Read full article at https://wccftech.com/dayz-creator-says-ai-fears-remind-him-people-worrying-about-google-wikipedia-ai-is-here/
The latest AIO cooler from Thermaltake will work with Intel's upcoming LGA 1954 platform, as spotted on the official website. Thermaltake Lists LGA 1954 as a Compatible Socket for MINECUBE 360 Ultra ARGB Sync AIO Cooler, Confirming Support for Intel Nova Lake Popular cooler and PC case maker, Thermaltake, has officially listed the Intel LGA 1954 socket as a compatible platform for one of its latest AIO coolers. Thermaltake's MINECUBE 360 Ultra ARGB Sync, which was showcased at Computex this year, lists the LGA 1954 on its compatibility list, which confirms that the cooler won't just be compatible with the […]
Read full article at https://wccftech.com/thermaltake-confirms-one-of-its-existing-aio-coolers-will-be-compatible-with-lga-1954-socket/
Pathea Games, the studio known for games like My Time at Portia, My Time at Sandrock, and the upcoming My Time at Evershine has just shadow-dropped something you'd be more likely to expect from Velan Studios after its game Knockout City, or even Psyonix as a spin-off from Rocket League with Superball, a new free-to-play 3v3 arcade hero football game that's out now on PC and Xbox Series X/S. Announced during the ID@Xbox and IGN Showcase, Superball is described as a mash between Rocket League, something that's made extremely obvious with its giant ball and arena style, and Overwatch with […]
Read full article at https://wccftech.com/rocket-league-minus-cars-f2p-superball-pathea-games/
ClearWork helps companies transform their operations by first automatically discovering and mapping their actual, end-to-end processes. Unlike old-school methods that rely on manual workshops and guesswork, our AI analyzes real user activity to give a precise, objective view of current operations and pinpoint friction points.
From there, we use AI to help you model and plan an optimized future state that's grounded in your operational reality. Finally, we provide an AI co-pilot, powered by your own data, and orchestrate automated, cross-platform workflows to ensure new processes are not only planned but also executed and sustained across the organization.
Data security company Fortanix Inc. announced a new joint solution with NVIDIA: a turnkey platform that allows organizations to deploy agentic AI within their own data centers or sovereign environments, backed by NVIDIA’s "confidential computing" GPUs.
“Our goal is to make AI trustworthy by securing every layer—from the chip to the model to the data," said Fortanix CEO and co-founder Anand Kashyap, in a recent video call interview with VentureBeat. "Confidential computing gives you that end-to-end trust so you can confidently use AI with sensitive or regulated information.”
The solution arrives at a pivotal moment for industries such as healthcare, finance, and government — sectors eager to embrace AI but constrained by strict privacy and regulatory requirements.
Fortanix’s new platform, powered by NVIDIA Confidential Computing, enables enterprises to build and run AI systems on sensitive data without sacrificing security or control.
“Enterprises in finance, healthcare and government want to harness the power of AI, but compromising on trust, compliance, or control creates insurmountable risk,” said Anuj Jaiswal, chief product officer at Fortanix, in a press release. “We’re giving enterprises a sovereign, on-prem platform for AI agents—one that proves what’s running, protects what matters, and gets them to production faster.”
At the heart of the Fortanix–NVIDIA collaboration is a confidential AI pipeline that ensures data, models, and workflows remain protected throughout their lifecycle.
The system uses a combination of Fortanix Data Security Manager (DSM) and Fortanix Confidential Computing Manager (CCM), integrated directly into NVIDIA’s GPU architecture.
“You can think of DSM as the vault that holds your keys, and CCM as the gatekeeper that verifies who’s allowed to use them," Kashyap said. "DSM enforces policy, CCM enforces trust.”
DSM serves as a FIPS 140-2 Level 3 hardware security module that manages encryption keys and enforces strict access controls.
CCM, introduced alongside this announcement, verifies the trustworthiness of AI workloads and infrastructure using composite attestation—a process that validates both CPUs and GPUs before allowing access to sensitive data.
Only when a workload is verified by CCM does DSM release the cryptographic keys necessary to decrypt and process data.
“The Confidential Computing Manager checks that the workload, the CPU, and the GPU are running in a trusted state," explained Kashyap. "It issues a certificate that DSM validates before releasing the key. That ensures the right workload is running on the right hardware before any sensitive data is decrypted.”
This “attestation-gated” model creates what Fortanix describes as a provable chain of trust extending from the hardware chip to the application layer.
It’s an approach aimed squarely at industries where confidentiality and compliance are non-negotiable.
According to Kashyap, the partnership marks a step forward from traditional data encryption and key management toward securing entire AI workloads.
Kashyap explained that enterprises can deploy the Fortanix–NVIDIA solution incrementally, using a lift-and-shift model to migrate existing AI workloads into a confidential environment.
“We offer two form factors: SaaS with zero footprint, and self-managed. Self-managed can be a virtual appliance or a 1U physical FIPS 140-2 Level 3 appliance," he noted. "The smallest deployment is a three-node cluster, with larger clusters of 20–30 nodes or more.”
Customers already running AI models—whether open-source or proprietary—can move them onto NVIDIA’s Hopper or Blackwell GPU architectures with minimal reconfiguration.
For organizations building out new AI infrastructure, Fortanix’s Armet AI platform provides orchestration, observability, and built-in guardrails to speed up time to production.
“The result is that enterprises can move from pilot projects to trusted, production-ready AI in days rather than months,” Jaiswal said.
Compliance remains a key driver behind the new platform’s design. Fortanix’s DSM enforces role-based access control, detailed audit logging, and secure key custody—elements that help enterprises demonstrate compliance with stringent data protection regulations.
These controls are essential for regulated industries such as banking, healthcare, and government contracting.
The company emphasizes that the solution is built for both confidentiality and sovereignty.
For governments and enterprises that must retain local control over their AI environments, the system supports fully on-premises or air-gapped deployment options.
Fortanix and NVIDIA have jointly integrated these technologies into the NVIDIA AI Factory Reference Design for Government, a blueprint for building secure national or enterprise-level AI systems.
In addition to current encryption standards such as AES, Fortanix supports post-quantum cryptography (PQC) within its DSM product.
As global research in quantum computing accelerates, PQC algorithms are expected to become a critical component of secure computing frameworks.
“We don’t invent cryptography; we implement what’s proven,” Kashyap said. “But we also make sure our customers are ready for the post-quantum era when it arrives.”
While the platform is designed for on-premises and sovereign use cases, Kashyap emphasized that it can also run in major cloud environments that already support confidential computing.
Enterprises operating across multiple regions can maintain consistent key management and encryption controls, either through centralized key hosting or replicated key clusters.
This flexibility allows organizations to shift AI workloads between data centers or cloud regions—whether for performance optimization, redundancy, or regulatory reasons—without losing control over their sensitive information.
Fortanix converts usage into “credits,” which correspond to the number of AI instances running within a factory environment. The structure allows enterprises to scale incrementally as their AI projects grow.
Fortanix will showcase the joint platform at NVIDIA GTC, held October 27–29, 2025, at the Walter E. Washington Convention Center in Washington, D.C. Visitors can find Fortanix at booth I-7 for live demonstrations and discussions on securing AI workloads in highly regulated environments.
Fortanix Inc. was founded in 2016 in Mountain View, California, by Anand Kashyap and Ambuj Kumar, both former Intel engineers who worked on trusted execution and encryption technologies. The company was created to commercialize confidential computing—then an emerging concept—by extending the security of encrypted data beyond storage and transmission to data in active use, according to TechCrunch and the company’s own About page.
Kashyap, who previously served as a senior security architect at Intel and VMware, and Kumar, a former engineering lead at Intel, drew on years of work in trusted hardware and virtualization systems. Their shared insight into the gap between research-grade cryptography and enterprise adoption drove them to found Fortanix, according to Forbes and Crunchbase.
Today, Fortanix is recognized as a global leader in confidential computing and data security, offering solutions that protect data across its lifecycle—at rest, in transit, and in use.
Fortanix serves enterprises and governments worldwide with deployments ranging from cloud-native services to high-security, air-gapped systems.
"Historically we provided encryption and key-management capabilities," Kashyap said. "Now we’re going further to secure the workload itself—specifically AI—so an entire AI pipeline can run protected with confidential computing. That applies whether the AI runs in the cloud or in a sovereign environment handling sensitive or regulated data.
Learn more about the startups chosen for Google for Startups Accelerator: AI for Cybersecurity.
A collection of Google's latest security features and updates for Cybersecurity Awareness Month 2025.
The TransAmerica Trail is a legendary off-road route, stretching more than 5,900 miles and known for its rugged, remote beauty. And for the first time, you can now explo…
Another powerful creation option for your short-form video clips.
Given that Reddit and G2 are commonly cited by AI chatbots, this could be valuable.
The tool can create ad assets based on your URL.
Get ready to see a broader range of ads in your Threads feed.
Australia's under 16 social media restrictions will come into effect in December.
Microsoft and OpenAI signed a deal extending Microsoft's rights to OpenAI models through 2032, confirming a 27% stake worth $135B
The post Microsoft Locks In OpenAI Partnership Through 2032 appeared first on Search Engine Journal.
The post AccessGrid raises $4.4M to advance mobile access control appeared first on StartupHub.ai.
AccessGrid raised $4.4M to expand its mobile access control system that turns smartphones into secure digital keys for buildings.
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The post AI’s True Impact: Productivity, Not Layoffs, Driving CEO Agendas appeared first on StartupHub.ai.
Despite widespread anxieties about artificial intelligence decimating the workforce, Steve Odland, CEO of The Conference Board, offers a more nuanced, and perhaps more optimistic, perspective: AI is not primarily a job killer, but a catalyst for productivity. He contends that while AI will profoundly reshape the professional landscape, current large-scale layoffs stem more from broader […]
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The post Google Backs AI Cybersecurity Startups in Latin America appeared first on StartupHub.ai.
Google's new accelerator program is investing in 11 AI cybersecurity startups in Latin America, aiming to fortify the region's digital defenses.
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The post E-commerce consumption could bump 20% because of agentic AI, says Mizuho’s Dan Dolev appeared first on StartupHub.ai.
Dan Dolev, Mizuho’s managing director and senior analyst covering the fintech and payments space, spoke with the host of CNBC’s “The Exchange” following the announcement of a strategic partnership between PayPal and OpenAI. The discussion centered on the potential total addressable market for “agentic commerce” and the specific upside for PayPal in this burgeoning domain, […]
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The post Fireworks AI raises $250M to advance its AI inference platform appeared first on StartupHub.ai.
Fireworks AI secured $250 million to expand its platform that makes AI inference faster and more cost-effective for developers.
The post Fireworks AI raises $250M to advance its AI inference platform appeared first on StartupHub.ai.
The post Nano Banana’s Creative Revolution: Unpacking DeepMind’s Viral Image Model appeared first on StartupHub.ai.
Google DeepMind’s Nano Banana, the image model that recently captivated the internet, represents a pivotal moment in the democratization and evolution of digital creativity. Its creators, Principal Scientist Oliver Wang and Group Product Manager Nicole Brichtova, recently sat down with a16z partners Yoko Li and Guido Appenzeller to unravel the model’s origins, its unexpected viral […]
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The post Google Gemini for Home: The AI Assistant’s Next Evolution appeared first on StartupHub.ai.
Google Gemini for Home is rolling out in early access, upgrading smart assistants with advanced conversational AI and introducing a premium subscription for enhanced features.
The post Google Gemini for Home: The AI Assistant’s Next Evolution appeared first on StartupHub.ai.
The post Mem0 raises $24M to cure AI’s digital amnesia appeared first on StartupHub.ai.
Mem0 is tackling AI's "digital amnesia" with a universal memory layer, aiming to become the foundational database for the next generation of intelligent agents.
The post Mem0 raises $24M to cure AI’s digital amnesia appeared first on StartupHub.ai.
The post Amazon’s AI-Driven Efficiency Reshapes Big Tech Workforce appeared first on StartupHub.ai.
The transformative power of artificial intelligence, while heralding unprecedented innovation, is simultaneously catalyzing a profound restructuring of the tech workforce, a reality starkly illustrated by Amazon’s recent corporate layoffs. As CNBC’s MacKenzie Sigalos reported on “Money Movers,” Amazon is embarking on a multi-year efficiency drive, predominantly focused on “hollowing out layers of middle management.” This […]
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The post AI Reshapes M&A Landscape, Trillions in Value Up for Grabs appeared first on StartupHub.ai.
The convergence of advanced artificial intelligence and a uniquely poised global economy is setting the stage for an unprecedented era of mergers and acquisitions, fundamentally altering how companies operate and how value is created. This transformative period, characterized by both immense opportunity and inherent risks, was a central theme in Ken Moelis’s discussion with CNBC’s […]
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The post Pomelli AI: Google’s Play for SMB Marketing appeared first on StartupHub.ai.
Google Labs' new Pomelli AI aims to democratize on-brand social media campaign generation for SMBs by leveraging AI to understand and replicate brand identity.
The post Pomelli AI: Google’s Play for SMB Marketing appeared first on StartupHub.ai.
The post AI Valuations Spark Bubble Fears Amidst Broader Market Optimism appeared first on StartupHub.ai.
A stark warning echoes from the latest CNBC Fed Survey: nearly 80% of respondents believe AI stocks are currently overvalued, with a quarter deeming them “extremely overvalued.” This sentiment, highlighted by CNBC Senior Economics Reporter Steve Liesman on “Squawk on the Street,” paints a picture of growing apprehension within the investment community regarding the sustainability […]
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The post Building AI Unicorns: Lessons from Casetext’s $650M Exit appeared first on StartupHub.ai.
“I cannot believe that they are doing it this way.” This sentiment, articulated by Jake Heller, co-founder and CEO of Casetext, encapsulates the entrepreneurial spark that ignited his $650 million AI legal startup, CoCounsel, recently acquired by Thomson Reuters. His candid talk at the AI Startup School on June 17th, 2025, offered a masterclass in […]
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Classic gaming enthusiasts may have to wait until next year to get their mitts on the a modernized Amiga A1200, but in the meantime they can pick up THEC64 Mini Black Edition. It’s got everything fans of the Commodore 64 remember, but in a smaller package that includes modern inputs and a slate of new games.
THEC64 is half the size of the
Yet another dual-screen "DS" handheld has been born, though this time it's through user modification of the Steam Deck OLED rather than a dedicated clone like the Anbernic RG DS.
This particular Steam Deck DS modding project is the most recent of its kind, but not the only one—there have been plenty of these posted to the r/SteamDeck subreddit
We're racing toward the end of 2025, and while there's still over two months left to go, we're confident in saying that there probably won't be any more high-profile handheld hardware launches this year. We do expect to see some systems based on Intel's new Panther Lake processors next year, but for now, the two highest-profile handheld releases
Corsair extends its PCIe 5.0 offerings with its MP700 PRO XT and MP700 Micro Corsair has just added two new SSDs to its PCIe 5.0 storage lineup, promising high-end SSD performance and Microsoft DirectStorage support. Catering to the high-end market, Corsair’s new MP700 PRO XT SSD promises performance levels that reach the limits of the […]
The post Corsair delivers peak PCIe 5.0 speeds with its new MP700 PRO XT appeared first on OC3D.
NVIDIA has shown off its next-gen Vera Rubin Superchip for the first time at GTC in Washington, primed to spark the next wave of AI. NVIDIA Has Received Its First Rubin GPUs In The Labs, Ready For Vera Rubin Superchip Mass Production Next Year, Around The Same Time or Earlier At GTC October 2025, NVIDIA's CEO Jensen Huang showcased the next-gen Vera Rubin Superchip. This is the first time that we are seeing an actual sample of the motherboard, or Superchip as NVIDIA loves to call it, featuring the Vera CPU and two massive Rubin GPUs. The motherboard also hosts […]
Read full article at https://wccftech.com/nvidia-shows-next-gen-vera-rubin-superchip-two-massive-gpus-production-next-year/
NVIDIA has announced a surprise partnership with Nokia to bring 6G connectivity by utilizing the firm's new AI-RAN products, involving Grace CPUs and Blackwell GPUs. NVIDIA's Collaboration With Nokia Allows Merging CUDA & Computing Tech With Existing RAN Infrastructure Team Green has managed to integrate AI into everything mainstream, and it seems that the telecommunications industry is now expected to benefit from the next wave of AI's computing capabilities. At the GTC 2025 keynote, NVIDIA's CEO announced a pivotal partnership with Nokia, formally entering the race for achieving 6G connectivity through a new suite of AI-RAN products combined with Nokia's […]
Read full article at https://wccftech.com/nvidia-announces-a-massive-partnership-with-nokia-bringing-next-gen-6g-connectivity/
Amazon is laying off more than 14,000 corporate jobs today, and per a report from Bloomberg, the video games division, Amazon Game Studios, is not immune to the cuts. While Amazon doesn't specify exactly how many people from its video games division will be laid off, a statement from Steve Boom, Amazon's head of audio, Twitch, and games, does call the cut "significant," and says that the cuts are happening despite Amazon being "proud" of the success it has had. While the studio's MMO, New World, isn't mentioned by name, the statement does say that Amazon is halting its game […]
Read full article at https://wccftech.com/amazon-video-game-division-hit-significant-cuts-amid-mass-14000-layoff/
Qualcomm will keep pace with Apple and announce its first 2nm chipset in late 2026, the Snapdragon 8 Elite Gen 6, directly succeeding the Snapdragon 8 Elite Gen 5. A tipster now shares some partial specifications of the chipset, claiming that it will feature LPDDR6 RAM and UFS 5.0 storage, bringing in a wave of improvements. However, the rumor also mentions that the Snapdragon 8 Elite Gen 6 will utilize TSMC’s more advanced ‘N2P’ process, which has been refuted on a previous occasion. Based on TSMC’s 2nm production timeline, its N2 wafers will be available in higher volume for customers like […]
Read full article at https://wccftech.com/snapdragon-8-elite-gen-6-to-get-lpddr6-and-ufs-5-0-support-but-will-stick-with-tsmc-n2-process/
Zack Fair's gameplay in Final Fantasy VII Rebirth is set to be significantly expanded by a new mod introducing new mechanics and skill for an overhauled combat experience. This Zack gameplay overhaul mod is being developed by NSK, the modder behind the Zack and Sephiroth Combat Fix mod whichaddressed some issues for the two characters and expanded their possibilities when added to the regular combat party outside their small playable segments. Judging from the video showcase shared a few days ago on YouTube, the changes being made to Zack's gameplay are going to be significant, leveraging his unique Charge mechanics […]
Read full article at https://wccftech.com/final-fantasy-vii-rebirth-zack-gameplay-mod/
It's a big day for Battlefield 6, with both its Season 1 update now live for players to jump into, and its new free-to-play battle royale mode, Battlefield REDSEC, also now available. EA and Battlefield Studios confirmed yesterday what was already rumored, that REDSEC would be revealed and launched today, and now it's here for all players on PC, PS5, and Xbox Series X/S. Once the gameplay trailer that was teased yesterday was over, the mode and the new season was officially live for all players to jump into, and we got our first major question of the day answered. […]
Read full article at https://wccftech.com/battlefield-6-season-1-battlefield-redsec-out-now-pc-ps5-xbox-series-x-s/
The Pro 27Q-10 is probably the cheapest QHD OLED gaming monitor available on the market and is currently available for just 2,399 Yuan in China. Lenovo Debuts Legion Pro Series OLED Monitors, Starting at $337; Available in Both 2K and 4K Variants with Up To 280Hz Refresh Rate Competition in the OLED display category is getting aggressive, and while we already have some QHD OLED gaming monitors available for as low as $450-$500, Lenovo just brought the price to under $350. Lenovo is the most popular PC brand on earth, isn't just involved in desktops and laptops; it is also […]
Read full article at https://wccftech.com/lenovo-launches-legion-pro-27q-10-the-cheapest-qhd-oled-monitor-at-just-337/
President Trump is expected to meet with NVIDIA's CEO, Jensen Huang, during his visit to South Korea, where he will congratulate him on the firm's recent achievements. President Trump Will Congratulate NVIDIA On Producing The First Blackwell Chip Wafer In the US Well, the timing of a meeting between President Trump and Jensen Huang is indeed a 'massive' coincidence, to say the least, especially since both the US and China have agreed on a trade deal framework, which is expected to reduce hostilities between the two nations. While speaking with business leaders in Tokyo, Japan, President Trump announced his meeting […]
Read full article at https://wccftech.com/president-trump-to-meet-nvidia-ceo-jensen-huang/
OpenAI has been working for quite a while now with the famous Apple designer, Jony Ive, to come up with a consumer AI device, one that would supposedly render smartphones obsolete, devastating Apple's legendary moat around its iPhones in the process. Now, we have just received the clearest sign yet that OpenAI is indeed working on such a device. What's more, Microsoft will no longer exercise any influence over the upcoming "Apple iPhone killer." OpenAI and Microsoft have successfully renegotiated their tie-up, removing the latter's influence over the former's upcoming "Apple iPhone killer" consumer device, among other things Microsoft and […]
Read full article at https://wccftech.com/microsoft-will-no-longer-have-any-say-in-openais-upcoming-apple-iphone-killer-consumer-device-decisions/
Wrekcreation, the sandbox open-world arcade racing game from Three Fields Entertainment, a studio founded by former Criterion developers who worked on the Burnout series, is out now on PC, PS5, and Xbox Series X/S. Published by THQ Nordic, Wreckreation gives players the freedom to create whatever kinds of tracks they want, from the kinds of things you'd only expect to see in Hot Wheels Unleashed to something super realistic if that's more your speed, and race the wide variety of vehicles on them to your heart's content. With more than 400 square kilometres of space to create tracks in and […]
Read full article at https://wccftech.com/sandbox-racer-wreckreation-out-now-pc-ps5-xbox-series/
The advent of AI and Meta's launch of its smart glasses have injected fresh air into the sector after Google decided to shelve its smart glasses in 2023, the sector has seen increased interest. In fact, Meta CEO Mark Zuckerberg has gone as far as to suggest that courtesy of AI, users who do not use smart glasses can find themselves at a cognitive disadvantage. To understand the smart glasses industry and how the gadgets can impact consumer electronics manufacturing, semiconductor fabrication and AI GPU production, we decided to talk to Vuzix Corporation's President, Enterprise Solutions Dr. Chris Parkinson. Vuzix […]
Read full article at https://wccftech.com/smart-glasses-can-be-the-future-of-chip-manufacturing-and-smartphone-ai-gpu-production-says-vuzixs-enterprise-solutions-head/
TSMC's former SVP, known for his key role in driving the Taiwan giant's chip technologies, is reportedly being pursued to join Intel Foundry, which could be a significant hiring move for Team Blue. Intel's Pursuit of TSMC's Former Executive Shows the Firm's 'Hunger' Towards a Comeback in the Chip Industry Intel has been scaling up its chipmaking ambitions since the change in leadership, and under CEO Lip-Bu Tan, the foundry division has vowed to gain recognition in the semiconductor industry. Structural changes are being made within the department, including adjustments to the management hierarchy and the approach towards specific chip […]
Read full article at https://wccftech.com/intel-foundry-reportedly-pursuing-former-tsmc-executive/
Developer ArenaNet has launched the sixth major expansion for Guild Wars 2 today, with Visions of Eternity now available to players on PC. Visions of Eternity adds a new island to explore called Castora, with two new maps to explore, a new storyline, and plenty more. The new storyline kicks off with whispers and rumors of the island of Castora, with the Tyrian Alliance stepping in to uncover more about the magical island once they discover that the Inquest has begun sniffing around for Castora. Alongside two new maps included with the new expansion, Shipwreck Strand and Starlit Weald, players […]
Read full article at https://wccftech.com/guild-wars-2-visions-of-eternity-expansion-out-now-pc/
Tampo is a modern task and team management platform built for startups and growing teams. It helps you organize projects, assign tasks, and collaborate seamlessly—all in one place. With features like multi-user assignments, real-time tracking, and smart filters, Tampo simplifies team coordination without sacrificing power. Designed to be fast, intuitive, and mobile-friendly, Tampo is the productivity partner your team needs to get more done, together.
Less than two weeks ahead of the United Nations climate conference, Bill Gates posted a memo on his personal blog encouraging folks to just calm down about climate change.
“Although climate change will have serious consequences — particularly for people in the poorest countries — it will not lead to humanity’s demise. People will be able to live and thrive in most places on Earth for the foreseeable future,” Gates wrote.
The missive seems to run counter to earlier climate actions taken by the Microsoft co-founder and billionaire, but also echoes Gates’ long-held priorities and perspectives. In some regards, it’s the framing, timing and broader political context that heighten the memo’s impact.
What the world needs to do, he said, is to shift the goals away from reducing carbon emissions and keeping warming below agreed-upon temperature targets.
“This is a chance to refocus on the metric that should count even more than emissions and temperature change: improving lives,” he wrote. “Our chief goal should be to prevent suffering, particularly for those in the toughest conditions who live in the world’s poorest countries.“
More than four years ago, Gates published “How to Avoid a Climate Disaster,” a book highlighting the urgency and necessity of cutting carbon emissions and promoting the need to reduce “green premiums” in order to make climate friendly technologies as cheap as unsustainable alternatives.
“It’ll be tougher than anything humanity’s ever done, and only by staying constant in working on this over the next 30 years do we have a chance to do it,” Gates told GeekWire in 2021. “Having some people who think it’s easy will be an impediment. Having people who think that it’s not important will be an impediment.”
Gates’ clean energy efforts go back even earlier. In 2006 he helped launch the next-gen nuclear company TerraPower, which is currently building its first reactor in Wyoming. In 2015 he founded Breakthrough Energy Ventures, a $1 billion fund to support carbon-cutting startups, which evolved into Breakthrough Energy, an umbrella organization tackling clean tech policies, funding for researchers and data generation.
Earlier this year, however, Gates began taking steps that suggested a cooling commitment to the challenge.
Roughly two months after President Trump took office in January, and as clean energy policies and funding began getting axed, Breakthrough Energy laid off staff. In May Gates announced he would direct nearly all of his wealth to his eponymous global health foundation, deploying $200 billion through the organization over two decades.
At the same time, many of the key points in the memo published today reflect statements that Gates has made in the past.
In both his new post and at a 2022 global climate summit organized in Seattle by Breakthrough Energy, Gates urged people to focus on reducing green premiums more than on cutting emissions as a key benchmark.
“If you keep the primary measures, which is the emissions reductions in the near term, you’re going to be very depressed,” Gates said. At his summit talk, he shared optimism that new innovations were arriving quickly and would address climate challenges.
A curious paradox in Gates’ stance is the reality that people living in lower-income nations and in regions important to the Gates Foundation are often hardest hit by the rising temperatures and natural disasters that are stoked by increased carbon emissions.
Gates acknowledged that truth in his post this week, and said that solutions such as engineering drought tolerant crops and making air conditioning more widespread can address some of those harms. At the Seattle summit three years ago, one of the Breakthrough Energy executives likewise said the organization was going to increase its investment into technologies for adapting to climate change.
On Nov. 10, global climate leaders will meet in Brazil for COP30 to discuss climate progress and issues. Gates has often attended the event, but the New York Times reported that won’t be the case this year.
UN efforts meanwhile continue to emphasize the importance of reducing emissions. A statement today from the organization notes that while carbon emissions are curving downward, it’s not happening fast enough.
The world needs to raise its climate ambitions, the statement continues, “to avoid the worst climate impacts by limiting warming to 1.5°C this century, as science demands.”
GitHub is making a bold bet that enterprises don't need another proprietary coding agent: They need a way to manage all of them.
At its Universe 2025 conference, the Microsoft-owned developer platform announced Agent HQ. The new architecture transforms GitHub into a unified control plane for managing multiple AI coding agents from competitors including Anthropic, OpenAI, Google, Cognition and xAI. Rather than forcing developers into a single agent experience, the company is positioning itself as the essential orchestration layer beneath them all.
Agent HQ represents GitHub's attempt to apply its collaboration platform approach to AI agents. Just as the company transformed Git, pull requests and CI/CD into collaborative workflows, it's now trying to do the same with a fragmented AI coding landscape.
The announcement marks what GitHub calls the transition from "wave one" to "wave two" of AI-assisted development. According to GitHub's Octoverse report, 80% of new developers use Copilot in their first week and AI has helped to lead to a large increase overall in the use of the GitHub platform.
"Last year, the big announcements for us, and what we were saying as a company, is wave one is done, that was kind of code completion," GitHub's COO Mario Rodriguez told VentureBeat. "We're into this wave two era, [which] is going to be multimodal, it's going to be agentic and it's going to have these new experiences that will feel AI native."
GitHub already updated its GitHub Copilot coding tool for the agentic era with the debut of GitHub Copilot Agent in May.
Agent HQ transforms GitHub into an open ecosystem that unites multiple AI coding agents on a single platform. Over the coming months, coding agents from Anthropic, OpenAI, Google, Cognition, xAI and others will become available directly within GitHub as part of existing paid GitHub Copilot subscriptions.
The architecture maintains GitHub's core primitives. Developers still work with Git, pull requests and issues. They still use their preferred compute, whether GitHub Actions or self-hosted runners. What changes is the layer above: agents from multiple vendors can now operate within GitHub's security perimeter, using the same identity controls, branch permissions and audit logging that enterprises already trust for human developers.
This approach differs fundamentally from standalone tools. When developers use Cursor or grant repository access to Claude, those agents typically receive broad permissions across entire repositories. Agent HQ compartmentalizes access at the branch level and wraps all agent activity in enterprise-grade governance controls.
At the heart of Agent HQ is Mission Control. It's a unified command center that appears consistently across GitHub's web interface, VS Code, mobile apps and the command line. Through Mission Control, developers can assign work to multiple agents simultaneously. They can track progress and manage permissions, all from a single pane of glass.
The technical architecture addresses a critical enterprise concern: Security. Unlike standalone agent implementations where users must grant broad repository access, GitHub's Agent HQ implements granular controls at the platform level.
"Our coding agent has a set of security controls and capabilities that are built natively into the platform, and that's what we're providing to all of these other agents as well," Rodriguez explained. "It runs with a GitHub token that is very locked down to what it can actually do."
Agents operating through Agent HQ can only commit to designated branches. They run within sandboxed GitHub Actions environments with firewall protections. They operate under strict identity controls. Rodriguez explained that even if an agent goes rogue, the firewall prevents it from accessing external networks or exfiltrating data unless those protections are explicitly disabled.
Beyond managing third-party agents, GitHub is introducing two technical capabilities that set Agent HQ apart from alternative approaches like Cursor's standalone editor or Anthropic's Claude integration.
Custom agents via AGENTS.md files: Enterprises can now create source-controlled configuration files that define specific rules, tools and guardrails for how Copilot behaves. For example, a company could specify "prefer this logger" or "use table-driven tests for all handlers." This permanently encodes organizational standards without requiring developers to re-prompt every time.
"Custom agents have an immense amount of product market fit within enterprises, because they could just codify a set of skills that the coordination can do, then standardize on those and get really high quality output," Rodriguez said.
The AGENTS.md specification allows teams to version control their agent behavior alongside their code. When a developer clones a repository, they automatically inherit the custom agent rules. This solves a persistent problem with AI coding tools: Inconsistent output quality when different team members use different prompting strategies.
Native Model Context Protocol (MCP) support: VS Code now includes a GitHub MCP Registry. Developers can discover, install and enable MCP servers with a single click. They can then create custom agents that combine these tools with specific system prompts.
This positions GitHub as the integration point between the emerging MCP ecosystem and actual developer workflows. MCP, introduced by Anthropic but rapidly gaining industry support, is becoming a de facto standard for agent-to-tool communication. By supporting the full specification, GitHub can orchestrate agents that need access to external services without each agent implementing its own integration logic.
GitHub is also shipping new capabilities within VS Code itself. Plan Mode allows developers to collaborate with Copilot on building step-by-step project approaches. The AI asks clarifying questions before any code is written. Once approved, the plan can be executed either locally in VS Code or by cloud-based agents.
The feature addresses a common failure mode in AI coding: Beginning implementation before requirements are fully understood. By forcing an explicit planning phase, GitHub aims to reduce wasted effort and improve output quality.
More significantly, GitHub's code review feature is becoming agentic. The new implementation will use GitHub's CodeQL engine, which previously largely focused on security vulnerabilities to identify bugs and maintainability issues. The code review agent will automatically scan agent-generated pull requests before human review. This creates a two-stage quality gate.
"Our code review agent will be able to make calls into the CodeQL engine to then find a set of bugs," Rodriguez explained. "We're extending the engine and we're going to be able to tap into that engine also to find bugs."
For enterprises already deploying multiple AI coding tools, Agent HQ offers a path to consolidation without forcing tool elimination.
GitHub's multi-agent approach provides vendor flexibility and reduces lock-in risk. Organizations can test multiple agents within a unified security perimeter and switch providers without retraining developers. The tradeoff is potentially less optimized experiences compared to specialized tools that tightly integrate UI and agent behavior.
Rodriguez's recommendation is clear: Begin with custom agents. This allows enterprises to codify organizational standards that agents follow consistently. Once established, organizations can layer in additional third-party agents to expand capabilities.
"Go and do agent coding, custom agents and start playing with that," he said. "That is a capability available tomorrow, and it allows you to really start shaping your SDLC to be personalized to you, your organization and your people."
Building AI for financial software requires a different playbook than consumer AI, and Intuit's latest QuickBooks release provides an example.
The company has announced Intuit Intelligence, a system that orchestrates specialized AI agents across its QuickBooks platform to handle tasks including sales tax compliance and payroll processing. These new agents augment existing accounting and project management agents (which have also been updated) as well as a unified interface that lets users query data across QuickBooks, third-party systems and uploaded files using natural language.
The new development follow years of investment and improvement in Intuit's GenOS, allowing the company to build AI capabilities that reduce latency and improve accuracy.
But the real news isn't what Intuit built — it's how they built it and why their design decisions will make AI more usable. The company's latest AI rollout represents an evolution built on hard-won lessons about what works and what doesn't when deploying AI in financial contexts.
What the company learned is sobering: Even when its accounting agent improved transaction categorization accuracy by 20 percentage points on average, they still received complaints about errors.
"The use cases that we're trying to solve for customers include tax and finance; if you make a mistake in this world, you lose trust with customers in buckets and we only get it back in spoonfuls," Joe Preston, Intuit's VP of product and design, told VentureBeat.
Intuit's technical strategy centers on a fundamental design decision. For financial queries and business intelligence, the system queries actual data, rather than generating responses through large language models (LLMs).
Also critically important: That data isn't all in one place. Intuit's technical implementation allows QuickBooks to ingest data from multiple distinct sources: native Intuit data, OAuth-connected third-party systems like Square for payments and user-uploaded files such as spreadsheets containing vendor pricing lists or marketing campaign data. This creates a unified data layer that AI agents can query reliably.
"We're actually querying your real data," Preston explained. "That's very different than if you were to just copy, paste out a spreadsheet or a PDF and paste into ChatGPT."
This architectural choice means that the Intuit Intelligence system functions more as an orchestration layer. It's a natural language interface to structured data operations. When a user asks about projected profitability or wants to run payroll, the system translates the natural language query into database operations against verified financial data.
This matters because Intuit's internal research has uncovered widespread shadow AI usage. When surveyed, 25% of accountants using QuickBooks admitted they were already copying and pasting data into ChatGPT or Google Gemini for analysis.
Intuit's approach treats AI as a query translation and orchestration mechanism, not a content generator. This reduces the hallucination risk that has plagued AI deployments in financial contexts.
Beyond the technical architecture, Intuit has made explainability a core user experience across its AI agents. This goes beyond simply providing correct answers: It means showing users the reasoning behind automated decisions.
When Intuit's accounting agent categorizes a transaction, it doesn't just display the result; it shows the reasoning. This isn't marketing copy about explainable AI, it's actual UI displaying data points and logic.
"It's about closing that trust loop and making sure customers understand the why," Alastair Simpson, Intuit's VP of design, told VentureBeat.
This becomes particularly critical when you consider Intuit's user research: While half of small businesses describe AI as helpful, nearly a quarter haven't used AI at all. The explanation layer serves both populations: Building confidence for newcomers, while giving experienced users the context to verify accuracy.
The design also enforces human control at critical decision points. This approach extends beyond the interface. Intuit connects users directly with human experts, embedded in the same workflows, when automation reaches its limits or when users want validation.
One of Intuit's more interesting challenges involves managing a fundamental shift in user interfaces. Preston described it as having one foot in the past and one foot in the future.
"This isn't just Intuit, this is the market as a whole," said Preston. "Today we still have a lot of customers filling out forms and going through tables full of data. We're investing a lot into leaning in and questioning the ways that we do it across our products today, where you're basically just filling out, form after form, or table after table, because we see where the world is headed, which is really a different form of interacting with these products."
This creates a product design challenge: How do you serve users who are comfortable with traditional interfaces while gradually introducing conversational and agentic capabilities?
Intuit's approach has been to embed AI agents directly into existing workflows. This means not forcing users to adopt entirely new interaction patterns. The payments agent appears alongside invoicing workflows; the accounting agent enhances the existing reconciliation process rather than replacing it. This incremental approach lets users experience AI benefits without abandoning familiar processes.
Intuit's experience deploying AI in financial contexts surfaces several principles that apply broadly to enterprise AI initiatives.
Architecture matters for trust: In domains where accuracy is critical, consider whether you need content generation or data query translation. Intuit's decision to treat AI as an orchestration and natural language interface layer dramatically reduces hallucination risk and avoids using AI as a generative system.
Explainability must be designed in, not bolted on: Showing users why the AI made a decision isn't optional when trust is at stake. This requires deliberate UX design. It may constrain model choices.
User control preserves trust during accuracy improvements: Intuit's accounting agent improved categorization accuracy by 20 percentage points. Yet, maintaining user override capabilities was essential for adoption.
Transition gradually from familiar interfaces: Don't force users to abandon forms for conversations. Embed AI capabilities into existing workflows first. Let users experience benefits before asking them to change behavior.
Be honest about what's reactive versus proactive: Current AI agents primarily respond to prompts and automate defined tasks. True proactive intelligence that makes unprompted strategic recommendations remains an evolving capability.
Address workforce concerns with tooling, not just messaging: If AI is meant to augment rather than replace workers, provide workers with AI tools. Show them how to leverage the technology.
For enterprises navigating AI adoption, Intuit's journey offers a clear directive. The winning approach prioritizes trustworthiness over capability demonstrations. In domains where mistakes have real consequences, that means investing in accuracy, transparency and human oversight before pursuing conversational sophistication or autonomous action.
Simpson frames the challenge succinctly: "We didn't want it to be a bolted-on layer. We wanted customers to be in their natural workflow, and have agents doing work for customers, embedded in the workflow."
Washington state Gov. Bob Ferguson is threading the needle when it comes to artificial intelligence.
Ferguson made a brief appearance at the opening reception for Seattle AI Week on Monday evening, speaking at AI House on Pier 70 about his approach to governing the consequential technology.
“I view my job as maximizing the benefits and minimizing harms,” said Ferguson, who took office earlier this year.
Ferguson called AI one of the “top five biggest challenges” he thinks about daily, both professionally and personally.
In a follow-up interview with GeekWire, the governor said AI “could totally transform our government, as well as the private sector, in many ways.”
His comments came just as Amazon, the largest employer in Washington state, said it would eliminate about 14,000 corporate jobs, citing a need to reduce bureaucracy and become more efficient in the new era of artificial intelligence.
Ferguson told the crowd that the future of work and “loss of jobs that come with the technology” is on his mind.
The governor highlighted Washington’s AI Task Force, created during his tenure as attorney general, which is studying issues from algorithmic bias to data security. The group’s next set of recommendations arrives later this year and could shape upcoming legislation, he said.
States are moving ahead with their own AI rules in the absence of a comprehensive federal framework. Washington appears to sit in the pragmatic middle of this fast-moving regulatory landscape — using executive action and an expert task force to build guidelines, while watching experiments in states such as California and Colorado.
Seattle city leaders also getting involved. Seattle Mayor Bruce Harrell last month announced a “responsible AI plan” that provides guidelines for Seattle’s use of artificial intelligence and its support of the AI tech sector as an economic driver.
Ferguson said he’s aware of how AI can “really revolutionize our economy and state in so many ways,” from healthcare to education to wildfire detection.
But he also flagged his concerns — both as a policymaker and parent. The governor, who has 17-year-old twins, said he worries about the technology’s impact on young people, referencing reports of teen suicides linked to AI chatbots.
Despite those concerns, Ferguson maintained an upbeat tone during his remarks at Seattle AI Week, citing the region’s technical talent and economic opportunity from the technology.
He noted that the state, amid a $16 billion budget shortfall this year, kept $300,000 in funding for the AI House, the new waterfront startup hub that hosted Monday’s event.
“There is no better place anywhere in the United States for this innovation than right here in the Northwest,” he said.
Related: A tale of two Seattles in the age of AI: Harsh realities and new hope for the tech community
EVERETT, Wash. — In an industrial stretch of Everett is a boxy, windowless building called Ursa. Inside that building is a vault built from concrete blocks up to 5 feet thick with an additional layer of radiation-absorbing plastic. Within that vault is Polaris, a machine that could change the world.
Helion Energy is trying to replicate the physics that fuel the sun and the stars — hence the celestial naming theme — to provide nearly limitless power on earth through fusion reactions.
The company recently invited a small group of journalists to visit its headquarters and see Polaris, which is the seventh iteration of its fusion generator and the prototype for a commercial facility called Orion that broke ground this summer in Malaga in Central Washington.
Few people outside of Helion have been provided such access; photographs were not allowed.
“We run these systems right now at 100 million degrees, about 10 times the temperature of the sun, and compress them to high pressure… the same pressure as the bottom of the Marianas Trench,” said Helion CEO and co-founder David Kirtley, referencing the deepest part of the ocean.
Polaris and its vault occupy a relative small footprint inside of Ursa. The majority of the space is filled with 2,500 power units. They’re configured into 4-foot-by-4-foot pallets, lined up in rows and stacked seven high. The units are packed with capacitors that are charged from the grid to provide super high intensity pulses of electricity — 100 gigawatts of peak power — that create the temperatures and pressure needed for fusion reactions.
All of that energy is carried through miles and miles of coaxial cables filled with copper, aluminum and custom-metal alloys. End-to-end, the cables would stretch across Washington state and back again — roughly 720 miles. They flow in thick, black bundles from the pallets into the vault. They curl on the floor in giant heaps before connecting to the tubular-shaped, 60-foot-long Polaris generator.
The ultimate goal is for the generator to force lightweight ions to fuse, creating a super hot plasma that expands, pushing on a magnetic field that surrounds it. The energy created by that expansion is directly captured and carried back the capacitors to recharge them so the process can be repeated over and over again.
And the small amount of extra power that’s produced by fusion goes into the electrical grid for others to use — or at least that’s the plan for the future.
Helion is a contender in a global race to generate fusion power for a rapidly escalating demand for electricity, driven in part by data centers and AI. No one so far has been able to make and capture enough energy from fusion to commercialize the process, but dozens of companies — including three other competitors in the Pacific Northwest — are trying.
The company aims by 2028 to begin producing energy at the Malaga site, which Microsoft has agreed to purchase. If it hits this extremely ambitious target — and many are highly skeptical — it could be the world’s first company to do so.
“There is a level of risk, of being aggressive with program development, new technology and timelines,” Kirtley said. “But I think it’s worth it. Fusion is the same process that happens in the stars. It has the promise of very low cost electricity that’s clean and safe and base load and always on. And so it’s worth being aggressive.”
Some in the sector worry that Helion will miss the mark and cast doubt on a sector that is working hard to prove itself. At a June event, the head of R&D for fusion competitor Zap Energy questioned Helion’s deadline.
“I don’t see a commercial application in the next few years happening,” said Ben Levitt. “There is a lot of complicated science and engineering still to be discovered and to be applied.”
Others are willing to take the bet. Helion has raised more than $1 billion from investors that include SoftBank, Lightspeed Venture Partners and Sam Altman, who is OpenAI’s CEO and co-founder, as well as Helion’s longtime chair of its board of directors. The company is able to unlock an additional $1.8 billion if it hits Polaris milestones.
The generator has been operating since December, running all day, five days a week, creating fusion, Kirtley said.
Helion is highly cautious — some would say too cautious — in sharing details on its progress. Helion officials say they must hold their tech close to the vest as Chinese competitors have stolen pieces of their intellectual property; critics say the secrecy makes it difficult for the scientific community to verify their likelihood of success in a very risky, highly technical field.
In August, Kirtley shared an online post about Helion’s power-producing strategy, which upends the conventional approach.
Most efforts are trying to achieve ignition in their fusion generators, which is a condition where the reactions produce more power than is required for fusion to occur. This feat was first accomplished at a national lab in California in 2022 — but it still wasn’t enough energy that one could put electricity on the grid.
Helion is not aiming for ignition but rather for a system that is so efficient it can capture enough energy from fusion without reaching that state.
Kirtley compares the strategy for producing power to regenerative braking in electric vehicles. Simply put, an EV’s battery gets the car moving, and regenerative braking by the driver puts energy back into the battery to help it run longer. In the fusion generator, the capacitors provide that initial power, and the fusion reaction resupplies the energy and a little bit more.
“We can recover electricity at high efficiency,” Kirtley said. Compared to other commercial fusion approaches, “we require a lot less fusion. Fusion is the hard part. My goal, ironically, is to do the minimum amount of fusion that we can deliver a product to the customer and generate electricity.”
Learn more about the new Gemini for Home voice assistant, now rolling out in early access.
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Here’s how students and faculty at higher education institutions are using Gemini.
Google has expanded the What’s happening feature within Google Business Profiles to restaurants and bars in the United Kingdom, Canada, Australia, and New Zealand. It is now available for multi-location restaurants, not just single-location restaurants.
The What’s happening feature launched back in May as a way for some businesses to highlight events, deals, and specials prominently at the top of your Google Business Profile. Now, Google is bringing it to more countries.
What Google said. Google’s Lisa Landsman wrote on LinkedIn:
How do you promote your “Taco Tuesday” in Toledo and your “Happy Hour” in Houston… right when locals are searching for a place to go?
I’m excited to share that the Google Business Profile feature highlighting what’s happening at your business, such as timely events, specials and deals, has now rolled out for multi-location restaurants & bars across the US, UK, CA, AU & NZ! (It was previously only available for single-location restaurants)
This is a great option for driving real-time foot traffic. It automatically surfaces the unique specials, live music, or events you’re already promoting at a specific location, catching customers at the exact moment they’re deciding where to eat or grab a cocktail.
What it looks like. Here is a screenshot of this feature:
More details. Google’s Lisa Landsman added, “We’ve already seen excellent results from testing and look forward to hearing how this works for you!”
Availability. This feature is only available for restaurants & bars. Google said it hopes to expand to more categories soon. It is also only available in the United States, United Kingdom, Canada, Australia, and New Zealand.
The initial launch was for single-location Food and Drink businesses in the U.S., UK, Australia, Canada, and New Zealand. It is now available for multi-location restaurants, not just single-location restaurants.
Why we care. If you manage restaurants and/or bars, this may be a new way to get more attention and visitors to your business from Google Search. Now, if you manage multi-location restaurants or bars, you can leverage this feature.
Marketing, technology, and business leaders today are asking an important question: how do you optimize for large language models (LLMs) like ChatGPT, Gemini, and Claude?
LLM optimization is taking shape as a new discipline focused on how brands surface in AI-generated results and what can be measured today.
For decision makers, the challenge is separating signal from noise – identifying the technologies worth tracking and the efforts that lead to tangible outcomes.
The discussion comes down to two core areas – and the timeline and work required to act on them:
Just as SEO evolved through better tracking and measurement, LLM optimization will only mature once visibility becomes measurable.
We’re still in a pre-Semrush/Moz/Ahrefs era for LLMs.
Tracking is the foundation of identifying what truly works and building strategies that drive brand growth.
Without it, everyone is shooting in the dark, hoping great content alone will deliver results.
The core challenges are threefold:
Why LLM queries are different
Traditional search behavior is repetitive – millions of identical phrases drive stable volume metrics. LLM interactions are conversational and variable.
People rephrase questions in different ways, often within a single session. That makes pattern recognition harder with small datasets but feasible at scale.
These structural differences explain why LLM visibility demands a different measurement model.
This variability requires a different tracking approach than traditional SEO or marketing analytics.
The leading method uses a polling-based model inspired by election forecasting.
A representative sample of 250–500 high-intent queries is defined for your brand or category, functioning as your population proxy.
These queries are run daily or weekly to capture repeated samples from the underlying distribution of LLM responses.
Tracking tools record when your brand and competitors appear as citations (linked sources) or mentions (text references), enabling share of voice calculations across all competitors.
Over time, aggregate sampling produces statistically stable estimates of your brand visibility within LLM-generated content.
Early tools providing this capability include:
Consistent sampling at scale transforms apparent randomness into interpretable signals.
Over time, aggregate sampling provides a stable estimate of your brand’s visibility in LLM-generated responses – much like how political polls deliver reliable forecasts despite individual variations.
While share of voice paints a picture of your presence in the LLM landscape, it doesn’t tell the complete story.
Just as keyword rankings show visibility but not clicks, LLM presence doesn’t automatically translate to user engagement.
Brands need to understand how people interact with their content to build a compelling business case.
Because no single tool captures the entire picture, the best current approach layers multiple tracking signals:
Nobody has complete visibility into LLM impact on their business today, but these methods cover all the bases you can currently measure.
Be wary of any vendor or consultant promising complete visibility. That simply isn’t possible yet.
Understanding these limitations is just as important as implementing the tracking itself.
Because no perfect models exist yet, treat current tracking data as directional – useful for decisions, but not definitive.
Dig deeper: In GEO, brand mentions do what links alone can’t
Measuring LLM impact is one thing. Identifying which queries and topics matter most is another.
Compared to SEO or PPC, marketers have far less visibility. While no direct search volume exists, new tools and methods are beginning to close the gap.
The key shift is moving from tracking individual queries – which vary widely – to analyzing broader themes and topics.
The real question becomes: which areas is your site missing, and where should your content strategy focus?
To approximate relative volume, consider three approaches:
Correlate with SEO search volume
Start with your top-performing SEO keywords.
If a keyword drives organic traffic and has commercial intent, similar questions are likely being asked within LLMs. Use this as your baseline.
Layer in industry adoption of AI
Estimate what percentage of your target audience uses LLMs for research or purchasing decisions:
Apply these percentages to your existing SEO keyword volume. For example, a keyword with 25,000 monthly searches could translate to 1,250-6,250 LLM-based queries in your category.
Using emerging inferential tools
New platforms are beginning to track query data through API-level monitoring and machine learning models.
Accuracy isn’t perfect yet, but these tools are improving quickly. Expect major advancements in inferential LLM query modeling within the next year or two.
The technologies that help companies identify what to improve are evolving quickly.
While still imperfect, they’re beginning to form a framework that parallels early SEO development, where better tracking and data gradually turned intuition into science.
Optimization breaks down into two main questions:
One of the most effective ways to assess your current position is to take a representative sample of high-intent queries that people might ask an LLM and see how your brand shows up relative to competitors. This is where the Share of Voice tracking tools we discussed earlier become invaluable.
These same tools can help answer your optimization questions:
From this data, several key insights emerge:
LLMs may be reshaping discovery, but SEO remains the foundation of digital visibility.
Across five competitive categories, brands ranking on Google’s first page appeared in ChatGPT answers 62% of the time – a clear but incomplete overlap between search and AI results.
That correlation isn’t accidental.
Many retrieval-augmented generation (RAG) systems pull data from search results and expand it with additional context.
The more often your content appears in those results, the more likely it is to be cited by LLMs.
Brands with the strongest share of voice in LLM responses are typically those that invested in SEO first.
Strong technical health, structured data, and authority signals remain the bedrock for AI visibility.
What this means for marketers:
Just as SEO has both on-page and off-page elements, LLM optimization follows the same logic – but with different tactics and priorities.
Off-page: The new link building
Most industries show a consistent pattern in the types of resources LLMs cite:
Citation patterns across ChatGPT, Gemini, Perplexity, and Google’s AI Overviews show consistent trends, though each engine favors different sources.
This means that traditional link acquisition strategies, guest posts, PR placements, or brand mentions in review content will likely evolve.
Instead of chasing links anywhere, brands should increasingly target:
The core principle holds: brands gain the most visibility by appearing in sources LLMs already trust – and identifying those sources requires consistent tracking.
On-page: What your own content reveals
The same technologies that analyze third-party mentions can also reveal which first-party assets, content on your own website, are being cited by LLMs.
This provides valuable insight into what type of content performs well in your space.
For example, these tools can identify:
From there, three key opportunities emerge:
The next major evolution in LLM optimization will likely come from tools that connect insight to action.
Early solutions already use vector embeddings of your website content to compare it against LLM queries and responses. This allows you to:
Current tools mostly generate outlines or recommendations.
The next frontier is automation – systems that turn data into actionable content aligned with business goals.
While comprehensive LLM visibility typically builds over 6-12 months, early results can emerge faster than traditional SEO.
The advantage: LLMs can incorporate new content within days rather than waiting months for Google’s crawl and ranking cycles.
However, the fundamentals remain unchanged.
Quality content creation, securing third-party mentions, and building authority still require sustained effort and resources.
Think of LLM optimization as having a faster feedback loop than SEO, but requiring the same strategic commitment to content excellence and relationship building that has always driven digital visibility.
LLM traffic remains small compared to traditional search, but it’s growing fast.
A major shift in resources would be premature, but ignoring LLMs would be shortsighted.
The smartest path is balance: maintain focus on SEO while layering in LLM strategies that address new ranking mechanisms.
Like early SEO, LLM optimization is still imperfect and experimental – but full of opportunity.
Brands that begin tracking citations, analyzing third-party mentions, and aligning SEO with LLM visibility now will gain a measurable advantage as these systems mature.
In short:
Approach LLM optimization as both research and brand-building.
Don’t abandon proven SEO fundamentals. Rather, extend them to how AI systems discover, interpret, and cite information.
Seattle is looking to celebrate and accelerate its leadership in artificial intelligence at the very moment the first wave of the AI economy is crashing down on the region’s tech workforce.
That contrast was hard to miss Monday evening at the opening reception for Seattle AI Week 2025 at Pier 70. On stage, panels offered a healthy dose of optimism about building the AI future. In the crowd, buzz about Amazon’s impending layoffs brought the reality of the moment back to earth.
A region that rose with Microsoft and then Amazon is now dealing with the consequences of Big Tech’s AI-era restructuring. Companies that hired by the thousands are now thinning their ranks in the name of efficiency and focus — a dose of corporate realism for the local tech economy.
The double-edged nature of this shift is not lost on Washington Gov. Bob Ferguson.
“AI, and the future of AI, and what that means for our state and the world — each day I do this job, the more that moves up in my mind in terms of the challenges and the opportunities we have,” Ferguson told the AI Week crowd. He touted Washington’s concentration of AI jobs, saying his goal is to maximize the benefits of AI while minimizing its downsides.
Seattle AI Week, led by the Washington Technology Industry Association, was started last year after a Forbes list of the nation’s top 50 AI startups included none from Seattle, said the WTIA’s Nick Ellingson, opening this year’s event. That didn’t seem right. Was it a messaging problem?
“A bunch of us got together and said, let’s talk about all the cool things happening around AI in Seattle, and let’s expand the tent beyond just tech things that are happening,” Ellingson explained.
So maybe that’s the best measuring stick: how many startups will this latest shakeout spark, and how can the Seattle region’s startup and tech leaders make it happen? Can the region become less dependent on the whims of the Microsoft and Amazon C-suites in the process?
“Washington has so much opportunity. It’s one of the few capitals of AI in the world,” said WTIA’s Arry Yu in her opening remarks. “People talk about China, people talk about Silicon Valley — there are a few contenders, but really, it’s here in Seattle. … The future is built on data, on powerful technology, but also on community. That’s what makes this place different.”
And yet, “AI is a sleepy scene in Seattle, where people work at their companies, but there’s very little activity and cross-pollinating outside of this,” said Nathan Lambert, senior research scientist with the Allen Institute for AI, during the opening panel discussion.
No, we don’t want to become San Francisco or Silicon Valley, Lambert added. But that doesn’t mean the region can’t cherry-pick some of the ingredients that put Bay Area tech on top.
Whether laid-off tech workers will start their own companies is a common question after layoffs like this. In the Seattle region at least, that outcome has been more fantasy than reality.
This is where AI could change things, if not with the fabled one-person unicorn then with a bigger wave of new companies born of this employment downturn. Who knows, maybe one will even land on that elusive Forbes AI 50 list. (Hey, a region can dream!)
But as the new AI reality unfolds in the regional workforce, maybe the best question to ask is whether Seattle’s next big thing can come from its own backyard again.
Related: Ferguson’s AI balancing act: Washington governor wants to harness innovation while minimizing harms
Microsoft and OpenAI announced the long-awaited details of their new partnership agreement Tuesday morning — with concessions on both sides that keep the companies aligned but not in lockstep as they move into their next phases of AI development.
Under the arrangement, Microsoft gets a 27% equity stake in OpenAI’s new for-profit entity, the OpenAI Group PBC (Public Benefit Corporation), a stake valued at approximately $135 billion. That’s a decrease from 32.5% equity but not a bad return on an investment of $13.8 billion.
At the same time, OpenAI has contracted to purchase an incremental $250 billion in Microsoft Azure cloud services. However, in a significant concession in return for that certainty, Microsoft will no longer have a “right of first refusal” on new OpenAI cloud workloads.
Microsoft, meanwhile, will retain its intellectual property rights to OpenAI models and products through 2032, an extension of the timeframe that existed previously.
A key provision of the new agreement centers on Artificial General Intelligence (AGI), with any declaration of AGI by OpenAI now subject to verification by an independent expert panel. This was a sticking point in the earlier partnership agreement, with an ambiguous definition of AI potentially triggering new provisions of the prior arrangement.
Microsoft and OpenAI had previously announced a tentative agreement without providing details. More aspects of the deal are disclosed in a joint blog post from the companies.
Shares of Microsoft are up 2% in early trading after the announcement. The company reports earnings Wednesday afternoon, and some analysts have said the uncertainty over the OpenAI arrangement has been impacting Microsoft’s stock.
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“We are super excited to announce a new partnership with the Department of Energy,” stated Lisa Su, Chair and CEO of AMD, during a CNBC interview. This monumental $1 billion collaboration will usher in the development of two advanced supercomputers, designed to tackle some of the most complex scientific challenges facing humanity. The partnership signifies […]
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The post Bitcoin Miners’ AI Pivot: A Strategic Masterclass in Energy and Compute appeared first on StartupHub.ai.
The burgeoning demand for artificial intelligence, a computational arms race among hyperscalers, has illuminated a critical bottleneck: access to reliable, scalable power. This very challenge, as discussed by CleanSpark CEO Matthew Schultz with CNBC’s Jordan Smith, is precisely where Bitcoin miners like CleanSpark find their strategic advantage. Their conversation unveils a nuanced pivot, not merely […]
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The post OpenAI Recapitalization Reshapes AI Landscape with Microsoft at the Helm appeared first on StartupHub.ai.
The recent finalization of OpenAI’s recapitalization plan marks a pivotal moment in the trajectory of artificial intelligence, not just for the involved parties but for the entire tech ecosystem. On CNBC, David Faber broke down the intricate details of this agreement, joined by Jim Cramer, who offered his characteristic sharp market commentary. Their discussion illuminated […]
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The post Wild Moose Emerges from Stealth with $7 Million Seed Round to Redefine Site Reliability Engineering with AI appeared first on StartupHub.ai.
Wild Moose, the AI-powered Site Reliability Engineering (SRE) platform acting as a first responder for production incidents, today announced its emergence from stealth with $7 million in seed funding. The round was led by iAngels, with participation from Y Combinator, F2 Venture Capital, Maverick Ventures, and others. The company is also backed by a distinguished […]
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The post Gemini for Education: Google’s AI Dominates Higher Ed appeared first on StartupHub.ai.
Google's Gemini for Education is rapidly integrating into higher education, offering no-cost AI tools to over 1000 institutions and 10 million students.
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The post Securitize IPO to bring tokenization to Nasdaq at $1.25B appeared first on StartupHub.ai.
The Securitize IPO is a bellwether moment, creating the first publicly-traded company focused purely on the infrastructure for tokenizing real-world assets.
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The post FriendliAI Expands Ultra-Fast AI Inference Platform with Nebius AI Cloud Integration appeared first on StartupHub.ai.
Enterprises can now deploy large-scale AI inference with FriendliAI’s optimized stack on Nebius AI infrastructure, combining top performance with cost efficiency.
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Seems like we've been on a northern lights roll lately, haven't we? There's one happening again tonight and the NOAA is even promising how the spectacular aurora display will be visible as far south as New York and Wisconsin. Forecasts say that a significant burst of solar activity colliding with Earth’s magnetic field will be creating the
After kids, teens, and even some adults are finished knocking on your door in hopes of scoring pieces of candy (or full-size candy bars, if you're really looking to impress), it won't be long until the Black Friday and Cyber Monday sales season is in full force. If you want to get a jump on the mad rush and are in the market for a Fire TV,
Cybersecurity experts are sounding the alarm over a new Android Trojan dubbed Herodotus, which is designed to deliberately slow down its own malicious activity to mimic the casual, imperfect behavior of a human user. Such behavior allows the malware to slip past a generation of security systems built to flag more rapid, robotic actions of
Windows Insiders are getting early access to an upcoming Windows 11 feature that is intended to improve system reliability by scanning system memory following a system crash. The optional feature is related to those frustrating BSOD errors that, aside from letting you know that your PC tripped over itself and bonked its head (as was the case
Samsung is expanding its range of storage card solutions with the release of the P9 Express, a microSD Express memory card with enough speed to keep up with gaming handhelds like Nintendo's Switch 2. While not exclusively aimed at the Switch 2, Nintendo's newest console is a big reason why we're starting to see more microSD Express memory
AMD will power two new AI supercomputers in the US, using MI355X and MI430X accelerators The US Department of Energy has announced a $1 billion deal under which AMD will deliver two next-generation supercomputers to the Oak Ridge National Laboratory (ORNL). These systems are designed to expand the US’s leadership in artificial intelligence (AI) and […]
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By Jeff Seibert
I’ve been building products and companies my entire career — Increo, Box, Crashlytics, Twitter and now, Digits — and I’ve had the privilege of speaking with some of the sharpest minds in venture and entrepreneurship along the way.
One recent conversation with a legendary investor really crystallized for me a set of truths about startups: what success really is, why some founders thrive while others burn out, and how to navigate the inevitable chaos of building something from nothing.
Here are some of the lessons I’ve internalized from years of building, observing and learning.
In the startup world, we talk a lot about IPOs, acquisitions and valuations. But those are milestones, not destinations.
The companies that endure don’t “win” and stop — they keep creating, adapting and pushing forward. They’re playing an infinite game, where the only goal is to remain in the game.
When you’re building something truly generative — driven by a purpose greater than yourself — there’s no point at which you can say “done.” If your company has a natural stopping point, you may be building the wrong thing.
The best founders I’ve met — and the best moments I’ve had as a founder — come from an almost irrational pull toward solving a specific problem I myself experienced.
You may want to start a company, but if you have to talk yourself into your idea, it probably won’t survive contact with reality. The founders who succeed are often the ones who can’t not work on their thing.
Starting a company shouldn’t be a career move — it should be the last possible option after every other path fails to scratch the itch.
Most companies don’t die because of one bad decision or one tough competitor. They die because the founders run out of energy.
Fatigue erodes vision, motivation and creativity. Protecting your own drive — keeping it clean and focused — may be the single most important survival skill you have.
That means staying close to the product, protecting time for customer work, and avoiding the slow drift into managing around problems instead of solving them.
It’s easy to get caught up in competitor moves, investor chatter or market gossip. But the most important question is always: Are we delivering joy to the customer?
If you’re losing focus, sign up for your own product as a brand-new user. Feel the friction. Fix it. Repeat.
At Digits, we run our own signup and core flows every week. It’s uncomfortable — it surfaces flaws we’d rather not see — but it keeps us anchored to the only metric that matters: customer delight.
Over the years, I’ve learned the most effective boards aren’t presentation theaters — they’re discussion rooms.
The best structure I’ve seen:
Good directors help you widen your perspective. They don’t hand you a to-do list. Rather, they help you see the problem in a way that makes the answer obvious.
When I think back to my time at Twitter, the most enduring lesson is that not all companies are built top-down. Some — like Twitter — are shaped more by their users than their executives.
Features like @mentions, hashtags and retweets didn’t come from a product roadmap — they came from the community.
That’s messy, but it’s also powerful. Sometimes your job isn’t to control the phenomenon, rather it’s to keep it healthy without smothering what made it magical in the first place.
If you’re building today, you have an advantage over the so-called “unicorn zombies” that raised massive rounds pre-AI and are now locked into defending old business models.
Fresh founders can design from scratch for the new reality; there’s no legacy to protect, no sacred cows to defend.
The macro environment? Irrelevant. The only timing that matters is when the problem calls you so strongly that not working on it feels impossible.
If there’s one takeaway from all of this, it’s that success is continuing. The real prize is the ability to keep playing, keep serving and keep creating.
If you’re standing at the edge, wondering if you should start — start. Take one step. See if it grows. And if it does, welcome to the infinite game.
Jeff Seibert is the founder and CEO of Digits, the world’s first AI-native accounting platform. He previously served as Twitter‘s head of consumer product and starred in the Emmy Award-winning Netflix documentary “The Social Dilemma.”
Illustration: Dom Guzman
While startup investment has been climbing lately, not all industries are partaking in the gains.
Cleantech is one of the spaces that’s been mostly left out. Overall funding to the space is down this year, despite some pockets of bullishness in areas like fusion and battery recycling.
The broad trend: Cleantech- and sustainability-related startup investment has been on a downward trajectory for several years now. And so far, 2025 is on track to be another down year.
On the bright side, however, there’s been some pickup in recent months, boosted by big rounds for companies in energy storage, fusion and other cleantech subsectors.
The numbers: Investors put an estimated $20 billion into seed- through growth-stage funding to companies in cleantech, EV and sustainability-related categories so far this year.
That puts 2025 funding on track to come in well below last year’s levels, which were already at a multiyear low.
Still, quarter by quarter, the pattern looks more encouraging. Investment hit a low point in Q1 of this year and recovered some in the subsequent two quarters. The current quarter is also off to a strong start.
Noteworthy recent rounds
The largest cleantech-related round of the year closed this month. Base Power, a provider of residential battery backup systems and electricity plans, raised $1 billion in Series C funding. The Austin, Texas-based company says its systems allow energy providers to more efficiently harness renewable power.
The second-largest round was Commonwealth Fusion Systems’ $863 million Series B2 financing. The Devens, Massachusetts-based company says it is moving closer to being the first in the world to commercialize fusion power.
For a bigger-picture view, below we put together a list of 10 of the year’s largest cleantech- and sustainability-related financings.
The broad takeaway: Startups innovating for an era of rising power consumption
Not to over-generalize, but if there was one big takeaway from recent cleantech and sustainability startup funding, it would be that founders and investors recognize that these are times of ever-escalating energy demand. They’re planning accordingly, looking to tap new sources of power, fusion in particular, as well as better utilize and scale existing clean energy sources.
Illustration: Dom Guzman
A new report exploring the potential for the Pacific Northwest to stake its claim as the global leader in responsible AI offers a paradoxical view. The Cascadia region, which includes Seattle, Portland and Vancouver, B.C., is described as a proven, promising player in the sphere — but with significant risks that threaten its success.
“We created companies that transformed global commerce,” writes former Gov. Chris Gregoire in a forward to the document. “Now we have the chance to add another chapter — one where Cascadia becomes the world’s standard-bearer for innovation that uplifts both people and planet.”
The Cascadia Innovation Corridor, which Gregoire chairs, released the report this morning as it kicks off its two-day conference. The economic advocacy group’s eighth annual event is being held in Seattle.
The study is built on an analysis by the Boston Consulting Group that ranks Cascadia’s three metro areas against 15 comparable regions in the U.S. and Canada for their economic competitiveness, including livability, workforce, and business and innovation climate. Seattle came in fourth behind Boston, Austin and Raleigh, while Portland ranked 13th and Vancouver 14th.
Over the past decade, the region’s gross domestic product and populations have both grown significantly, and when combined, their economies approach the 18th largest in the world.
Cascadia’s strengths, the report explains, include tech engines such as cloud giants Microsoft and Amazon in Washington, silicon chip manufacturing in Oregon, and quantum innovation in Vancouver, as well as academic excellence from the University of Washington, University of British Columbia and Oregon State University.
But as time goes on and as business and civic leaders aim for the prize of AI dominance, cracks in the system are increasingly troubling.
The report notes that multiple regions around the U.S. and Canada have created AI-focused hubs with hundreds of millions of dollars in public and private funding to bolster their hold on the sector.
New Jersey has a half-billion dollar “AI Moonshot” program including tax incentives and public-worker AI training programs; New York’s “Empire AI Consortium” has an AI computing training center at the University of Buffalo and startup supports; and California has a public-private task force to increase AI adoption within government services and connecting tech leaders with state agencies.
For its part, Seattle Mayor Bruce Harrell announced a “responsible AI plan” this fall that provides guidelines for the municipality’s use of artificial intelligence and its support of the AI tech sector as an economic driver, which includes the earlier launches of the startup-focused AI House and Foundations.
But what the region really needs to succeed is a collaborative effort tapping all of the metro areas’ assets.
“For Cascadia, the lesson is clear: without a coordinated strategy that links our strengths in cloud computing, semiconductors, and research, we risk falling behind,” states the Cascadia Innovation Corridor report. “Acting together, we can position Cascadia not just to keep pace, but to lead.”
With the iPhone 17 lineup now in the hands of consumers, the legendary rumor mill, which typically revolves around Apple's new products, is naturally shifting its focus towards next year's lineup. The iPhone 18, as well as the much-anticipated iPhone 20, which is due in 2027 and would commemorate 20 years since the first iPhone launched all the way back in 2007. Now, a new rumor suggests that Apple is transitioning towards simplified buttons in stages. The iPhone 18 lineup is likely to adopt a less complicated mechanical button for camera control, which will be replaced entirely by solid-state buttons […]
Read full article at https://wccftech.com/apple-iphone-18-to-use-a-simplified-camera-control-button-iphone-20-to-feature-haptics-instead-of-mechanical-buttons/
Death Stranding 2: On the Beach now supports the PlayStation 5's power saver mode, and its implementation is among the most interesting to date, according to a new technical analysis. In the latest episode of their weekly podcast, the tech experts at Digital Foundry examined how the two entries in the Kojima Productions series support Power Saver Mode, a newly introduced operating mode for the PlayStation 5 console that cuts CPU resources in half, halves the memory bandwidth, and reduces CPU and GPU clocks to reduce the system's power consumption. While the implementation in Death Stranding: Director's Cut was not […]
Read full article at https://wccftech.com/death-stranding-2-on-the-beach-most-interesting-power-saver-mode/
The INSPIRE series RTX 5050 is probably the smallest RTX 5050 editions, which offer a single fan design and weigh just 551 grams. MSI Launches Small Form-Factor RTX 5050 INSPIRE ITX and OC GPUs, Boasting Dual-Slot Thickness MSI has officially launched two new GeForce RTX 5050 cards in the INSPIRE series. These are probably the smallest RTX 5050 cards on the market, boasting a dual-slot design and a single-fan cooler to ensure compatibility with very small ITX cases. Apart from MSI, PNY also has a similarly compact GeForce RTX 5050, which measures just 147mm. The INSPIRE ITX RTX 5050 cards […]
Read full article at https://wccftech.com/msi-intros-geforce-rtx-5050-inspire-itx-and-oc-cards-measuring-just-147mm/
EA is pushing its employees to use AI for basically every task, but the results can be flawed, resulting in more work for developers. Business Insider recently talked with current EA staff, who confirmed that the company's leadership has spent the past year or so pushing its 15,000 employees to use AI for virtually every task, from producing code and concept art for games to advising managers how to speak to staff about a certain number of topics, including pay or promotions. The AI tools used to produce code are among those creating the most issues for developers. It is […]
Read full article at https://wccftech.com/ea-is-pushing-employees-to-use-ai-for-everything-including-producing-code-requiring-manual-fixing/
Intel's CEO, Lip-Bu Tan, has discussed the stake taken by the US government in the company, claiming that it was a necessary step to ensure that the American chipmaker could compete with Taiwan's TSMC. Intel's CEO Also Tells Specifics About His Meeting With President Trump, Calling It a Massive Success Well, the interest from the Trump administration in Intel was indeed a surprise for many of us, but for CEO Lip-Bu Tan, this initiative was "good to have", as he claims that it is similar to how Taiwan supports TSMC or South Korea backs the likes of Samsung Foundry. In […]
Read full article at https://wccftech.com/intel-ceo-says-us-government-stake-was-a-deliberate-move/
OnexPlayer has officially launched its flagship handheld, the OneXfly Apex, with a liquid-cooled AMD Ryzen AI MAX+ 395 SoC. AMD Ryzen AI MAX+ 395 Gets Liquid-Cooled Inside A Handheld With OneXPlayer's OneXfly Apex The OneXfly Apex handheld was teased last month and is positioned to be a flagship device featuring the AMD Ryzen AI MAX+ 395 SoC. This SoC has already been featured in other handhelds such as GPD Win 5 and Ayaneo Next 2. Now, OneXPlayer is rolling out its own high-end handheld, offering a nice upgrade vs the Ryzen AI 300 "Strix Point" stack. Just to recap the […]
Read full article at https://wccftech.com/onexfly-apex-handheld-launch-amd-ryzen-ai-max-395-liquid-cooling-128-gb-85wh-battery/
The popular PS3 emulator has updated its latest GPU recommendation list to AMD's RDNA and NVIDIA's Turing series. RPCS3 Announces Updated GPU Requirements for the Emulator; Recommends At Least AMD RX 5000 or NVIDIA RTX 2000 Series RPCS3 has just announced the new recommended GPU requirements for its popular PS3 emulator, which comes as a result of major GPU manufacturers ending support for some of its older generation GPU series. RPCS3 announced on X that it no longer "recommends" the AMD RX 400 and NVIDIA GTX 900 series GPUs as the recommended GPUs. The newer GPU recommendations now start with […]
Read full article at https://wccftech.com/rpcs3-removes-amd-rx-400-500-and-nvidia-gtx-900-1000-series-from-recommended-gpu-requirements/
A vapor chamber will make a significant difference to the overall temperatures of the M6 iPad Pro, with Apple previously reported to bring this cooling upgrade to its flagship tablet lineup. The California-based giant is often known to commence product development several months in advance, and according to the latest report, Apple is already in talks with two suppliers that could manufacture this crucial component. The M6 iPad Pro’s vapor chamber is reported to be provided by a Chinese and Taiwanese manufacturer Considering that the M6 iPad Pro launch will materialize approximately 18 months after the M5 iPad Pro’s inception, […]
Read full article at https://wccftech.com/apple-shortlisting-m6-ipad-pro-vapor-chamber-suppliers/
Mockin is a tool for simulating professional real-time AI interviews with personalized feedback and resume matching.
We’ve gathered 200+ real interview questions to practice, get personalized feedback, and master the STAR method to ace your next interview! Built for designers by designers.
Enterprises looking to sell goods and services online are waiting for the backbone of agentic commerce to be hashed out; but PayPal is hoping its new features will bridge the gap.
The payments company is launching a discoverability solution that allows enterprises to make its product available on any chat platform, regardless of the model or agent payment protocol.
PayPal, which is a participant in Google’s Agent Payments Protocol (AP2), found that it can leverage its relationship with merchants and enterprises to help pave the way for an easier transition into agentic commerce and offer flexibility that will benefit the ecosystem.
Michelle Gill, PayPal's GM for small business and financial services, told VentureBeat that AI-powered shopping will continue to grow, so enterprises and brands must begin laying the groundwork early.
“We think that merchants who've historically sold through web stores, particularly in the e-commerce space, are really going to need a way to get active on all of these large language models (LLMs),” Gill said. “The challenge is that no one really knows how fast all of this is going to move. We’re trying to help merchants think through how to do all of this as low-touch as possible while using the infrastructure they already have without doing a bazillion integrations.”
She added that AI shopping would also bring about “a resurgence from consumers trying to ensure their investment is protected.”
PayPal partnered with website builder Wix, Cymbio, Commerce and Shopware to bring products to chat platforms like Perplexity.
PayPal’s Agentic Commerce Services include two features. The first is Agent Ready, which would allow existing PayPal merchants to accept payments on AI platforms. The second is Shop Sync, which will enable companies’ product data to be discoverable through different AI chat interfaces. It takes a company’s catalog information and plug its inventory and fulfillment data to chat platforms.
Gill said the data goes into a central repository where AI models can ingest the information.
Right now, companies can access Shop Sync; Agent Ready is coming in 2026.
Gill said Agentic Commerce Services is a one-to-many solution that would be helpful right now, as different LLMs scrape different data sources to surface information.
Other benefits include:
Fast integration with current and future partners;
More product discovery over the traditional search, browse and cart experiences;
Preserved customer insights and relationships where the brand continues to have control over their records and communications with customers.
Right now, the service is only available through Perplexity, but Gill said more platforms will be added soon.
Agentic commerce is still very much in the early stages. AI agents are just beginning to get better at reading a browser. while platforms like ChatGPT, Gemini and Perplexity can now surface products and services based on user queries, people cannot technically buy things from chat (yet).
There’s a race right now to create a standard to enable agents to transact on behalf of users. Other than Google’s AP2, OpenAI and Stripe have the Agentic Commerce Protocol (ACP), and Visa recently launched its Trusted Agent Protocol.
Beyond enabling a trust layer for agents to transact, enterprises struggle with fragmentation in agentic commerce. Different chat platforms use different models, which also interpret information in slightly different ways. Gill said PayPal learned that when it comes to working with merchants, flexibility is critical.
“How do you decide if you're going to spend your time integrating with Google, Microsoft, ChatGPT or Perplexity?" Gill noted. "And each one of them right now has a different protocol, a different catalog, config, a different everything. That is a lot of time to make a bet as to where you should spend your time."
Google Arts & Culture is launching a new collection to honor the rich heritage of the province of North Gyeongsang in South Korea.
AI tools can help teams move faster than ever – but speed alone isn’t a strategy.
As more marketers rely on LLMs to help create and optimize content, credibility becomes the true differentiator.
And as AI systems decide which information to trust, quality signals like accuracy, expertise, and authority matter more than ever.
It’s not just what you write but how you structure it. AI-driven search rewards clear answers, strong organization, and content it can easily interpret.
This article highlights key strategies for smarter AI workflows – from governance and training to editorial oversight – so your content remains accurate, authoritative, and unmistakably human.
More than half of marketers are using AI for creative endeavors like content creation, IAB reports.
Still, AI policies are not always the norm.
Your organization will benefit from clear boundaries and expectations. Creating policies for AI use ensures consistency and accountability.
Only 7% of companies using genAI in marketing have a full-blown governance framework, according to SAS.
However, 63% invest in creating policies that govern how generative AI is used across the organization.
Even a simple, one-page policy can prevent major mistakes and unify efforts across teams that may be doing things differently.
As Cathy McPhillips, chief growth officer at the Marketing Artificial Intelligence Institute, puts it:
So drafting an internal policy sets expectations for AI use in the organization (or at least the creative teams).
When creating a policy, consider the following guidelines:
Logically, the policy will evolve as the technology and regulations change.
It can be easy to fall into the trap of believing AI-generated content is good because it reads well.
LLMs are great at predicting the next best sentence and making it sound convincing.
But reviewing each sentence, paragraph, and the overall structure with a critical eye is absolutely necessary.
Think: Would an expert say it like that? Would you normally write like that? Does it offer the depth of human experience that it should?
“People-first content,” as Google puts it, is really just thinking about the end user and whether what you are putting into the world is adding value.
Any LLM can create mediocre content, and any marketer can publish it. And that’s the problem.
People-first content aligns with Google’s E-E-A-T framework, which outlines the characteristics of high-quality, trustworthy content.
E-E-A-T isn’t a novel idea, but it’s increasingly relevant in a world where AI systems need to determine if your content is good enough to be included in search.
According to evidence in U.S. v. Google LLC, we see quality remains central to ranking:
It suggests that the same quality factors reflected in E-E-A-T likely influence how AI systems assess which pages are trustworthy enough to ground their answers.
So what does E-E-A-T look like practically when working with AI content? You can:
Dig deeper: Writing people-first content: A process and template
LLMs are trained on vast amounts of data – but they’re not trained on your data.
Put in the work to train the LLM, and you can get better results and more efficient workflows.
Here are some ideas.
If you already have a corporate style guide, great – you can use that to train the model. If not, create a simple one-pager that covers things like:
You can refresh this as needed and use it to further train the model over time.
Put together a packet of instructions that prompts the LLM. Here are some ideas to start with:
With that in mind, you can put together a prompt checklist that includes:
Dig deeper: Advanced AI prompt engineering strategies for SEO
A custom GPT is a personalized version of ChatGPT that’s trained on your materials so it can better create in your brand voice and follow brand rules.
It mostly remembers tone and format, but that doesn’t guarantee the accuracy of output beyond what’s uploaded.
Some companies are exploring RAG (retrieval-augmented generation) to further train LLMs on the company’s own knowledge base.
RAG connects an LLM to a private knowledge base, retrieving relevant documents at query time so the model can ground its responses in approved information.
While custom GPTs are easy, no-code setups, RAG implementation is more technical – but there are companies/technologies out there that can make it easier to implement.
That’s why GPTs tend to work best for small or medium-scale projects or for non-technical teams focused on maintaining brand consistency.
RAG, on the other hand, is an option for enterprise-level content generation in industries where accuracy is critical and information changes frequently.
Create parameters so the model can self-assess the content before further editorial review. You can create a checklist of things to prompt it.
For example:
Even the best AI workflow still depends on trained editors and fact-checkers. This human layer of quality assurance protects accuracy, tone, and credibility.
About 33% of content writers and 24% of marketing managers added AI skills to their LinkedIn profiles in 2024.
Writers and editors need to continue to upskill in the coming year, and, according to the Microsoft 2025 annual Work Trend Index, AI skilling is the top priority.
Professional training creates baseline knowledge so your team gets up to speed faster and can confidently handle outputs consistently.
This includes training on how to effectively use LLMs and how to best create and edit AI content.
In addition, training content teams on SEO helps them build best practices into prompts and drafts.
Ground your AI-assisted content creation in editorial best practices to ensure the highest quality.
This might include:
Build a checklist to use during the review process for quality assurance. Here are some ideas to get you started:
AI is transforming how we create, but it doesn’t change why we create.
Every policy, workflow, and prompt should ultimately support one mission: to deliver accurate, helpful, and human-centered content that strengthens your brand’s authority and improves your visibility in search.
Dig deeper: An AI-assisted content process that outperforms human-only copy
Google's John Mueller said case sensitivity matters and SEOs shouldn't just hope it works.
The post Google’s Advice On Canonicals: They’re Case Sensitive appeared first on Search Engine Journal.
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“Large language models have well-known issues and constraints. And so if you want to solve complex problems, you’re going to want to adopt what’s called multi-method agentic AI, which combines large language models with other kinds of proven automation technologies so that you can build more adaptable, more transparent systems that are much more likely […]
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The post Google Arts & Culture Elevates Virtual Travel with AI Tours appeared first on StartupHub.ai.
Google Arts & Culture is redefining virtual exploration with new AI tours for North Gyeongsang, South Korea, featuring interactive, Gemini-powered commentary.
The post Google Arts & Culture Elevates Virtual Travel with AI Tours appeared first on StartupHub.ai.
The post Nvidia’s AI Imperative: Beyond Moore’s Law, Network is the New Compute appeared first on StartupHub.ai.
Michael Kagan, CTO of Nvidia and co-founder of Mellanox, recently engaged in a candid discussion with Sonya Huang and Pat Grady at Sequoia’s Europe100 event, offering profound insights into Nvidia’s meteoric rise as the architect of AI infrastructure. His commentary illuminated the pivotal role of the Mellanox acquisition in transforming Nvidia from a mere chip […]
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Amazon confirmed Tuesday that it is cutting about 14,000 corporate jobs, citing a need to reduce bureaucracy and become more efficient in the new era of artificial intelligence.
In a message to employees, posted on the company’s website, Amazon human resources chief Beth Galetti signaled that additional cutbacks are expected to take place into 2026, while indicating that the company will also continue to hire in key strategic areas.
Reuters reported Monday that the number of layoffs could ultimately total as many as 30,000 people, which is still a possibility as the cutbacks continue into next year. At that scale, the overall number of job cuts could eventually be the largest in Amazon’s history, exceeding the 27,000 positions that the company eliminated in 2023 across multiple rounds of layoffs.
“This generation of AI is the most transformative technology we’ve seen since the Internet, and it’s enabling companies to innovate much faster than ever before,” wrote Galetti, senior vice president of People Experience and Technology.
The goal is “to be organized more leanly, with fewer layers and more ownership, to move as quickly as possible for our customers and business,” she explained.
Galetti wrote that the company is “shifting resources to ensure we’re investing in our biggest bets and what matters most to our customers’ current and future needs” — indicating that layoff decisions are based whether teams and roles align with the company’s direction.
Amazon’s corporate workforce numbered around 350,000 people in early 2023, the last time the company provided a public number. At that scale, the initial reduction of 14,000 represents about 4% of Amazon’s corporate workforce. However, the number is a much smaller fraction of its overall workforce of 1.55 million people, which includes workers in its warehouses.
Cuts are expected across multiple regions and countries, but they are likely to hit hard in the Seattle region, home to the company’s first headquarters and its largest corporate workforce. The region has already felt the impact of major layoffs by Microsoft and others, as companies adjust to the uncertain economy and accelerate investments in AI-driven automation.
Many displaced tech workers here have found job searches slower and more competitive than in previous cycles in which the tech sector was more insulated than other industries.
The cuts at Amazon are the latest pullback after a pandemic-era hiring spree. They come two days before the company’s third quarter earnings report. Amazon and other cloud giants have been pouring billions into capital expenses to boost AI capacity. Cutting jobs is one way of showing operating-expense discipline to Wall Street.
In a memo to employees in June, Amazon CEO Andy Jassy wrote that he expected Amazon’s total corporate workforce to get smaller over time as a result of efficiency gains from AI.
Jassy took over as Amazon CEO from founder Jeff Bezos in mid-2021. In recent years he has been pushing to reduce management layers and eliminate bureaucracy inside the company, saying he wants Amazon to operate like the “world’s largest startup.”
Bloomberg News reported this week that Jassy has told colleagues that parts of the company remain “unwieldy” despite the 2023 layoffs and other efforts to streamline operations.
As part of its report, Reuters cited sources saying the magnitude of the cuts is also a result of Amazon’s strict return-to-office policy failing to cause enough employees to quit voluntarily. Amazon brought workers back five days a week earlier this year.
Impacted teams and people will be notified of the layoffs today, Galetti wrote.
Amazon is offering most impacted employees 90 days to find a new role internally, though the timing may vary based on local laws, according to the message. Those who do not find a new position at Amazon or choose to leave will be offered severance pay, outplacement services, health insurance benefits, and other forms of support.
John Carmack reports performance issues with Nvidia’s DGX Spark AI system John Carmack, ID Software founder and former CTO of Oculus VR, has been testing an Nvidia DGX Spark AI system. So far, he is not impressed by the performance the system has delivered. His system appears to be maxing out at 100 watts, which […]
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Battlefield is getting a free-to-play Battle Royale mode EA has confirmed that Battlefield REDSEC will launch on October 28th at 3 PM GMT, a free-to-play Battle Royale game that debuts alongside Battlefield 6’s Season 1 content. Battlefield REDSEC acts as EA’s counter to Call of Duty: Warzone. Currently, exact details for the new game are […]
The post Battlefield REDSEC is launching today – Here’s what you need to know appeared first on OC3D.
There's little doubt that The Matrix franchise is criminally underserved when it comes to videogame adaptations, despite being theoretically a perfect fit for the medium. In the 26 years since the original movie's theatrical debut, we only got two decent games: 2003's single player action/adventure game Enter the Matrix and 2005's MMORPG The Matrix Online. More recently, the interactive experience The Matrix Awakens was released in late 2021, but it was really just a tech demo for Unreal Engine 5 and a tease at the level of quality that gaming fans of the IP never really got to fully experience. […]
Read full article at https://wccftech.com/the-matrix-creators-wanted-kojima-make-a-game-on-the-ip-konami-refused/
Today at GTC 2025, NVIDIA's CEO, Jensen Huang, will deliver the opening keynote live from Washington, US, for the first time. NVIDIA GTC Comes To Washington, D.C, US: CEO Jensen Huang To Talk About Next Chapter of AI, Watch It Live Here NVIDIA's GTC 2025 is just a few hours away, and while you might be wondering, didn't GTC already happen a few months back? Well, it should be mentioned that while GTC used to be a one-time per annum affair in the past, the recent growth and success have turned NVIDIA's GTC into more of a quarterly event. As […]
Read full article at https://wccftech.com/watch-nvidia-gtc-2025-ceo-jensen-huang-keynote-live-washington-us/
The iPhone 17 lineup is expected to be Apple’s last to ship with Qualcomm’s 5G modems as the company prepares its transition to ship all of its iPhone 18 models with the C2 baseband chip. This in-house solution was said to be in development shortly after the iPhone 16e was announced, and while we will witness its materialization in 2026, a new report states that, unlike other Apple chipsets like the A20 and A20 Pro, it will not leverage TSMC’s newest 2nm process, but a lithography that is a couple of generations old. The C2 5G modem will reportedly be mass […]
Read full article at https://wccftech.com/apple-c2-to-be-mass-produced-on-older-tsmc-process-says-report/
A team of modders is working on Bully Online, a modification for the PC version of Bully: Scholarship Edition that promises to allow players to roam the grounds of Bullworth Academy and the nearby town with their friends. The Wii and Xbox 360 versions of Scholarship Edition did have a multiplayer mode, but it was limited to two players and only allowed them to face off in the class minigames. According to community creator SWEGTA, Bully Online promises much more, including free roam support, solo and group minigames, and even a role-playing system. They were able to add a 'fully […]
Read full article at https://wccftech.com/bully-online-mod-promises-let-you-roam-rockstars-classic-with-friends/
This morning, indie Chinese developer ChillyRoom unveiled Loulan: The Cursed Sand, one of the games funded through the PlayStation China Hero Project. The game is a hack 'n' slash action RPG viewed from a Diablo-like camera. The setting is the ancient Silk Road, in China's Western Regions. Loulan: The Cursed Sand tells the tragic love story of an exiled royal guard who returns to the titular fallen kingdom amidst the chaos of war in search of his beloved princess. Players will step into the game as the skeletal warrior known as 'The Cursed Sand', mastering the power of sand as […]
Read full article at https://wccftech.com/loulan-the-cursed-sand-chinese-hack-n-slash-arpg/
Samsung looks to be all set to announce its first triple-folding smartphone, the Galaxy Z TriFold, and even though the device is expected to be limited to a few markets, it was high time that we saw smartphones gravitate to a new form factor. Just before the official announcement happens, a series of images provides a first look at the Galaxy Z TriFold, showing a dual-infolding structure that can transform into a large-screen tablet. The Galaxy Z TriFold was on display at the Samsung booth at the K-Tech Showcase, with one report stating that the prototype did not display any […]
Read full article at https://wccftech.com/samsung-galaxy-z-trifold-first-look-image-gallery/
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The post On-Policy Distillation LLMs Redefine Post-Training Efficiency appeared first on StartupHub.ai.
On-policy distillation LLMs from Thinking Machines Lab offer a highly efficient and cost-effective method for post-training specialized smaller models, combining direct learning with dense feedback.
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The post Tensormesh exits stealth with $4.5M to slash AI inference caching costs appeared first on StartupHub.ai.
Tensormesh's AI inference caching technology eliminates redundant computation, promising to make enterprise AI cheaper and faster to run at scale.
The post Tensormesh exits stealth with $4.5M to slash AI inference caching costs appeared first on StartupHub.ai.
Self Hosted Project is platform to launch your own VPN server in minutes—no tech skills needed. Full root access, 32+ locations, total privacy. No KYC, no logs, 7 protocols. Just your server. VPN done right. Self-hosted. Self-controlled.
Meta plans to lay off more than 100 employees in Washington state as part of a broader round of cuts within its artificial intelligence division.
A new filing with the state’s Employment Security Department shows 101 employees impacted, including 48 in Bellevue, 23 in Seattle, and four in Redmond, along with 23 remote workers based in Washington.
The filing lists dozens of affected roles across Meta’s AI research and infrastructure units, including software engineers, AI researchers, and data scientists. Meta product managers, privacy specialists, and compliance analysts were also affected.
Meta is cutting around 600 positions in its AI unit, Axios reported last week. The company is investing heavily in AI and wants to create a “more agile operation,” according to an internal memo cited by Axios. Meta has just under 3,000 roles within its superintelligence lab, CNBC reported.
The separations at Meta in Washington take effect Dec. 22, according to the Worker Adjustment and Retraining Notification (WARN) notice filed Oct. 22.
Meta employs thousands of people across multiple offices in the Seattle region, one of its largest engineering hubs outside Menlo Park.
The latest reductions mark another contraction for Meta’s Pacific Northwest footprint following multiple rounds of layoffs over the past several years.
The company’s rapid expansion in Seattle over the past decade made it one of the emblems of the region’s tech boom, coinciding with Microsoft’s resurgence and Amazon’s rise.
Among the Bay Area titans, Google was among the first to establish a Seattle-area engineering office, way back in 2004. However, it was Facebook’s decision to open its own outpost across from Pike Place Market in 2010 that really got the attention of their Silicon Valley tech brethren.
In the decade that followed, out-of-town companies set up more than 130 engineering centers in the region.
However, more recently Meta has made moves to trim its Seattle-area footprint.
Apple earlier this year took over a building previously occupied by Meta in Seattle’s South Lake Union neighborhood, near Amazon’s headquarters. CoStar reported in April that Meta listed its other Arbor Blocks building for sublease.
Meta previously gobbled up much of the planned office space at the Spring District, a sprawling development northeast of downtown Bellevue, including a building that was originally going to be a new REI headquarters. But it has subleased some of the space since then to companies such as Snowflake, which recently took an entire building from Meta at the Spring District.
Meta’s office in Redmond, near Microsoft’s headquarters, is focused on its mixed reality development.
GeekWire has reached out to the company for an updated Seattle-area headcount.
Meta’s cuts come amid reported layoffs at Amazon that could impact up to 30,000 workers.
Tech companies have laid off more than 128,000 employees this year, according to Layoffs.fyi. Last year, companies cut nearly 153,000 positions.
Quietnet blocks ads, tracking, and harmful websites before they even reach your phone, laptop, or TV — no apps needed, and it works for every device in your home or office.
We make the internet faster, safer, and more private for families and small businesses — without the noise. We're not backed by big tech or VC money. We're privacy-focused, bootstrapped, and already seeing people pay for peace and quiet online. QuietNet is built by people who care — no ads, no tracking, just a cleaner, safer internet for your family or team.
AMD gains $3 billion by divesting from ZT Systems’ manufacturing business – retains key talent AMD has confirmed that it has officially divested from ZT Systems’ manufacturing business, selling it to Sanmina for $3 billion. This recoups most of AMD’s acquisition costs from its ZT Systems (ZTS) purchase earlier this year, and secures AMD a […]
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Voxtara is your personal AI speech coach that helps you become a more confident and effective public speaker. Whether you're preparing for a big presentation, teaching a class, or pitching to investors, Voxtara provides instant, actionable feedback to help you improve.
Key Features: • AI-Powered Analysis: Get comprehensive feedback on clarity, pacing, confidence, engagement, and body language • Video Recording: Record practice sessions up to 5 minutes • Deep-Dive Reports: Detailed analysis • Progress Tracking: Watch your speaking skills improve over time with detailed analytics • Practice Reminders: Set custom reminders • Session History: Review past performances
Today, we announced a collaboration with NextEra Energy to accelerate nuclear deployment across the U.S., including the restart of the Duane Arnold Energy Center in Iowa…
These quick tips could help you get more traction with your email outreach.
With cyber scams on the increase, TikTok is looking to help raise awareness among its user community.
YouTube launched Ask Studio, an AI assistant in YouTube Studio that analyzes channel data to surface comment insights, performance analysis, and content ideas.
The post YouTube Introduces ‘Ask Studio’ AI For Channel Analytics appeared first on Search Engine Journal.
OpenAI is telling companies that “relationship building” with AI has limits. Emotional dependence on ChatGPT is considered a safety risk, with new guardrails in place.
The post OpenAI Flags Emotional Reliance On ChatGPT As A Safety Risk appeared first on Search Engine Journal.
The post Edge AI: The Key to Sustainable AI Energy Efficiency appeared first on StartupHub.ai.
Arm and SCSP's new paper highlights edge computing as the strategic imperative for achieving AI energy efficiency and securing U.S. competitiveness.
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AMD and the DOE are launching Lux and Discovery supercomputers at ORNL, a $1 billion investment to establish secure U.S. Sovereign AI infrastructure.
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The post ASEAN’s AI Ambition: Infrastructure, Innovation, and Tailored Governance appeared first on StartupHub.ai.
“Infrastructure is destiny,” declared James Hairston, Head of International Policy & Partnerships for Asia, Africa, & Latin America at OpenAI, encapsulating the strategic imperative facing Southeast Asia in the burgeoning age of artificial intelligence. This powerful statement set the stage for a compelling discussion at the Bloomberg Business Summit at ASEAN in Kuala Lumpur, where […]
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Microsoft’s efforts to include its Copilot AI in as many of its services and products as possible has landed the company in some hot water. The Australian Competition and Consumer Commission (ACCC) is taking the company to court, accusing the software giant of misleading customers with its integration of Copilot into Microsoft 365 plans.
This
Retroid is making waves in the handheld gaming space—a year after the September release of the Retroid Pocket 5, Retroid is following up with both a proper Retroid Pocket 6 and a Retroid Pocket G2, the latter of which serves as a souped-up refresh of Pocket 5 with the same external shell. Both handhelds are targeting a similar $200-$300 USD
Since the bombshell announcement of new Halo installment coming to PlayStation just two days ago, the wider public seems convinced that Xbox's battle in the console war is over. And now, comments made by Xbox Game Studios head Matt Booty seem to be lending credence to that, declaring TikTok a bigger competitor to Xbox than PlayStation. There's
OCCT 15 delivers a major update with a new storage test modeled after CrystalDiskMark, plus enhanced GPU diagnostics through an improved 3D adaptive test that detects errors more precisely and adds a coil-whine detection feature.
So, I stumbled upon this interesting portable monitor, which is unusually large to be called "portable", but considering there are users who would want something that can be useful for both travel and regular use, the UMax 24 looked interesting. I have reviewed a few UPERFECT portable monitors, including the Dual-Stack UStation Delta Max, which is one of the best options for work and gaming. However, UMax's big 24.5-inch screen size makes it an interesting option for daily usage if you are considering a versatile option for your desktop and travel. Personally, I wanted to see if I could replace […]
Read full article at https://wccftech.com/review/uperfect-umax-24-portable-monitor-review/
Apple will eventually introduce the M5 MacBook Air in a few months now that it has officially started selling the M5 MacBook Pro, but you will not immediately see the discounts on the company’s newer portable Macs, making the M4 MacBook Air models a more attractive proposition. Why? Because Amazon has slashed both the 13-inch and 15-inch versions by $200, and best of all, you can configure these machines up to 24GB unified RAM and a 512GB SSD. The base model starts from $799, making it an instant steal. The M5 MacBook Air will likely adopt the same ‘fanless’ cooling […]
Read full article at https://wccftech.com/do-not-wait-for-the-m5-macbook-air-because-amazon-offers-200-off-on-m4-macbook-air/
Halo: Campaign Evolved marked the official confirmation of something that felt like it would never happen just a short few years ago, with Halo officially coming to PlayStation. Following that announcement, GameStop, the retailer that was initially known for selling physical video games that's now more known for turning into a glorified Pop Funko and merch store called the 'Console Wars' over. Of all entities, the White House, which would normally have more important things to post about, responded with an AI-generated image of President Trump in Spartan armor with the caption "Power to the players." GameStop's original post comes […]
Read full article at https://wccftech.com/gamestop-console-wars-over-halo-on-ps-white-house-trump-ai-spartan-armor/
Gearbox founder Randy Pitchford was recently interviewed by Shacknews alongside a few other colleagues to discuss the making of Borderlands 4, the studio's latest game, which was released on September 12. The video runs for 73 minutes, and right toward the end, Pitchford goes into exactly what is needed to create such a big videogame like Borderlands 4. Interestingly, he then adds that the gaming industry as a whole is just getting started and 'figuring out' videogames, which haven't yet received their 'Citizen Kane' moment yet. To make a game like Borderlands 4 takes a big investment. It's a massive, […]
Read full article at https://wccftech.com/borderlands-boss-gaming-hasnt-even-produced-single-masterpiece-yet/
Qualcomm has announced its latest AI chips, which are designed to scale up to a purpose-built rack-level AI inference solution, but interestingly, they employ mobile memory onboard. Qualcomm's New AI Chips Take a 'Daring' Pivot Away From HBM To Target Efficient Inferencing Workloads Qualcomm has come a long way from being a mobile-focused firm, and in recent years, the San Diego chipmaker has expanded into new segments, including consumer computing and AI infrastructure. Now, the firm has announced its newest AI200 and AI250 chip solutions, which are reportedly designed for rack-scale configurations. This not only marks the entry of a […]
Read full article at https://wccftech.com/qualcomm-new-ai-rack-scale-solution-actually-uses-lpddr-mobile-memory-onboard/
Watch out, DeepSeek and Qwen! There's a new king of open source large language models (LLMs), especially when it comes to something enterprises are increasingly valuing: agentic tool use — that is, the ability to go off and use other software capabilities like web search or bespoke applications — without much human guidance.
That model is none other than MiniMax-M2, the latest LLM from the Chinese startup of the same name. And in a big win for enterprises globally, the model is available under a permissive, enterprise-friendly MIT License, meaning it is made available freely for developers to take, deploy, retrain, and use how they see fit — even for commercial purposes. It can be found on Hugging Face, GitHub and ModelScope, as well as through MiniMax's API here. It supports OpenAI and Anthropic API standards, as well, making it easy for customers of said proprietary AI startups to shift out their models to MiniMax's API, if they want.
According to independent evaluations by Artificial Analysis, a third-party generative AI model benchmarking and research organization, M2 now ranks first among all open-weight systems worldwide on the Intelligence Index—a composite measure of reasoning, coding, and task-execution performance.
In agentic benchmarks that measure how well a model can plan, execute, and use external tools—skills that power coding assistants and autonomous agents—MiniMax’s own reported results, following the Artificial Analysis methodology, show τ²-Bench 77.2, BrowseComp 44.0, and FinSearchComp-global 65.5.
These scores place it at or near the level of top proprietary systems like GPT-5 (thinking) and Claude Sonnet 4.5, making MiniMax-M2 the highest-performing open model yet released for real-world agentic and tool-calling tasks.
Built around an efficient Mixture-of-Experts (MoE) architecture, MiniMax-M2 delivers high-end capability for agentic and developer workflows while remaining practical for enterprise deployment.
For technical decision-makers, the release marks an important turning point for open models in business settings. MiniMax-M2 combines frontier-level reasoning with a manageable activation footprint—just 10 billion active parameters out of 230 billion total.
This design enables enterprises to operate advanced reasoning and automation workloads on fewer GPUs, achieving near-state-of-the-art results without the infrastructure demands or licensing costs associated with proprietary frontier systems.
Artificial Analysis’ data show that MiniMax-M2’s strengths go beyond raw intelligence scores. The model leads or closely trails top proprietary systems such as GPT-5 (thinking) and Claude Sonnet 4.5 across benchmarks for end-to-end coding, reasoning, and agentic tool use.
Its performance in τ²-Bench, SWE-Bench, and BrowseComp indicates particular advantages for organizations that depend on AI systems capable of planning, executing, and verifying complex workflows—key functions for agentic and developer tools inside enterprise environments.
As LLM engineer Pierre-Carl Langlais aka Alexander Doria posted on X: "MiniMax [is] making a case for mastering the technology end-to-end to get actual agentic automation."
MiniMax-M2’s technical architecture is a sparse Mixture-of-Experts model with 230 billion total parameters and 10 billion active per inference.
This configuration significantly reduces latency and compute requirements while maintaining broad general intelligence.
The design allows for responsive agent loops—compile–run–test or browse–retrieve–cite cycles—that execute faster and more predictably than denser models.
For enterprise technology teams, this means easier scaling, lower cloud costs, and reduced deployment friction. According to Artificial Analysis, the model can be served efficiently on as few as four NVIDIA H100 GPUs at FP8 precision, a setup well within reach for mid-size organizations or departmental AI clusters.
MiniMax’s benchmark suite highlights strong real-world performance across developer and agent environments. The figure below, released with the model, compares MiniMax-M2 (in red) with several leading proprietary and open models, including GPT-5 (thinking), Claude Sonnet 4.5, Gemini 2.5 Pro, and DeepSeek-V3.2.
MiniMax-M2 achieves top or near-top performance in many categories:
SWE-bench Verified: 69.4 — close to GPT-5’s 74.9
ArtifactsBench: 66.8 — above Claude Sonnet 4.5 and DeepSeek-V3.2
τ²-Bench: 77.2 — approaching GPT-5’s 80.1
GAIA (text only): 75.7 — surpassing DeepSeek-V3.2
BrowseComp: 44.0 — notably stronger than other open models
FinSearchComp-global: 65.5 — best among tested open-weight systems
These results show MiniMax-M2’s capability in executing complex, tool-augmented tasks across multiple languages and environments—skills increasingly relevant for automated support, R&D, and data analysis inside enterprises.
The model’s overall intelligence profile is confirmed in the latest Artificial Analysis Intelligence Index v3.0, which aggregates performance across ten reasoning benchmarks including MMLU-Pro, GPQA Diamond, AIME 2025, IFBench, and τ²-Bench Telecom.
MiniMax-M2 scored 61 points, ranking as the highest open-weight model globally and following closely behind GPT-5 (high) and Grok 4.
Artificial Analysis highlighted the model’s balance between technical accuracy, reasoning depth, and applied intelligence across domains. For enterprise users, this consistency indicates a reliable model foundation suitable for integration into software engineering, customer support, or knowledge automation systems.
MiniMax engineered M2 for end-to-end developer workflows, enabling multi-file code edits, automated testing, and regression repair directly within integrated development environments or CI/CD pipelines.
The model also excels in agentic planning—handling tasks that combine web search, command execution, and API calls while maintaining reasoning traceability.
These capabilities make MiniMax-M2 especially valuable for enterprises exploring autonomous developer agents, data analysis assistants, or AI-augmented operational tools.
Benchmarks such as Terminal-Bench and BrowseComp demonstrate the model’s ability to adapt to incomplete data and recover gracefully from intermediate errors, improving reliability in production settings.
A distinctive aspect of MiniMax-M2 is its interleaved thinking format, which maintains visible reasoning traces between <think>...</think> tags.
This enables the model to plan and verify steps across multiple exchanges, a critical feature for agentic reasoning. MiniMax advises retaining these segments when passing conversation history to preserve the model’s logic and continuity.
The company also provides a Tool Calling Guide on Hugging Face, detailing how developers can connect external tools and APIs via structured XML-style calls.
This functionality allows MiniMax-M2 to serve as the reasoning core for larger agent frameworks, executing dynamic tasks such as search, retrieval, and computation through external functions.
Enterprises can access the model through the MiniMax Open Platform API and MiniMax Agent interface (a web chat similar to ChatGPT), both currently free for a limited time.
MiniMax recommends SGLang and vLLM for efficient serving, each offering day-one support for the model’s unique interleaved reasoning and tool-calling structure.
Deployment guides and parameter configurations are available through MiniMax’s documentation.
As Artificial Analysis noted, MiniMax’s API pricing is set at $0.30 per million input tokens and $1.20 per million output tokens, among the most competitive in the open-model ecosystem.
Provider | Model (doc link) | Input $/1M | Output $/1M | Notes |
MiniMax | $0.30 | $1.20 | Listed under “Chat Completion v2” for M2. | |
OpenAI | $1.25 | $10.00 | Flagship model pricing on OpenAI’s API pricing page. | |
OpenAI | $0.25 | $2.00 | Cheaper tier for well-defined tasks. | |
Anthropic | $3.00 | $15.00 | Anthropic’s current per-MTok list; long-context (>200K input) uses a premium tier. | |
$0.30 | $2.50 | Prices include “thinking tokens”; page also lists cheaper Flash-Lite and 2.0 tiers. | ||
xAI | $0.20 | $0.50 | “Fast” tier; xAI also lists Grok-4 at $3 / $15. | |
DeepSeek | $0.28 | $0.42 | Cache-hit input is $0.028; table shows per-model details. | |
Qwen (Alibaba) | from $0.022 | from $0.216 | Tiered by input size (≤128K, ≤256K, ≤1M tokens); listed “Input price / Output price per 1M”. | |
Cohere | $2.50 | $10.00 | First-party pricing page also lists Command R ($0.50 / $1.50) and others. |
Notes & caveats (for readers):
Prices are USD per million tokens and can change; check linked pages for updates and region/endpoint nuances (e.g., Anthropic long-context >200K input, Google Live API variants, cache discounts).
Vendors may bill extra for server-side tools (web search, code execution) or offer batch/context-cache discounts.
While the model produces longer, more explicit reasoning traces, its sparse activation and optimized compute design help maintain a favorable cost-performance balance—an advantage for teams deploying interactive agents or high-volume automation systems.
MiniMax has quickly become one of the most closely watched names in China’s fast-rising AI sector.
Backed by Alibaba and Tencent, the company moved from relative obscurity to international recognition within a year—first through breakthroughs in AI video generation, then through a series of open-weight large language models (LLMs) aimed squarely at developers and enterprises.
The company first captured global attention in late 2024 with its AI video generation tool, “video-01,” which demonstrated the ability to create dynamic, cinematic scenes in seconds. VentureBeat described how the model’s launch sparked widespread interest after online creators began sharing lifelike, AI-generated footage—most memorably, a viral clip of a Star Wars lightsaber duel that drew millions of views in under two days.
CEO Yan Junjie emphasized that the system outperformed leading Western tools in generating human movement and expression, an area where video AIs often struggle. The product, later commercialized through MiniMax’s Hailuo platform, showcased the startup’s technical confidence and creative reach, helping to establish China as a serious contender in generative video technology.
By early 2025, MiniMax had turned its attention to long-context language modeling, unveiling the MiniMax-01 series, including MiniMax-Text-01 and MiniMax-VL-01. These open-weight models introduced an unprecedented 4-million-token context window, doubling the reach of Google’s Gemini 1.5 Pro and dwarfing OpenAI’s GPT-4o by more than twentyfold.
The company continued its rapid cadence with the MiniMax-M1 release in June 2025, a model focused on long-context reasoning and reinforcement learning efficiency. M1 extended context capacity to 1 million tokens and introduced a hybrid Mixture-of-Experts design trained using a custom reinforcement-learning algorithm known as CISPO. Remarkably, VentureBeat reported that MiniMax trained M1 at a total cost of about $534,700, roughly one-tenth of DeepSeek’s R1 and far below the multimillion-dollar budgets typical for frontier-scale models.
For enterprises and technical teams, MiniMax’s trajectory signals the arrival of a new generation of cost-efficient, open-weight models designed for real-world deployment. Its open licensing—ranging from Apache 2.0 to MIT—gives businesses freedom to customize, self-host, and fine-tune without vendor lock-in or compliance restrictions.
Features such as structured function calling, long-context retention, and high-efficiency attention architectures directly address the needs of engineering groups managing multi-step reasoning systems and data-intensive pipelines.
As MiniMax continues to expand its lineup, the company has emerged as a key global innovator in open-weight AI, combining ambitious research with pragmatic engineering.
The release of MiniMax-M2 reinforces the growing leadership of Chinese AI research groups in open-weight model development.
Following earlier contributions from DeepSeek, Alibaba’s Qwen series, and Moonshot AI, MiniMax’s entry continues the trend toward open, efficient systems designed for real-world use.
Artificial Analysis observed that MiniMax-M2 exemplifies a broader shift in focus toward agentic capability and reinforcement-learning refinement, prioritizing controllable reasoning and real utility over raw model size.
For enterprises, this means access to a state-of-the-art open model that can be audited, fine-tuned, and deployed internally with full transparency.
By pairing strong benchmark performance with open licensing and efficient scaling, MiniMaxAI positions MiniMax-M2 as a practical foundation for intelligent systems that think, act, and assist with traceable logic—making it one of the most enterprise-ready open AI models available today.
Anthropic is making its most aggressive push yet into the trillion-dollar financial services industry, unveiling a suite of tools that embed its Claude AI assistant directly into Microsoft Excel and connect it to real-time market data from some of the world's most influential financial information providers.
The San Francisco-based AI startup announced Monday it is releasing Claude for Excel, allowing financial analysts to interact with the AI system directly within their spreadsheets — the quintessential tool of modern finance. Beyond Excel, select Claude models are also being made available in Microsoft Copilot Studio and Researcher agent, expanding the integration across Microsoft's enterprise AI ecosystem. The integration marks a significant escalation in Anthropic's campaign to position itself as the AI platform of choice for banks, asset managers, and insurance companies, markets where precision and regulatory compliance matter far more than creative flair.
The expansion comes just three months after Anthropic launched its Financial Analysis Solution in July, and it signals the company's determination to capture market share in an industry projected to spend $97 billion on AI by 2027, up from $35 billion in 2023.
More importantly, it positions Anthropic to compete directly with Microsoft — ironically, its partner in this Excel integration — which has its own Copilot AI assistant embedded across its Office suite, and with OpenAI, which counts Microsoft as its largest investor.
The decision to build directly into Excel is hardly accidental. Excel remains the lingua franca of finance, the digital workspace where analysts spend countless hours constructing financial models, running valuations, and stress-testing assumptions. By embedding Claude into this environment, Anthropic is meeting financial professionals exactly where they work rather than asking them to toggle between applications.
Claude for Excel allows users to work with the AI in a sidebar where it can read, analyze, modify, and create new Excel workbooks while providing full transparency about the actions it takes by tracking and explaining changes and letting users navigate directly to referenced cells.
This transparency feature addresses one of the most persistent anxieties around AI in finance: the "black box" problem. When billions of dollars ride on a financial model's output, analysts need to understand not just the answer but how the AI arrived at it. By showing its work at the cell level, Anthropic is attempting to build the trust necessary for widespread adoption in an industry where careers and fortunes can turn on a misplaced decimal point.
The technical implementation is sophisticated. Claude can discuss how spreadsheets work, modify them while preserving formula dependencies — a notoriously complex task — debug cell formulas, populate templates with new data, or build entirely new spreadsheets from scratch. This isn't merely a chatbot that answers questions about your data; it's a collaborative tool that can actively manipulate the models that drive investment decisions worth trillions of dollars.
Perhaps more significant than the Excel integration is Anthropic's expansion of its connector ecosystem, which now links Claude to live market data and proprietary research from financial information giants. The company added six major new data partnerships spanning the entire spectrum of financial information that professional investors rely upon.
Aiera now provides Claude with real-time earnings call transcripts and summaries of investor events like shareholder meetings, presentations, and conferences. The Aiera connector also enables a data feed from Third Bridge, which gives Claude access to a library of insights interviews, company intelligence, and industry analysis from experts and former executives. Chronograph gives private equity investors operational and financial information for portfolio monitoring and conducting due diligence, including performance metrics, valuations, and fund-level data.
Egnyte enables Claude to securely search permitted data for internal data rooms, investment documents, and approved financial models while maintaining governed access controls. LSEG, the London Stock Exchange Group, connects Claude to live market data including fixed income pricing, equities, foreign exchange rates, macroeconomic indicators, and analysts' estimates of other important financial metrics. Moody's provides access to proprietary credit ratings, research, and company data covering ownership, financials, and news on more than 600 million public and private companies, supporting work and research in compliance, credit analysis, and business development. MT Newswires provides Claude with access to the latest global multi-asset class news on financial markets and economies.
These partnerships amount to a land grab for the informational infrastructure that powers modern finance. Previously announced in July, Anthropic had already secured integrations with S&P Capital IQ, Daloopa, Morningstar, FactSet, PitchBook, Snowflake, and Databricks. Together, these connectors give Claude access to virtually every category of financial data an analyst might need: fundamental company data, market prices, credit assessments, private company intelligence, alternative data, and breaking news.
This matters because the quality of AI outputs depends entirely on the quality of inputs. Generic large language models trained on public internet data simply cannot compete with systems that have direct pipelines to Bloomberg-quality financial information. By securing these partnerships, Anthropic is building moats around its financial services offering that competitors will find difficult to replicate.
The strategic calculus here is clear: Anthropic is betting that domain-specific AI systems with privileged access to proprietary data will outcompete general-purpose AI assistants. It's a direct challenge to the "one AI to rule them all" approach favored by some competitors.
The third pillar of Anthropic's announcement involves six new "Agent Skills" — pre-configured workflows for common financial tasks. These skills are Anthropic's attempt to productize the workflows of entry-level and mid-level financial analysts, professionals who spend their days building models, processing due diligence documents, and writing research reports. Anthropic has designed skills specifically to automate these time-consuming tasks.
The new skills include building discounted cash flow models complete with full free cash flow projections, weighted average cost of capital calculations, scenario toggles, and sensitivity tables. There's comparable company analysis featuring valuation multiples and operating metrics that can be easily refreshed with updated data. Claude can now process data room documents into Excel spreadsheets populated with financial information, customer lists, and contract terms. It can create company teasers and profiles for pitch books and buyer lists, perform earnings analyses that use quarterly transcripts and financials to extract important metrics, guidance changes, and management commentary, and produce initiating coverage reports with industry analysis, company deep dives, and valuation frameworks.
It's worth noting that Anthropic's Sonnet 4.5 model now tops the Finance Agent benchmark from Vals AI at 55.3% accuracy, a metric designed to test AI systems on tasks expected of entry-level financial analysts. A 55% accuracy rate might sound underwhelming, but it is state-of-the-art performance and highlights both the promise and limitations of AI in finance. The technology can clearly handle sophisticated analytical tasks, but it's not yet reliable enough to operate autonomously without human oversight — a reality that may actually reassure both regulators and the analysts whose jobs might otherwise be at risk.
The Agent Skills approach is particularly clever because it packages AI capabilities in terms that financial institutions already understand. Rather than selling generic "AI assistance," Anthropic is offering solutions to specific, well-defined problems: "You need a DCF model? We have a skill for that. You need to analyze earnings calls? We have a skill for that too."
Anthropic's financial services strategy appears to be gaining traction with exactly the kind of marquee clients that matter in enterprise sales. The company counts among its clients AIA Labs at Bridgewater, Commonwealth Bank of Australia, American International Group, and Norges Bank Investment Management — Norway's $1.6 trillion sovereign wealth fund, one of the world's largest institutional investors.
NBIM CEO Nicolai Tangen reported achieving approximately 20% productivity gains, equivalent to 213,000 hours, with portfolio managers and risk departments now able to "seamlessly query our Snowflake data warehouse and analyze earnings calls with unprecedented efficiency."
At AIG, CEO Peter Zaffino said the partnership has "compressed the timeline to review business by more than 5x in our early rollouts while simultaneously improving our data accuracy from 75% to over 90%." If these numbers hold across broader deployments, the productivity implications for the financial services industry are staggering.
These aren't pilot programs or proof-of-concept deployments; they're production implementations at institutions managing trillions of dollars in assets and making underwriting decisions that affect millions of customers. Their public endorsements provide the social proof that typically drives enterprise adoption in conservative industries.
Yet Anthropic's financial services ambitions unfold against a backdrop of heightened regulatory scrutiny and shifting enforcement priorities. In 2023, the Consumer Financial Protection Bureau released guidance requiring lenders to "use specific and accurate reasons when taking adverse actions against consumers" involving AI, and issued additional guidance requiring regulated entities to "evaluate their underwriting models for bias" and "evaluate automated collateral-valuation and appraisal processes in ways that minimize bias."
However, according to a Brookings Institution analysis, these measures have since been revoked with work stopped or eliminated at the current downsized CFPB under the current administration, creating regulatory uncertainty. The pendulum has swung from the Biden administration's cautious approach, exemplified by an executive order on safe AI development, toward the Trump administration's "America's AI Action Plan," which seeks to "cement U.S. dominance in artificial intelligence" through deregulation.
This regulatory flux creates both opportunities and risks. Financial institutions eager to deploy AI now face less prescriptive federal oversight, potentially accelerating adoption. But the absence of clear guardrails also exposes them to potential liability if AI systems produce discriminatory outcomes, particularly in lending and underwriting.
The Massachusetts Attorney General recently reached a $2.5 million settlement with student loan company Earnest Operations, alleging that its use of AI models resulted in "disparate impact in approval rates and loan terms, specifically disadvantaging Black and Hispanic applicants." Such cases will likely multiply as AI deployment grows, creating a patchwork of state-level enforcement even as federal oversight recedes.
Anthropic appears acutely aware of these risks. In an interview with Banking Dive, Jonathan Pelosi, Anthropic's global head of industry for financial services, emphasized that Claude requires a "human in the loop." The platform, he said, is not intended for autonomous financial decision-making or to provide stock recommendations that users follow blindly. During client onboarding, Pelosi told the publication, Anthropic focuses on training and understanding model limitations, putting guardrails in place so people treat Claude as a helpful technology rather than a replacement for human judgment.
Anthropic's financial services push comes as AI competition intensifies across the enterprise. OpenAI, Microsoft, Google, and numerous startups are all vying for position in what may become one of AI's most lucrative verticals. Goldman Sachs introduced a generative AI assistant to its bankers, traders, and asset managers in January, signaling that major banks may build their own capabilities rather than rely exclusively on third-party providers.
The emergence of domain-specific AI models like BloombergGPT — trained specifically on financial data — suggests the market may fragment between generalized AI assistants and specialized tools. Anthropic's strategy appears to stake out a middle ground: general-purpose models, since Claude was not trained exclusively on financial data, enhanced with financial-specific tooling, data access, and workflows.
The company's partnership strategy with implementation consultancies including Deloitte, KPMG, PwC, Slalom, TribeAI, and Turing is equally critical. These firms serve as force multipliers, embedding Anthropic's technology into their own service offerings and providing the change management expertise that financial institutions need to successfully adopt AI at scale.
The broader question is whether AI tools like Claude will genuinely transform financial services productivity or merely shift work around. The PYMNTS Intelligence report "The Agentic Trust Gap" found that chief financial officers remain hesitant about AI agents, with "nagging concern" about hallucinations where "an AI agent can go off script and expose firms to cascading payment errors and other inaccuracies."
"For finance leaders, the message is stark: Harness AI's momentum now, but build the guardrails before the next quarterly call—or risk owning the fallout," the report warned.
A 2025 KPMG report found that 70% of board members have developed responsible use policies for employees, with other popular initiatives including implementing a recognized AI risk and governance framework, developing ethical guidelines and training programs for AI developers, and conducting regular AI use audits.
The financial services industry faces a delicate balancing act: move too slowly and risk competitive disadvantage as rivals achieve productivity gains; move too quickly and risk operational failures, regulatory penalties, or reputational damage. Speaking at the Evident AI Symposium in New York last week, Ian Glasner, HSBC's group head of emerging technology, innovation and ventures, struck an optimistic tone about the sector's readiness for AI adoption. "As an industry, we are very well prepared to manage risk," he said, according to CIO Dive. "Let's not overcomplicate this. We just need to be focused on the business use case and the value associated."
Anthropic's latest moves suggest the company sees financial services as a beachhead market where AI's value proposition is clear, customers have deep pockets, and the technical requirements play to Claude's strengths in reasoning and accuracy. By building Excel integration, securing data partnerships, and pre-packaging common workflows, Anthropic is reducing the friction that typically slows enterprise AI adoption.
The $61.5 billion valuation the company commanded in its March fundraising round — up from roughly $16 billion a year earlier — suggests investors believe this strategy will work. But the real test will come as these tools move from pilot programs to production deployments across thousands of analysts and billions of dollars in transactions.
Financial services may prove to be AI's most demanding proving ground: an industry where mistakes are costly, regulation is stringent, and trust is everything. If Claude can successfully navigate the spreadsheet cells and data feeds of Wall Street without hallucinating a decimal point in the wrong direction, Anthropic will have accomplished something far more valuable than winning another benchmark test. It will have proven that AI can be trusted with the money.
Some enterprises are best served by fine-tuning large models to their needs, but a number of companies plan to build their own models, a project that would require access to GPUs.
Google Cloud wants to play a bigger role in enterprises’ model-making journey with its new service, Vertex AI Training. The service gives enterprises looking to train their own models access to a managed Slurm environment, data science tooling and any chips capable of large-scale model training.
With this new service, Google Cloud hopes to turn more enterprises away from other providers and encourage the building of more company-specific AI models.
While Google Cloud has always offered the ability to customize its Gemini models, the new service allows customers to bring in their own models or customize any open-source model Google Cloud hosts.
Vertex AI Training positions Google Cloud directly against companies like CoreWeave and Lambda Labs, as well as its cloud competitors AWS and Microsoft Azure.
Jaime de Guerre, senior director of product management at Gloogle Cloud, told VentureBeat that the company has been hearing from a lot of organizations of varying sizes that they need a way to better optimize compute but in a more reliable environment.
“What we're seeing is that there's an increasing number of companies that are building or customizing large gen AI models to introduce a product offering built around those models, or to help power their business in some way,” de Guerre said. “This includes AI startups, technology companies, sovereign organizations building a model for a particular region or culture or language and some large enterprises that might be building it into internal processes.”
De Guerre noted that while anyone can technically use the service, Google is targeting companies planning large-scale model training rather than simple fine-tuning or LoRA adopters. Vertex AI Services will focus on longer-running training jobs spanning hundreds or even thousands of chips. Pricing will depend on the amount of compute the enterprise will need.
“Vertex AI Training is not for adding more information to the context or using RAG; this is to train a model where you might start from completely random weights,” he said.
Enterprises are recognizing the value of building customized models beyond just fine-tuning an LLM via retrieval-augmented generation (RAG). Custom models would know more in-depth company information and respond with answers specific to the organization. Companies like Arcee.ai have begun offering their models for customization to clients. Adobe recently announced a new service that allows enterprises to retrain Firefly for their specific needs. Organizations like FICO, which create small language models specific to the finance industry, often buy GPUs to train them at significant cost.
Google Cloud said Vertex AI Training differentiates itself by giving access to a larger set of chips, services to monitor and manage training and the expertise it learned from training the Gemini models.
Some early customers of Vertex AI Training include AI Singapore, a consortium of Singaporean research institutes and startups that built the 27-billion-parameter SEA-LION v4, and Salesforce’s AI research team.
Enterprises often have to choose between taking an already-built LLM and fine-tuning it or building their own model. But creating an LLM from scratch is usually unattainable for smaller companies, or it simply doesn’t make sense for some use cases. However, for organizations where a fully custom or from-scratch model makes sense, the issue is gaining access to the GPUs needed to run training.
Training a model, de Guerre said, can be difficult and expensive, especially when organizations compete with several others for GPU space.
Hyperscalers like AWS and Microsoft — and, yes, Google — have pitched that their massive data centers and racks and racks of high-end chips deliver the most value to enterprises. Not only will they have access to expensive GPUs, but cloud providers often offer full-stack services to help enterprises move to production.
Services like CoreWeave gained prominence for offering on-demand access to Nvidia H100s, giving customers flexibility in compute power when building models or applications. This has also given rise to a business model in which companies with GPUs rent out server space.
De Guerre said Vertex AI Training isn’t just about offering access to train models on bare compute, where the enterprise rents a GPU server; they also have to bring their own training software and manage the timing and failures.
“This is a managed Slurm environment that will help with all the job scheduling and automatic recovery of jobs failing,” de Guerre said. “So if a training job slows down or stops due to a hardware failure, the training will automatically restart very quickly, based on automatic checkpointing that we do in management of the checkpoints to continue with very little downtime.”
He added that this provides higher throughput and more efficient training for a larger scale of compute clusters.
Services like Vertex AI Training could make it easier for enterprises to build niche models or completely customize existing models. Still, just because the option exists doesn’t mean it's the right fit for every enterprise.
A new framework developed by researchers at Google Cloud and DeepMind aims to address one of the key challenges of developing computer use agents (CUAs): Gathering high-quality training examples at scale.
The framework, dubbed Watch & Learn (W&L), addresses the problem of training data generation in a way that doesn’t require human annotation and can automatically extract demonstrations from raw videos.
Their experiments show that data generated W&L can be used to train or fine-tune existing computer use and foundation models to improve their performance on computer-use tasks. But equally important, the same approach can be used to create in-context learning (ICL) examples for computer use agents, enabling companies to create CUAs for bespoke internal tasks without the need for costly training of specialized models.
The web is rich with video tutorials and screencasts that describe complex workflows for using applications. These videos are a gold mine that can provide computer use agents with domain knowledge and instructions for accomplishing different tasks through user interface interactions.
However, before they can be used to train CUA agents, these videos need to be transformed into annotated trajectories (that is, a set of task descriptions, screenshots and actions), a process that is prohibitively expensive and time-consuming when done manually.
Existing approaches to address this data bottleneck rely on annotating these videos through the use of multimodal language models, which usually result in low precision and faulty examples. A different approach uses self-play agents that autonomously explore user interfaces to collect trajectories. However, techniques using this approach usually create simple examples that are not useful in unpredictable real-world situations.
As the researchers note in their paper, “Overall, these approaches either rely on brittle heuristics, are costly as they rely on explorations in real environments or generate low-complexity demonstrations misaligned with human intent.”
The Watch & Learn framework tries to address the challenges of creating CUA demonstrations by rethinking the problem formulation.
Instead of directly generating trajectories or depending on complex multi-stage pipelines, the researchers frame the problem as an “inverse dynamics objective”: Given two consecutive observations, predict the intermediate action that produced the transition.
According to the researchers, this formulation is “easier to learn, avoids hand-crafted heuristics and generalizes robustly across applications.”
The W&L framework can be broken down into three key stages: Training an inverse dynamics model (IDM), retrieving raw videos, and training CUA agents.
In the first phase, the researchers used agents to interact with live web pages to create a large corpus of 500,000 state transitions (two consecutive observations and the action that resulted in the transition). They then used this data (along with 132,000 human-annotated transitions from existing open datasets) to train an inverse dynamics model (IDM) that takes in two consecutive observations and predicts the transition action. Their trained IDM, which is a small transformer model, outperformed off-the-shelf foundation models in predicting transition actions.
The researchers then designed a pipeline that retrieves videos from platforms such as YouTube and runs them through IDM to generate high-quality trajectories. The IDM takes in consecutive video frames and determines the actions (scroll, click) that caused the changes in the environment, which are then packaged into annotated trajectories. Using this method, they generated 53,125 trajectories with high-accuracy action labels.
These examples can be used to train effective computer use models for specific tasks. But the researchers also found that trajectories extracted through IDM can serve as in-context learning examples to improve the performance of CUAs on bespoke tasks at inference time. For ICL, they use Gemini 2.5 Flash to add additional reasoning annotations to the observation/action examples in the trajectories, which can then be inserted into the CUA agent’s prompt (usually 3-5 examples) during inference.
“This dual role (training and in-context guidance) enables flexible integration with both open-source models and general-purpose agents,” the researchers write.
To test the usefulness of W&L, the researchers ran a series of experiments with closed and open source models on the OSWorld benchmark, which evaluates agents in real desktop and operating system environments across different tasks, including productivity, programming and design.
For fine-tuning, they used their corpus of 53,000 trajectories to train two open source models: UI-TARS-1.5, a strong, open source vision-language-action model designed specifically for computer use, and Qwen 2.5-VL, an open-weight multimodal LLM.
For in-context learning tests, they applied W&L examples to general-purpose multimodal models such as Gemini 2.5 Flash, OpenAI o3 and Claude Sonnet 4.
W&L resulted in improvements on OSWorld in all model categories, including up to 3 points for ICL on general-purpose models and up to 11 points for fine-tuned open-source models.
More importantly, these benefits were achieved without any manual annotation, “demonstrating that web-scale human workflows can serve as a practical and scalable foundation for advancing CUAs towards real-world deployment,” the researchers write.
This could have important implications for real-world applications, enabling enterprises to turn their existing corpora of videos and conference recordings into training data for CUAs. It also makes it easier to generate new training trajectories. All you will need to do is record videos of performing different tasks and have them annotated by an IDM. And with frontier models constantly improving and becoming cheaper, you can expect to get more from your existing data and the field continues to progress.
Follow-up: Amazon confirms 14,000 corporate job cuts, says push for ‘efficiency gains’ will continue into 2026
Original story: Amazon is preparing to lay off as many as 30,000 corporate employees in a sweeping workforce reduction intended to reduce expenses and compensate for over-hiring during the pandemic, according to a report from Reuters on Monday.
GeekWire has contacted Amazon for comment.
Layoff notifications will start going out via email on Tuesday, according to Reuters, which cited people familiar with the matter. One employee at Amazon told GeekWire the workforce is on “pins and needles” in anticipation of cuts.
Bloomberg reported that cuts will impact several business units, including logistics, payments, video games, and Amazon Web Services.
Amazon’s corporate workforce numbered around 350,000 in early 2023. It has not provided an updated number since then.
The company’s last significant layoff occurred in 2023 when it cut 27,000 corporate workers in multiple stages. Since then the company has made a series of smaller layoffs across different business units.
Fortune reported this month that Amazon planned to cut up to 15% of its human resources staff as part of a wider layoff.
Amazon has taken a cautious hiring approach with its corporate workforce, following years of huge headcount growth. The company’s corporate headcount tripled between 2017 and 2022, according to The Information.
The reported cuts come as Amazon is investing heavily in artificial intelligence. The company said earlier this year it expects to increase capital expenditures to more than $100 billion in 2025, up from $83 billion in 2024, with a majority going toward building out capacity for AI in AWS.
Amazon CEO Andy Jassy also hinted at potential workforce impact from generative AI earlier this year in a memo to employees that was shared publicly.
“We will need fewer people doing some of the jobs that are being done today, and more people doing other types of jobs,” he wrote. “It’s hard to know exactly where this nets out over time, but in the next few years, we expect that this will reduce our total corporate workforce as we get efficiency gains from using AI extensively across the company.”
Amazon reported 1.54 million total employees as of June 30 — up 3% year-over-year. The majority of the company’s workforce is made up of warehouse workers.
Amazon employs roughly 50,000 corporate and tech workers in buildings across its Seattle headquarters, with another 12,000 in Bellevue.
The company reports its third quarter earnings on Thursday afternoon.
Fellow Seattle-area tech giant Microsoft has laid off more than 15,000 people since May as it too invests in AI and data center capacity. Microsoft has cut more than 3,200 roles in Washington this year.
Last week, The New York Times cited internal Amazon documents and interviews to report that the company plans to automate as much as 75% of its warehouse operations by 2033. According to the report, the robotics team expects automation to “flatten Amazon’s hiring curve over the next 10 years,” allowing it to avoid hiring more than 600,000 workers even as sales continue to grow.
GeekWire reporter Kurt Schlosser contributed to this story.
Learn more about Google’s work with the USO and how it plans to launch a program that will enable service members to stay in touch with loved ones.
We announced the Public Preview of our personal health coach will start rolling-out tomorrow. Our vision is to help empower everyone to live a longer, healthier life wit…
Starting tomorrow and over the next week, the personal health coach preview will be available for eligible U.S. Fitbit Premium users.
This could be an easier way to showcase relevant items to each user.
So now, X users have another AI bot to develop feelings for.
Consumers who use security keys on X will need to take note.
Will this get more people posting their thoughts in the app?
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