Amazon Exposes Years-Long GRU Cyber Campaign Targeting Energy and Cloud Infrastructure


High DDR5 pricing is causing AMD/AM4 CPU price rises Consumer-grade DDR5 memory modules have seen priceΒ increases ofΒ 178-258%, forcing PC builders to consider alternative upgrade paths. Instead of moving to newer DDR5 platforms, some PC builders are upgrading to AMDβs DDR4-based AM4 platform. Why? The answer is simple: they can keep using the DDR4 memory they [β¦]
The post AMD AM4 CPU pricing spike as PC market forces alternative upgrades appeared first on OC3D.
The post Progress Stalls: Sheryl Sandberg Warns AI Could Exacerbate Gender Inequality appeared first on StartupHub.ai.
The latest Lean In-McKinsey study reveals a stark truth: progress for women in the workplace is not just slowing, itβs stalling. Sheryl Sandberg, a pivotal figure in advocating for womenβs leadership, returned to the public spotlight to deliver this sobering message, underscoring how emerging technologies like artificial intelligence threaten to further widen the gender gap. [β¦]
The post Progress Stalls: Sheryl Sandberg Warns AI Could Exacerbate Gender Inequality appeared first on StartupHub.ai.
The post AI Fuels Megadeal Surge, Redefining M&A Landscape appeared first on StartupHub.ai.
Nearly a quarter of megadeals this year were AI-driven, a stark indicator of artificial intelligenceβs transformative power in the M&A landscape. This trend, highlighted by Paul Griggs, U.S. Senior Partner at PwC, during his recent interview with Frank Holland on CNBCβs Worldwide Exchange, underscores a pivotal shift where strategic positioning and technological advancement are paramount. [β¦]
The post AI Fuels Megadeal Surge, Redefining M&A Landscape appeared first on StartupHub.ai.
The post Unifying AI Operations: Flexible Orchestration Beyond Kubernetes appeared first on StartupHub.ai.
The sheer velocity of AI innovation demands an infrastructure that can adapt, not just scale. At IBMβs TechXchange in Orlando, Solution Architect David Levy and Integration Engineer Raafat βRayβ Abaid illuminated the critical need for a paradigm shift in how AI and machine learning workloads are managed, moving beyond the traditional automation paradigms. Their discussion [β¦]
The post Unifying AI Operations: Flexible Orchestration Beyond Kubernetes appeared first on StartupHub.ai.
The post House proposes bill to advance data center buildout speed appeared first on StartupHub.ai.
The proposed legislation, dubbed βThe SPEED Act,β seeks to significantly reduce the time required for permitting and construction of data centers and associated power infrastructure. This is a crucial development, as the voracious appetite of AI for computational power necessitates a corresponding acceleration in the physical infrastructure that supports it. The bill proposes to limit [β¦]
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Google Search Console seems to have fixed the weeks long delay with the search performance reports. For the past few weeks, we had 50+ hour delays for these reports, but as of the past several hours, the reports seem to be up-to-date.
Now up-to-date. If you go to the search performance report, you should just see anywhere between about 2 β 6 hours of delay, which is typically normal. At some point over the past few weeks, the delays were over 70 hours.
This is what I see:

The delays started a few weeks ago and it took about three weeks to clear the delay and backlog of data.
Page indexing report. Meanwhile, the page indexing report delay we reported many weeks ago, is still delayed. It is now almost a full month delayed and Google has not fixed it yet. Google did post a notice at the top of the report that reads:
βDue to internal issues, this report has not been updated to reflect recent dataβ
Why we care. If you use Search Console reporting for your analytics and reporting for your stakeholders and clients, this can be super frustrating. It does seem like the performance reports are now flowing data normally. But that indexing report is still very delayed and will cause headaches with reporting.
Meanwhile, Google released a number of new features in the past few weeks including:


Managing large catalogs in Google Performance Max can feel like handing the algorithm your wallet and hoping for the best.Β
La Maison Simons faced that exact challenge: too many products and not enough control. Then they rebuilt their segmentation with Channable Insights and turned a βblack boxβ campaign into a revenue-generating machine.
Simons originally split campaigns by product category. It sounded logical β until their best-selling sweater ate the budget and newer or overlooked products never had a chance to surface.
Static segmentation meant limited visibility and slow decisions.
Marketers stayed stuck making manual tweaks while Google kept auto-prioritizing only what was already working.
Enter Channable Insights. Product-level performance data (ROAS, clicks, visibility) now powers dynamic grouping:

Products automatically move between these segments as performance shifts β no manual work needed. As Etienne Jacques, Digital Campaign Manager, Simons, put it:
βOne super popular item no longer takes all the money.β
Instead of waiting 30 days for signals, Simons switched to a rolling 14-day window.
The result: faster reactions, sharper accuracy, and less wasted spend in a fast-moving catalog.
Why stop at Google? The same segmentation logic was automatically applied on:
Cross-channel consistency creates compounding optimization.
Without raising ad spend, Simons unlocked:
Even the βinvisiblesβ turned into surprise profit drivers once they finally got the spotlight.
Automation restored marketing controlΒ βΒ it didnβt remove it.
Teams can finally learn from the data and influence which products grow, instead of letting PMax run everything on autopilot.

Want Simons-style ROAS gains without extra ad spend? Start by testing the quality of your product data with a free feed and segmentation audit.


How much have DDR5 memory prices increased? We all know that DDR5 memory pricing has shot up, but how bad is the situation? Has AI-driven datacenter demand ruined the DRAM market? Yes, but how much is it hitting our wallets? Today we have looked at todayβs DRAM pricing and have compared it to 30 days [β¦]
The post Itβs bad β Hereβs how much DDR5 pricing has increased appeared first on OC3D.
The post Physical AIβs Off-Screen Revolution: Sanjit Biswas on Scaling Real-World Impact appeared first on StartupHub.ai.
The next transformative wave of artificial intelligence is unfolding not in the digital ether, but in the tangible, messy reality of the physical world. This was the central thesis articulated by Sanjit Biswas, CEO of Samsara, in a recent discussion with Sequoia Capitalβs Sonya Huang and Pat Grady. Biswas, a serial founder known for scaling [β¦]
The post Physical AIβs Off-Screen Revolution: Sanjit Biswas on Scaling Real-World Impact appeared first on StartupHub.ai.
Google's core updates can trigger issues that standard SEO audits fail to catch. Here are eight factors to check.
The post Eight Overlooked Reasons Why Sites Lose Rankings In Core Updates appeared first on Search Engine Journal.
Samsung denies SATA SSD phase-out rumours, calling them false Samsung has officially denied reports that it plans to phase out its SATA SSDs and other consumer products. This follows recent rumours that Samsung planned to wind down its SATA SSD production to free up manufacturing capacity for data centre and AI customers. With Micron killing [β¦]
The post Samsung refutes consumer SSD phase-out rumours appeared first on OC3D.
Introducing VT Chat, a privacy-first AI chat application that keeps all your conversations local while providing advanced research capabilities and access to 15+ AI models including Claude 4 Sonnet and Claude 4 Opus, O3, Gemini 2.5 Pro and DeepSeek R1.
Research features: Deep Research does multi-step research with source verification, Pro Search integrates real-time web search with grounding web search powered by Google Gemini.
There's also document processing for PDFs, a "thinking mode" to see complete AI reasoning, and structured extraction to turn documents into JSON. AI-powered semantic routing automatically activates tools based on your queries.
Live website previews in your Mac menu bar
Autonomous AI for smarter e-signatures
Detect hidden apps on MacOS
The post Salesforce AI Careers: A New Talent Pipeline Emerges appeared first on StartupHub.ai.
Salesforce's global Workforce Development programs are actively shaping the landscape of AI careers, equipping over 120,000 learners with critical skills and certifications.
The post Salesforce AI Careers: A New Talent Pipeline Emerges appeared first on StartupHub.ai.
The post Amazon Upskills Workforce for Agentforce AI Era appeared first on StartupHub.ai.
Amazon is strategically investing in employee 'Agentforce AI' skills through Salesforce Trailhead, preparing its workforce for the agentic AI era.
The post Amazon Upskills Workforce for Agentforce AI Era appeared first on StartupHub.ai.

Open Source, Free Anonymous AI Chat - Ready to Run Locally
Read books with Elon Musk, Steve Jobs, or anyone you choose
Test apps in a click with AI QA agents that scale like infra
One dashboard to run and organize multiple AI CLI agents
Dial in espresso & pourover
A showcase for AI-assisted builds, inspiration, and how-tos
Test data as code: YAML rules, Git versioned, & CI/CD ready
A browser-first marketplace for PC games
Private ai chat with 30+ open source models
Open source DevOps agent for devs who just want to ship
Easiest solution to deploy multimodal AI to mobile
The post NVIDIA Acquires SchedMD, Bolstering AI Infrastructure appeared first on StartupHub.ai.
NVIDIA's acquisition of SchedMD, the creator of Slurm, strategically enhances its control over critical open-source workload management for HPC and AI.
The post NVIDIA Acquires SchedMD, Bolstering AI Infrastructure appeared first on StartupHub.ai.

Outage Owl monitors 20+ vendor status pages in real time and alerts your team and customers when issues arise. Add a single script to show a website banner during outages and connect Slack to notify your team before tickets pile up. Create custom incidents and messages, tune alert rules, delays, and quiet hours, and keep everyone informed within seconds. Set up in under five minutes, and start free with one alert rule.
Apparently, no oneΒ knows if TikTok will be allowed to remain in the U.S.

Insights into some of the major trends among Snapchat users in 2025.
SOme handy pointers for your LinkedIn video content approach.Β

Threads is looking to encourage more topical engagement in the app.
Ahrefs data suggests Googleβs AI Mode and AI Overviews often align on meaning while citing different URLs.
The post Google AI Mode & AI Overviews Cite Different URLs, Per Ahrefs Report appeared first on Search Engine Journal.
Zinggit is an AI-powered voice note to text app designed to take your idea to content quicker. No more typing out ideas, or trying to create an outline. Just speak your thoughts and 'vibe type' your first draft. Perfect for busy business owners with tons of ideas, agency owners trying to sound out their next article, or social media managers who want to summarise an idea into a post.
The post White House AI Czar David Sacks on Navigating the AI Frontier: Regulation, Race, and Jobs appeared first on StartupHub.ai.
The rapid acceleration of artificial intelligence has ignited a multifaceted debate spanning innovation, national security, and economic impact, a tension vividly explored in a recent CNBC βClosing Bell Overtimeβ interview. David Sacks, the White House AI and Crypto Czar, spoke with Morgan Brennan about President Trumpβs executive order aiming to streamline AI regulation, the intensifying [β¦]
The post White House AI Czar David Sacks on Navigating the AI Frontier: Regulation, Race, and Jobs appeared first on StartupHub.ai.
Google's John Mueller explains that staggered site migrations may impact how the site is understood
The post Google Explains Why Staggered Site Migrations Impact SEO Outcome appeared first on Search Engine Journal.
Phantom is an AI website builder designed to help anyone go from an idea to a fully functional website in just a few minutes. It handles all the heavy lifting automatically β setting up authentication, database, payments, analytics, and even AI integrations for you. Instead of juggling multiple tools or writing code from scratch, you just describe what you want, and Phantom builds it out instantly.
It runs on a network of specialized AI agents, each focused on a different area like frontend, backend, bug fixing, and review. This makes the process faster, more accurate, and more creative. Phantom lets you skip the setup and get straight to building β without needing technical expertise.
The post Teslaβs Trillion-Dollar AI Future: Dan Ives on Autonomy and Robotics appeared first on StartupHub.ai.
Wedbush Securitiesβ Dan Ives recently offered a compelling vision of Teslaβs future, asserting that the company, alongside Nvidia, stands at the forefront of the βphysical AI revolution.β This isnβt merely about electric vehicles; itβs about the profound convergence of hardware and artificial intelligence to create tangible, real-world autonomous capabilities. Ivesβs commentary underscores a pivotal shift [β¦]
The post Teslaβs Trillion-Dollar AI Future: Dan Ives on Autonomy and Robotics appeared first on StartupHub.ai.
The post Bolmo Advances Byte-Level Language Models with Practicality appeared first on StartupHub.ai.
AI2's Bolmo makes byte-level language models practical by "byteifying" existing subword models, offering superior character understanding and flexible inference.
The post Bolmo Advances Byte-Level Language Models with Practicality appeared first on StartupHub.ai.
The post Rebuilding American Industry: The AI-Powered Factory Renaissance appeared first on StartupHub.ai.
Erin Price-Wright, a General Partner at Andreessen Horowitz, unveiled a compelling vision for βThe Renaissance of the American Factoryβ as part of the firmβs 2026 Big Ideas series. Her presentation posits that Americaβs industrial muscle, which has atrophied over decades due to offshoring, financialization, and regulatory burdens, is poised for a significant resurgence. This revitalization [β¦]
The post Rebuilding American Industry: The AI-Powered Factory Renaissance appeared first on StartupHub.ai.
The post Beyond Snippets: The Evolving Landscape of AI Code Evaluation appeared first on StartupHub.ai.
The rapid ascent of AI in code generation, from single-line suggestions to architecting entire codebases, demands an equally sophisticated evolution in how these models are evaluated. This critical shift was at the heart of Naman Jainβs compelling presentation at the AI Engineer Code Summit, where the Engineering lead at Cursor unpacked the journey of AI [β¦]
The post Beyond Snippets: The Evolving Landscape of AI Code Evaluation appeared first on StartupHub.ai.
The post Google DeepMind Unveils Gemini 3 and Nano Banana Pro, Redefining AI Development appeared first on StartupHub.ai.
Google DeepMind recently showcased its latest advancements in artificial intelligence at the AI Engineer Code Summit, where Product Manager Kat Kampf and Product & Design Lead Ammaar Reshi introduced Gemini 3 Pro and Nano Banana Pro. Their presentation, βBuilding in the Gemini Era,β highlighted how these new models, combined with the Google AI Studio, are [β¦]
The post Google DeepMind Unveils Gemini 3 and Nano Banana Pro, Redefining AI Development appeared first on StartupHub.ai.
The post NVIDIA Nemotron 3 Nano launches on FriendliAI appeared first on StartupHub.ai.
FriendliAI is aggressively positioning itself as the crucial infrastructure layer for productionizing the new wave of efficient, open-source agentic AI models.
The post NVIDIA Nemotron 3 Nano launches on FriendliAI appeared first on StartupHub.ai.
The post Unsloth Accelerates LLM Fine-Tuning on NVIDIA GPUs appeared first on StartupHub.ai.
Unsloth, combined with NVIDIA GPUs and Nemotron 3 models, is democratizing efficient, specialized LLM fine-tuning for next-generation agentic AI applications.
The post Unsloth Accelerates LLM Fine-Tuning on NVIDIA GPUs appeared first on StartupHub.ai.
The post Vertex AI Unlocks Flexible Open Model Deployment appeared first on StartupHub.ai.
The accelerating pace of AI development has made the deployment of open models a critical challenge, often mired in infrastructure complexities. Google Cloudβs Vertex AI platform, as detailed by Developer Advocate Ivan Nardini in his recent video, βServing open models on Vertex AI: The comprehensive developerβs guide,β directly addresses this by offering a strategic roadmap [β¦]
The post Vertex AI Unlocks Flexible Open Model Deployment appeared first on StartupHub.ai.

Weβre sharing a practical playbook to help organizations streamline and enhance sustainability reporting with AI.Corporate transparency is essential, but navigating fragβ¦ 
Google Ads launched VTC-optimized bidding for Android app campaigns, letting advertisers toggle bidding toward conversions that happen after an ad is viewed rather than clicked.
Previously, VTC worked as a hidden signal inside Googleβs systems. Now, itβs a clear, explicit optimization option.

The shift. Google is shifting app advertising away from click-centric logic and toward incrementality and influence, especially for formats like YouTube and in-feed video. This update aligns bidding more closely with how users actually discover and install apps.
Why we care. You can now bid beyond clicks, improving measurement for video-led app campaigns and strengthening the case for upper-funnel activity.
Who benefits most. Video-first app advertisers and teams focused on awareness, engagement, and long-term growth βΒ not just last-click installs.
What to watch
First seen. This update was first spotted by Senior Performance Marketing Executive Rakshit Shetty when he posted on LinkedIn.

Sergey Brin, Googleβs co-founder, admitted that Google βfor sure messed upβ by underinvesting in AI and failing to seriously pursue the opportunity after releasing the research that led to todayβs generative AI era.
Google was scared. Google didnβt take it seriously enough and failed to scale fast enough after the Transformer paper, Brin said. Also:
The full quote. Brin said:
Yes, but. Google still benefits from years of AI research and control over much of the technology that powers it, Brin said. That includes deep learning algorithms, years of neural network research and development, data-center capacity, and semiconductors.
Why we care. Brinβs comments help explain why Googleβs AI-driven search changes have felt abrupt and inconsistent. After years of hesitation about shipping imperfect AI, Google is now moving fast (perhaps too fast?). The volatility we see in Google Search is collateral damage from that catch-up mode.
Where is AI going? Brin framed todayβs AI race as hyper-competitive and fast-moving: βIf you skip AI news for a month, youβre way behind.β When asked where AI is going, he said:
One more thing. Brin said he often uses Gemini Live in the car for back-and-forth conversations. The public version runs on an βancient model,β Brin said, adding that a βway better versionβ is coming in a few weeks.
The video. Brinβs remarks came at a Stanford event marking the School of Engineeringβs 100th anniversary. He discussed Googleβs origins, its innovation culture, and the current AI landscape. Hereβs the full video.

Google updated its JavaScript SEO documentation to clarify that noindex tags may prevent rendering and JavaScript execution, blocking changes.
The post Google Warns Noindex Can Block JavaScript From Running appeared first on Search Engine Journal.
Prototype HDMI 2.2 hardware will be showcased at CES The HDMI Licensing Administrator has confirmed that early HDMI 2.2 prototype hardware will be showcased at CES 2026. This will give the world its first look at the next-generation display technology. With HDMI 2.2, the HDMI standardβs maximum bandwidth will increase from 48 Gbps (HDMI 2.1) [β¦]
The post Expect to see HDMI 2.2 in action at CES 2026 appeared first on OC3D.
Core Temp is a small, free utility that monitors CPU temperatures by reading data directly from each processor core. It delivers accurate, real-time readings, supports a wide range of CPUs, and runs with minimal overhead. If you want precise temperature monitoring, Core Temp delivers.
ResumaLive is a platform where video creators build swipeable, shareable profiles that introduce them in under 2 minutes.
Clients don't have time to dig through scattered links, they leave before they understand you. ResumaLive guides them through your identity, your credibility, your showreel, your personality, and how to reach you. like a movie trailer for your career. It doesn't replace your portfolio or social media. It gets your foot in the door, then they explore the rest.
The post AIβs Real Boom: Data Centers, ROI, and a Maturing IPO Market appeared first on StartupHub.ai.
βEvery single AI company on the planet is saying if you give me more compute, I can make more revenue.β This assertion by Matt Witheiler, Head of Late-Stage Growth at Wellington Management, cuts directly to the core of the current artificial intelligence boom, framing the debate around an βAI bubbleβ not as a question of [β¦]
The post AIβs Real Boom: Data Centers, ROI, and a Maturing IPO Market appeared first on StartupHub.ai.
The post Rockefellerβs Ruchir Sharma Declares AI Market in βAdvanced Stages of a Bubbleβ appeared first on StartupHub.ai.
The current euphoria surrounding artificial intelligence has propelled the tech sector to unprecedented valuations, prompting seasoned financial analysts to question the sustainability of this growth. Ruchir Sharma, Chairman of Rockefeller International and Founder & CIO of Breakout Capital, offers a sobering perspective, asserting that the market is already in the βadvanced stages of a bubble.β [β¦]
The post Rockefellerβs Ruchir Sharma Declares AI Market in βAdvanced Stages of a Bubbleβ appeared first on StartupHub.ai.
The post Apple Engineers Squeeze Powerhouse Vision Models into a Single Layer for Hyper-Efficient Image Generation appeared first on StartupHub.ai.
Generative AI is getting a major speed and efficiency boost, thanks to a surprisingly simple new framework from Apple researchers. The paper, βOne Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation,β introduces the Feature Auto-Encoder (FAE), a novel approach that dramatically slashes the complexity required to integrate massive, pre-trained visual encoders (like DINOv2 [β¦]
The post Apple Engineers Squeeze Powerhouse Vision Models into a Single Layer for Hyper-Efficient Image Generation appeared first on StartupHub.ai.

Google has updated its JavaScript SEO basics documentation to clarify how Googleβs crawler handles noindex tags in pages that use JavaScript. In short, if βyou do want the page indexed, donβt use a noindex tag in the original page code,β Google wrote.
What is new. Google updated this section to read:
In the past, it read:
Why the change. Google explained, βWhile Google may be able to render a page that uses JavaScript, the behavior of this is not well defined and might change. If thereβs a possibility that you do want the page indexed, donβt use a noindex tag in the original page code.β
Why we care. It may be safer not to use JavaScript for important protocols and blocking of Googlebot or other crawlers. If you want to ensure a search engine does not rank a specific page, make sure not to use JavaScript to execute those directives.

The SEO industry is entering its most turbulent period yet.
Traffic is declining. AI is absorbing informational queries.Β
Social platforms now function as search engines. Google is shifting from a gateway to an answer engine.
The result is a sector running in circles β unsure what to measure, what to optimize, or even what SEO is meant to do.
Yet within this turbulence, something clear has emerged.
A single marketing metric that cuts through the noise and signals brand health and future demand.Β
A metric that marketers and SEOs can align around with confidence.
That metric is share of search.
The old model of being discovered by accident through classic search behavior is disappearing.
AI Overviews answer questions without sending traffic anywhere.Β
Meta is already rolling out its own AI to answer user queries.Β
TikTok and YouTube continue to grow as product discovery engines.Β
It is only a matter of time before LinkedIn becomes a business search engine powered by conversational AI.
We are witnessing a seismic shift.Β In moments like this, measurement becomes even more important.Β
Many SEO metrics are losing meaning, but one is rapidly gaining importance.
Share of search is a metric developed by James Hankins and Les Binet.Β
It is calculated by dividing a brandβs search volume by the total search volume for all brands in its category.Β
The result shows the proportion of category interest the brand commands.
The value is not in the calculation itself, but in what the metric correlates with.
Studies published by the Institute of Practitioners in Advertising (IPA) show that share of search correlates strongly with market share and future buying behavior.Β
As the IPA notes:
In simple terms, consumers search for brands they are considering, buying, or using.Β
That makes search behavior one of the clearest available signals of real demand.
Share of search was never designed to be perfect. It does not capture every nuance of how people find information across platforms.Β
It was built as a practical proxy for brand demand β and right now, practical measurement is exactly what the industry needs.
Dig deeper: Measuring what matters in a post-SEO world
Traffic as a measurement has become almost meaningless.Β
It has been easy to inflate, manipulate, and misunderstand.
Goodhartβs Law explains why. When a measure becomes a target, it stops being a good measure.Β
Traffic was treated as a target for years, and as a result, it stopped being a reliable indicator of anything meaningful.
Now traffic is falling β not because brands are doing anything wrong, but because AI is answering questions before users ever reach a website.
Ironically, this makes traffic more meaningful again, as much of the noise that once inflated it is disappearing.
The bigger advantage, however, belongs to share of search.Β
It cannot be inflated through content tactics or gamed by chasing trends. It reflects underlying consumer interest.
That is why share of search has become so significant.Β
It shows whether a brand is being searched for more or less than its competitors.Β
When share of search rises, brand demand is growing.Β When it falls, demand is weakening.
If an entire category collapses β as it did with air fryers once most consumers had already bought one β the metric also provides a clear signal that demand for the overall market is shrinking.
There is another advantage. Share of search is a multi-platform metric.
People no longer search in one place.Β
Product searches may begin on Amazon, TikTok, or Facebook.Β
Credibility checks often happen on YouTube. Long-form research may still take place on Google.
Discovery is fragmented, and behavior is fluid.
Share of search adapts to this reality. It is platform agnostic.Β
You can measure it using Google Trends, Ahrefs, Semrush, My Telescope, or any platform that provides reliable volume estimates.Β
You can track demand across Amazon, TikTok, YouTube, and emerging AI search interfaces.
Where the behavior happens matters less than the signal itself.Β
If people are looking for your brand, they are demonstrating intent.
This cross-platform visibility is critical because AI search sends little traffic to websites.Β
ChatGPT, Claude, and other LLMs present answers, snippets, and summaries, but rarely generate click-through.Β
Links are often buried, inaccessible, or accompanied by friction.
Instead, these systems trigger brand search.Β
Users encounter a brand in an AI response, then search for it when they want more information.
As a result, share of search becomes the tail-end signal of everything marketing does, including AI exposure.Β
When share of search rises, marketing is working. When it falls, it is not.
However, the metric needs a champion.
The SEO industry has spent years focused on two types of keywords:Β
That approach made sense when classic search was the dominant discovery channel. That world is disappearing.
Yet many SEOs continue to cling to outdated deliverables, such as structured data micro-optimization or churning out endless blog posts to influence hypothetical AI citations.
Citations are a distraction.Β
At best, they are a minor signal in LLM outputs.Β
At worst, they are a misleading metric that will not stand up to financial scrutiny.Β
When CFOs start questioning the value of SEO budgets, citations will not hold up as evidence of ROI.
Share of search will.
SEOs who embrace share of search position themselves not as keyword tacticians, but as strategic insights partners.Β
They become interpreters of demand who help:
This shift changes the role of SEO entirely.Β
Instead of being judged by how much content they produce, SEOs begin to be valued for how well they understand search behavior and the commercial impact of that behavior.
A well-structured share of search report tells a coherent story:
In the AI era, this narrative becomes essential.Β
Someone inside the organization must understand how people search, where they search, and what the numbers mean.
SEOs are naturally positioned to fill that role. You have the background and the expertise.Β
And as AI automates more mechanical SEO tasks, this progression becomes increasingly natural.
Because share of search requires interpretation.
Dig deeper: Why LLM perception drift will be 2026βs key SEO metric
Share of search does not have to be a single top-level number. It can be:
Consider the air fryer category.Β
Demand collapsed across the market once most consumers had already purchased one.Β
Within that collapse, however, individual models rose and fell based on their appeal.Β
Ninjaβs latest model, for example, showed spikes and dips that revealed shifts in consumer interest long before sales data arrived.
Share of search acts as early detection for market movement.
SEOs who understand this level of nuance become indispensable. They can:
This is the future skill set β not chasing rankings, but interpreting behavior.
As AI becomes more integrated into search and site optimization, many mechanical SEO tasks will be increasingly automated.Β
The interpretation of marketing performance, however, cannot be fully automated.
Share of search requires human judgment.Β
It requires an understanding of context, seasonality, category dynamics, and brand strategy.Β
That role can and should belong to the SEO professional.
Some agencies may label this function an insights specialist or a data analyst.Β
Some organizations may house it within marketing.Β
But the people who understand search behavior most deeply are SEOs.Β
They are best positioned to interpret what the numbers mean and communicate those insights to leadership teams.
Leadership teams need to understand what is happening with their brand.
Marketing leaders are already discussing share of search, and it is beginning to appear in boardroom conversations.Β
It is quickly becoming a central indicator of brand strength.Β
In an AI-driven world where traffic is scarce and visibility is fragmented, the strategic imperative is clear.
Brands need to be searched for. Those that are searched for endure. Those that are not fade.
That is why share of search is not just another metric. It is becoming the metric.Β
SEOs who embrace it can elevate their role, influence, and strategic value at exactly the moment the industry needs it most.
The advice for SEOs is simple: Learn share of search.
To get started:
You will not become fluent in the metric without using it. Once you do, its applications become clear.
Share of search is the bridge that connects SEO to the broader world of brand.
Take the first step.
Sapphire wants AMD to let them βgo nutsβ with their GPU designs Ed Crisler, Sapphire Technologyβs North American PR Manager, has openly stated that he would like GPU manufacturers to give their partners more freedom when building their graphics cards. Sapphire would like to βgo nutsβ when building graphics cards, but tight rules limit what [β¦]
The post Sapphire wants AMD to let them βgo nutsβ on their GPUs appeared first on OC3D.
The post Content, Consolidation, and the Creatorβs Cut: Isaacson on AI, Media Mergers, and Musk appeared first on StartupHub.ai.
βPeople who create content should be part of the party when the proceeds get divided up,β asserts Walter Isaacson, the esteemed biographer and advisory partner at Perella Weinberg, during a recent appearance on CNBCβs βSquawk Box.β This fundamental principle, he argues, is the linchpin for navigating the burgeoning age of artificial intelligence, particularly as major [β¦]
The post Content, Consolidation, and the Creatorβs Cut: Isaacson on AI, Media Mergers, and Musk appeared first on StartupHub.ai.


As marketing channels and touchpoints multiply rapidly, the way success is measured significantly impacts long-term growth and executive perception.Β
Click-based attribution β across models like last-click, first-click, linear, and time-decay β remains the default.Β
But as a standalone measurement strategy, itβs showing its age.Β
Click metrics now carry disproportionate weight in executive dashboards, and that reliance introduces real limitations.
Click-based models can still reveal valuable insights into digital engagement.Β
However, when the C-suite bases major budget and strategy decisions solely on clicks, they risk overlooking critical aspects of the customer journey β often the very pieces that matter most.
This article examines:
The goal isnβt to demonize clicks β they still belong in the toolbox. But they should provide context, not serve as the foundation.
Click-based attribution tracks ad clicks and assigns conversion credit to the marketing touchpoints that drove them.Β
Models like first-click, last-click, linear, time-decay, and data-driven approaches differ only in how they split that credit across the user journey.
Digital ad platforms and many analytics tools default to click-based models because clicks are relatively easy to capture, understand, and report.Β
Theyβre deterministic, clean, and simple to interpret at a glance.
That cleanliness, however, can be misleading.Β
Click-based attribution depends entirely on a user interacting with tracking links or tags.Β
If a user doesnβt click, or clicks but converts later or elsewhere, the touchpoint may be missed or misattributed.
This approach can work in a simple, linear funnel.Β
But as customer journeys become multi-device, multi-channel, and increasingly offline, clicks lose context quickly.
Dig deeper: The end of easy PPC attribution β and what to do next
Todayβs buyers rarely follow the neat, linear paths that click-based models assume.Β
Instead, they move across devices, channels, and even offline touchpoints.
Think social media, LLMs like ChatGPT, and brand exposure from video, influencers, or website content.Β
Many of these interactions never generate a tracked click, yet they play a critical role in shaping perception, intent, and eventual conversion.
For example, a buyer may watch a brandβs video on LinkedIn during their morning commute.Β
Later, they read a third-party review and skim a few case studies on the brandβs website.
Days later, they type the brand name directly into Google and convert.Β
In a click-based model, only the final branded search click receives credit.Β
The video, the review, and the content that built trust remain invisible.
These arenβt minor attribution blind spots β they represent a canyon.Β
Click-based models place the most weight on the final click.Β
As a result, they often over-index lower-funnel activity from channels like retargeting ads or branded search.Β
These channels convert more frequently, but they do not create demand on their own.
For C-level decision-makers, this creates a dangerous bias.Β
Dashboards light up for retargeting campaigns and branded search, so budgets flow there.
Mid- and upper-funnel investments β brand building, awareness, content, and influencers β are reduced or cut.Β
Over time, the brandβs long-term growth engine is choked in favor of short-term, easily quantifiable wins.
Dig deeper: Marketing attribution models: The pros and cons
Not all marketing impact shows up as clicks.Β
A video ad or thought-leadership piece may plant a seed without prompting an immediate click, yet the message can linger.Β
It may lead to later brand searches or site visits, outcomes that are difficult to capture through click-based measurement.
As a result, brand power, creative messaging, and top-of-funnel reach are underrepresented in click-based models.Β
Over time, organizations that optimize solely around click-based attribution may unintentionally deprioritize creativity, brand-building, and long-term equity.
Weβre moving toward a future where third-party cookies are diminished or gone, privacy rules continue to tighten, and tracking becomes less precise.Β
Under these conditions, click tracking grows more difficult, less reliable, and increasingly misaligned.
Without stable identifiers, many of the assumptions behind click-based models β βthis click belongs to that userβ or βthis click led to that conversionβ β begin to unravel.Β
Attribution becomes a house of cards built on data that may not hold up as privacy and tracking norms continue to shift.
When click-based reporting dominates, budgets tend to flow toward what looks good β the activities that drive visible revenue and deliver clean, direct ROI.Β
That often comes at the expense of demand generation efforts that support long-term growth, such as brand campaigns, content, awareness, and other upper-funnel media.
This approach may βworkβ for a few months or even years.Β
Over time, however, the pipeline dries up.Β
Awareness declines, organic reach stagnates, and the brand loses its ability to attract new audiences at scale.
Marketing shifts into a zero-sum exercise focused on extracting conversions from existing demand rather than expanding it.Β
Without sustained investment in brand equity and demand generation, competitiveness, brand loyalty, and lifetime value (LTV) suffer.
In essence, optimizing for short-term ROAS puts long-term brand health at risk.
When KPIs are click-based:
The result is marketing silos working toward different objectives.
Fragmentation increases.
Ad platforms and tracking tools report click-based conversions, but many of those conversions are self-crediting, particularly within paid media platforms.Β
When you rely heavily on these numbers without scrutiny or connection to the broader user journey, you risk making high-stakes decisions based on biased data.
If click-based attribution is flawed, how should performance be evaluated?Β
The short answer is a combination of approaches grounded in real business outcomes.
At a higher level β especially when multiple channels are involved, including online, offline, paid media, organic media, and PR β MMM helps quantify channel-level contribution to sales, revenue, or other business outcomes.Β
It looks at broad correlations over time using aggregated data rather than user-level clicks.
MMM, supported by machine learning, improved data resolution, and more frequent refresh cycles, has become more accessible and actionable.Β
It isnβt a replacement for click- or site-based data, but a powerful complement.Β
Dig deeper: MTA vs. MMM: Which marketing attribution model is right for you?
User-level path analysis still has a place when privacy and tracking allow.Β
Multi-touch models that consider multiple touchpoints can provide richer insight, but they work best as one input among many rather than a single source of truth.Β
They offer path visibility, but without incrementality testing or support from MMM, they still risk over-crediting and bias.
Marketing value isnβt confined to a single sale or conversion.
LTV, retention, and long-term value creation matter just as much.Β
Tying spend to CAC payback, churn, loyalty, and retention creates a measurement framework aligned with long-term business goals.
Incrementality testing measures what marketing actually adds by identifying net-new conversions, revenue, lift, or awareness.Β
It separates what would have happened anyway from what your efforts truly drove.
This approach isnβt as clean as click tracking and requires more planning and discipline, but it delivers causality.Β
It allows you to say, with confidence, βThis spend generated X% incremental lift.β
Dig deeper: Why incrementality is the only metric that proves marketingβs real impact
Not all impact is transactional.Β
Upper-funnel signals such as viewability, time-in-view, attention scores, and engagement matter.Β
Creative resonance, brand recall, and impact often influence later behavior that never appears as a click.
Looking beyond clicks to metrics like creative recall, brand lift, share of voice, sentiment, and qualitative feedback helps anchor measurement to real brand value and audience expectations.
A modern measurement framework isnβt built around one model or metric.Β
It brings together complementary methods to create a clearer, more balanced view of performance.
The most effective measurement frameworks take a portfolio approach.Β
MMM, incrementality, multi-touch attribution (when possible), attention metrics, and customer lifecycle metrics work together to triangulate performance from multiple perspectives.
This diversity reduces bias and balances short-term performance with long-term brand health.
It also makes it possible for the C-suite to see more than conversions alone β including impact, growth potential, and sustainable value.
Executives care about revenue, margin, and growth. Not just clicks.Β
Reframe KPIs around the key metrics that matter, such as:
Package those into dashboards that tell a story:Β
When dashboards lead with vanity metrics like click volume, CTR, or raw conversion rate, insight is limited. Lead instead with business outcomes.
Build narrative-driven dashboards that connect investment to results, learning, and action.
Lean toward data storytelling instead of data reporting.Β
That story resonates with executives. It links marketing to business value, not just to marketing activity.
Modern analytics tools β including AI and predictive forecasting β can help:
Use them to simulate scenarios, test assumptions, and support business cases.
These tools arenβt silver bullets. They work best as accelerators for sound strategic thinking.Β
Changing how performance is measured doesnβt happen automatically.
It requires clear framing, evidence, and a deliberate transition rather than an abrupt overhaul.
Often, executives cling to click-based metrics because theyβre easy to understand (βone user clicked, we got a saleβ) and seemingly real-time.Β
They want fast feedback and accountability. Demand creation efforts often feel abstract and hard to justify.
Be prepared to address that directly:
Click-based attribution doesnβt need to be discarded overnight. Instead:
Over time, incentives begin to shift. Media moves beyond clicks, creative focuses on quality and resonance, and analytics emphasizes causality and long-term value.
Executives rarely object to logic β they object to noise.Β
Frame your case with clarity and use data.Β
Show examples, run tests, show incremental lift, and then build dashboards that tell a clear story.
Once you prove that a dollar invested in brand or top-of-funnel media delivers compounding value over time, leadership hopefully becomes less attracted to short-term click metrics.Β
They begin to appreciate marketing as an investment, not a cost center.
Click-based attribution has served marketing teams for years. It offered a clean way to connect conversions to touchpoints.Β
But the landscape has changed.Β
For C-level teams, judging performance by clicks alone is like judging a companyβs health by heart rate alone. Itβs useful, but incomplete.
Modern marketing requires a richer view β one that blends data, causality, business outcomes, and long-term brand building.
As marketing leaders, our job isnβt to chase the next click.Β
Itβs to build brands that last, drive sustained growth, and help leadership see marketing not as a cost, but as a strategic investment.

Every week, new data highlights both the overlap and the divergence between effective organic search techniques across traditional SEO (Google SERPs) and GEO (ChatGPT, AI Overviews, Perplexity, etc.).Β
Itβs a lot to absorb. One week, headlines say traditional SEO tactics work fine for ChatGPT.
The next, youβll see reports that one platform is elevating Reddit while another is dialing it back.
Given how quickly this landscape shifts, I want to break down the approach, process, and resources my team is using to tackle content in 2026.Β
This goes far beyond a content calendar.Β
Itβs about combining audience understanding, the interplay of organic platforms, and your brandβs perspective to build a content system that delivers real value.
The emphasis on quality and value in content is good for marketers.
The tenets of E-E-A-T remain central to our approach because they apply to AI search discoverability as much as to traditional SEO.Β
Producing strong content still depends on a rich understanding of your audience, good fundamental structures, and solid delivery methods β skills that always matter.
Start with your audience.Β
Approach content like any other product or service:Β
Approach content like any other product or service:
That said, content that has performed well in Google may not work as effectively for LLM search.Β
Instead of writing primarily for blue-link SERPs, we now focus on creating content that stands on its own as an authoritative, structured data source, with trust and originality as ranking signals.Β
That means prioritizing clarity, factual depth, and a consistent brand perspective that AI models can reliably quote.
In an age of mass AI content, original insights, data, and human perspective are key differentiators, so content systems should include a step for βoriginal proofβ β data, interviews, or commentary that make the material uniquely trustworthy.
Weβre also thinking more about how content gets used in AI experiences, not just how itβs found.Β
Summaries, bullet points, and explainers that answer layered intent are increasingly valuable.Β
Incorporating schema, structured data, and a consistent brand voice improves how AI systems read and represent your content.Β
In short, the goal is to optimize for retrievability and credibility, not just ranking.
The content strategy path I like to prescribe is as follows:
Once your research is conducted, youβll have what you need to craft content and deploy it in multiple ways.Β
The linear workflow that persisted for years in traditional SEO, however, must evolve into a modular content engine β one where a single research output fuels multiple media types (articles, YouTube scripts, short-form video, LinkedIn posts, etc.), with platform-native variations all aligned to a central narrative theme.
A few years ago, I would have started with well-known, well-established tools like Ahrefs and Semrush.Β
While those remain useful for benchmarking, they no longer represent how people discover or consume information as AI search transforms user behavior in real time.Β
AI search abstracts away keywords β users are asking multi-intent questions, and LLMs are generating synthesized answers.Β
SEO analysis is now, rather than the main starting point, one piece of the research pie.Β
Itβs still important, but search optimization is now embedded throughout the content process.
The tools below have been important in the past, and my team still leans on them as part of a more holistic approach to content planning.
Surveys are useful but can be expensive when youβre trying to reach audiences outside your CRM.Β
You can still get strong insights by engaging subject matter experts who share the same professional experiences, challenges, and responsibilities as your target audience.Β
Slack communities, live or virtual meet-ups, and memberships in organizations like the AMA or ANA can all offer on-the-ground perspectives that support your content mapping.
Itβs critical to include intent analysis from AI tools and conversational search data.Β
Understanding how users phrase questions to AI systems can inform structure and tone.
Not all social media posts are created equal, but understanding your audience includes knowing where your audience likes to engage: X, Reddit, YouTube, TikTok, etc. (Not to mention that Reddit citations show up prominently in ChatGPT results.)
Utilize these platforms to gather real-time information on what your audience is discussing and to increase brand mentions, which will send strong signals to ChatGPT and similar tools.
Shift from tracking keyword overlap to evaluating content depth, originality, and entity coverage β where your brandβs expertise can fill gaps or improve on generic AI-summarized answers.
For many years, SEO marketers focused on impressions and clicks, although more advanced practitioners also incorporated down-funnel metrics, such as leads, conversions, pipeline impact, and revenue.Β
Today, SEOs must expand their KPIs to include brand mentions in:
These are the new indicators of helpfulness and value.
Weβve seen strong successes with AI search visibility that complement our traditional SEO results, but our understanding of best practices continues to evolve with each new round of aggregated data on AI search results and shifting user behavior.
In short, keep a parallel track of what has worked recently and where the trends are heading, since ChatGPT and its competitors are changing user behavior in real time β and with it, the shape of organic discovery across platforms.
Cloudflare's sixth annual Year in Review reveals how AI crawlers, security threats, and traffic patterns changed in 2025.
The post Cloudflare Report: Googlebot Tops AI Crawler Traffic appeared first on Search Engine Journal.
Sometimes I really wish the chip makers would get out of the way and let us partners just make our cards. Give us the chip. Give us the RAM. Tell us what we have to provide to make it work with the board. And then let us make the cards. Let us have our fun. Let us go nuts. Let there be real differentiation. Sometimes it feels like this market becomes too too much the same.
The post Reinforcement Learning Comes Home: NVIDIA and Unsloth Democratize AI Mastery appeared first on StartupHub.ai.
Reinforcement Learning, once the exclusive domain of supercomputers and multi-million dollar data centers, has decisively stepped into the realm of local computing. This shift, highlighted in a recent tutorial by Matthew Berman, demonstrates how powerful AI models can now be trained on consumer-grade NVIDIA RTX GPUs using open-source tools like Unsloth, fundamentally democratizing access to [β¦]
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The post Nvidia and AI Stocks Poised for Higher Rerating, Says Fundstratβs Tom Lee appeared first on StartupHub.ai.
The prevailing sentiment around artificial intelligence, despite its unprecedented surge, often grapples with questions of sustainability and valuation. Yet, Tom Lee, Fundstrat Global Advisors head of research and Fundstrat Capital CIO, posits a distinctly bullish outlook, arguing that leaders in the AI space, notably Nvidia, are not overvalued but rather poised for a significant upward [β¦]
The post Nvidia and AI Stocks Poised for Higher Rerating, Says Fundstratβs Tom Lee appeared first on StartupHub.ai.
The post Swarm Intelligence: Decoding the Power and Perils of Multi-Agent AI appeared first on StartupHub.ai.
The notion that multiple, specialized AI agents can collectively outperform a single, monolithic system represents a significant shift in artificial intelligence development. Anna Gutowska, an AI Engineer at IBM, articulates this concept with clarity, illustrating how βmany simple AI agents, each with a small job, coming together to solve big, complex problems.β This paradigm, known [β¦]
The post Swarm Intelligence: Decoding the Power and Perils of Multi-Agent AI appeared first on StartupHub.ai.
The post Soverli smartphone OS cracks the mobile sovereignty problem appeared first on StartupHub.ai.
The Soverli smartphone OS enables a fully auditable, isolated operating system to run simultaneously with Android, eliminating the security-usability trade-off.
The post Soverli smartphone OS cracks the mobile sovereignty problem appeared first on StartupHub.ai.



This season, Google Search and Shopping Ads are expected to surge past $70 billion in holiday spending. But thereβs a hidden flaw in the auction system β one most advertisers donβt realize is costing them money even when competitors arenβt in the game.
BrandPilot calls this the Uncontested Google Ads Problem, and itβs becoming one of the most overlooked sources of wasted ad spend in peak retail season.
During SMX Next, John Beresford, Chief Revenue Officer at BrandPilot, unpacked how a little-known behavioral quirk in Googleβs auction logic can cause advertisers to overspend on their own brand terms, their Shopping placements, and even their category keywords β simply because Google doesnβt automatically reduce your CPC when competition disappears.
Instead of paying less when youβre the only bidder, you may be paying the same high rate youβd pay when rivals are activeβ¦ without realizing it.
Itβs a phenomenon happening thousands of times a day across major brands, and many marketers never notice itβs occurring.
In his session, Beresford discussed:
He also shared examples of how advertisers are reclaiming wasted spend and reinvesting it into growth β without sacrificing impression share, traffic, or revenue.
Watch BrandPilotβs session now (for free, no registration required) to learn how to:
If youβre running Google Search or Shopping campaigns this holiday season, you canβt afford to miss this session. Learn how to stop the Google Grinch from stealing your budget β and start turning those savings into real performance gains.

One of last year's standout gaming stories was the rise of indie hits, proving that while game dev budgets balloon, spectacle matters less than how fun a game is to play.
Yono rewards you to scroll less. Stay under 1 hour on Instagram and TikTok per day -> earn 5 points -> stack points -> redeem them at local spots you actually want to visit. 30 points = free specialty coffee, or two Guinness pints, or dessert. The less you doomscroll, the more you earn. Businesses get free foot trafficβthey set their offers, pay nothing, and 76% of users buy extra items and return without promotions. You turn phone addiction into real money: scroll less, earn rewards, support local spots, and afford to go out again.
Real-time screen translator for any game
Visual pattern mapping for adhd & neurodivergent minds
Free AEO analytics with content tools to boost AI rankings
Keep 95% of your revenue.
Automated pre-meeting research in Google Calendar.
Help parents explain the world, one question at a time
Minimalist writing editor with vim mode
Syllaby: Create, Edit, PublishβAll in One
Turn websites into APIs
AI-native engineer hiring via real-work simulations
Remix your tabs into custom apps tailored uniquely to you!
Transform voice memos into actionable notes

CodersNote is an AI-powered learning platform that personalizes how students and professionals learn programming. It creates customized roadmaps, courses, and projects based on each learnerβs goalsβwhether itβs frontend development, AI, data science, or any other tech career path.
The prebuild roadmaps and 3,000+ free learning resources available on the platform are carefully chosen and designed by 14 industry experts, ensuring learners follow the most relevant and up-to-date path in tech. It also provides real-time guidance, interview preparation, and 24/7 AI supportβhelping learners build practical skills, stay motivated, and achieve faster career growth in technology.
YouTube is making it easier for creators and brands to maximize collaborations.
Following the implementation of new restrictions, Australian teens have quickly adjusted.
Nvidia plans FP64 comeback following Blackwellβs disappointing HPC results While Nvidia Blackwell series GPUs have proven highly popular for AI workloads, the supercomputing community is disappointed by their lack of FP64 (double-precision) performance. In fact, Nvidiaβs new B300 βBlackwell Ultraβ chip practically ignores FP64 with its anaemic 1.2 teraflops of performance. For context, Nvidiaβs A100 [β¦]
The post Nvidia plots return to FP64 with next-gen HPC ships appeared first on OC3D.
Meta is looking to improve its data ingestion processes based on real world conversation.
More ways to stay up to date with the latest info from X.
X's prospects are improving, though it's still well below pre-Elon revenue levels.
TikTok is looking to draw in more live content viewers.
MSI celebrates 10 years of GODLIKE performance with its MEG X870E GODLIKE X Edition motherboard MSI has just launched their new MEG X870E GODLIKE X Edition motherboard, a new AM5 flagship motherboard thatβs limited to 1000 units. This motherboard is both a high-end motherboard and a collectorβs item, boasting high-end specifications and unique numbering. Weβve [β¦]
The post MSI launches its MEG X870E GODLIKE X Edition motherboard appeared first on OC3D.
GigLegal is dedicated to empowering New York City's independent workforce. We aim to provide affordable, accessible, and easy-to-understand legal tools, ensuring every freelancer can operate with the confidence and security of a large corporation. We believe legal protection should be a standard, accessible tool, not an expensive barrier.
The biggest challenges in freelancing are non-payment and scope creep. GigLegal is designed to solve these problems at their root. We combine legally-sound contracts with a secure escrow service, and create a 'trust protocol' that aligns expectations for both freelancers and their clients from day one.
The post The Future of Code: From Syntax to AI-Guided Vibe Engineering appeared first on StartupHub.ai.
The advent of large language models is fundamentally reshaping the very act of software creation, moving developers from the meticulous crafting of syntax to a more abstract, intent-driven collaboration with artificial intelligence. This profound shift was the central thesis of Kitze, founder of Sizzy, in his recent discourse on the evolution from βvibe codingβ to [β¦]
The post The Future of Code: From Syntax to AI-Guided Vibe Engineering appeared first on StartupHub.ai.
The post The Generative AI Threat is Already in Your Browser: Malicious Chrome Extensions Explode in Latest Cyber Scourge appeared first on StartupHub.ai.
The rush to integrate Generative AI into daily workflows has opened a dangerous new front in the cyber security war, one thatβs hiding in plain sight: the humble browser extension. New research from Palo Alto Networks security experts, Shresta Seetharam, Mohamed Nabeel, and William Melicher, reveals a disturbing trend of malicious GenAI-themed Chrome extensions being [β¦]
The post The Generative AI Threat is Already in Your Browser: Malicious Chrome Extensions Explode in Latest Cyber Scourge appeared first on StartupHub.ai.
Thevenin is an Internal Development Platform (IDP) designed for organizations that need to build with startup speed while maintaining rigorous enterprise standards regarding governance, security, and data sovereignty.
Developers can easily create docker containers and attach files, variables and even volumes. Organizations can check what has been changed and who did it through version control and limit cloud resource usage by environment.
Upload 100s of product images. Get SEO titles, descriptions & tags automatically. Sync directly to your WooCommerce or Shopify store. Go from photos to profitable listings in minutes.
Create Topical Authority via our maps feature, which plans and visualizes your content in a way never seen before. Get Keyword Research on the map directly with out competitor analysis tool, revolutionizing the way keyword research is done. No more second guessing which keywords are actually being used and how.
Let AI agents write & manage your SaaS emails
Open source, webhook-free payments that AI can one-shot
The easiest way to use GitHub Octicons in your Blazor apps
Learn, invent and innovate electronics
AI-powered video creation for work
The post Intelligence as Parsimony and Self-Consistency: Rethinking AIβs Foundations appeared first on StartupHub.ai.
Professor Yi Ma, a world-renowned expert in deep learning and artificial intelligence, presented a compelling challenge to the prevailing paradigms of AI during his interview on Machine Learning Street Talk. Speaking with the host, Tim Scarfe, Professor Ma systematically dismantled common assumptions about large language models (LLMs) and 3D vision systems, arguing that current successes [β¦]
The post Intelligence as Parsimony and Self-Consistency: Rethinking AIβs Foundations appeared first on StartupHub.ai.
TaskYak makes scheduling background jobs on your infrastructure simple and collaborative. Managing task orchestration can be a heavy lift β the Yak helps carry that load. Unlike Airflow, which can take a degree in DevOps to configure and maintain, TaskYak can be set up in under five minutes, getting your team up and running with clear, team-based workflow management right away.
The post MiniMax M2: An Agentic Model Engineered for Real-World Developer Experience appeared first on StartupHub.ai.
The true measure of an AI modelβs utility isnβt just its benchmark scores, but its seamless integration into the messy, dynamic reality of human workflows. This philosophy underpins MiniMax M2, the latest AI model unveiled by Senior Researcher Olive Song at the AI Engineer Code Summit. Songβs presentation highlighted MiniMaxβs distinctive approach as both a [β¦]
The post MiniMax M2: An Agentic Model Engineered for Real-World Developer Experience appeared first on StartupHub.ai.
FindMark is a smart bookmark manager that makes it easy to organize and search your saved links. Instead of digging through folders, you can find anything instantly using tags, filters, and powerful search syntax.
It also includes cloud backup, a private space for sensitive bookmarks, and a recycle bin for easy recovery. Designed for Chrome and Edge, FindMark helps you keep your online resources tidy, searchable, and safe β all in one place.
Building a custom liquid cooling distro plate using unusual methods The growing availability of 3D printers, laser cutters and other tools has started an at-home manufacturing revolution. With the proper knowledge, you can now build almost anything. On YouTube, Visual Thinker has put his skills to the test by creating a custom PC liquid cooling [β¦]
The post Modder rethinks PC liquid cooling with 3D printing, silicone, and a laser appeared first on OC3D.




































AMD wants to hire engineers with experience with Intelβs PowerVia tech AMD has issued a new job listing for a Physical Design Verification CAD Engineer, and has asked explicitly for candidates who have βknowledge of Power Viaβ, an Intel technology. This suggests that AMD may make some future chips with Intel silicon inside. PowerVia is [β¦]
The post Why AMD wants engineers with knowledge of Intel silicon appeared first on OC3D.

The post AI Breaks Data Barriers with Text-to-SQL appeared first on StartupHub.ai.
The long-standing chasm between business acumen and technical data querying is finally narrowing, thanks to advancements in artificial intelligence. Michael Dobson, Product Manager at IBM, recently presented on how Large Language Models (LLMs) are powering Text-to-SQL capabilities, fundamentally changing the paradigm of data analytics. His insights revealed how this technology empowers non-technical users to extract [β¦]
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The post Tinker launches OpenAI API compatibility, challenging vendor lock-in. appeared first on StartupHub.ai.
Tinker is now generally available and introduced an OpenAI API-compatible interface, drastically lowering the switching cost for developers seeking alternatives.
The post Tinker launches OpenAI API compatibility, challenging vendor lock-in. appeared first on StartupHub.ai.
Clevera is an AI-driven platform that transforms raw screen recordings into professional-grade product videos, tutorials, and demos in minutes. Just record your screen using the Clevera macOS app, and our AI automatically removes pauses and misclicks, writes a natural narration script, generates a voiceover, and syncs everything perfectly.
You can customize your video with different tones, voices, and branding options, or instantly translate it into 23 languages. Clevera also supports LiveSync, so any updates you make are instantly reflected everywhere your video is embeddedβno re-exports needed.