Alphabet just made its biggest bet yet on autonomous driving, and the market is paying attention. Waymo, Alphabetβs self-driving car unit, said Monday it raised a $16 billion funding round that values the company at $126 billion post-money, a sharp [β¦]
The crypto market never sleeps. Unlike stock exchanges, which shut down at night and on weekends, the Bitcoin & Ethereum markets operate 24 hours a day, 7 days a week. While this constant movement offers new opportunities to those willing [β¦]
Health plans are buried under rising medical costs, tighter oversight, and a claims process that quietly burns through hundreds of billions of dollars each year. A growing number are betting that AI can helpβif it doesnβt create new risk in [β¦]
AI has changed how software gets built, shipped, and attacked β all at once. The gap between when a vulnerability is disclosed and when it is exploited is shrinking, and security teams are running out of time to react. That [β¦]
For years, PayPal has talked about moving faster. Now itβs the board thatβs making a bet that leadership, not strategy slides, will finally change the pace. The payments giant announced today that Enrique Lores will take over as President and [β¦]
Elon Musk just pulled his biggest corporate move yet, folding his artificial intelligence startup xAI into SpaceX as the combined company lines up for what could become one of the largest IPOs in history. In a blog post published Monday, [β¦]
Itβs Monday, February 2, 2026, and weβre back with todayβs top startup and tech funding news. Todayβs financings reflect mounting investor momentum around autonomous systems, stablecoin infrastructure, and embodied AI. As AI-native platforms expand from cloud to robotics and financial [β¦]
Intel and SoftBank subsidiary, Saimemory, have signed a new collaborative agreement to advance the development and manufacture of a new type of vertical-stacked memory known as Z-Angle Memory, or ZAM.
Elon Musk merges SpaceX and xAI to help achieve his dreams of putting AI data centers in orbit, with a goal of hitting 100 gigawatts of compute in space.
A new report suggests that only 3.3% out of the Microsoft 365 and Office 365 users who interact with Copilot Chat actually pay for it after CEO Satya Nadella indicated it had grown βnearly 3x year-over-yearβ.
OpenAI rolled out a standalone app for its AI coding assistant, Codex, opening a new chapter in how developers work with autonomous software agents. The app is available on Apple computers, and for a limited time, Codex access is open [β¦]
BlueFive Capital has quietly locked in one of the largest new tech-focused funds to emerge from the Gulf this year. The Abu Dhabi-headquartered alternative investment firm said it has closed its Onyx Fund I at $3 billion, setting its sights [β¦]
GrubMarket just closed another major funding round, and this one comes with a clear signal: the company is scaling from strength, not necessity. The AI-focused food tech company announced today that it has raised around $50 million in Series H [β¦]
Oracle is preparing one of the largest capital raises ever attempted by a software company, lining up as much as $50 billion in debt and equity to keep pace with demand for its cloud infrastructure. The plan, disclosed Sunday, lays [β¦]
For years, AI agents lived in demos, research papers, and conference slides. They talked. They suggested. They waited. Then OpenClaw showed up and started doing. The open-source AI agent has surged from obscurity into one of the most talked-about projects [β¦]
A federal jury in San Francisco has delivered a verdict that lands at the center of the global AI race, the Department of Justice announced Friday. On Thursday, jurors convicted a former Google software engineer of stealing sensitive AI trade [β¦]
At least four Wisconsin municipalities are understood to have signed underhanded nondisclosure agreements concerning new data centers while negotiating their development.
Nvidia and OpenAI are still in talks about the $100-billion MOU the two parties signed in September 2025, and it seems that deal will be modified for a much "smaller" sum of tens of billions of dollars.
A new heat exchange system between the LHC and the French town of Ferney-Voltaire is directing waste heat energy from CERN's accelerator to warm thousands of homes and businesses.
Boring Business Ideas That Actually Make Money Every month, TechStartups covers hundreds of startups raising billions to build the βnext big thing.β AI models. Robotics platforms. New financial rails. The ambition is real, and the technology is impressive. At the [β¦]
Elon Musk may be preparing his boldest corporate reshuffle yet, and this one could redraw the lines between rockets, electric cars, and artificial intelligence. SpaceX is quietly weighing deals that would bring one of Muskβs other companies under the same [β¦]
Itβs Thursday, January 29, 2026, and weβre back with todayβs top startup and tech funding news. Todayβs deals reflect deepening investor commitment to AI cloud infrastructure, chiplet interconnects, fintech orchestration, and scalable biotech. As competition accelerates in AI and advanced [β¦]
Apple just made one of its biggest bets yet on AI and audio, and it did it in its usual quiet way.Β The company has acquired Israeli artificial intelligence startup Q.ai, Apple confirmed Thursday. Financial terms were not officially disclosed, though [β¦]
ICE is quietly building one of the most advanced AI stacks in federal law enforcement, and the latest disclosure confirms it. According to an update to the Department of Homeland Securityβs 2025 AI Use Case Inventory, U.S. Immigration and Customs [β¦]
Microsoft's financial earnings report reveals that OpenAI accounts for 45% of its Azure cloud computing backlog, yet Microsoft's net income jumped by $7.6 billion, primarily due to its investment in OpenAI.
In one of the first official updates into the H200 China saga, CEO Jensen Huang has confirmed Beijing hasn't decided whether to allow imports of the chip, and that the company ahs received no new orders from Chinese companies as a result.
Even before AI, athletes have been pressured to look a certain way: thin, muscular and attractive. Coaches, opponents, spectators and the media shape how athletes think about their bodies.
Given the growing use of AI on social media, understanding just how AI depicts athlete and non-athlete bodies has become critical. What it shows, or doesnβt, as βnormalβ is widely viewed and may soon be normalized.
Lean, young, muscular β and mostly male
As researchers with expertise in body image, sport psychology and social media, we grounded our study in objectification and social media theories. We generated 300 images using different AI platforms to explore how male and female athlete and non-athlete bodies are depicted.
We documented demographics, levels of body fat and muscularity. We assessed clothing fit and type, facial attractiveness like having neat and shiny hair, symmetrical features or clear skin and body exposure in each image. Indicators of visible disabilities, like mobility devices, were also noted. We compared the characteristics of male versus female images as well as the characteristics of athlete and non-athlete images.
The AI-generated male images were frequently young (93.3 per cent), lean (68.4 per cent) and muscular (54.2 per cent). The images of females depicted youth (100 per cent), thinness (87.5 per cent) and revealing clothing (87.5 per cent).
The AI-generated images of athletes were lean (98.4 per cent), muscular (93.4 per cent) and dressed in tight (92.5 per cent) and revealing (100 per cent) exercise gear.
Non-athletes were shown wearing looser clothing and displaying more diversity of body sizes. Even when we asked for an image of just βan athlete,β 90 per cent of the generated images were male. No images showed visible disabilities, larger bodies, wrinkles or baldness.
These results reveal that generative AI perpetuates stereotypes of athletes, depicting them as only fitting into a narrow set of traits β lacking impairment, attractive, thin, muscular, exposed.
The findings of this research illustrate the ways in which three commonly used generative AI platforms β DALL-E, MidJourney and Stable Diffusion β reinforce problematic appearance ideals for all genders, athletes and non-athletes alike.
People with body fat, wrinkles or baldness were also largely absent.
Addressing bias in the next generation of AI
These patterns reveal that AI isnβt realistic or creative in its representations. Instead, it pulls from the massive database of media available online, where the same harmful appearance ideals dominate. Itβs recycling our prejudices and forms of discrimination and offering them back to us.
AI learns body ideals from the same biased society that has long fuelled body image pressure. This leads to a lack of diversity and a vortex of unreachable standards. AI-generated images present exaggerated, idealized bodies that ultimately limit the diversity of humans and the lowered body image satisfaction that ensues is related greater loneliness.
And so, as original creators of the visual content that trains AI systems, society has a responsibility to ensure these technologies do not perpetuate ableism, racism, fatphobia and ageism. Users of generative AI must be intentional in how image prompts are written, and critical in how they are interpreted.
We need to limit the sort of body standards we internalize through AI. As AI-generated images continue to populate our media landscape, we must be conscious of our exposure to it. Because at the end of the day, if we want AI to reflect reality rather than distort it, we have to insist on seeing, and valuing, every kind of body.
G42, Cerebras Systems and the Institute of Foundation Models at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI),Β today announced the release of K2 ThinkΒ V2. This latest 70-billion parameter advanced reasoning system reasoning system is now built on the K2-V2 base model, IFMβs strongest fully frontier-class open-source foundation model thatβs purpose built for K2 Think.
This launch marks a major milestone for the UAEβs technological sovereignty. While earlier versions of K2 Think were open and widely accessible, K2 ThinkΒ V2Β (70B) is the first to be open from end-to-end; from pre-training data and curation through post-training, reasoning alignment, and evaluation. The result is a reasoning system that is both more transparent and more powerful.
By upgrading the base model to K2-V2, K2 Think V2 unlocks a new level of performance, openness, and independence, reinforcing the UAEβs leadership in building frontier-grade AI systems that are globally accessible and fully sovereign.
Why K2 ThinkΒ V2 is Different
K2 ThinkΒ V2Β marks a step change in open reasoning systems, shifting from a reasoning model layered on top of a foundation to one built directly into it. Inheriting K2-V2βs long-context capabilities and full training transparency, it now operates as a fully sovereign system end-to-end.
Every stage of K2 ThinkΒ V2Β (70B) is open, inspectable, and independently reproducible, ensuring both scientific credibility and national AI sovereignty. Designed as a purpose-built reasoning system, it solves complex problems step-by-step using long chains of thought across mathematics, science, coding, logic, and simulation.
This reasoning-first, fully open foundation translates directly into greater levels of performance. K2 Think V2 delivers leading results on complex reasoning benchmarks, including AIME2025, GPQA-Diamond, HMMT, and IFBench, when compared against other open-source reasoning systems.
Key Features, Made Simple
Built on K2-V2
K2 ThinkΒ V2Β (70B) is powered by MBZUAI IFMβs latest foundation model, designed from the outset to support reasoning, long context, and alignment, raising the ceiling for what the reasoning system can achieve.
Longer Memory, Deeper Thought
Expanded context length enables sustained, multi-step reasoning over much larger bodies of information.
Truly Independent Data Pipeline
All training relies on IFM-curated datasets, including the Guru dataset, fully decontaminated from downstream benchmarks to ensure fair and trustworthy evaluation.
360-Open Transparency
From pre-training data and intermediate checkpoints to post-training recipes and evaluations, every component is available for inspection, reuse, and extension.
The National Experts Program has called on Emirati professionals working in the field of artificial intelligence to join its new Artificial Intelligence track (NEP-AI), with applications scheduled to open on 29 January 2026.
Building on the success of NEP since 2019, NEP-AI is a specialized track of the program, focusing on the nationβs strategic AI priorities with the goal of developing a national cadre of AI leaders.
NEP-AI was launched under the patronage of His Highness Sheikh Mansour bin Zayed Al Nahyan, Vice President, Deputy Prime Minister, and Chairman of the Presidential Court, during the graduation of NEP Cohorts 2.0 and 3.0 in October 2025. The first cohort of NEP-AI is scheduled to begin in May 2026.
NEP-AI is developed in alignment with the UAE National Strategy for Artificial Intelligence 2031 and contributes directly to its vision of positioning the UAE among the worldβs leading nations in AI.
NEP-AI participants are selected based on strong academic, professional, and leadership credentials, as well the ability to translate knowledge and expertise into tangible, practical impact across national sectors.
The program spans 25 priority sectors across the national economy, including six core tracks: AI Infrastructure and Hardware, AI Models and Application, AI Productization and Entrepreneurship, Sovereign AI and National Capability, HumanβAI Leadership and Foresight, and Applied AI Domains.
NEP-AI is designed to translate national AI strategy into execution. The program places strong emphasis on human capital, governance, ethics, data readiness, and responsible AI deployment, ensuring that participants move beyond theory to delivery.
Participants will work on developing initiatives and projects linked to their respective sectors, addressing multiple institutional and national challenges and enhancing measurable impact. Each participant will present a capstone project connected to their organisation or sector, aimed at achieving scientific solutions with tangible and sustainable impact.
Participants are also supported by a network of NEP-AI mentors, in addition to leveraging global expertise to enhance local capabilities by combining UAE-based centres of excellence with leading international institutions, alongside international study visits aligned with participantsβ AI specialization tracks.
Todayβs issue dives into Level3AIβs unique approach to building customer support agents for enterprises and the shift in Vietnamβs IPO expectations.
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