Welcome to Eye on AI, with AI reporter Sharon Goldman. The pro-Iran meme machine trolling Trump with AI Lego cartoons\u2026Amazon\u2019s Andy Jassy defends Amazon\u2019s $200 billion spending spree…OpenAI pauses Stargate U.K. data center, citing energy costs.<\/p>\n
It\u2019s been another one of those wild weeks in AI, with Anthropic electing not<\/a> to release its new Claude Mythos model because of concerns about the cybersecurity risks it poses (and forming a coalition to use a preview version of the model to bolster cybersecurity defenses); Meta releasing<\/a> its first AI model since hiring Alexandr Wang; and mounting expectations about OpenAI\u2019s upcoming new \u201cSpud\u201d model.\u00a0<\/p>\n Most of these AI models run on Nvidia GPUs, the sophisticated and expensive AI chips (at over $30,000 a pop) that power their training and output. But across the industry, access to those chips remains a bottleneck. OpenAI president Greg Brockman, for example, has said allocating GPUs at OpenAI is \u201cpain and suffering.\u201d<\/p>\n This week, at the HumanX conference in San Francisco, I discovered that even inside Nvidia, GPUs are scarce.<\/p>\n I sat down with Bryan Catanzaro, who leads applied deep learning research at Nvidia, overseeing teams working on AI-driven graphics, speech recognition, and simulation. Catanzaro was also among the first, back in the early-to-mid 2010s, to notice researchers snapping up Nvidia GPUs to train AI models\u2014a signal that helped push CEO Jensen Huang to double down on AI, setting the stage for the company\u2019s now-historic run.<\/p>\n Today, though, even Catanzaro\u2019s teams are struggling to access enough GPUs.\u00a0\u201cMy team uses AI very deeply in our work, and their primary complaint is they want higher limits,\u201d Catanzaro told me. \u201cThey want more GPUs.\u201d<\/p>\n \u201cEfficiency is also intelligence\u201d<\/p>\n In fact, he said one of his main jobs now is simply trying to secure more compute for his teams. \u201cWe\u2019re all supply constrained,\u201d he said. \u201cJensen will say, \u2018I\u2019m sorry, Bryan, but those are sold.\u2019 We operate within those constraints.\u201d<\/p>\n One of Catanzaro\u2019s projects has been leading the team building Nvidia\u2019s Nemotron, a family of models that are open source\u2014meaning users can freely download them to use, study, or modify. To be clear, Nvidia isn\u2019t trying to compete in the model-building race with the likes of OpenAI and Anthropic. Instead, it\u2019s building them to strengthen a developer ecosystem that remains tied to Nvidia hardware and software.\u00a0<\/p>\n The Nemotron models are known for being particularly GPU-efficient. And Catanzaro said it\u2019s the very constraints on GPU access at Nvidia itself that is driving the push to make Nemotron models more efficient. \u201cIn a supply-constrained world, efficiency is also intelligence,\u201d he said.\u00a0<\/p>\n No longer a science project<\/p>\n But surprisingly, efficiency isn\u2019t bad for business. Catanzaro said it was Jevons Paradox at work: When something becomes more efficient, demand often surges. \u201cPeople find all sorts of new ways to use a thing when it gets more efficient,\u201d he said.<\/p>\n Still, he acknowledged that Nemotron\u2019s growing visibility inside Nvidia has also helped unlock more resources. \u201cWe\u2019ve been working on [Nemotron] for a long time, but it\u2019s really only in the past six months that it\u2019s gotten more attention. As people inside Nvidia better understand the importance of this work, you get better storytelling, better collaboration, and more support across the company.\u201d<\/p>\n Nvidia has realized, he added, that it can no longer take a hands-off approach to the AI ecosystem. In the past, Nvidia could rely on others to build the models and applications that drove demand for its chips. Now, as AI becomes more competitive and chip-constrained, the company sees a more active role for itself in shaping how that ecosystem develops.<\/p>\n \u201cIn the past, some people felt like we could just let the ecosystem take care of itself,\u201d he said. \u201cNow it\u2019s much more obvious that Nvidia has a bigger role to play\u2014a real responsibility and opportunity with Nemotron.\u201d<\/p>\n That framing also helps elevate the Nemotron work inside Nvidia, where teams are competing for scarce GPU resources. \u201cThis isn\u2019t a science project,\u201d Catanzaro said. \u201cIt\u2019s not just me asking for resources for my team. This is about Nvidia\u2019s future.\u201d<\/p>\n With that, here\u2019s more AI news.<\/p>\n Sharon Goldman FORTUNE ON AI<\/p>\n Meta unveils Muse Spark, its first AI model since hiring Alexandr Wang and a bellwether for CEO Mark Zuckerberg\u2019s multi-billion dollar AI push<\/a>\u2013by Jeremy Kahn<\/p>\n Supermicro launches internal probe after cofounder\u2019s arrest on charges of $2.5 billion in chip smuggling<\/a>\u2013by Amanda Gerut<\/p>\n A Meta employee created a dashboard so coworkers can compete to be the company\u2019s No. 1 AI token user\u2014and Zuckerberg doesn\u2019t even rank in the top 250<\/a>\u2013by Jacqueline Munis<\/p>\n AI IN THE NEWS<\/p>\n The pro-Iran meme machine trolling Trump with AI Lego cartoons.\u00a0A new report from Wired<\/a> describes how a group of young pro-Iranian creators called Explosive Media is using AI-generated, Lego-style videos to spread sophisticated, viral propaganda during the current conflict, reaching millions across TikTok, X, and Instagram. Unlike traditional state messaging, the videos blend humor, internet-savvy cultural references, and simplified storytelling to resonate with American audiences, even incorporating memes and English-language rap. Researchers say the strategy is effective because it distills complex geopolitical events into highly shareable content while tapping into existing disaffection in the U.S., illustrating how AI tools are enabling a new kind of \u201cslopaganda\u201d war\u2014where influence campaigns are faster, more targeted, and far more culturally fluent than in the past.<\/p>\n Amazon’s Andy Jassy defends Amazon\u2019s $200B spending spree. GeekWire reported<\/a> on\u00a0Amazon CEO Andy Jassy’s latest shareholder letter, which revealed that AWS\u2019s AI business has already reached a $15 billion annual revenue run rate, which Jassy argued means demand is strong enough to justify roughly $200 billion in planned capex. Jassy framed AI as a \u201conce-in-a-lifetime\u201d opportunity and positioned Amazon squarely in the middle of the current AI \u201cland rush,\u201d pointing to surging demand for its custom chips like Trainium\u2014some of which are already largely sold out years in advance\u2014as well as interest from customers eager to secure future capacity. The letter makes clear that Amazon is betting aggressively on owning more of the AI stack, from infrastructure to chips to potentially selling those capabilities externally.<\/p>\n OpenAI pauses Stargate UK data center, citing energy costs. According to Bloomberg<\/a>, OpenAI is pausing its planned Stargate data center project in the UK, highlighting how even the most aggressive AI infrastructure buildouts are running up against real-world constraints like energy costs and regulation. The move comes as the company reins in spending ahead of a potential IPO and narrows focus to its core ChatGPT business amid intensifying competition from Anthropic and Google. While OpenAI says it still sees long-term potential in the UK, the decision underscores a broader reality: Massive AI infrastructure bets\u2014from Texas to Norway to the UAE\u2014are increasingly shaped not just by ambition, but by economics, geopolitics, and access to affordable power.<\/p>\n EYE ON AI NUMBERS75%<\/p>\n That’s how many executives say their AI strategy is more about optics than any actual internal guidance, according to Writer’s new 2026 Enterprise AI Adoption Report<\/a>, which surveyed 2,400 knowledge workers including 1,200 C-suite executives and 1,200 employees. In addition, 39% have no plan for how AI actually drives revenue. Yet, 69% are planning layoffs this year.<\/p>\n
sharon.goldman@fortune.com <\/a>
@sharongoldman<\/a><\/p>\n