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tors is a solid step. SpaceX and Tesla founder Elon Musk echoed that oversight is long overdue. Demis Hassabis from Google DeepMind called the essay a step in the right direction. Microsoft CEO Satya Nadella emphasized that pursuing AI without keeping human benefit at the center isn’t worth doing. Tech investor Gavin Baker posted a great write-up below summarizing these industry responses Will Chinese labs follow the suit? Some social media users, including former CNBC anchor Deirdre Bosa, turne

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sm that gives rise to these off-balance sheet guarantees and backstops is the same one we described in The Front End Gets Crowded (institutional article). The Gigascalers (Amazon, Microsoft, Google, Meta, Oracle) have been gatekeeping the investment grade capital that the AI buildout runs on and have benefitted tremendously from the high spread between offtake price they are being charged, and spot/short-term price that they are selling at as well as services that sit on top. In response, Nvidia

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s well as a great deal of startups and regular-sized companies, is indicative of the overall spend of the AI industry, with the caveat that it doesn’t include massive players like Microsoft or major banks, and customers can opt out of being included in research. I also want to be clear that when Ramp says “AI products and services,” that includes AI startups that sell subscriptions with subsidized token spend, meaning that users can burn far more than their subscription price in tokens. This mea

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r” part of circular financing to people, in the sense that some of the agreements are kind of clunky. NVIDIA funds OpenAI, who then spends that money to rent back NVIDIA GPUs from Microsoft, Google, Amazon, or CoreWeave, and then that money is used…to buy servers from Taiwanese ODMs (original design manufacturers) that build their servers, who then buy GPUs from NVIDIA to put in them. The reason it’s clunky is that people will, even if it’s not true, claim that there’s some indeterminately-large

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r “free”. Classic examples include 1) Google offering Chrome for free and open-sourcing Android, which increased access to the web and made search advertising more valuable and 2) Microsoft retaining the right to license MS-DOS to IBM’s competitors, which helped turn the PC into a commodity hardware platform. In Nvidia’s case, AI models and applications are the complements to its GPUs. The long-term health of their business depends on a vibrant, diverse AI ecosystem that exists outside of just A

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ts to Central London. Farage was, until Keir Starmer’s ouster, the bookies’ favorite to be the next UK Prime Minister. Meanwhile, in 2022, the largest tech companies in the world (Microsoft, Google, Meta, Amazon and NVIDIA) had hit a rough patch of flat-to-low growth after desperate measures had failed to help. While both the media and world governments were adept at making moves to sustain systemic thinking — that the system or systems know best and must be protected (we must prop up banks, we

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You can talk about what a pig wants. That’s very natural to us. But there are also more exotic things that we can usefully apply the intentional stance to. You can talk about what Microsoft, the corporation, wants. You can talk about corporations in general having the intention to do regulatory capture or to make profit. They’re not the same type of biological organism that humans and animals are. But the intentional stance often applies to them. I just think AI agents are another such system in

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nd associated hardware; Create demand for AI compute for its customers NVIDIA has succeeded in doing the first primarily by selling these GPUs to hyperscalers like Amazon, Google, Microsoft, Oracle, and Meta, who make up somewhere between 50% and 60% of its GPU sales depending on which analyst you ask. The rest comes from a mixture of unnamed “sovereign AI customers” and “neoclouds” — companies that exist to raise debt, buy NVIDIA GPUs, and put them in data centers to rent to theoretical AI cust

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ne of AI’s most frustrating lies is that it sells itself as “autonomous” as it continues the depressing trend of software that blames the user for its failure to meet their needs. Microsoft, Google, Meta and Amazon have made their products increasingly-convoluted, then attached a supposedly-magical tool to them that somehow makes them more convoluted. You know what I’d love? Spell-check to work in Google Docs rather than putting a red squiggly line underneath and saying “yeah there’s probably so

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vely all of MiniMax's 2026 downloads are of models above 70B, along with 88% of Moonshot's, 55% of DeepSeek's and 39% of Z.ai's. No large American account looks like this: Google, Microsoft and IBM Granite record essentially none of their 2026 downloads above 70B, and NVIDIA and Meta only 14% and 9%. The difference becomes clearer in total downloads. Moonshot’s frontier-only portfolio recorded 37M downloads over the year, while Qwen’s broader release strategy across model sizes reached 2,045M (a

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of bubble-and-burst cycle. At the time, the internet had become the world’s number one hot topic; people believed the internet would change everything. So on the application side, Microsoft went all-out to crush Netscape’s browser with IE—because that entry point, that portal—just like today, every internet application is fighting over the entry point for users—back then it was the same: everyone believed the browser was the number one gateway, because everything had to go through the browser, s

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two AI labs, which insist on a closed-source approach and reportedly lobby for policies that could constrain open models. The other is a coalition of tech companies led by Nvidia, Microsoft and Meta, which are strongly in favor of open-weight models. They signed a letter last week warning against “premature restrictions” on open-weight models and launched an open AI security alliance, an organization building tools to defend against cyber attacks from frontier models. Both sides have justifiable

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CLOUD Timothy Prickett Morgan Published fri 31 Jul 2026 // 19:23 UTC For those of us who grew up watching Microsoft DOS on X86 PCs transform into the Windows Server platform along with applications, databases, and middleware, the modern Microsoft – a cloud innovator and an AI force in its own right – is a behemoth to behold. The financial results just sound silly, with market capitalization in the trillions and revenues in the hundreds of billions. This may all sound like funny money, but its re

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are the most powerful general AI tools because they have good applications and harnesses powered by very strong AI models. But what about everyone else? If your workplace runs on Microsoft, you may only have access to Copilot, which uses a mix of AI models and is okay for working with office documents but lags badly in terms of its agentic abilities. And for the technically inclined, Chinese open weights models like Kimi K3, DeepSeek, and Qwen are surprisingly capable, but do require expertise

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e. Maybe chatbots can grow into products and don’t need to be wrapped in software. Maybe one lab will start out-executing all the others and pull ahead on sheer product dynamism - Microsoft, Google, Facebook and Apple had to execute their way into a wining position before they had winner-takes-all efforts. Maybe something else will happen. In particular, we have not one but two potential dei ex machina - Trump and China. China is reportedly considering regulating open source and some people clos

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nt: HUMAIN in Saudi Arabia at up to 600,000 GB300, Stargate Abilene at a 450,000 GPU target, South Korea’s national 260,000 Blackwell program, Nscale’s 200,000 GB300 commitment to Microsoft, xAI Colossus 2 at roughly 110,000 installing, Argonne Solstice and Equinox at 110,000 combined, and Stargate Norway at 100,000 announced. This is why “GPU count” is becoming an incomplete question. The constraint has moved outward to power, land, cooling, interconnect, permitting, debt, and offtake. A GPU or

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ic, has benefitted tremendously from open research — indeed, the AI revolution was kicked off by my former team (Google Brain) freely publishing the Transformers paper! Imagine if Microsoft’s terms of use barred anyone from using their tools to build competitive software, or if Google barred using it to search for information to work on competing search engines. Anthropic’s argument that it was unsafe for others to be able to make advances in AI also rang hollow. Initially, Anthropic silently de

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le to fully complete “Cooling Tower” on 3/10 attempts (with all other models at 0/10), as they do not give its average performance we are not able to incorporate this information. Microsoft CTI-REALM Description: This is the only benchmark explicitly focused on cyber defense. Given cyber threat intelligence reports, it tasks models to generate detection rules to apply on endpoint/cloud telemetry logs. Scores are given as average ‘Reward’ in [0,1] based on how well their decision rules function.

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owork are part of the rollout. Anthropic also launched Claude for Small Business, with pre-built connectors for QuickBooks, PayPal, HubSpot, Canva, DocuSign, Google Workspace, and Microsoft 365. No IT team required. Why it matters: The Big Four are the consulting firms already inside every major corporation on the planet. When KPMG and PwC both go all-in on the same AI in the same week, that’s a distribution event, not a product announcement. Your consultants are probably already using Claude on

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s: if they've got access to private information, if they've got internet access, and if someone can give them an instruction that's untrusted, then they're not safe." MORE CONTEXT Microsoft's bad obsession is showing up in shabby services and slipshod software. Here's proof; Singapore boffins get diverse SIEMs singing in harmony with agentic rule translation; Shadow IT has given way to shadow AI. Enter AI-BOMs; Five Eyes spook shops warn rapid rollouts of agentic AI are too risky Fry concluded:

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