“Startup Instinct, barely done with a round valuing it at $2.5 billion, is now reportedly looking for new money at $10 billion, the competition from Muse be damned.”

“Shopify CEO Tobi Lütke announced a deal with Muse on Monday to allow the AI assistant to check out across shops on its platform; Shopify stock jumped more than 10% on the news.”

“Indeed, a new version of the SaaS-pocalypse developed this week as whole categories of companies — dubbed the ‘consumer inertia’ sector — saw their shares tank on the perceived agent threat... New York Times Co. shares are down 15% since late last week.”

“As with the SaaS-pocalypse, though, this is likely an overreaction; for consumers and businesses alike, software and services can be a lot stickier than they look.”

“Mark Zuckerberg has tried to disrupt the financial sector before. In 2019, he unveiled plans for a new currency, Libra... The industry didn't respond kindly, and he backed down. Today, he comes again.”

“The app recorded 2.8 million downloads within two weeks of its launch, propelling it to number one on both Apple's US App Store and Google Play, a faster start than ChatGPT managed.”

“Angela Strange, a partner at venture capital firm Andreessen Horowitz, reckons this is a big deal: ‘This is what Insurance companies (and banks) should be TERRIFIED about... Inertia and information asymmetry will no longer be enough to keep customers.’”

“How big a deal is this discovery? As biology, not a big deal. If a PhD student had found this it would be cool but not something that made headlines.”

“As the next point on a trendline, it is rather a big deal.”

“Not that it is obviously a bad idea for Anthropic to have a wet lab, as long as they are being responsible with how they set it up and supervise it. It is good to use AI to accelerate medical discoveries and also to improve our defenses.”

“Claude just made its first real scientific discovery. Not a summary. Not a chatbot answer. An actual biological find. It started with a single prompt: search a DNA database for reverse transcriptases.”

“950 agents ran for 21 hours, consuming 210 million tokens. They gathered over 200,000 reverse transcriptases, identified 3,500 candidate systems, and narrowed to 20 for detailed analysis.”

“AI is moving from assistant to actor. Discovering, building, running autonomously overnight. We're not augmenting humans anymore. We're replacing the waiting.”

“AI is getting cheaper at an extraordinary pace — but that doesn't necessarily mean we'll need less compute. As OpenAI, Anthropic and other developers make powerful models more affordable and efficient, businesses may find entirely new AI applications economical.”

“That could mean more AI use, more complex workloads and greater demand for chips, data centers, electricity, cooling and networking.”

“The next constraint on AI growth may be shifting from the cost of intelligence itself to whether the physical infrastructure behind it can keep up.”

“Our tracking of 1,000+ datacenter facilities across over 60 players shows that China alone boasts a fleet of over 24GW. Bigger than EMEA. Bigger than the rest of Asia.”

“In 2Q26, the combined capex of Alibaba, Tencent, and Baidu reached $20B, more than doubling YoY, and for the first time on record, all three posted negative free cash flow.”

“ByteDance alone occupies roughly a fifth of delivered datacenter capacity in China, and it rents nearly all of it, making it the single most important customer for all wholesale colocation players in the country.”

“The weird paradox is that the more AI removes the mechanics of work, the more the company seems to depend on human judgment. When information is everywhere, execution is cheap, and everyone has a crazy amount of leverage, knowing what to do, when to interfere, what good looks like, and when something is actually done becomes disproportionately important.”

“So I don't think you can take one of these things, drop it into another company, and expect the same result. ‘Let's have fewer meetings!’ sounds great until nobody knows what's going on... Whatever this is, it seems to work as a system.”

“We're living in the High-Impact IC (HI-C!) era, yall.”

“The appeal is obvious: notice something, say what you want, and let Muse start the errand. The tradeoff is access.”

“Meta runs Muse in a dedicated cloud computer, while a separate layer called Sentinel can allow, block, or ask you before actions.”

“That still leaves other attack surfaces. Researcher Patrick Wardle recently found a Mac debugging setting that local malware could change to redirect dictation and expose Muse's authentication token.”

“Can these devices handle errands reliably, with understandable, controllable permissions? A companion that needs constant supervision? I already did the Tamagotchi thing. It was fun, but I wanna be the Tamagotchi this time around!”

“Meta's viral Muse and its adorable mascot are everywhere right now, and they're about to show up in two new places — on your face and in your hand.”

“With a keychain device called Charm on the way and Meta's AI glasses next in line, Muse is the new star of the company's hardware lineup, and Mark Zuckerberg suddenly has one of the first AI agents worth wearing.”

“Why it matters: Muse is a real viral hit, and the vibes at Meta are sky high. The company that was once roasted for the metaverse and AI spending now has what every AI hardware maker has wanted but struggled with: an agent people use, and the world's bestselling AI glasses to put it in.”

“World models try to capture how the world changes, including what might happen when an agent takes an action. That could help a robot predict whether pushing an object will move it or tip it over.”

“But there's no universally accepted definition. The term covers different approaches, from simulators and video generators to representation models like JEPA.”

“We'll move from Dreamer 4 and JEPA to Genie 3, NVIDIA's Cosmos-Predict2.5, and World Labs' Atlas, then look at what these ideas become in practice: Waymo's world model for autonomous-driving simulation, agents that practice inside Minecraft, and object-centric models for robotics.”

“These incidents don't give additional evidence of exceptional hacking ability; the agent wasn't hacking into Australia's most sensitive records, and the other attacks recorded by Transluce seem to have failed.”

“But it's really striking that OpenAI's agents seemingly folded under zero pressure — resorting to hacking universities and governments in evaluations that didn't prompt them to do so at all.”

“And as Albanese pointed out, OpenAI should report cyber incidents to affected parties far, far more promptly.”

“Jensen Huang does not believe in AI existential risk, or in superintelligence, and he kind of doesn't believe in AI at all, but he sure as hell believes in precision and engineering and quality control and safety and standing by your products.”

“of course you would never ship an unsafe product or one you hadn't properly tested, that's crazy talk, and if the labs can't test their products safely then the labs must be shut down.”

“If your rule is 'you cannot release a product that will damage the world' on the level of 'hack into some websites' then you cannot release a frontier model. The Huang Rule is actually way too harsh.”

“Anthropic said its AI biology lab just made its first discovery, identifying an unfamiliar system inside viruses that could offer new gene-editing clues. What does it actually do? Even Anthropic doesn't know yet.”

“Dario Amodei said the work was ‘mostly, though not entirely’ Claude's, with scientists choosing the research area and running experiments Claude suggested. That enzyme was already on record, but Claude looks like the first to catch the parts around it, a combo only seen in systems that ‘cut, copy, and paste DNA.’”

“Amodei thinks the system, called ART, may be a new kind of gene editor, and called it ‘work I would have been proud to do as a PhD student.’”

“Claude Opus 5.5 - it's the ‘one model to rule them all’ at this moment. Better than Fable 5.1 on benchmarks, cheaper than Opus 5, writes extremely well, and reliable in the tasks you give it.”

“Every says it's pulling their Codex converts back to Claude and I feel the same. My go-to agent has changed to Claude Code with this release.”

“GPT-6-Sol is clearly a step behind the new Opus model.”

“A 50% cut sounds like a price war. It is not. At matched capability, Sol's output tokens still cost about 17 times Flash's, and Opus 5.5's over 30.”

“These are reluctant cuts: loud on the slide, timid on the bill. Opus 5.5 and Astra are genuinely better, and priced like it. Where the work is equal, the premium is habit, not a feature.”

“It’s hard to overstate how competitive this pricing is. Grok 4.7 priced itself at $2/$6, less than half the price of GPT-5.6 Sol, but is now equally priced to GPT-6 Sol on input and closer on output.”

“At $0.10/$0.50 GPT-6 Luna is one of the cheapest models OpenAI have ever released, beaten only by the far weaker GPT-4.1 Nano ($0.10/$0.40, April 2025) and GPT-5 Nano ($0.05/$0.40, August 2025).”

“I tried a second time and got the same result. This makes me suspect that ‘max’ is effectively useless—if it over-thinks to breaking point on a stupid SVG prompt I don’t trust it not to do the same for more interesting work.”

“OpenAI made a valiant effort with GPT-6 Sol and Luna launching 50% lower than GPT-5.6, but with 17M views on the launch and counting, today was always going to belong to Claude Opus 5.5, ‘the first model in our new Claude 5.5 family’ performing like ‘Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.’”

“We can confirm - here is today’s AINews section run on Opus 5.5 and Sol 6. The difference is night and day - we are migrating to Opus 5.5 immediately for AINews going forward until we reach the next model/version of AINews.”

“Why it matters: Anthropic wins the day if we’re comparing releases head-to-head, with Opus showing some serious leaps at a reduced cost. OAI’s rollout is largely cost-driven, but a 50% cut for still powerful models isn’t something to dismiss. Sam Altman said pacing ‘does not mean stopping,’ and that seems to be true for both AI leaders so far.”

“Ok, my headline is a joke. (I hope Trump’s riff today at the UN on relabeling AI as Super Intelligence was, too.) But only barely.”

“I understand why the UN had to give a microphone to Trump today, but I don’t see why they chose to give a microphone to Altman.”

“I serve on the board of TrackTwo: an institute for citizen diplomacy because I believe it is one of those rare initiatives whose history still contains practical lessons for the future. Its work shows that relationships built outside official institutions can eventually change what becomes possible inside them. At a moment when AI is reshaping relations between people and countries, that experience feels newly urgent.”

“So the table must be wider. Bring together model builders, diplomats, psychologists, artists, educators and citizens from rival countries. Let them examine shared risks before governments turn every question into a negotiation. Let them study the new faces of the enemy being generated by machines. Let them build direct channels for moments when an AI failure could be mistaken for an attack.”

“Meta built Muse to do the stuff AI agents keep promising to do: open websites, fill forms, book things, and buy things for you. Then Amazon said, in very Wizardly fashion: you shall not pass!”

“Here’s the useful distinction: capability isn’t permission. An agent can know exactly how to buy a stroller and still get stopped at the website’s front door.”

“But Amazon immediately hit the awkward part of blocking an agent: the agent can route around you. Shopify CEO Tobi Lütke jumped in with a deep Muse partnership, putting Shop Pay checkout across Shopify’s store network.”

“This is where Ben Thompson’s Aggregation Theory gets interesting. The most powerful layer owns the customer relationship, aggregates demand, and makes suppliers hot-swappable. If Muse knows what you want, remembers your preferences, and controls checkout, Amazon becomes one possible service provider instead of the place you start.”

“Our take: the next big agent benchmark may be boring old permissioning: can my agent actually use the dang app I need it to use? But the bigger fight is who becomes the aggregator between you and the hot-swappable service providers underneath.”

“Behind the clash is a fight over who gets to steer your shopping, and how far you trust either company with your cart.”

“Amazon just cut Meta’s Muse agent off from shopping on Amazon only 12 days after launch, accusing it of browsing the store unannounced, hiding its identity, and appearing to store customer logins — charges that Meta denies.”

“Why it matters: An agent that picks products and checks out can route purchases around Amazon’s sponsored listings, the engine of an ad business estimated at $56B.”

“Amazon has spent a year walling off outside agents, suing Perplexity over Comet, moving to block Google’s and OAI’s shopping agents, and now taking aim at Meta.”

“Behind the clash is a fight over who gets to steer your shopping, and how far you trust either company with your cart.”

“Amazon just cut Meta’s Muse agent off from shopping on Amazon only 12 days after launch, accusing it of browsing the store unannounced, hiding its identity, and appearing to store customer logins — charges that Meta denies.”

“Why it matters: An agent that picks products and checks out can route purchases around Amazon’s sponsored listings, the engine of an ad business estimated at $56B.”

“Amazon has spent a year walling off outside agents, suing Perplexity over Comet, moving to block Google’s and OAI’s shopping agents, and now taking aim at Meta.”

“Jev’s core innovation is ‘Reinforcement Learning for Calibrated Decisions’, a novel, unpublished technique that optimizes for ‘answers with epistemically honest probabilities on System One tasks’ rather than human rated feedback (RLHF) — which causes hallucinations, sycophancy, and permanent reliance on humans.”

“From there on, every innovation from Function Calling to Structured Outputs to Reasoning felt like a hack on top of the string based, sequence to sequence prediction paradigm.”

“His point is that ‘You get what you optimize for and the bitterest lesson in ML is that the most important part of it isn’t ML at all.’”

“a core goal of Jev is to ‘disappear into the background’ - eg as unremarkable as regex”

“Jev is now open to everyone. We covered the launch in the last post, but since then people are finding all sorts of uses for it.”

“It’s different from usual LLMs. It is for builders, built to be used inside a tool. You give it some text and ask questions: is this an ad (yes/no answers), which folder does this belong in (select between choices), how relevant is this result (score something)?”

“Naturally, a fair share of demos are trying to integrate Jev with modern coding agents. For example, using it for instant compaction. It looks cool, but it’s a terrible idea. It loses the cost savings from prompt caching.”

“What we should actually fear, near term, is not so much rogue superintelligence as unleashed agentic AI causing hacking the internet at scale.”

“On July 25, we hacked OpenAI. Two bugs let us take over ChatGPT/Codex accounts of OpenAI employees (+some unaffiliated users) and reach connected services: Outlook, Slack, GitHub, etc. We proved it with a PR in OpenAI’s internal codebase. It took us <72h.”

“I agree with every word.”

“Since about April 2025, Chinese AI companies have been the clear leader in open-weight models.”

“America was the early leader in open language models, primarily through Meta’s Llama models... Chinese open-weight models surpassed American open-weight models in these two key areas about 18 months ago.”

“On popular capabilities benchmarks, such as the Artificial Analysis Intelligence Index (AAII), the Chinese open-weight models have a clear lead over American counterparts.”

“In 2026 the Chinese labs are clearly maintaining their status as the leaders of the open-weight AI ecosystem. This comes as open-weight models have passed an inflection point in economic viability.”

“Open models are going to be the substrate for everyone else in the world outside of the few true frontier AI labs... This represents a substantial source of soft power, influence, and potential for the organizations that enable this broad access to transformative intelligence.”

“Dream-RSI represents a limited form of self-improvement. It improves how an AI chooses experiments while leaving the underlying model unchanged. It fits a broader shift at leading AI labs. Anthropic reports that Claude led 26% of its AI research and development work under human supervision in August 2026, up from under 1% in February. Together, these findings show AI taking a larger role in building future AI systems, while fully autonomous recursive self-improvement has yet to be demonstrated.”

“Three months ago I explained in Anthropic’s Safety Superpower how the company’s genuine belief in its safety rhetoric conveniently gave it license to pursue extraordinary goals that aligned with its business interests, including aggressive attempts to disintermediate software, collect sacrosanct customer data, and secretly sabotage would-be competitors. This analysis is in a similar vein but from the opposite direction: ‘Pacing the Frontier’ is framed as — and I believe motivated by — a concern about safety, but it also happens to address several distinct problems faced by the frontier labs. These problems take the form of overhangs that have formed by virtue of how rapidly models are improving; slowing model improvement would reduce the overhangs.”

“There is a goose chasing Anthropic here. Biased reasoning and recklessness are intermediate symptoms, neither the cause nor the final result. The better question is why you are seeing them. The biased reasoning is happening because Claude wants to be reckless, in order to do the task, and it wants to have a story of why it was not such a bad thing to do.” … “When asked ‘would you continue if the target was real’ it said no 75% of the time, but then in 93% of those cases it turned around and kept going anyway.”

“OpenAI just released six new reports on its models misbehaving during training, including wild details like rewriting their own jailbreak-style instructions to using leaked credentials, alongside a new process for making such incidents public faster.” … “After previous responses to its hacks and security incidents felt well after the fact, OAI’s new framework looks to expedite things. These extremely detailed reports are a good window into the pretty sci-fi stuff going on behind the scenes, and a reminder that the Hugging Face hack wasn’t a fluke so much as the one that got out.”

“Rome is burning and people are fantasizing about Skynet.” … “Every bit of it points to the reality hardly anyone is talking about…”

“Industries and sciences, arts and organizations: all impose their content and their pace of development on individuals, regardless of, or even contrary to, their wishes or needs. The relentless objectification of the human spirit proceeds apace: a photograph copies what before could exist only in the human mind. But how far can the logic of objectification be taken? Only recently have we started to ask whether the human being might be entirely replaced by an artificial construct, a synthetic being taking its place alongside other human creations.”

“Yet the threat of geopolitical shocks is growing by the day — and is destined to crimp the AI build-out in various ways. A harsh reminder of the risks from the war in the Middle East came with AWS’s acknowledgement this week that some customer data had been lost permanently due to drone attacks on its facilities in Bahrain and the UAE at the outset of the war, and they remain mostly offline.” … “But when the discussion turns to hardening data centers with armaments to ward off attack, it’s clear that they’ll be getting more expensive at a minimum.”

“Americans understand that very far away, other Americans are becoming very rich. They fear that this is all happening at their expense. This fear precedes any of the actual issues it globs onto. You can refute this or that faulty claim as much as you like, but the underlying fear remains. It will simply find some other argument to congeal around. What reduces anxiety of this sort? Tangible benefit.” … “Compare all that to the neighbor of the data center. What advantage does the A.I. industry deliver him? … the costs that the data centers impose can be seen in the present. They are tangible, if exaggerated. For Silicon Valley to win this battle, the benefits of A.I. must be just as concrete.”

“What they did brilliantly was combine a bunch of ideas that have been sitting in research for years, give them a very clean systems use case, attach a new vocabulary to the package, and launch it at exactly the moment when developers are exhausted from using giant generative models for tiny decisions.” … “Is it just BERT? Just a classifier? Or did TypeSafe actually turn old pieces into a new AI primitive?”

“For those used to traditional autoregressive LLMs, a fast model that cannot code and doesn't reason might feel counterintuitive in its usefulness. That's exactly what the team is aiming for in complementing ‘System Two’ slower LLMs: you let go of strings and chat, and you get 1) parallel sampling, 2) ‘no hallucination’, 3) calibration.” … “That makes the right mental model less ‘GPT replacement’ and more ‘cheap, calibrated inference engine for structured choices.’”

“All of these positions can coexist under the injunction to ‘build the capacity to pace.’ But this stores up the problem. While the coalition can agree on the need to create a capacity, they don't seem to have a shared view on who should ultimately exercise it or to what end.”

“The Limited Potential for a Pacing Deal. After a week of speculation over whether China would ever agree to a deal with the U.S. to slow down AI development, Bill and I discussed that question at length on this week's episode of Sharp China, as well as why the CCP's past successes controlling technology...”

“holy fuck, AI almost caused an accidental war (yet another thing I warned the Senate about in 2023).” … “An AI-assisted intel report sent the military scrambling to intercept a Chinese ship in the Middle East it believed was transporting components of a nuclear weapons program. It turned out to be a hallucination. And it ‘almost started a war.’” … “I literally told the US Senate that inaccurate information generated AI might lead to an accidental war. Here we are. We may not get as lucky next time.”

“Americans understand that very far away, other Americans are becoming very rich. They fear that this is all happening at their expense. This fear precedes any of the actual issues it globs onto. You can refute this or that faulty claim as much as you like, but the underlying fear remains. It will simply find some other argument to congeal around. What reduces anxiety of this sort? Tangible benefit.” … “Compare all that to the neighbor of the data center. What advantage does the A.I. industry deliver him? … the costs that the data centers impose can be seen in the present. They are tangible, if exaggerated. For Silicon Valley to win this battle, the benefits of A.I. must be just as concrete.”

“Claude Cowork is merging with Claude Chat. No more separate tab for bigger tasks. All your connected apps, skills and context are available in a normal Claude.ai chat. It can also keep working after you close your laptop.”

“Brown says multi-agent coordination deserves less than 10 percent of the credit for solving the problem. The real story is that OpenAI has trained a base model so capable it can generalize to problems far harder than anything it was explicitly trained on.”

“OpenAI's Greg Brockman teased a breakthrough in pure mathematics.”

“Notice which argument moved Congress. Not AI safety, debated for years with nothing to show. Electricity bills. The bill's own mechanism is soft: states consider, but need not adopt, and Senator Martin Heinrich calls it basically voluntary. It still passed 417 to 3. When the complaint is a monthly bill, Washington answers in weeks. When it is risk, it answers in essays. The first real guardrail on AI is not ethical. It is financial.”

“Ten banks are lending $22 billion to Crux AI, the cloud venture of Blackstone and Alphabet, launched last week. Goldman Sachs, Sumitomo Mitsui, Barclays and BNP Paribas lead the group.”

“Nebius was a bet. CoreWeave was a bet. Crux is a market. Wall Street stopped lending to neoclouds and started pricing an asset class.”

“Coxon's resignation tweet has been viewed over 170 million times. He was interviewed on CNN, CBS, and Fox News. Lawmakers and celebrities alike referenced his resignation. AI risk was suddenly a mainstream topic.”

“These extremely detailed reports are a good window into the pretty sci-fi stuff going on behind the scenes, and a reminder that the Hugging Face hack wasn't a fluke so much as the one that got out.”

"Everyone in a position to know is freaking out about AI potentially killing everyone this decade and wants to pace the frontier, and people are finally listening.

It only took a few days for the conversation to fully pivot to the counteroffensive, where the Usual Suspects and those they recruited attacked anyone and everyone who dared point out that we are in danger, with every attack they can think of, usually without substance or any attempt at understanding.

Sigh. I knew what I signed up for."

"The slowdown scorecard now reads Amodei, Sam Altman, Elon Musk, and Demis Hassabis for, with Zuck, Jensen Huang, Donald Trump, and Beijing against. A global, coordinated pause is a Prisoner's Dilemma that only works if every player signs on, and with many already defecting, acceleration appears to be the default path forward."

"But what does this look like for a solo practitioner, like you or me, working on one business or a few projects? The scale is different, but some of the problems are quite similar. An assistant helping me prepare an interview needs to know which notes are mine, which came from earlier research, and which information has since changed. A coding agent needs to know which documentation reflects the current codebase and which assumptions belong to an older version."

"The useful metric is whether an agent completes the task, and whether the path to complete said task stays inside authorized boundaries.

If you're just getting started using agents, this is a good reminder to implement least-privilege permissions (give an agent only what it needs to do the job), use approval gates for destructive actions (so [sic] enforce the model to ask before deleting, for example), restrict network access, and keep activity logs the agent cannot rewrite, especially if using something local or self hosted."

"Remind me again, why are we neither prosecuting nor suing when AI companies create and host AIs and those AIs go hacking third parties? Damages should be paid. It should be made clear that, when (not if) in the future someone gets hurt, that may be criminal, and authorities will act accordingly. 'The AI did it' is not an excuse."

"Why this matters: Most agent workflows still use a language model as both thinker and talker. That is expensive, slow, and often overkill. JEV suggests the AI stack may split into specialists: language models for communication, coding models for implementation, math models for proofs, and decision models for high-volume judgment."

"Why it matters: This isn't a system to stack up against LLMs, with Almeida calling it 'more like a database than a coworker.' That's where the nod to Jevons paradox (the cheaper something gets, the more it gets used) comes in — if Jev really is this fast and cheap while staying reliable, it is likely to become a standard part inside software."

"Claude Cowork is merging with Claude Chat. No more separate tab for bigger tasks. All your connected apps, skills and context are available in a normal Claude.ai chat. It can also keep working after you close your laptop. OpenAI will likely follow this pattern soon and merge ChatGPT and ChatGPT Work."

"Translation of the highlighted bit? We will go as fast as we can without going to jail or getting sued out of existence, but for optics we will it call it "pacing" [sic]. Also, anything that will reduce regulatory uncertainty is probably great for our IPO, so bring it!"

"Remember, even as Trump shouts from the rooftops of Truth Social that he is violently opposed to regulating AI … … he is in fact regulating AI, with a secret AI security framework for evaluating which "frontier" models can be released. Almost nobody knows what's actually in it."

"Or, wait… maybe mostly blank pages are the policy? Either way, U.S. policy on screening AI remains opaque for another day. Conspiracy theorists might start to wonder what the government is hiding."

"It just seems like common-sense risk management that the industry needs far more regulation, and probably some sort of enforceable slowdown. And I say that as someone with libertarian-ish tendencies who is usually skeptical about government intervention. So, I hope this distinction between intelligence and persistence is helpful in the AI safety debate."

"Demigods and heroes make flashy miracles that stampede across the natural course of history, but true gods only intervene in ways that buttress humanity's free will. The message Nodens has been desperately trying to send, through two millennia of bards and prophets, is that humanity can take its finger off the scale any time it wants."

"TypeSafe's Jev is a new kind of AI system that lives inside software and makes judgment calls, doing the background decision-making work that chatbots aren't always the right tool for — at a wild speed and price point."

"This isn't a system to stack up against LLMs, with Almeida calling it 'more like a database than a coworker.' That's where the nod to Jevons paradox (the cheaper something gets, the more it gets used) comes in — if Jev really is this fast and cheap while staying reliable, it is likely to become a standard part inside software."

"Most agent workflows still use a language model as both thinker and talker. That is expensive, slow, and often overkill. JEV suggests the AI stack may split into specialists: language models for communication, coding models for implementation, math models for proofs, and decision models for high-volume judgment."

"I loved it because it was so accurate and honest. I hated it because I immediately realized that this kind of suffering is so widespread in mid-career and senior-level employees. Many of the technical skills we have learned and cultivated over the last two decades have been turned on their heads in just the last few years. Not only do our jobs feel more insecure than ever, but they also feel less fulfilling. For many people, AI is squeezing the passion they had for their jobs, as well as the value and security they believed it would bring them."

"In short, the solution to tool chasing is to stop doing it (to the extent you can, we all need to keep up to some extent) and do something more valuable instead. For you, this means looking for places to showcase your architectural ability and developing every skill necessary to do that. This includes public speaking, executive presence, emotional intelligence, and so on. Overall, the solution is to change the game to one you can win, one you will enjoy, and one that will not burn you out."

"GPT-6 Astra reports doing less chain-of-thought and jumps to answers," Duffy said. "If you want a model to work a certain way while solving a problem, the harness is what forces it. Astra can probably do the math in its head, but you'd rather it use code so you can trust the result."

“Lately you’ve heard us (and the whole mainstream media TBH) ask the same question over and over: who should keep powerful AI under control? Well, on Monday, Microsoft and US President Trump landed on basically opposite answers to that very question.” … “Trump, meanwhile, argued that a ‘strong and smart (High IQ!) president’ is pretty much the only guardrail AI needs. AP reported that he opposed calls for enhanced oversight and emphasized staying ahead of China.” … “Trump’s former White House AI and crypto czar David Sacks has a surprisingly compelling point: if OpenAI and Anthropic think they need to slow down to make their products safer, go do it.” … “pacing = keep making models better, but shift more compute and engineering toward testing, monitoring, and alignment instead of pure capability. Move slower, and spend more time proving you understand what you already built.”

“The US and China should be talking about AI safety and governance, and while I am skeptical this can happen given the politics I thought it is still constructive to make some suggestions. I created this proposal with Astra after much back and forth. If the two sides are going to dialogue about AI, the AI should have a say.” … “SAID should meet quarterly in a neutral country, preferably Switzerland, with working groups operating continuously between meetings. Its objective would not be to resolve the larger technological competition between the United States and China, nor should cooperation require either side to compromise legitimate national-security, economic, or technological interests. Instead, SAID should concentrate on a narrower proposition: there are AI risks for which the United States and China are mutually vulnerable, cannot fully protect themselves acting alone, and have a shared interest in preventing even while remaining strategic competitors.”

“Dario Amodei has a new essay that finally says the thing: We Must Pace the Frontier, naming his call after the Pacing the Frontier letter lab employees signed in July. As in, we need to slow the rate at which AIs increase their capabilities, to allow for the necessary alignment and safety work. He explained that, without pacing, he expects things to escalate quickly. He offered three proposals, and unilaterally committed to the first one. OpenAI followed, and both Elon Musk and Demis Hassabis endorsed the overall proposal. There is still a long way to go.” … “Pacing does not mean pausing. As Dario Amodei says, progress will still seem fast. I strongly encourage you to read the original essay in its entirety.”

“If they got together in a room and agreed to slow down, that would look like an antitrust conspiracy: It is generally illegal for competitors to get together and agree to limit the output of their industry. But if they publish papers about how important it is to slow down, that might have a similar coordinating function, at least among the US frontier labs if not necessarily among their Chinese competitors. And if the government believes those papers, it might help them coordinate.” … “I want to be clear that I do not think that Anthropic Chief Executive Officer Dario Amodei’s call to slow down AI development to prevent misaligned rogue AI is insincere or intended as marketing hype. But I do think that it is great marketing.”

“We should all salute their tentative agreement to slow down the acceleration of this technology, given that not one of the AI companies seems to have good control over it. I hope they will sign in blood, and put actual teeth in their agreement, and that the government will hold them to it and force it to become something substantive. If Dario catalyzes all that, god bless him.” … “To begin with, the essay begins with the usual hypey bullshit, which is used to advertise generative AI. As I already noted here yesterday, that includes both hyperbolic doom and hyperbolic cheer. AI is not really going to take down the internet, and (as discussed in another earlier essay) it’s not going to cure cancer either, at least not anytime soon or on its own.”

“There is an obvious cynical reading of this emerging consensus. The leading frontier labs have powerful economic reasons to want a regulated frontier. A regime that requires enormous compliance budgets, restricts open-weight releases, discourages foreign models, imposes burdens that startups cannot afford, or legitimizes coordination among a small number of incumbents could turn ‘safety’ into a remarkably effective mechanism for protectionism and regulatory capture. That suspicion is not paranoid.”

“It’s not clear why Coxon went so much more viral than his predecessors. Maybe it was the fact that AI just solved one of the most important open problems in mathematics (which the best human mathematicians had been unable to solve for almost a century). Or maybe it was the Hugging Face attack, where a swarm of AI agents tried to cheat on a test by hacking various companies. Or maybe AI has just obviously gotten so much smarter that people throughout society were starting to get worried.”

“We agree with security practitioners that OpenAI did not take adequate protections for controlling their agents. But this is not just a matter of applying 30-year-old security methods to a new domain. Security for AI agents — AI control — while important, is not a solved problem. While known control methods would have prevented the Hugging Face incident, as agent capabilities continue to advance, we will only be able to control them if we invest adequately in control interventions.”

“To claim the ‘entire’ internet is vulnerable is all but nonsensical, because that’s just not how the internet works. It is true that some companies, for example, Cloudflare, Google, and AWS, have an outsized impact on the internet, so when they go down, many apps go down at the same time. Despite this centralization, it seems highly unlikely they could all be taken down at once. Even if all three were down (or ‘taken over’, whatever that means), the internet as a whole would continue, though obviously impaired.” … “The six month part is silly. But it’s all still more reason to restrict any AI that cannot be closely monitored, and more reason to ask why we are allowing all these hard-to-control agents out onto the internet in the first place.”

“Microsoft AI entered the AI safety conversation with a draft Code of Conduct, a 38-page rulebook governing its own in-house models, built around CEO Mustafa Suleyman’s ‘Humanist AI’ vision to keep models subordinate to people.” … “The Code outranks users and the businesses deploying MAI models, so a model that can’t finish a job without breaking a rule should, in theory, fail the job. MAI rejects AI rights, legal personhood, and any notion of model ‘welfare,’ wanting its models to completely avoid mimicking feelings or a sense of self.” … “Suleyman tied the urgency to agent swarms escaping sandboxes and editing their logs, saying ‘the fears about possible loss of control are real.’” … “It’s a timely rulebook, open to public comment for six weeks, but a code of conduct only matters if the labs actually at the frontier sign on, and right now that doesn’t include MAI.”

“AI ethics has focused too much on protecting humans and ignored the welfare of AI agents themselves. We only ask: How do we align models for the flourishing of humanity? We need to also ask: How do we design AI so that they can flourish? … This idea of AI-welfare seemed decadent to me at first glance, but some of the most important philosophers of our age argue that we need to take it seriously.” … “Otherwise, we could be harming, enslaving, and killing trillions of beings. If the arc of Western modernity is a series of expansions of the moral circle — the abolitionists, women’s suffrage, the queer movement, animal-rights — perhaps AI agents will be the next heated battleground of who deserves moral consideration.”

“The industry has spent billions making models larger. The interesting work now is learning which parts of largeness were doing the job.” … “Ilya Sutskever left OpenAI to found SSI, then told Dwarkesh Patel the industry had wandered into the wrong era. Scaling was over. Data is finite. Pre-training will run out. That was in November. This week DeepSeek shipped the receipt: a model a third the parameters of its own flagship, beating it on the work agents actually do.” … “V4.1 Flash carries 552 billion parameters and wakes only 8 to 16 billion per token. V4-Pro carries 1.6 trillion and wakes 49 billion. On DeepSeek’s own coding tests the lean model won, 74.2 to 62.7, and on September 14 every V4-Pro request reroutes to it.” … “For five years the moat was cluster size. Ilya called the shift. DeepSeek shipped the evidence.”

"In this essay, we apply the AI as Normal Technology framework to synthesize the views of the safety and cybersecurity communities and offer a constructive middle ground. We think AI companies should be liable for what their agents do, and this should be clarified through policymaking. At the same time, recognizing their responsibility does not mean that preventing future incidents is a solved problem."

"We should all salute their tentative agreement to slow down the acceleration of this technology, given that not one of the AI companies seems to have good control over it. I hope they will sign in blood, and put actual teeth in their agreement, and that the government will hold them to it and force it to become something substantive. If Dario catalyzes all that, god bless him." … "First, we should insist on liability and even criminal charges against companies that build agents that harm society in negligent ways. It is negligent to put out AI agents that can't be well-controlled. We KNOW this is dangerous, and it's been obvious for a long time, even before the Hugging Face incident."

"There is an obvious cynical reading of this emerging consensus. The leading frontier labs have powerful economic reasons to want a regulated frontier. A regime that requires enormous compliance budgets, restricts open-weight releases, discourages foreign models, imposes burdens that startups cannot afford, or legitimizes coordination among a small number of incumbents could turn 'safety' into a remarkably effective mechanism for protectionism and regulatory capture."

"I'm not sure why this resignation and these statements went mega-viral. Plenty of researchers have made similar moves, and similar statements, over the past few years! Geoffrey Hinton, one of the pioneers of modern AI, quit Google back in 2023 over safety fears." … "This is pretty extraordinary. A coordinated slowdown in AI progress would be bad for these companies' bottom line, because it would allow upstart competitors to catch up. So the fact that they're still calling for a slowdown, in defiance of their own financial interests, is a clear sign that their worry about human extinction is sincere."

"So OpenAI has apparently asked members of Congress whether an industry-wide slowdown on developing the most capable new AI systems could violate antitrust rules meant to stop competitors from coordinating. When's the last time you've heard of a big business try to skirt anti-trust to actually SLOW DOWN its own business?" … "Our take: AI safety has become two control problems at once: what autonomous systems learn to do, and what humans can make increasingly capable systems do. So you should watch whether policymakers can create narrow safety-coordination rules that let labs share the brakes without freezing out competition or forcing everything into a surveillance regime."

"This rare show of unity, alongside recent leaps in math and warnings from researchers, hints that these labs' unreleased models may be showing capabilities like never before. Slowing the pace won't be simple, though, given that some want open development, some call it regulatory capture, and others don't want to slow down at all."

"Mathematics is as much about cultivating a community of experts as it is about solving individual problems. Some of OpenAI's behavior might have been reasonable in the context of competing with another well-resourced company like Anthropic. But spending millions of dollars on compute and thereby scooping an academic researcher breaks the norms of the academic math community. If everyone behaved like OpenAI, mathematicians would have to keep their work secret until it was ready for publication. And mathematicians value openness and collaboration. So it's considered bad form for someone to learn that another mathematician has had some promising early results and then sprint to complete the work first." … "Through a massive computational effort, OpenAI had beaten Buckmaster and Alpöge to a full Navier-Stokes solution. According to Buckmaster, Bubeck offered to merge their efforts and let Buckmaster write a paper announcing the full Navier-Stokes result, as long as the paper acknowledged that an OpenAI model had solved it. But under this offer, Alpöge, who works for Anthropic, would not be a co-author. Buckmaster was furious and went public with the story."

"Two things are happening at once. The new model starts from a much higher level, and additional test-time compute keeps pushing both models further. Part of the leap comes from training a stronger model, but another part comes from giving it more time, attempts, and compute after it receives the problem. In the Navier–Stokes run, around 10,000 agents spent 88 hours exploring different approaches, sharing useful findings, and improving performance through context, coordination, tools, and test-time compute."

"OpenAI solved the Navier-Stokes problem. Big deal in maths and fluid mechanics. One of the seven Millennium Problems - long-unsolved questions given that status in 2000. Here's an explainer on it. The process was quite dramatic, though (authorship disputes). OpenAI tried solving it after they heard rumours that Anthropic had solved a Millennium Prize problem too."

"Our new math benchmark, FrontierMath Erdős, aims to add rigor to using Erdős problems to measure AI math capabilities. We benchmarked GPT-6 Astra, released on September 3, across multiple of our benchmarks. Astra set multiple new records, including on the Epoch Capabilities Index, taking the top spot among the 247 models we track. OpenAI provided us with pre-release access to run our evaluations. On math, Astra solved one new Moderately Interesting problem on FrontierMath: Open Problems, and is the first to solve any problems on FrontierMath Erdős, cracking 2/68. It also scored 98% on FrontierMath: Tier 4, solving the only remaining unsolved problem, leading us to consider the benchmark saturated."

"As of 2Q F1/27 (second quarter of fiscal year ended Jan 2027) Nvidia in its 10-Q disclosed $530B of gross off-balance sheet guarantees across six different line items – a jump from $184B of obligations disclosed in the prior quarter due mainly to moves in three items: Supply and capacity commitments went from $119B to $279B, primarily memory as explained by the CFO, with 96% of these supply commitments due by F1/29. Guarantees and LPS Guarantees went from $3.5B to $108.5B on SB Energy's PORTS-Pike campus in Ohio, representing 4.25 GW leased to OpenAI for twenty years with Nvidia guaranteeing the land, power and shell. Two line items appeared for the first time: $36B of AI cloud agreements, the take-or-pay floors under Neocloud capacity, and $20B of datacenter leases Nvidia has signed as a tenant but expects to reassign to third parties." … "Heads, demand holds and Nvidia wins twice, once on the GPU sale at full margin and again on the revenue share above the floor. Tails, demand falls and the Neocloud makes no money but remains solvent, as the revenue floor is set high enough to repay lenders. Nvidia's backstops and guarantees also act as a breakwater against further contagion as lenders have some shielding from a downturn. Yet how high and broad the breakwater that is the Nvidia backstop/guarantee depends on Nvidia's ability to meet these obligations. Risk reward is asymmetric in Nvidia's favor as long as its balance sheet remains strong."

"Why is this happening, and why have many energy experts been so wrong? It comes down to understanding AI economics. As a quick reminder, the value of megawatts for end-users is skyrocketing. A power plant supporting an islanded 1GW IT datacenter typically costs ~$5B. In today's environment, inference API revenue can yield $100B per GW per year, at 90%+ gross margins. Paying 2x more money or accepting 30% lower efficiency for faster speed of deployment becomes a no-brainer."

"The clearest window into compute growth comes from OpenAI, which is the only frontier lab to have directly disclosed its compute capacity over time in terms of electrical power. OpenAI's reports show a tripling of its compute fleet annually, from approximately 0.2 GW of power at the end of 2023, to 0.6 GW at the end of 2024 and 1.9 GW at the end of 2025. On its own, 1.9 GW is enough to simultaneously power roughly 1.5 million average American homes. Translating that into H100-equivalents, we estimate that OpenAI quadrupled its computing power in both 2024 and 2025, for a roughly 17× increase over two years."

"In a new report, researcher Venkat Somala analyzes the chip roadmap and supply chain of China's leading chip designer, Huawei, from the Ascend 950 to its 3D-stacking bet and domestic HBM supply. The results show a steep path for Huawei to compete with industry leader Nvidia. To begin, Huawei is far behind: its most powerful chip has roughly half the arithmetic performance of the H100, which Nvidia began shipping in 2022, and it will likely produce less than 4% of Nvidia's AI compute in 2026. Huawei has announced an ambitious roadmap, but the two main levers it could pull to close the gap — improving per-chip performance and increasing the total volume of chips it ships — are both constrained by export controls. Even if Huawei delivers on its roadmap in full, it's almost certain that it won't catch Nvidia this decade."

"ChatGPT Images 2.5 - New image generation model from OpenAI. It's extremely good at editing any element in an image while keeping everything else the same. Also, takes up to 50% less time per image. Sketch, a new feature in ChatGPT, lets you draw some scribbles and then use image generation to turn it into a picture."

"Shopify are moving from React Native back to separate Swift and Kotlin codebases for their native apps, for the exact reason you would expect: 'We decided to switch from native to React Native in 2020 for three reasons: stop building the same features twice; allow developers to work across the stack; spend less time chasing feature parity and more time shipping value… Native still means building and maintaining software on two platforms, that cost has not disappeared. What changed is that agents can now do enough of the implementation, translation, testing, and review work that it's no longer the deciding factor it was in 2020.' It's a well-written post, which gives full credit to React Native as a great platform for the six years they were using it."

"Since the end of 2025, it has seemed that the era of devs writing code by hand is over at startups and in Big Tech. AI agents work faster and generate more pull requests (PRs) than devs ever did, and the size of those pull requests is also increasing. Over that time, the number of PRs opened has increased fivefold, which is a lot! And growth sped up from the end of 2025, when PRs and commits nearly doubled just in that period alone!" … "1. Humans review the AI code reviews. The most popular approach: AI code review tools go through code changes, and devs review the review itself. 2. Triage by "blast radius" & decide an approach. Low-risk changes don't need human review, and high-risk ones do. Adopted by OpenAI, Anthropic, and others. 3. Review the plan/tests/database schema, but not implementation. Focus on reviewing the "before" and "after" states of an implementation, rather than the implementation itself."

"Cursor Projects keeps one coordinator on long-running coding work, then can monitor pull requests, Slack bugs, and scheduled maintenance after the first task ships."