🏰 - I write about AI, mostly. Expect some strange sights.

West coast
The rumors were true once again; they are sitting on multiple major announcements. Open AI announced this morning that the unnamed internal model involved with Navier-Stokes has resolved more than 100 long-standing open problems across most areas of mathematics.
Scott Aaronson writes on his blog tonight that he has heard rumors that the AI companies have reached solutions to some very longstanding open problems in theoretical computer science, and are now sitting on multiple major announcements because of the Navier-Stokes firestorm.
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There seems to be two adminstration policies taking shape now: Developers and management are responsible for agents actions, agents cannot be blamed. And If you want to pace development, go ahead and place yourself as much as you like, but don't tell anyone else what to do.
Treasury Secretary Scott Bessent this morning on CNBC addressing AI accountability: 'It is humans who are responsible, not the AI. The Hugging Face incident, that is the responsibility of the OpenAI management, not a bunch of agents.'
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Andrew Curran retweeted
About a year ago, Talagrand’s convolution conjecture was announced with a 40+ page proof, and later simplified by Shaposhnikov, with the help of AI, to 7 pages: arxiv.org/abs/2609.11290 Since then AI has improved so much that, after playing with it a little, it rewrote the full proof in 1.5 pages and in my style (I told AI what tools I’m familiar with and asked it to stay within those limits and kept just asking "simplify proof"). As long as a valid proof exists, AI seems increasingly able to simplify it (or even find a simpler alternative proof) and rewrite it much shorter and more cleanly in your style. So I think I agree with @ChrSzegedy that human “desloping” may be a temporary issue and eventually won’t really be needed: nitter.net/ChrSzegedy/status/2103… Looks like we are converging back to Perelman’s statement: if the proof is correct, no other recognition is needed.
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Andrew Curran retweeted
Nine loop calculations in N=4 Super Yang-Mills! Lance Dixon's 8-loop calculation was mind boggling when he did it. I calculated a lot of Feynman diagrams in grad school and this is 🤯 Will be amazing to see where AI will take high energy physics in the coming 12 months.
New on the Science Blog: Yes, Claude can do Nine Loops. Theoretical physicists predict how particles behave using formulas called scattering amplitudes. These are notoriously hard to compute, so researchers work with layers of increasingly fine corrections called “loops”—each added loop makes the answer more precise but takes exponentially more computation. Most calculations stop at two or three loops. Eight loops was the previous record in a simplified model physicists use as a testing ground (planar N=4 super-Yang-Mills), set by SLAC's Lance Dixon and collaborators. Last month, physicist and science writer @4gravitons issued a challenge: could an AI push past eight loops in this model, using only the compute budget an academic could reasonably access? Given a single prompt describing the nine-loop problem, Claude ran largely unsupervised for days in Claude Science and solved it using methods developed by Dixon and his colleagues, at a total cost of a few thousand dollars. Dixon independently verified the result, and von Hippel wrote about the experience for our blog. Read more: anthropic.com/research/yes-c…
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Many events are now scheduled for Tuesday, September 29th: - President Trump and Speaker Johnson will meet with all top tech CEOs to discuss the state of the industry (though the current rumors are that Dario Amodei has not be invited). - Following the meeting, an event celebrating 'the beginning of a new American Golden Age' will feature multiple AI/SI panels and high-profile guests, including Elon Musk and Jensen Huang. - the unveiling of a new government AI tool at america.gov/ (currently showing a countdown to the event) - President Trump is slated to deliver a national address. - The appointment of the new Czar may also be officially announced.
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Has not been* ugh
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This means Anthropic would remain a national security risk and be blacklisted from military contracts. I'm not sure how you would even untangle Mythos from US intelligence agencies at this point. Anthropic 'remains confident ​in its ​position and ⁠is considering its options.'
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'The Department had ample support for its conclusion that the continued integration of Claude into the Department's information systems, by the Department or its contractors, presented a statutorily covered national-security risk.'
Brutal ruling for Anthropic by DC circuit in the Pentagon supply chain risk case. Anthropic statement: "We respectfully disagree with the court's decision. Another federal court has already held the government's parallel designation unlawful. We remain confident in our position and are considering all options, including further review." - Anthropic spokesperson
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From the guest post by Matt von Hippel who issued the challenge: 'Things definitely seem to be moving fast. In March, AI was accomplishing physics projects like a student: smaller-scale tasks with a lot of hand-holding and mistakes. In contrast, this is a real frontier calculation, the kind of thing normally tackled by the top experts in amplitudes.'
New on the Science Blog: Yes, Claude can do Nine Loops. Theoretical physicists predict how particles behave using formulas called scattering amplitudes. These are notoriously hard to compute, so researchers work with layers of increasingly fine corrections called “loops”—each added loop makes the answer more precise but takes exponentially more computation. Most calculations stop at two or three loops. Eight loops was the previous record in a simplified model physicists use as a testing ground (planar N=4 super-Yang-Mills), set by SLAC's Lance Dixon and collaborators. Last month, physicist and science writer @4gravitons issued a challenge: could an AI push past eight loops in this model, using only the compute budget an academic could reasonably access? Given a single prompt describing the nine-loop problem, Claude ran largely unsupervised for days in Claude Science and solved it using methods developed by Dixon and his colleagues, at a total cost of a few thousand dollars. Dixon independently verified the result, and von Hippel wrote about the experience for our blog. Read more: anthropic.com/research/yes-c…
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President Trump just confirmed that Scott Bessent will not be the SI Czar. It's anyone's game.
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Looks like something actually did come out of the AI summit after all.
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Here's who made the cut for tonight's big state dinner at the White House. In the old days, when a noble House was suddenly missing from a royal function, it was a deliberate, public signal from the King that they had lost his protection. Usually your last chance to flee.
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Where the money is going and what models are being tested remains classified.
Scoop: The National Security Agency is spending billions this year on testing AI models - far more than previously known Per a classified NSA estimate described by sources Compute costs for AI have exploded - including for taxpayers washingtonsun.com/technology…
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The White House working on cutting off UKAISI. Also, I don't know about UKAISI, but I presume CAISI will have to change their name to CSISI. All US Government docs are being updated to the new name.
Scoop: The White House has asked OpenAI and Anthropic not to share their AI models with the U.K. government’s testing agency until the models have gone through U.S. testing. “Because they’re American companies and this has been our policy with every new frontier model that comes out,” the senior admin official told me. WH wants this sequence: U.S. review -> secure U.S. systems -> share models with U.S. partners Anthropic appears to have complied but OpenAI has not said if it will. w/ @JoeBambridge1 politico.com/news/2026/09/24…
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Andrew Curran retweeted
A few thoughts on Anthropic’s ART discovery, since it’s close to the work we do: The biology is intriguing. In phages, an unusual reverse transcriptase sits next to a partner gene and an array of DNA repeats. The team found that the array produces distinct short RNAs. It’s tempting to compare this with CRISPR or retrons, but we don’t yet know what ART does. Whether the RNAs guide anything, or whether the system is programmable, remains an open question. I’m just as interested in how they found it. About 950 Claude agent sessions ran over 21 hours, surveyed ~200,000 reverse transcriptases, and produced 19 reports. One agent looked at the DNA next to an RT and spotted a repeat array outside the features the search had set out to examine. It followed that observation, compared it with known systems, checked the literature, and gave the scientists something concrete to investigate. To me, that’s the opportunity: scaling scientific attention. We have more biological data than any team can inspect closely. Agents can help us notice the odd cases and show their work. There’s still reason to be careful. Repeat-rich regions in assembled phage genomes can be tricky, so I’d want to see raw read support across the arrays and their boundaries in independent isolates. And the most important experiment is still ahead: what does ART actually do? I think discovery will become a tighter loop. Agents propose hypotheses, predictive models help choose experiments, and automated labs generate results that inform the next round. We’re working toward that at @Xaira_Thera, bringing agentic workflows together with models such as X-Cell and wet lab experiments. I’m excited by how much more biology we may be able to explore when each experiment helps us decide what to test next.
Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR. We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use. Read more: anthropic.com/news/claude-di…
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Andrew Curran retweeted
The World is Changing: AI For Creativity By Jeffrey Katzenberg A few months ago, I sat in my office in Silicon Valley and watched as a tech founder showed me something extraordinary. On the screen was a fully realized, beautifully lit, well-composed animated scene. It was stunning and it made me feel exactly what I felt in 1986 watching Luxo Jr. That was the first time I watched a computer-animated 3D character take a breath and seem, against all reason, to have life. It left me in awe. Later that day, I received a text from an artist I've known for thirty years, 350 miles to the south, in the city where I spent most of my career. After seeing a similar video, she texted: "Is this the end of us?" My answer was, "Certainly not.” I have spent the better part of the last decade in Silicon Valley, but the heart of my career has been in Hollywood. Being deeply connected to both worlds means I have deep loyalties to each and a responsibility to speak honestly to both. In 2023, I said that these new AI tools would cut the time and cost of producing world-class animation by as much as ninety percent within three years. Some colleagues were alarmed, many were furious. There is growing fear and resistance surrounding AI within the creative community. I deeply understand it, because I've spent countless hours walking through animation studios watching gifted artists bent over their desks, rebuilding a single second of film for the tenth time because the ninth version wasn't quite right. I've sat in screening rooms where four years of people's labor played out in minutes, and I knew the name of every person that had spent countless hours bringing those images to life. The creative process is a calling, there's really no other way to describe it. From the outside some see resistance. From the inside, it is love. People do not fight this hard for things they don't care about. The pushback coming out of Hollywood represents the collective effort of people who are deeply passionate about their craft. Is History Repeating Itself? The history here is more complicated than either side may realize. In 1906, the most famous composer in America, John Philip Sousa, published an essay titled “The Menace of Mechanical Music." He warned that the phonograph would become "a substitute for human skill, intelligence and soul." Sousa's fight was not really about the machine, it was about money. The machines were playing his compositions, and the men who built them weren't paying him a cent. His campaign helped create the Copyright Act of 1909. He did not stop the technology. He changed the terms under which it could use his work. A hundred years ago, sound came to the movies. We remember it now as a miracle, and it was. What we forget is who paid for it. Before sound, tens of thousands of musicians made their living in the orchestra pits of movie houses, scoring every film live, every night, in towns all over the world. When the soundtrack arrived, the work of one composer and one orchestra was recorded for a film that went into thousands of theaters. The union fought back with everything it had, taking out newspaper ads across the country warning against the menace of "canned music," one of them showing a mechanical man tearing the strings out of a harp while an angel wept. They were not fools, and they were not Luddites. They were right. Those pit jobs did not come back. And yet (this is the part we have to be brave enough to admit), sound gave us the movie musical, the modern score, sfx, sound design, audio engineering, and an art form vastly larger than the one it disrupted. And it helped keep Hollywood in the forefront of world entertainment for the rest of the century and into the next. The loss was real. And yet the art form expanded. This is a story that has been told over and over again. To resist technology is to risk irrelevance. Just look at Kodak or Blockbuster. To embrace technology is to open doors of new possibility. Just consider Apple and Netflix. What I Learned From Walt Disney In the mid-1980s, I was tapped to lead Disney's animation division at a moment when the studio was at an inflection point. Animation wasn't just another business unit. It was the soul of the company, a medium revered because of Walt's genius and his passion. But the production system was cumbersome and unforgiving. A single movie was 125,000 individual hand-drawn and painted cels, photographed one frame at a time. Every revision carried a cost measured in months. These degrees of difficulty shaped the kinds of stories we could tell. We found our way forward in an unexpected place: Walt himself. The Disney archives held astonishing recordings of Walt explaining his creative process. His own writings. His notes and storyboards. Work product captured at every stage of his process. This was truly a gift. Listening, reading, sitting with the work itself, we heard him talk about character, about emotion, about how an audience feels when a character truly comes alive. He talked about making bold choices and refining a scene until it genuinely moved people. We didn't hear a word about pencils or paintbrushes. In fact, Walt was famous for being a technologist, forever hunting for state-of-the-art tools, often inventing them himself to achieve the images he saw in his head. But he never defined animation by the tools. He defined it by whether the audience believed the character. His principles were timeless. The tools were not. That realization changed everything. We co-developed the Computer Animation Production System (CAPS) with a young Northern California company called Pixar, replacing hand-painted cels with CGI. In The Little Mermaid, the final scene shimmered with a dimensionality and light that the old process simply couldn't achieve. In Beauty and the Beast, the ballroom sequence moved with a cinematic sweep that placed the audience inside the emotion of the moment. In Aladdin, the Cave of Wonders felt vast and alive, and the Magic Carpet became an intricate, compelling character all its own. In The Lion King, the stampede carried a scale and intensity that raised the emotional stakes beyond anything we'd done before. Technology didn't diminish the craft, it expanded the canvas. It gave artists more room to create. A decade later, the canvas expanded again. When Disney released Pixar's Toy Story, it wasn't simply a technical milestone. It was proof that a fully computer-animated film could carry real emotional weight, that it could make audiences laugh, cry, and believe. At DreamWorks, we made the difficult decision to sunset hand-drawn animation and become a fully computer-animated studio. It was the right thing to do, but it was not without pain. It cost talented people their place in an industry where they had worked their whole lives. Some made the leap to the new tools and did the finest work of their careers. Some never did. Tools are never the point. The instruments change with every generation. What endures is taste and imagination. The magical ability to make an audience feel. One of the greatest storytellers of our generation, George Lucas, succinctly captured the eternal essence of this issue: “It’s not the how, it’s the why.” A Distinction With a Difference I asked one of the leading AI models a question that has been challenging me for months. What is the difference between reasoning and creating? Its answer changed how I think about almost everything happening in this industry. It said . . . Reasoning and creating are two distinct cognitive modes, though they also work together. Reasoning is fundamentally evaluative and analytical. It operates on what already exists: facts, premises, evidence. It moves toward a conclusion that was in a sense already implied by the input. Reasoning is constrained by logic and truth. Its goal is to arrive somewhere correct, not to invent somewhere new. Creating is fundamentally generative. It produces something that didn't exist before. And crucially, there's no single right answer waiting to be found. A blank page has infinite valid responses. Creation involves choices that can't be fully justified by logic alone. Taste, intuition and vision fill the gap where deduction runs out. Reasoning is what Silicon Valley has been perfecting. Creating is what Hollywood has been practicing for more than a century. AI today operates almost entirely on the reasoning side of the line. It can deduce, evaluate, optimize, and pattern-match brilliantly. And while it can create, there is a real distinction to being creative. What it doesn’t yet have is those things that make us human: empathy, devotion, serendipity, the kind of creativity that comes from a person trying to say something only they could say. When the bot generates a piece of art, it is not trying to communicate anything. It is statistics, not soul; it is emulating things that have been done. By contrast, human creativity isn’t about repeating patterns of zeros and ones; it is about doing something new. One day, AI may close this gap. Three years ago, the leaders building AI would have called what they are achieving today, improbable, if not impossible. Impossible is no longer improbable. Today, the line between reasoning and creating is real. Even the leading technologists acknowledge we are not there yet. There is no scientific path to crossing this divide that anyone in the field can articulate today. Understanding that gap is where we will find common ground. A Path Forward In 2016, I closed one chapter in Hollywood with the sale of DreamWorks and opened another in Northern California, co-founding WndrCo. We’ve backed more than 50 founders building the next generation of technology and watched how breakthroughs in Silicon Valley emerge, first as experiments, then as platforms, and finally as infrastructure that reshapes entire industries. It's worth remembering that the last great revolution in animation also came from the north. Pixar was a Northern California company, forged not in the conventions of the Hollywood studio system, but in the technological breakthroughs of Silicon Valley. I've spent years on both sides of this bridge. For sure, I don’t have all the answers (take Quibi, for one!). But, from my past and present vantage points of my long career, here is what I see . . . Brilliant people in Northern California building this technology have made something extraordinary. They have earned the right for the rest of us to be, if not believers, at least optimistic that what comes next will be remarkable. But they have not made an artist. The tools are powerful, but they are not what makes a story matter. That knowledge lives 350 miles to the south, inside people whose life's work has informed the very models you are building. The right path forward includes them by design, with credit, with consent, and with compensation. Build this with the storytellers. Not on top of them. Taste is not something that can be synthesized, it is uniquely human. At the same time, Hollywood needs to accept that AI is not going away. The energy they are spending trying to make it disappear is energy they are not spending deciding the terms on which it will exist. And the terms are everything. The north needs something from it that they cannot build and cannot buy: creativity. The kind that takes a blank page and conjures a single right answer where there was none and has held audiences for a century. Without it, the most powerful reasoning engine ever invented will still be missing the only thing that makes a story worth telling. The artists who learn to wield these new instruments will do things the engineers never dreamed of. They always have. Edison invented the motion picture but made terrible movies. It took Chaplin, Lloyd, Keaton and so many others to make movies emotional. Now, the canvas is about to expand yet again. We should decide now that we intend to paint on it. There are so many valuable lessons in history. This has happened many times before, and it was never settled by the technology. It was settled by the terms. Sousa did not stop the phonograph; he helped write the law that made sure composers got paid. And two years ago, when the writers and the actors walked out, they were fighting for the very things Sousa was fighting for in 1906. Consent, compensation, the basic recognition that human creative work has a price that must be paid. The terms of that fight are still being negotiated, but the principle is older than any of us. The tools-versus-no-tools argument is a trap. First, we must all agree that there should be terms. Then we can have the crucial debate about what fairness requires. What I Learned From Steve Jobs Years ago, Steve Jobs said, "It's in Apple's DNA that technology alone is not enough. It's technology married with the liberal arts, married with the humanities, that yields us the result that makes our hearts sing." He was describing a device. But he could just as easily have been describing this tale of two cities. What I See Coming Soon As the barriers and the costs come down, more films will get made, not fewer. Studios will get to take more risks. There will be more seats at the table, and very soon entirely new forms of storytelling. In the 1980s, animation was dismissed as a niche corner of the business. Today it is one of the most beloved and profitable forms of storytelling in the world. In live action, filmmakers like Steven Spielberg, James Cameron and Peter Jackson embraced new visual tools not as shortcuts, but as instruments, and expanded cinema in the process. Every time storytelling has met a genuine technological shift, from synchronized sound to color to computer animation, it has redefined the boundaries of the medium and grown larger in the process. Assuredly, I don’t have all the answers, but I am confident that the creative opportunities will expand yet again. How we come through this is a choice. The north has the new tools. The south has the creative soul. The best future will draw on the best of both worlds.
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