I am at https://xitter.cf/t.co/0U1Ki0IP41 Senior Fellow at @ffdweb⢕ Special Advisor for @EFF THEY STOLE OUR REVOLUTION NOW WE'RE STEALING IT BACK

Meta Francisco
Joined December 2006
Danny O'Brien🤖 retweeted
1/ We discovered something totally unexpected about the neural structure of consciousness that overturns decades of thinking on its biological basis and brings us significantly closer to the recipe for generating conscious awareness. New preprint: biorxiv.org/content/10.64898… (led by @HesseJanis, with @FrankLanfranchi, @_conor_mcgrory, @Yuelin_Shi, and @EngelTatiana)
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Danny O'Brien🤖 retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Danny O'Brien🤖 retweeted
When Unit Distance conjecture dropped I was dismissive: this is just one combinatorial problem that benefitted from a heavily computational approach. When Navier-Stokes dropped I was deeply rattled and uncertain: this is a huge problem, but not a problem ordinary mathematicians work on and it cost millions of compute, so not the budget ordinary mathematicians have. Clearly a huge development but felt hard to disentangle what it really portends. When the nearly 400 problems recently dropped, including ones I had used for years in grant proposals as North Stars guiding my research, I felt… relieved and optimist! I didn’t expect to, but I realized that this takes the uncertainty and anxiety away—it was a deep cut of problems across math, each solved on average with only 3hrs of complete, from a model that will soon be in user hands. The writing on the wall is unmissable now: math is entering a new era. Not just millennium problem math, but ALL math research. I find this exciting and feel more optimistic than I have been until now— because we can stop fretting over how capable AI is and how serious the threat to the profession is and move on to acceptance and finding ways to make the most of this powerful new tool—which I think will be thrilling! Just as one tiny example of an exciting prospect that comes to mind. OpenAI solved about 400 of 4000 problems—why did these fall while the others didn’t? Imagine defining a new difficulty measure, somewhat akin to Kolmogorov complexity, that’s roughly how hard a math problem is to solve with an AI (I know this is extremely ill-defined and not practical, but just humor me for a moment). As we solve some problems and fail at others a landscape of values of this parameter emerges. Among human-hard problems, what kind of range is there for this AI difficulty measure? Why? Which problems and fields have the highest value in this measure? Can we prove upper or lower bounds on it? What problems have the highest values? It will be amazing to look back at the millennium problems and see the wide range of AI difficulty they posed, and to try to understand why that is. This is just one random thought, but it’s an exciting avenue that will tell us so much about hard problems that we never could even ask before, a new window of research that can open now that AI in math is the new normal. There’s so much else that we’ll be able to do and explore in this human-AI hybrid math system, I’m finally feeling ready to embrace it and honestly quite excited about it!
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Danny O'Brien🤖 retweeted
Five years ago this month, OpenAI released a dataset of grade school math problems, which all AIs at the time struggled with. Consider some of the problems:
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Danny O'Brien🤖 retweeted
Hoy se concretó la vulneración de derechos más arbitraria de la que he sido testigo. Una funcionaria administrativa ordenó la deportación inmediata de @olabini sin ningún motivo o prueba. Todo bajo la excusa de que son informes secretos porque, supuestamente Ola habría cometido actos en contra de la seguridad del estado ecuatoriano. Hoy Ola será deportado y se prohíbe su ingreso al país por 10 años. Como duele mi país sus funcionarios y sus instituciones.
Actualización. Por falta de traductor, se suspendió la audiencia administrativa en contra de @olabini. Se nos dijo que nos volverían a convocar a las 20h00 para continuar con la audiencia. Les pedimos estar al tanto ya que Ola sigue, sin ninguna orden de autoridad competente retenido en el edificio de migración frente al mall el jardín.
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Urgente! Hace una hora fue retenido de migración de Ecuador. Dicen que han revocado mi visa!! Estoy en migración frente a El Jardín. Temo que van a destruir mi vida otra vez.
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If you're a #sanfrancisco artist, free yourself from digital monopolies with @grayarea's Beyond Big Tech. Learn IT ALL from the politics and ethics of decentralized tech, to setting up a Raspberry Pi with your own services. Scholarships available! grayarea.org/course/beyond-b…
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Danny O'Brien🤖 retweeted
Claude Opus 5.5 has the best visual design of any model I have tested so far
Claude-Pop - I'm Upping My P(Doom)
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Danny O'Brien🤖 retweeted
The audio description feature somehow got turned on in the middle of a Doctor Who episode, and suddenly a cheery narrator started describing everything as it happened. I thought, "Whoa, they're doing a Brechtian distancing device."
Does anyone have any more examples
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I wondered what they were up to
me: “look i know san francisco gets a bad rap but i love it here, it’s cooler than you think” out of towner visiting friend, pointing up:
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Danny O'Brien🤖 retweeted
me: “look i know san francisco gets a bad rap but i love it here, it’s cooler than you think” out of towner visiting friend, pointing up:
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Danny O'Brien🤖 retweeted
A brief throwaway movie line that I think about all the time in Congress and the U.S. government, delivered by Captain Kirk in Star Trek II: The Wrath Of Khan- “You have to learn why things work on a Starship.”
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Danny O'Brien🤖 retweeted
After working on multiple games with this woman, I truly WISH you guys could see her casting audition videos compared to her competition. It's like watching 1996 Michael Jordan turn up to a high school basketball game.
Alguien me puede explicar por qué esta mujer sale en todos los videojuegos del mundo?
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Begun the Accelerationist (Dept of) War Has
Americanism, not effective altruism. The United States will continue to be AI DOMINANT! 🇺🇸
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Danny O'Brien🤖 retweeted
I think this was ultimately the right move.
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Danny O'Brien🤖 retweeted
Here at Galadriel, we are building a different kind of AI. Instead of a Dark Lord, it will be a queen. Not dark but beautiful and terrible as the dawn! Tempestuous as the sea, and stronger than the foundations of the earth! All shall love it and despair!
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Excellent new eval harness
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Danny O'Brien🤖 retweeted
since a lot of folks asked me, this is the research agenda I have in mind for **generative cryptography** > "what can we unlock if AI could write cryptography?" 1) ai agents can engage in cryptographic interactions 2) autoresearch can improve protocols 3) solve open problems
You want to do lean & cryptography? Reach out!
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if you're firstflagPOISONED you may be entitled to compensation. call 1.1.1.1 on port 22 now
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Danny O'Brien🤖 retweeted
Come visit our Burning Man art piece that we installed today. It's a mile-long line of solar powered LED strobes that create a streak of light moving at the speed of the Earth's rotation. You can feel your spin. At 11:00 and far fence.
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