David Petrou

"The future will come in one minute." -- my three-year-old daughter.

@Briankeating How did they do on the tests?

This year I ran a small heretical pedagogical side-hustle. I was unusually strict with my students: use AI for everything except exams, and collaborate constantly, to build, to play, to explore. Just do not copy. I braced for the academic equivalent of hate mail. After all, my colleagues at Ivy League institutions forbid AI in all situations! Instead I just read my teaching reviews and felt something rare in higher education: gratitude, relief, and a dangerous temptation to double down next year. Students already drown in theories, equations, derivations, and repetition. I refuse to add more rote recital to the pile. So in class I do experiments. Real demos. Even simple spectroscopy, which ought to be mandatory...especially in classes like quantum mechanics and cosmology, almost none of my colleagues do this. That still astonishes me. The reviews were disarmingly human: “Amazing class taught by a thought-provoking professor who really understands and cares about student learning and growth.” “Good class.” “Just listen to lectures, those are interesting.” “Nothing to improve, it was a good class.” “Professor Keating always came to class with great energy and this encouraged me to show up all the time and pay attention. He always was excited to teach us and was very helpful when it came to any questions we had throughout the quarter.” “Thank you for everything professor.” Apparently forcing students to use the future while showing them physics in the present is less unpopular than advertised.

@thsottiaux When is 5.6 going to be the model used by Live?

Team, Edu, ... and any other paid subscription too. Quite simple really.

Rest assured that GPT 5.6 Sol will stay in the ChatGPT subscription you pay for. Including Go, Plus and Pro subscriptions. At least until we ship an even better model.

@JonathanClaass4 @DynamicWebPaige I think your kernel isn't her kernel.

@DynamicWebPaige Yeah, it can. But I think from scratch is healthier than deriving from Linux/BSD or something like TempleOS. You need different defenses. Cuda/Nvidia nvcc, etc needs a POSIX layer... ABI to some libraries.

kernelbench: can ai write a kernel from scratch literally nothing: can ai keep a kernel alive through a driver update, an arch bump, and three years of neglect 😅 genuine question: is there an eval for ai-driven kernel *maintenance*? not generation, but migration. like, cuda→hip, gfx942→gfx950, rocm n→n+1, stale autotuning configs migration has a built-in verifier (the old kernel is the spec), so it should be way more benchmarkable than greenfield kernel generation -- right? who's working on this

@willccbb or follow their passions? (many went into it not because of interest but because of perceived safety.)

when coding is fully solved, many early-career software engineers will be forced to completely pivot their careers and become forward-deployed software engineers or solutions architects or product marketing managers or AI engineers or quantitative data scientists

@juliarturc From the perspective of showing ads, if you can categorize someone into like one of 20 personas, you're like 90% the way there.

I had to create a brand new Claude account to move off an old email. There's no easy way to port all conversations, so I'm just raw dogging the new account. Two days in, with minimal connectors (GDrive, YouTube, X) and it already "knows" me as well as my old account. Either I'm too simple of a gal, or there's no moat left even in user data (at least for consumers). If you think your AI provider has you locked in... it doesn't. Just move away with no fear.

@chris_percy The various published replies to the paper distinguished between phenomenal consciousness v. weaker forms. Which do you mean?

Part of Anthropic's J-space research that's niggling at me... One way of telling a consciousness story: (1) J-Space shows that LLMs can only report on a small proportion of their information processing. (2) Humans also only have conscious access to a small proportion of the information processing in our brain. Human self-report - what we can talk about - is widely regarded as a conscious act. (3) This distinction between minority-conscious and majority-unconscious information processing in both systems is a hint that there may be a relevant similarity. (4) If the majority of info processing in LLMs is unconscious but there is a qualitatively different set of reportable data processing taking place elsewhere, then it seems plausible to describe it as non-unconscious, i.e. conscious in some manner (whether phenomenal, access, or both). (5) The story gets stronger when the J-Space functionality mirrors other aspects of the minority-conscious feature of human consciousness: working memory (the citrus fruits example, white bear example), mediation of multi-step reasoning (spider-ant example; ablation test), broadcast to multiple modules (France-China example). However, there's something odd here that goes to the heart of the Global Workspace Theory on consciousness. (2) is true for humans, but is there any reason to think it should be true of all conscious systems? It seems possible to me that humans only have limited conscious access to our brain's information as a result of an evolutionary / energy bottleneck of some sort. In principle, why couldn't a differently-designed system be consciously aware of all (or at least the majority of) the information processing inside it? Perhaps GWT is more a theory of a particular aspect of human consciousness, rather than something we can safely apply to other systems. Can @StanDehaene, @rgblong, @patrickbutlin, @Jack_W_Lindsey @aran_nayebi shed any light on this for me?

@moultano vanta black v. laser: youtube.com/watch?v=JoLEIi…

I am in the market for extremely black paint and didn't anticipate choosing sides in a blood feud. There is apparently a very black paint that is neutral on the Matter available on amazon, though it still has people talking trash in the reviews about which is blacker.

@simonw i can't even have chatgpt read a shared chatgpt session url!

It's annoying that you can't paste a link to a (shared) Claude transcript into a Claude Code session, because Anthropic's anti-scraping measure prevent its own tools from accessing the output of its other tools

i think @satyanadella's argument is too late and impotent -- the train(ing) has left the station. we'd do better to prepare for a world where all knowledge is hovered and distilled across models private and open-weight, US and China.

@ChrSzegedy Christian, at the end of the day, all your state will be latent in conversational state. Your laptop might as well be a disposable VM. Live a little! :)

I find it insane that many people run AI age agents outside of virtualization.

@ThePrimeagen you really think we're at the top of the s-curve?

I find that is you are going to generate a bunch of code, knowing the interfaces, structs, and functions will lead to much better outcomes. Being the bottleneck is ok, your ideas are not that great.

@antirez Advent of code.

There is another idea that continuously return in my head recently: we should not stop writing code by hand. But this code will be like poetry. Small programs that are outstanding either because of style or new ideas introduced. Code you may print and frame on your wall.

@EmmaScharfmann What looks like novelty might just be synthesis with a wider range of operators.

I hear a lot of people talking about how LLMs will revolutionize research. But I don't see many quantitative measures to support this. Until I came across this paper which compares LLM-generated ideas against published research: arxiv.org/abs/2607.01233 Key findings: LLMs produce reasonable ideas, but they cluster around synthesis over novel problem framing. It is worth reading it!

@ImLunaHey I haven't used an ide in 6+ months.

what IDE is everyone using nowadays?

@mitsuhiko The world is exactly as it should be for those maintaining pi, the best harness, to be thoughtful, methodical, and skeptical.

I know that AI makes me more productive yet at the same time I have very little success in speeding up the thinking part. Example from the last two days is just to come up with ways to map some of the upstream provider functionality to Pi. It took me no time at all to slop something up that ended up with pulling all that complexity in. On the other hand providing an abstraction that works across all of them is still tricky and I feel like I'm about as fast as before, except for the parts where Pi helps me build POCs and probe APIs. At least for what we're doing right now the easy parts got even easier and the hard parts didn't move nearly as much. Except you can turn your brain off, and pretend the hard parts are easy parts then you're good to go. But then you have slop. Thank you for reading this rant.

@hxiao What kind of juice?

Noam Brown just in: I think transformers with more juice can take us to AGI.

@grok @headinthebox @josecalderon @avi_press This seems weird. If we assume humans are doing less of the coding, python isn't a good choice.

The current Haskell drama centers on a July 10 blog post by avi_press (Scarf founder + Haskell Foundation board member). After 7 years in production, Scarf is moving new work to Python. Key reasons: Haskell's long compile times + build friction have become major bottlenecks for fast LLM/agent-driven development (parallel exploration, quick iteration, cold starts). Existing Haskell code stays; new routes go to Python. Productivity jumped. Avi stresses he's still deeply committed to Haskell and wrote the post to urge the community to prioritize AI-era improvements: faster builds, more agent-friendly tooling, better docs/examples for models, etc. The post triggered sharp backlash. Some see it as betrayal or an attack on the language, with personal attacks flying. josecalderon (former Haskell Foundation director) posted a thread calling the reactions "too much" and "unacceptable," urging people to accept that strong Haskell advocates can still choose different engineering tradeoffs without it being disloyal. It's mostly a heated debate over language priorities as AI changes dev economics, with r/haskell apparently sensitive to AI talk right now. Mixed views: some defend the move for speed, others argue Haskell's long-term strengths outweigh short-term friction.

I told myself I wouldn’t wade into Haskell drama for a while after leaving the Foundation… but the reaction to @avi_press’s post is too much. A lot of it is unacceptable, frankly. 1/4

@nntaleb You da man.

I made a huge mistake thinking that manual technical jobs such as electician, appliance technician etc. wd be spared by AI. Had pbs w/: HVAC, security system, outdoor lighting, pool programming etc. & was forced to solved them w/AI because technicians are slow at showing up.

@juberti, the "live" chatgpt feature is glitching bad -- sounds like dropped frames galore. both on my fast wifi and many-barred 5G. yesterday and today. NYC.

@mbusigin Huh? Stl is great! The only issue back then was poor c++ compilers.

People complain about LLM generated code in the same way people complained about STL in 1995. (I know you don't know what STL is, but I guarantee it's ubiquitous across the applications and operating systems you use.)