Alexis Rondeau

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October 2026 · 4 dispatches

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Thank you @karpathy because I now realize that, while the curve's vertigo has been real for me for years, there's a HUGE gap in my communication skills to translate what I'm experiencing here on the edge with those closer to the center in a way that makes sense to them.

"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."

Quoting @karpathy · Oct 11, 2026

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.

Mosey

The longest-lived people don’t exercise — they get up and move every twenty minutes. I built Mosey to put that nudge into a Mac workday: after twenty minutes at the desk, your walking pad starts on its own, three to twenty minutes, a different walk each time at a pace it sets. Step on when you’re ready, step off whenever you like. Nothing counts down at you, no streaks, no account — and it’s free. Coming to the Mac App Store.

Open →

Quasi

We spend ten or more hours a day staring at screens. Quasi is my small experiment in computing without one: you speak into a pocket recorder while your phone stays locked in your bag, and a few short sounds tell you that you were heard, understood, and that the thing you asked for is done. An aural language for a screen-free life — an experiment, not a product.

Open →

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Accelerating scientific discovery with AI-powered Empirical Research Assistance: Autoresearch at Google (2025)

Lovely and very relatable: Once you have the experiment harness in place, you wanna test it against at least four kinds of interesting problems.

  • Genomics: Batch integration of single cell RNA sequencing data
  • Public health: Prediction of U.S. COVID-19 hospitalizations
  • Geospatial analysis: Segmentation of remote sensing images
  • Neuroscience: Whole-brain neural activity prediction

Same for me. It becomes utterly fascinating.

Thank you @elliottadams for sending me this

research.googleAccelerating scientific discovery with AI-powered Empirical Research Assistance↗ research.google