What can a neuron compute? Real biological neurons are complex, but how capable are they? Using a new method, we found that a single cortical neuron can classify cats vs dogs, recognize spoken words, and solve 10-bit parity, all tasks thought to require entire networks. (1/15)

Two years ago the best virtual cell model was ridge regression and yesterday the best virtual cell model was ... ridge regression. But sure, throw a billion more parameters at the problem, no one is stopping you.

Andrej Karpathy thinks AGI's impact on the economy will just be folded into the existing rate of growth. AI will be barely noticeable in GDP statistics. When he came on the show, I pushed back, saying AGI will cause a massive jump in productivity and growth. Watch our back-and-forth on this:

This is a super exciting release - Claude Fable 5 is the same underlying model as Mythos but with added safeguards. The benchmarks are great and it's SOTA on everything by a margin but I'll add that *qualitatively* also, this is a major-version-bump-deserving step change forward (imo of the same order as Claude 4.5 was in November), peaking especially for long problem-solving sessions on very difficult problems. You can give it a lot more ambitious tasks than what you're used to, the model "gets it" and it will just go, and it's never felt this tempting to stop looking at the code at all (but don't do this in prod!). The model still has quirks that people will run into and the safeguards are configured to be a little too trigger happy for launch, which can hopefully be tuned over time. I feel a lot of things changing as working software increasingly comes out on a tap. The Jevon's paradox kicks in and I feel my own demand for software growing substantially. You can ask for anything - explainers, visualizers, dashboards, bespoke single-use apps (e.g. a full wandb that is hyper-specific just for your project), you can 10X your test suite, auto-optimize code, run giant research projects with custom HTML for the results, anything! "Free your mind" (Matrix ref). Really looking forward to all the things people build!

AI can't compress a clinical trial. It can't generate the data we don't have yet. Our CEO Neil Kumar pushed back on the AI hype with @bloomberg at #MIGlobal with @MilkenInstitute – not because the tools aren't valuable, but because the years still take years.

Here is the key problem in the recent paper arguing that neurons are simple. It is the same logical problem plaguing much of neuroscience.

Simple input-output dependencies explain neuronal activity ( @ChrisWLynn ) has made the rounds on X with divided opinions. I show in this blog that while neurons are described simply, so can explicitly complex units: Describe and Arise are distinct claims. open.substack.com/pub/anshks…

1/n Are biological neurons linear-nonlinear computers, like perceptrons, or is their output governed by non-linear interactions between inputs? If the activity of a neuron is well fit by linear models that sum inputs, does that mean that the neural computation actually is linear?

Simple input-output dependencies explain neuronal activity ( @ChrisWLynn ) has made the rounds on X with divided opinions. I show in this blog that while neurons are described simply, so can explicitly complex units: Describe and Arise are distinct claims. open.substack.com/pub/anshks…

Today I'm posting a new blog about an astonishing scientific own goal. Hundreds of papers have reported using a completely wrong antibody to investigate the tumor suppressor p16. This mistake has happened because scientists have muddled the names of two proteins 🧵

RAS finally getting drugged is one of the great stories in modern biology, and almost nobody outside oncology understands why it's such a big deal. YOU'LL LEARN SOMETHING AWESOME TODAY. i am going to keep this as understandable (and simple) as i can. OPEN THE THREAD. 🧵

1/ We’re so glad to share this new study 💫 Does the brain learn like a Deep Net? 🧠⚙️ - 📄Misalignment Between Backpropagation and the Hierarchy of Brain Responses to Images - 🔗arxiv.org/abs/2605.28693 Thread below 🧵

People often complain about tough peer reviews But papers that elicited stronger criticism from reviewers and required more-extensive revisions received more citations tha did papers that drew light comments and sailed through the peer-review process. We need to embrace constructive criticism if we want to do stronger work. nature.com/articles/d41586-0…

ANNOUNCEMENT: WE’RE SAVING SCIENCE! We’re often told that science is “self-correcting.” But that’s not really true. Science doesn’t correct itself like a thermostat adjusting the temperature in your house. Science is a human institution run by human beings. And human beings are vulnerable to career incentives, groupthink, moral fads, political pressure, and fear. And when those forces capture academic journals, peer review stops being a filter for bad ideas and starts becoming more of a credentialing system for fashionable nonsense. This isn’t exactly new. In 1996, the physicist Alan Sokal managed to publish a totally gibberish article in the journal Social Text full of trendy postmodern jargon. His point was simple: if you flatter the ideological commitments of certain academic editors, nonsense can pass as real scholarship. Two decades later, @ConceptualJames, @HPluckrose , and @peterboghossian pulled off the “grievance studies” hoax, placing over a half dozen absurd papers in peer-reviewed journals. One paper used dog parks to analyze rape culture and queer performativity. Another rewrote parts of Mein Kampf in the language of feminist theory. The problem wasn’t just that fake papers got published. It was that they were completely indistinguishable from the real thing. And today, the problem is even worse. We now have serious SCIENCE journals publishing papers about feminist lesbians marrying brine shrimp. We have disturbing papers that aim to “queer” and sexualize infants. We have scholarship on “lesbian-queer-trans-canine relationalities” and “trans-dog intimacies.” But while Clown World papers are concerning because it makes a complete mockery of academia, the same broken, ideologically captured system is also publishing research in legitimate science and medical journals that pushes sex and gender pseudoscience, relies on deeply flawed data, and influences policies on the medical transition of children and young adults. That’s not funny. That affects real people. It affects medicine. It affects law. It affects children. And when critics try to respond, they often discover there’s no serious mechanism for correction. Submitted Letters to the Editor often go completely ignored. Contrary evidence is rejected without comment. As a result, the best critiques are often relegated to personal blog posts, social media threads, or newspaper op-eds, while the original paper remains in the literature wearing the armor of “peer review.” That is untenable. So Kevin McCaffree, editor-in-chief of Theory and Society (@Theory_Society), and I decided to do something about it. Today, in the Wall Street Journal, we announced a first-of-its-kind article type called “Peer Review.” The idea is simple: publication should be the beginning of academic scrutiny, not the end of it. A Peer Review article can critique a paper from any scholarly journal. It can address problems with methods, evidence, logic, definitions, theory, or interpretation. But it has to focus on the claims and arguments, not personal attacks. Submissions are capped at 2,500 words and go through a straightforward merit review instead of endless gatekeeping and ideological screening. We ask just one basic question: Is this critique coherent, serious, reasonable, or even popular enough to deserve scholarly attention? If yes, it gets published. And the authors of the original paper get a built-in right of reply, so readers can see the critique and the response in a legitimate academic venue. That’s how science is supposed to work. Science becomes self-correcting only when real people build the mechanisms that allow correction to happen. That’s what we’ve done. Now it’s time for academics to use it. Read our announcement on the @WSJ below. 🔗wsj.com/opinion/a-way-to-cha…