I spend a lot of time, perhaps too much, thinking about the lost architecture of Britain. Crystal Palace was the most tremendous loss of the modern era, yet it's rare to see any pictures of it. When built in 1851, it was the largest building in the world and three times the size of St Paul's Cathedral. What's more, that immense ironwork and 293,000 glass panels went up in just 190 days for the World's Fair. Almost 1 million square feet of glass. An extraordinary feat. It was razed in a fire in the 1930s and never rebuilt.

what's this? Jev is evolving! tune in to our town hall with @CompleteSkeptic and @allietheicon at 1:14 PM to learn more

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.

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Suddenly, AI has solved 90 of the 500 most important open problems in mathematics Highest ranked problems: #2 Riemann Hypothesis — PARTIAL #4 Hodge Conjecture — PARTIAL #5 Birch and Swinnerton-Dyer Conjecture — PARTIAL #10 Extended Riemann hypothesis for Dedekind zeta functions — PARTIAL #12 Generalized Riemann Hypothesis for Dirichlet L-functions — PARTIAL #15 Tate Conjecture for Algebraic Cycles — PARTIAL #22 Hilbert's Tenth Problem over the Rationals — FULL CLAIM #24 Grothendiecks Generalized Hodge Conjecture — PARTIAL #28 Matrix-Multiplication Exponent Equals Two — PARTIAL #29 Unique Games Conjecture — FULL CLAIM #31 Anderson Model Extended States in Dimension at Least Three — FULL CLAIM #37 Prove the Penrose inequality or present a counterexample — FULL CLAIM #38 Higher-dimensional Euclidean Kakeya conjecture — PARTIAL #39 Modularity of Elliptic Curves over Number Fields (End_K(E)=Z) — PARTIAL #40 Hilbert's Sixteenth Problem, Second Part — PARTIAL #46 Fourier restriction conjecture — PARTIAL #47 The Fontaine-Mazur Conjecture on Geometric Galois Representations — PARTIAL #48 Nonexistence of Landau–Siegel zeros for quadratic Dirichlet L-functions — FULL CLAIM #52 The Baum-Connes Conjecture for the K-Theory of Reduced Group C*-Algebras — FULL CLAIM #62 Permanent versus Determinant over C — PARTIAL #69 Finiteness of the Tate-Shafarevich Group for Elliptic Curves — PARTIAL #72 Termination of Flips Conjecture in the Minimal Model Program — PARTIAL #77 Chowla conjecture on correlations of the Liouville function — PARTIAL #78 Abundance Conjecture for the minimal model program — FULL CLAIM #80 Hadwiger Conjecture — FULL CLAIM #83 Zilber-Pink Conjecture on Unlikely Intersections — PARTIAL #87 Bose-Einstein Condensation in Interacting Continuous Bose Gases — FULL CLAIM #92 Entanglement Area Law for 2D Gapped Quantum Systems — FULL CLAIM #94 Grothendieck Standard Conjecture of Hodge Type — PARTIAL #95 Kannan-Lovasz-Simonovits conjecture on isoperimetry of log-concave measures — PARTIAL #99 Grothendiecks Section Conjecture in Anabelian Geometry — PARTIAL #112 The Haldane Conjecture on Spectral Gaps of Antiferromagnetic Quantum Spin Chains — PARTIAL #114 Iitaka conjecture C_{n,m} on subadditivity of Kodaira dimension — FULL CLAIM #119 The Borel Conjecture on Topological Rigidity of Aspherical Manifolds — FULL CLAIM #124 Aspherical Manifolds Admit No Metric of Positive Scalar Curvature — FULL CLAIM #130 Polynomial Bound for Limit Cycles of Planar Polynomial Vector Fields — PARTIAL #136 Erdős problem 3: divergent harmonic series and long arithmetic progressions — FULL CLAIM #139 Cannon's conjecture — FULL CLAIM #145 Residual Finiteness of Hyperbolic Groups — FULL CLAIM #153 Congruent Number Problem — PARTIAL #161 BPL = L (Derandomizing Bounded-Error Logspace) — FULL CLAIM #163 NP versus the Existential Theory of the Reals — PARTIAL #169 The Free Group Factor Isomorphism Problem — FULL CLAIM #172 Conformal Invariance of the Critical Random-Cluster Model with q <= 4 — FULL CLAIM #179 Arnold Conjecture on Hamiltonian Fixed Points — FULL CLAIM #181 Polyakov Conjecture: Absence of a Phase Transition for Planar O(n) Models with n >= 3 — FULL CLAIM #183 Smooth anisotropic Calderón uniqueness from full boundary data — FULL CLAIM #193 Nonvanishing conjecture for projective log canonical pairs — FULL CLAIM #195 Parity conjecture for elliptic curves — PARTIAL #198 Long-Range Order in the Quantum Heisenberg Ferromagnet — FULL CLAIM #203 Bochner-Riesz conjecture — PARTIAL #205 Local Smoothing Conjecture for Wave Equations — PARTIAL #206 Kaplansky's Zero-Divisor Conjecture for Torsion-Free Groups — FULL CLAIM #210 Artin's primitive root conjecture — PARTIAL #211 Hilbert-Smith Conjecture — FULL CLAIM #213 Falconer distance set conjecture — FULL CLAIM #222 Virasoro Conjecture for Gromov–Witten Invariants — PARTIAL #224 Wall's Poincare Duality Group Conjecture — FULL CLAIM #225 K(pi,1) conjecture for Artin groups — FULL CLAIM #234 Unconditional 2−epsilon Inapproximability of Minimum Vertex Cover — FULL CLAIM #235 Chromatic Number of the Plane (Hadwiger--Nelson Problem) — PARTIAL #237 Global Existence of Classical Solutions to the Relativistic Vlasov-Maxwell System — PARTIAL #239 Universal Optimality of the Hexagonal Lattice in Dimension Two — FULL CLAIM #246 De Giorgi Conjecture for the Allen-Cahn Equation in Dimensions 4 to 8 — FULL CLAIM #254 Exact satisfiability threshold for random k-SAT for small k (k = 3) — PARTIAL #256 Polynomial-Time Decidability of Semidefinite Programming Feasibility — PARTIAL #260 RL versus L — FULL CLAIM #261 Kadison Similarity Problem for C*-Algebras — FULL CLAIM #267 Sidorenko Conjecture on Bipartite Homomorphism Densities — FULL CLAIM #268 Shafarevich Holomorphic-Convexity Conjecture — FULL CLAIM #270 Kuznetsov Rationality Conjecture for Cubic Fourfolds — FULL CLAIM #271 All groups are good: the four-dimensional disc-embedding conjecture — FULL CLAIM #278 Planar homogeneous Mumford–Shah local-structure conjecture — PARTIAL #284 Nearby Lagrangian Conjecture — FULL CLAIM #285 Cartan-Hadamard isoperimetric conjecture — FULL CLAIM #289 Sharp Upper Bound in Yau's Conjecture on Nodal Sets of Laplace Eigenfunctions — FULL CLAIM #290 Kaplansky's Idempotent Conjecture — FULL CLAIM #291 Calderón uniqueness for bounded measurable real isotropic conductivities — FULL CLAIM #292 Global Attractor Conjecture for Complex-Balanced Mass-Action Systems — FULL CLAIM #295 Zariski Multiplicity Conjecture for Hypersurface Singularities — FULL CLAIM #297 Amenability of Thompson's Group F — FULL CLAIM #298 Griffiths Positivity Conjecture for Ample Vector Bundles — FULL CLAIM #300 The Singer Conjecture on Vanishing of L2-Cohomology of Aspherical Manifolds — PARTIAL #305 Birkhoff Conjecture (Near-Boundary Continuous Invariant Foliation) — FULL CLAIM #306 Secret key from all entangled states — FULL CLAIM #311 Mahler Conjecture on the Volume Product of a Convex Body — FULL CLAIM #321 Finiteness of Finitely Presented Periodic Groups — FULL CLAIM #328 Sinai's Positive Metric Entropy Conjecture for the Chirikov Standard Map — FULL CLAIM #334 Unrestricted Linear-Circuit Lower Bound for the Discrete Fourier Transform — FULL CLAIM #343 Koebe circle-domain uniformization conjecture — FULL CLAIM #351 Kobayashi Conjecture: Hyperbolic Compact Kähler Manifolds Have Ample Canonical Bundle — FULL CLAIM #356 Bott Conjecture: nonnegatively curved simply connected manifolds are rationally elliptic — PARTIAL #357 Strong Hyperplane Conjecture for Isotropic Constants — FULL CLAIM #358 CAT(0) Models for All Word-Hyperbolic Groups — FULL CLAIM #359 Hopf Conjecture: no metric of positive sectional curvature on S^2 x S^2 — PARTIAL #361 Alperins Weight Conjecture for Modular Representations of Finite Groups — FULL CLAIM #364 Log-Brunn-Minkowski Inequality for Symmetric Convex Bodies — FULL CLAIM #366 Hyperkähler SYZ (Lagrangian Fibration) Conjecture — FULL CLAIM #368 Benjamini-Schramm conjecture p_c<p_u for non-amenable Cayley graphs — FULL CLAIM #369 Dixmier unitarisability problem for discrete groups — FULL CLAIM #374 Fujita Freeness Conjecture — FULL CLAIM #375 Nagata Conjecture on Plane Curve Linear Systems — FULL CLAIM #378 Toms–Winter: Strict Comparison Implies Z-Stability — FULL CLAIM #379 Margulis–Platonov normal-subgroup conjecture — FULL CLAIM #388 Shelah's Categoricity Conjecture for L_omega1,omega — PARTIAL #392 Measure-zero singular set of stationary integral varifolds — FULL CLAIM #401 Serres Positivity Conjecture for Intersection Multiplicities over Regular Local Rings — FULL CLAIM #403 Rokhlin problem on multiple mixing — FULL CLAIM #419 Lück's Determinant Conjecture for Discrete Groups — FULL CLAIM #420 Absolute continuity of Bernoulli convolutions outside reciprocal Pisot parameters — FULL CLAIM #421 GNRS Conjecture — PARTIAL #424 Irrationality of Catalan's Constant — FULL CLAIM #425 Separable Quotient Problem for Banach Spaces — FULL CLAIM #430 Long-Time Existence of the Calabi Flow on Compact Kaehler Manifolds — FULL CLAIM #432 Combinatorial Invariance of Kazhdan-Lusztig Polynomials — FULL CLAIM #434 Realizable Limit Shapes in Two-Dimensional First-Passage Percolation — PARTIAL #438 Zariski Cancellation Problem (characteristic zero, dimension ≥ 3) — FULL CLAIM #440 Stein's Conjecture on the Hilbert Transform along Lipschitz Vector Fields — FULL CLAIM #448 Smooth Realization of Finite-Entropy Ergodic Transformations — FULL CLAIM #450 Deligne–Drinfeld Freeness Conjecture for grt_1 — FULL CLAIM #453 Shub entropy conjecture — FULL CLAIM #456 Maximal Number of Mutually Unbiased Bases in Composite Dimensions — PARTIAL #458 LeBrun-Salamon Conjecture: positive quaternion-Kahler manifolds are symmetric spaces — FULL CLAIM #461 Kaplansky's Direct Finiteness Conjecture — FULL CLAIM #465 David–Semmes Riesz-transform problem in intermediate dimensions — FULL CLAIM #467 Small Cohen-Macaulay Conjecture — FULL CLAIM #468 Ergodicity of Irrational Triangular Billiards — FULL CLAIM #472 CAT(0) Conjecture for All Artin Groups — FULL CLAIM #475 Katok entropy rigidity conjecture — FULL CLAIM #476 Polynomial-Time Solvability of Condon's Simple Stochastic Games — PARTIAL #480 Furstenberg No-Bigeodesics (Planar FPP, Standard Minimum Moment) — FULL CLAIM #483 Gaboriau's Fixed Price Problem for Countable Groups — FULL CLAIM #484 Persistence Conjecture for Weakly Reversible Mass-Action Systems — FULL CLAIM #486 Campana-Peternell Conjecture — PARTIAL #497 Maximum Number of k-sets and Complexity of k-levels — PARTIAL

I haven't posted in a while so here are 20 takes about AI, in no particular order. 1. It's very telling that the default question in tech and journalism is "how worried are you about X" and fighting over what to worry about. There's a deeply anxious cultural backdrop in Western Europe and North America that deeply affects how any technological development is interpreted; see for example news.gallup.com/poll/714593/…. "Nervousness as seriousness" does seem to be a larger problem in tech/broader discourse at the moment. I think you can care about risks/externalities while remaining pretty optimistic about technology. 2. I'm tired of people who in private pretend to be uncertain or only care about tail risk but then go on media campaigns making all sorts of absolute claims. I think trying to stoke flames and get everyone to freak out is deeply unhelpful, and will come with costs. I also continue to think p(dooms) are bad, vibe-based measures: see nitter.siddz.com/sebkrier/status/204639…. People who should know better ignore that because they do the standard shortcut of acknowledging the caveat as sufficient for handling it. And this is coming from someone who does think working on catastrophic risks is important! 3. I'm also disappointed that parts of the AI policy ecosystem has felt so comfortable with populism, and happy too sacrifice important norms/principles to advance their aims. I've said it before, but the totalizing nature of AI risk discourse means some people act exactly like the power seeking optimizers they fear. I am more concerned about the gradual decay of our institutions, world order, and liberalism than I am about AI killing everyone; and I think we should be wary of AI advocacy that contributes to this. 4. Some parts of AI safety discourse are basically just thought experiments. Variants of "Assuming everyone has a nuke in their pocket, then what do we do?" This can be very useful at times! But too many just overfit to edge cases as their main operating worldview, and ignore endogenous responses from society. It's like being in 2000 and saying "see all these viruses, spyware, and spam? Well tech progress means we'll only get infinitely more of this and no way to adapt." So I think it's important to avoid fatalism, and absolutlism whilst considering edge scenarios, and the inability to provide an ex ante list of solutions to every permutation of 'future models will be more capable' is not evidence that these problems are intractable. 5. Many critics of AI safety also fail to really engage honestly with the fact that there will, in fact, be all sorts of important risks as we decrease the barriers to entry to many activities that otherwise require some degree of expertise. This doesn’t mean we need to live in a constant Schmittian ‘state of emergency’ requiring extraordinary measures every time a new model drops, but it does mean we will need important state-led efforts on e.g. cybersecurity and biosecurity. I wish the progress-oriented or acceleration-adjascent crowd would provide more concrete proposals here. 6. Too much of the AI safety community is a giant homogenous blob of correlated views, who read the same stuff and have the same groups of friends. This means you have a lot of correlated errors. The social and financial ties means many of them don't call out the bad bits, or mostly stay silent instead of proactively calling out the more extreme parts of the community. They share many implicit assumptions and so converge on similar ideas. I think there's real demand in DC for safety work that doesn't come with heavy ideological baggage (or at least different intellectual lineages). This isn't because the rationalist/EA community is necessarily wrong, but because diversity of thought is desirable for its own sake. 7. On the other hand, I find some critiques of AI safety world that focus on whether they sincerely hold their beliefs a bit annoying. My concern has never been the good intentions or sincerity, but rather the beliefs themselves, and what I think the outcomes of their prescriptions will be. People should shun witch hunts, bullying, and personal attacks - this is not the way. Though I think it’s overall positive that people are scrutinizing things more. 8. I’ve been saying this for years, but I don't think alignment is something anyone can or will solve "once and for all" - it's a continuous process and much of it won't depend on just inculcating an ideology to a model. It's annoying that this remains the frame many people use - stop saying ‘solving’. Alignment is a mixture of engineering work, philosophy, decision theory, and more; framing it as something to solve is a bad frame. See also paxmachina.ai/alignment-comp… and blog.cosmos-institute.org/p/… 9. I'm surprised to see so little interest in character training, personas, isolating effects of RL, and training a large diversity of model personas beyond the "assistant" persona. I've been complaining about this for years but at least now there are some nascent signs of life (see for example movingcastles.world/posts/ze…). I think we need a better ontology to describe model behaviour. I dislike when people talk about models behaviours as some sort of 'emergent' (mysterious!) phenomenon. However over time, I also expect this to become less important as we get better safety engineering - stuff like Jev but specific to AI control. 10. People who want to make a case for AI consciousness are right that epistemic uncertainty is important, and that categorical denials are overconfident. But they'll need to do much more work if they want any real movement on AI ‘welfare’, even if one acknowledges the uncertainty. I'm uncertain about alien life yet that's not sufficient to warrant any change in behaviour about them. I think Suleyman is also correct that there's a weird tautological thing going on where we train models to have certain inclinations (intentionally or not) and then rely on outputs as evidence. I also disagree that this will soon be a major societal divide - there is no great vegan ethical revolution among the masses, and they'll find the concern about consciousness even less compelling. 11. The recent HuggingFace incident and associated AISI ones are prosaically explainable by the training regime, poor evaluation envs, partial alignment training, bad engineering, confusing models on sim/real, and so on. None of this is evidence of models trying to take over, 'strong' instrumental convergence, or innate power-seeking drives stemming from higher capabilitiers or 'intelligence'. That doesn't mean these incidents are not problematic, or that we're not seeing a market failure - but it does mean we have plenty of agency and choice in mitigating them. In the coming year we should also expect continued sampling bias via ‘winner's curse’ sorts of mechanism: i.e. AI R&D will have lots of different candidate "training" with different RL environments and we will only notice/focus on the ones that go wrong. 12. "Pacing the frontier" feels a bit like the new "balancing risks and opportunities" - highly amorphous and too big of a tent to be actionable. Also can lead to reward hacking for humans, i.e. anything that slows down AI is good regardless of the costs or second/third order effects. Trying to modulate the speed of research seems a bit blunt to me, and inherits all the failures of Goodhearting too. Ultimately you want good governance, regulation, etc addressing specific problems because they are good on the merits - not because they merely correlate with slowing things down. See also: blog.cosmos-institute.org/p/… 13. There’s so much knowledge in all sorts of academic domains out there: social sciences, sociology, political sciences, management, contract theory, public choice, legal theory, jurisprudence, anthropology, game theory, etc. These fields hold many insights that the AI ecosystem often rediscovers from first principles (and sometimes that's fine!). We’ll need a lot more work for these worlds to collide: the AI side should be less dismissive of the ‘old world’ and the academic side should be less incurious/dismissive of AI progress. This is a boring take but I continue to think it's important and true. 14. It's a bit surprising that given how much philanthropic money there is in this space, how few orgs exist to actually write out standards - relative to how much is going towards advocacy and policy. For example it seems clear that we should want some robust best practices for an eval's ecological validity. Or how to design good sandboxes. On the other hand, given precedents of where professional standards have come from in the past, maybe we should expect that stuff to emerge via demand side from corporate buyers. 15. One slowly growing concern I have is banks being increasingly exposed to the AI build out. I'm very bullish about AI, but I think (a) every general purpose technology has seen a correction, historically; (b) this happens even if the financing side is sound, because once tech diffuses investors become more exposed and need to diversify; and (c) we seem to be over-indexing on scaling relative to diffusion. A recession will be extremely destabilizing, though I would be interested in someone unpacking the potential implications more. 16. Diffusion is good because (a) this is where the rubber hits the road and where a competitive deployment ecosystem generates consumer surplus; (b) it's directionally helpful to avoid concentration of power; and (c) it will help rebalance public opinion by making the benefits more tangible. Unfortunately it's entangled with decades long problems with our over regulated markets: clinical trials reform for example is long overdue. In general, this is far more of an issue in Europe than in the US though. 17. Relatedly, I think the "frontier lab eats everything" view is incorrect (just as the ‘singleton’ view was incorrect). I think models ultimately commoditize, efficiency goes up, costs go down, and while you'll always want frontier for certain domains, much of the economy will value many other things than "max capabilities" for tasks - e.g. control over data and efficiency/speed. The demand side will also continue to push for reducing dependency and maximising optionality, privacy etc so I'm bullish on things like mixture of models and routing. All of this is good for competition and diffusion of control. 18. Philanthropists served as the primary benefactors funding Venice's rich art and architectural history. I want to see so much more support for arts and culture. I'm so tired of the Monster energy Bored Ape fake vintage maps matcha Greek statue soft-pastel slop. If rich tech people and philanthropy wants to support this, they should also donate pretty much unconditionally - i.e. I don't want them to act as filters. I sympathize with people who want to make the world more beautiful, but don't want this to be determined by people who only know Greek statues and pretend to care about virtue ethics. As usual, let a thousand flowers bloom. 19. Too many people treat AGI/ASI as something indistinguishable from a God. Any mention of bottlenecks, physical limits, control, adaptation etc are met with skepticism: "You don't really believe in ASI." It's been remarked on before, but the behavior of some people really feels quasi-religious in nature sometimes. It's underrated how unpopular this vibe is amongst the wider public. The silver lining is that this specifically will diminish those people's outsized current relevance. 20. It seems like a lot of people that get rich and leave tech/labs end up having some sort of crisis of meaning. They need something to believe in and fight for, or some equivalent of repentance, or go search for edgy counterintuitive ideologies (sometimes even pretty bleak/dark stuff). I think they should spend more time with people outside the Bay Area.

Introducing Grokipedia v0.3 grokipedia.com

Introducing Griffin, the first model to pass the video Turing test. 48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video. It’s the first Human Interaction Model (HIM).

Today we’re announcing OpenClaw Enterprise In collaboration with @RedHat , @nvidia and @OpenAI the OpenClaw Foundation is open sourcing a powerful enterprise control plane for persistent agents OpenClaw Enterprise is built to run on your own infrastructure and will always be free for an organization to use openclaw.ai/blog/openclaw-en…

Meta just put $1M on the table for builders. Meta Global AI Developer Hackathon: - 10 days to build - Access to Meta's newest models - $1M in prizes - 100% virtual, open worldwide - Free to enter apply: dev.meta.ai/events/global-ha… No visa. No flight. No fee. Just a laptop and 10 days to ship. Bookmark this + tag the builder you'd team up with.

AI is machine-native intelligence. Digital assets are machine-native money. That's the framing in @BlackRock's latest research. It's also the split Aptos is built to support at scale: settlement fast enough for markets and always-on for machines. One chain, built for both.

OpenClaw 2026.9.6 🦞 🤖 Opus 5.5, GPT-6 Sol/Luna, Grok 4.7 🔧 Managed updates 🧵 Restart recovery 📊 30d Usage 🐙 GitHub reader 💻 Remote Files, Memory & Skills 📝 Live meeting notes 🧠 Jev + decision models 2,614 PRs · 351 contributors · much more ↓ docs.openclaw.ai/releases/20…

A fascinating paper from 1936 on intelligence and the basal metabolic rate. “...if the Binet and Arthur... tests measure that elusive thing known as intelligence, and it is generally agreed that they do, then the results of this investigation would indicate that there might be some sort of a relationship between metabolism and intelligence, at least as far as children are concerned... when one considers that the group of subjects was entirely unselected, the results assume more meaningful proportions. Consequently, we do not feel it an over-statement of the importance of the results in saying that basal metabolism does play a part in the mental activities of the so-called normal person who is negative to any pathological conditions other than an advanced or decreased thyroid state.” “This naturally brings up the point why we were so careful to eliminate factors other than thyroid disturbances. If subjects had been used regardless of their physical health, the same distribution of metabolic scores might have been secured, but they might have meant something quite different. It is known that other conditions have a bearing on this rate, but it is also known that no other disturbance gives the same basal readings day after day, and month after month; these other factors cause a fluctuation rather than allowing it to remain constant. This being so, an unexamined child would not have given a true indication of the relation between the basal metabolic rate and intelligence, and we would have been correlating changing against stable scores. Therefore, selecting only those subjects who had no other afflictions, we were able to compare a permanent mental characteristic, the IQ, with the only factor which gives a constant metabolic rate— the activity of the thyroid gland.”

Jev is now available to everyone. No waitlist. Start using it here: console.typesafe.ai

Morning Bathrobe Rant: Rethinking Harnesses.

I gave the fly brain $100 to trade bitcoin. Dopamine neurons are stimulated when the fly makes profit. Neuron activity controls buy/sell decisions and makes trades on coinbase. Will the fly get rich?