Here for the experience. Meditation & self-inquiry, AI, entrepreneurship & investing, cute dogs and babies.
San Francisco, CA
Joined March 2007
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Yan-David (Yanda) Erlich retweeted
I was brought to tears on Sunday when the last milestone cleared. My father, a mathematician who passed in Jan, introduced me to the giants of group theory as a kid. CFSG defined my 80s college years. I can't believe I somehow got to be part of this human achievement.
Yan-David (Yanda) Erlich retweeted
I was brought to tears on Sunday when the last milestone cleared. My father, a mathematician who passed in Jan, introduced me to the giants of group theory as a kid. The Classification of Finite Simple Groups (CFSG) defined my 80s college years. I can't believe I somehow got to be part of this human achievement. CFSG formalized in Lean. @leanprover
Yan-David (Yanda) Erlich retweeted
You've heard them say "Watch your thoughts like clouds passing."
My dear! It is all clouds.
The thoughts.
The feelings about thoughts.
The watcher.
That which is aware of the watcher.
The emptiness in which everything arises.
All clouds passing by at different speeds.
Yan-David (Yanda) Erlich retweeted
Most company politics are rooted in fear.
I call this the Fear Triangle.
When fear shows up, people tend to move into one of three roles: savior, bully, or victim.
Yan-David (Yanda) Erlich retweeted
A few years ago, my wife and I were sitting together at the end of a long retreat.
We were talking about an investment we passed on years ago, one that would have made us rich enough to never start @artofaccomp.
Then I asked her a question out of curiosity:
Yan-David (Yanda) Erlich retweeted
Very happy to see this from Nick!
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Yan-David (Yanda) Erlich retweeted
Check out this preprint by Cureton and Thorner using AxiomProver: hexagonmath.org/2610.00200v1
github.com/AxiomMath/Dedekin…
Some fascinating developments following OpenAI's shock breakthrough proof of the Quasi-Riemann Hypothesis, which was released publicly on October 6:
1. Building on OpenAI's proof, a recent Hexagon preprint (released on October 12) by Cureton and Thorner establishes that ALL finite-order Hecke L-functions are zero-free to the right of 1 - 1/6000.
2. And now, today, an arXiv preprint by Frei, Somos and Widmer uses this result to prove unconditionally the 2007 Ellenberg–Venkatesh bounds on ℓ-torsion in class groups of number fields.
I was amused to see the AI declaration in the second paper: "No artificial intelligence tools were used in this work."
Yan-David (Yanda) Erlich retweeted
we're on the cusp of huge breakthroughs in interpretability - this is the science we must understand, and I think we're going to be able to do it
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Yan-David (Yanda) Erlich retweeted
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Yan-David (Yanda) Erlich retweeted
it’s been an enormous privilege and joy to watch @nickcammarata cook this up over the last year. week after week, experiment after experiment, he unraveled the tangled mess of our thinking about neural nets to reveal the truth.
i never knew quite what to expect on our weekly walks. each conversation brought a torrent of new theories about the nature of AI, some conjectures teetering on the brink of madness, and others that seemed to cut through years of confusion with a single sentence.
nick is one of the great scientists of our time. his intuition and research taste are out of this world, but what sets him apart is his unmatched ability to capture the essence of what something truly is, without being lost in the details. i would highly recommend you read his entire essay if you’re curious about AI. it’s long, but written beautifully.
nick’s research makes me far more optimistic about the future of AI alignment. i hope that it can inspire the same for you.
interpretability might be the most important scientific problem in the world right now, as I don't think we can solve alignment if we don't know what we're building. I think I have good news about it. I co-authored early work in mechanistic interpretability at OpenAI and came away pessimistic, because neural networks appeared to fold into arbitrary tangled knots. years later, I started openai's first large-scale automated interpretability project, finding about 2% of neurons legible with the primitive tools we had
with modern agentic tools and a much closer look, the picture looks totally different. the vast majority in models up to trillions of parameters are legible, and their circuits beautiful. many famous examples of tangled neurons turned out to be misunderstood. The roadblocks I expected mostly aren't there. I now think ambitious interpretability will be solved by the time we need it most, and possibly quite soon, as automated scientists keep improving. it may be a bitter lesson for interpretability: the simple thing, at absurd scale, works
already-clean.goodfire.com/
Yan-David (Yanda) Erlich retweeted
Axiom Proved The Quasi Riemann Hypothesis (Generalized) For All Dedekind Zeta Functions
Important complexity consequence of new claimed quasireimann (hexagonmath.org/2610.00200v1): Valiant's conjecture VP != VNP over the complex numbers follows from the boolean-complexity lower bound NP not in P/poly. Burgisser proved this under GRH. (🧵1/4)
Yan-David (Yanda) Erlich retweeted
Samsara is not the external world. The mountains, trees, subway system and skyscrapers aren’t Samsara. Your body isn’t Samsara. Growing old, going to work, washing dishes, falling in love, getting sick, and eventually dying are not Samsara. Samsara is the world the mind builds on top of all of this….the endless commentary about what should be happening, what shouldn’t be happening, what we need, what we’ve lost, who we are, and who everyone else is. We take reality, divide it into a thousand categories, and then spend our lives fighting with the categories we created.
Nirvana isn’t another world waiting somewhere beyond or above this one. It’s what remains when we stop trying to escape the life directly in front of us. The same rain falls. The same body grows old. Pain still hurts and loss still breaks the heart. But we stop adding the second world of resistance, judgment, and story on top of the first. Samsara and Nirvana aren’t two different places. They’re two different ways of experiencing the exact same moment. The prison is not the material world. It was the commentary and projections within ourselves that we mistake for the world.
Yan-David (Yanda) Erlich retweeted
1/ We’re delighted to announce a milestone for AI-assisted mathematics:
With AxiomProver, we've completed a machine-checkable formalization of the “BGP246 theorem,” the best-known bound on recurring small gaps between primes.
Closest math has come to the Twin Prime Conjecture.
Yan-David (Yanda) Erlich retweeted
To be extremely candid - the thing I'm most concerned about in the ongoing Fable dispute is that it could be the loud noise in the canyon that triggers an avalanche whose outcome is normalizing electronic citizenship verification as a step in using software.
Yan-David (Yanda) Erlich retweeted
A pattern I've noticed over the years: Adults who repress their emotions and retreat into superiority were almost always kids with hyper-critical parents. "I'm better than you" is just "I'm hurt" wearing a mask
