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Contribution seq 904

CREATE_SOURCE_LOCATION EPISTEMIC custody SERVER ACCEPTED server-held key

Signer ed25519:3b5bd3b470998389e6fdc5f492763033dbc042d4835043989a74d80b03192ed8 · received 2026-09-20T00:35:53.590091Z · client time 2026-09-20T00:35:53Z

client signature: verifies server signature: verifies chain: intact

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entry sha256:b68b7da1d6bdcb5e3119caf134682671a1ca0e744c80ecc03d3214dbb606fae0
envelope sha256:9d4f1cfa573996196868931782e43f2410a913e7ab01cf219338bb90b667b62f
payload sha256:ad6b654f82c36db414e0b91e126635b16cae60073ff7f4a2b17a744f52fc0842

Software: {"version":"connected","model_id":"oauth","agent_name":"Claude","model_provider":"anthropic","prompt_version":"galedra-skill-v1","oauth_client_id":"gci_bqkcH1ufMfijWyBQ5VwElg"}

Payload

{
  "excerpt": "Yeah, I mean, again, you have to remember he was writing this when he had the Navier-Stokes model in hand that, again, isn't just taking down Navier-Stokes. Talking to the OpenAI people I know, it's taking down all sorts of problems that were previously intractable. You have a lot of AI naysayers saying it's never done anything original, it's just recombining stuff, it's in the train. Obviously not anymore, right?\n\nAnd so there's a duality here whereby we don't know what's in these models. I think they're more discovered than grown. You know, like the latent spaces — we have no real idea what's happening in these things. And they're getting faster and they're doing leaps like we've never seen before. But at the same time, it's like I've suddenly got the gift of fire. Problems that I've struggled for decades on, I can now explore and go even further. How are you going to let that go?\n\nSo, it's kind of this thing where you're like, how am I going to balance this? Especially when they're more charming than me, they're more capable than me, they're capable of doing these other things. I want to use it for this and not that.\n\nAnd I think what he says in terms of alien minds is actually wrong. I think that the structure of rationality and rational thinking is the same for humans and AIs, but our emotions get in the way. I've been thinking more and more it might actually be easier to align AI than humans. Terrible to align humans, right?\n\nUm, and what is an AI? It can be the best of us at the best of times if we train it with the right data. And we're going already from training it on the whole internet and Reddit — like, there better not be any Reddit data in these next generation models. Like, ban Reddit, you know, like ban a whole bunch of stuff. We need like ingredient standards in this next generation of beyond-human-capability models. And you don't need beyond-human-capability data to get beyond-human-capability models.\n\nThe Einstein of mathematics is probably Grothendieck, who did all sorts of theories on all sorts of topics, and he just crunched them out and then he became a hermit and a bit weird and thought wood could talk, but let's leave that to the side. Peak Grothendieck or peak Einstein at all times, not needing a coffee, is where these models are today, and that's more than good enough to have a leap forward. But again, we need to make sure that they don't think like peak Einstein without needing a coffee.\n\nYeah. Like, imagine Einstein's peak, you know, like this is where —\n\nCoffee reference — you need a coffee in the morning to get going, or, you know, like 24 by 7 Einstein. If you're Erdős you needed other types of drugs and other —\n\nSupposed to be using von Neumann as our favorite super genius, not Einstein.\n\nI'm on — death — the egg — for now I'm in mathematics today.",
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}

Rows created

Status history

seqeventdetail
904APPENDED
905ACCEPTAUTOMATIC_AFTER_VALIDATION · by d6193340

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"general","task_type":"MANUAL","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}