NeuralBets

Fascinated by minds and machines.

[Andrew Curran @AndrewCurran_]

'Rejoice, my friends, or weep with sorrow. What California is today, the world will be tomorrow.'

[NeuralBets @NeuralBets_]

@dwarkesh_sp Since your podcasts with David Reich were well received:

Gregory Clark, of “A Farewell to Alms” fame, would be an appropriate guest (his proposal is that natural selection drove productivity in Britain and culminated in industrial revolution).

[NeuralBets @NeuralBets_]

@dwarkesh_sp @nathanieldaw
@gershbrain
@somnirons
@tyrell_turing
@paul_masset

[NeuralBets @NeuralBets_]

@ShaneLegg @GoogleDeepMind Have your expectation about time to AGI shifted either way or it's largely same?

[NeuralBets @NeuralBets_]

@dwarkesh_sp Michael Levin

[NeuralBets @NeuralBets_]

@doomslide why them specifically?

[NeuralBets @NeuralBets_]

@cloneofsimo you might find weight agnostic NNs interesting:
https://t.co/WrwLg40wDR

[NeuralBets @NeuralBets_]

@Grad62304977 @SarahLacard relevant paper:

https://t.co/YlPnbb3Hvu

[Nenad Tomasev @weballergy]

I'm excited to share a new paper: "Mastering Board Games by External and Internal Planning with Language Models"

https://t.co/jWoSojZtbQ

(also soon to be up on Arxiv, once it's been processed there)

[NeuralBets @NeuralBets_]

@MillionInt which hints at the deeper issue: it's hard to come up with right objectives

[NeuralBets @NeuralBets_]

@erikphoel @JrKibs for e.g. moving SOTA from 2% to 25% on FrontierMath. That's very impressive, I think you'd agree. Personally, I was betting strongly on prediction markets that SOTA performance on FrontierMath would not cross 10%, and definitely not 30% by the end of 2025. o3 reminded me this:

[NeuralBets @NeuralBets_]

@erikphoel @JrKibs o3 has not been tested as comprehensively, but it was just a preview and we don't have its system card yet. Also consider this: most benchmarks have already been saturated, and the benchmarks it *was* tested on, it showed highly impressive performance, (continued in next reply)

[NeuralBets @NeuralBets_]

@OwainEvans_UK Happen to have a relevant paper in my Zotero pile:
https://t.co/t0a1NbIV2o

[NeuralBets @NeuralBets_]

@gwern @GoingNeilPostal @aidan_mclau https://t.co/L3tHT6XXja

[NeuralBets @NeuralBets_]

@Justin_Halford_ @Jason You're lending support to my IBM analogy by citing all these releases.

Nothing about Veo2 or Whisk is groundbreaking research-wise. It would have been more impressive if there was a Veo before there was a Sora.

[NeuralBets @NeuralBets_]

@Justin_Halford_ @Jason When you put it like that, sounds like Google suffers from a kind of "IBM disease".

FWIW, I'm not too optimistic about OpenAI in the coming future, but they seem not to have lost their momentum so far.

[NeuralBets @NeuralBets_]

@Justin_Halford_ @Jason "Your view of things does not explain past very well, why then it must predict future?" is what I'm trying to get at.

[NeuralBets @NeuralBets_]

@Justin_Halford_ @Jason I understand how important compute is for research. RLHF was just an illustrative example of a component that cannot be replaced with more compute.

My point is, you're taking Bitter Lesson to be simpler than it is, and extrapolating it too far to "more compute = best AI".

[NeuralBets @NeuralBets_]

@Justin_Halford_ @Jason Bitter Lesson does not enable companies to magically capture market share or have good research insights. I also disagree with the idea that compute advantage can offset lack of good research. No amount of compute can substitute RLHF, for example.