Nathan Lambert
speaker
1,814 appearances
3 recordings
2 series
first heard Feb 2025
last heard 1 Feb
Nathan Lambert’s voice in public audio — every appearance, attributed to the second.
Trend
recordings per month · last 12 monthsRecordings per month over the last 12 months — 2 in all, peaking in Feb 2026 with 1.
Appearances
July and that was like a true vibe coded website and like I have a job make plots and stuff and then I came back to refresh it in the last few weeks and it's like Cloud Opus 4.5 versus whatever model at the time was like just crushed all the issues that it had from building in June and July and like
It might be a bigger model.
There's a lot of things that go into this, but there's still progress coming.
Yeah.
And I think that there's
And this sometimes comes off as like, almost like disillusioned from people, leadership, AI companies saying this, but they're like, it's held for 13 orders of magnitude of computers or something.
Like, why would it ever end?
So I think fundamentally it is pretty unlikely to stop.
It's just like, eventually we're not even going to be able to test the bigger scales because of all the problems that come with more compute.
I think that there's a lot of talk on how 2026 is a year when very large Blackwell compute clusters, like gigawatt scale facilities, hyperscalers are coming online.
And these were all contracts for power and data centers that were
signed and sought out in like 22 and 2023 so before or right after chat gpt so it took this two to three year lead time to build these bigger clusters to train the models well there's obviously immense interest in building even more data centers than that so that is like kind of the crux that people are saying it's like these new clusters are coming the labs are going to have more compute for training they're going to utilize this but it's not a given and it's like i i've seen so much progress that i expect it and i expect a little bit bigger models and i expect um
I would say it's more like we will see a $2,000 subscription this year.
We've seen $200 subscriptions.
It's like that could 10X again.
And these are the kinds of things that could come and they're all downstream of this like bit bigger model that offers just a little bit more cutting edge.
It ends up being all of the above.
So I think that all of your decisions when you're training a model come back to pre-training.
So if you're gonna scale RL on a model, you still need to decide on your architecture that enables this.
We were talking about like,
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