All-In with Chamath, Jason, Sacks & Friedberg
Sep 21, 2026 · 23 min · 10 segments
(0:00) Welcome Naveen Rao (4:45) Is energy really the problem? The cost of a token, power contracts & the gap to close (10:24) Cutting out the middleman: abstractions, dynamical systems & a new kind…
And now I want to tell you about Unconventional AI, which is rethinking the foundations of how a computer works.
So the-- we're going back to first principles here to really try to build a new machine.
We wanna rethink that for the singular purpose of making something very power efficient.
And the goal has been within, it was initially within five years to get to a thousand X power efficiency.
I've actually revised this to three and a half years because things have gone faster than we anticipated.
We've actually solved very deep scientific problems quicker because of AI, interestingly enough.
These are people with like math PhDs and, um, you know, theoretical neuroscience, that kind of thing.
They come up with, you know, concepts that we think would, uh, effectively give us more power efficiency from the perspective of moving less information around.
And we then translate that into models, uh, that do real things, trained on real data and evaluated against real criteria.
So these are people who architect a physical circuit, um, actually design those circuits, uh, model them and see if it actually works.
Um, then eventually we have to build a system and, and a board and all that kind of stuff and build a product.
And now I want to tell you about Unconventional AI, which is rethinking the foundations of how a computer works.
So the-- we're going back to first principles here to really try to build a new machine.
We wanna rethink that for the singular purpose of making something very power efficient.
And the goal has been within, it was initially within five years to get to a thousand X power efficiency.
I've actually revised this to three and a half years because things have gone faster than we anticipated.
We've actually solved very deep scientific problems quicker because of AI, interestingly enough.
These are people with like math PhDs and, um, you know, theoretical neuroscience, that kind of thing.
They come up with, you know, concepts that we think would, uh, effectively give us more power efficiency from the perspective of moving less information around.
And we then translate that into models, uh, that do real things, trained on real data and evaluated against real criteria.
So these are people who architect a physical circuit, um, actually design those circuits, uh, model them and see if it actually works.
Um, then eventually we have to build a system and, and a board and all that kind of stuff and build a product.
The rest of this transcript — segmented and speaker-labeled, so you land on the exact moment something was said
Search every transcript — by keyword, by phrase, or by meaning, across every show Radar indexes
Trends — what is surging across podcasts, measured against its own baseline
Alerts — when a name you follow appears in a newly indexed episode
No account is needed to search Radar.