Gavin Uberti
speaker
403 appearances
1 recordings
1 series
first heard Jun 2026
last heard 30 Jun
Gavin Uberti’s voice in public audio — every appearance, attributed to the second.
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recordings per month · last 12 monthsRecordings per month over the last 12 months — 1 in all, peaking in Jun 2026 with 1.
Appearances
On an MOE model, only a small fraction of the parameters is being used for any given token at any given moment.
But...
If you have a large number of users on a piece of hardware, you can go kind of take that brain, cut it up into many different experts on many different servers, and run a huge amount of volume through it.
So you'll have a bunch of different pieces of traffic.
You'll have many of them using each part of the brain at any given point in time, and you'll also make the cost per thought, cost per token, way, way lower.
So I think you're going to end up with these giant scale distributed brains.
The form factor of this is a big data center with a bunch of chips, a huge amount of flops, and a huge amount of scale up interconnect.
You think we'll see a trillion-dollar individual data center?
Absolutely.
It is a matter of time.
It's like asking, will you see a billion-dollar fab or a $10 billion fab or a $100 billion fab?
It is inevitable that the economies of scale don't stop at, oh, $40 billion is the magic number for fabs.
No, the coffee wafer keeps going down as you keep spending more money.
And the same thing will be true of plants that go out and make steel or plants that go out and make tokens.
Frame it as thinking is really valuable, that every company in the world runs on thinking.
And we are entering this really unique moment in time where you have machines that can go think almost as good and as soon as good and as soon better than the best humans can.
Loading these machines is going to be a huge opportunity.
But more important than that, the way in which you go ahead and run this kind of thinking is going to be very, very different as demand goes higher and higher and higher and higher.
There's a unique moment right now to build a new set of solutions, a new roadmap for how do you run a future quadrillion parameter models for a billion people all at the same time on a gigantic scale up cluster.
And importantly, it's people who build systems that as they get more and more chips put together, get cheaper.
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