Roman Chernin
speaker
1,558 appearances
3 recordings
3 series
first heard May 2026
last heard 7 Jun
Roman Chernin’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 — 3 in all, peaking in Jun 2026 with 2.
Appearances
And the economics of the products of our customers, if they work, they can grow, and then we can grow with them.
It's not like just supply demand situation and then absolutely elastic prices.
They're elastic for some extent, but we also want to be meaningful and we want to be thoughtful kind of what our customers need.
And by the way, it's not only GPU hour cost.
It's all the optimizations you do, all the real, we call it TCO, total cost of ownership that you like.
And this is partially why we build the software platform.
And I'm sorry, come back to product again and again.
You want to speak about capacity, but people too much obsessed about capacity, like capacity is important, too much obsessed about the nominal price of capacity.
You can price GPU $3, $4, and $5.
Depending on the use case and depending on the quality of the platform, it can create completely different outcomes for the customer in the real cost.
How long it works, like what is the effective uninterrupted time that you can run there?
If you talk about inference, how much tokens you can extract, we see all these optimizations that happening that changes the price of the tokens in order of magnitude.
So people so much speak about the cost of particular GPU, but
If you do the right thing with the model, you can change the price in the times.
And this all should work together as a system, not just as a... Again, if you speak about raw infrastructure, then you can manage only the price.
But if you build the platform and if you provide the high level of the service to the customer, then you can extract much more economics, not only from the infrastructure cost structure, right?
What customer needs.
know you speak with a lot of product founders and this is the same what customer needs at the end of the day how customers evolve in their needs where is the demand moving so it's like we see all this transition from training to inference we see transition from
just using the models to building agents.
And we see the transition from mostly AI labs consuming AI compute to enterprises coming in the game.
Showing 181–200 of 1,558 · page 10 of 78
← Previous
Next →