Eiso Kant

In the last six months, the world has still a huge supply shortage, and we can see this. If you're an early-stage startup, there's lots of paths for you. If you're a frontier AI company, you need to make decisions about who do you partner with, who do you work with, how much do you do yourself? I'm making decisions today that will impact us on compute in 12 or 18 months from now.

In the last six months, the world has still a huge supply shortage, and we can see this. If you're an early-stage startup, there's lots of paths for you. If you're a frontier AI company, you need to make decisions about who do you partner with, who do you work with, how much do you do yourself? I'm making decisions today that will impact us on compute in 12 or 18 months from now.

In the last six months, the world has still a huge supply shortage, and we can see this. If you're an early-stage startup, there's lots of paths for you. If you're a frontier AI company, you need to make decisions about who do you partner with, who do you work with, how much do you do yourself? I'm making decisions today that will impact us on compute in 12 or 18 months from now.

It's very rare to be at early stage companies where you have to make decisions right now that impact you on physical infrastructure a year and a year and a half later. Have we seen that demand supply imbalance change? The world has still far more demand for GPU and GPU-like compute than that supply that's available.

It's very rare to be at early stage companies where you have to make decisions right now that impact you on physical infrastructure a year and a year and a half later. Have we seen that demand supply imbalance change? The world has still far more demand for GPU and GPU-like compute than that supply that's available.

It's very rare to be at early stage companies where you have to make decisions right now that impact you on physical infrastructure a year and a year and a half later. Have we seen that demand supply imbalance change? The world has still far more demand for GPU and GPU-like compute than that supply that's available.

If you want to become a hyperscaler that is able to put data centers all over the world with GPUs in it that are going to allow you to serve these models to everyone, an infrastructure player, that's probably it. And that's probably just a starting point.

If you want to become a hyperscaler that is able to put data centers all over the world with GPUs in it that are going to allow you to serve these models to everyone, an infrastructure player, that's probably it. And that's probably just a starting point.

If you want to become a hyperscaler that is able to put data centers all over the world with GPUs in it that are going to allow you to serve these models to everyone, an infrastructure player, that's probably it. And that's probably just a starting point.

If we look at the massive CapEx investments that all of the cloud companies are doing, they're far above $100 billion when you look at them over the course of a couple of years.

If we look at the massive CapEx investments that all of the cloud companies are doing, they're far above $100 billion when you look at them over the course of a couple of years.

If we look at the massive CapEx investments that all of the cloud companies are doing, they're far above $100 billion when you look at them over the course of a couple of years.

Now, in the race towards more and more capable AI, closing that gap between human intelligence and machine intelligence, I think we are all pushing the frontier more and more possible, and we're seeing how that gap closes as we're scaling up our models and scaling up our data. I don't think anyone has a definite answer of how many dollars is it going to take from here to there.

Now, in the race towards more and more capable AI, closing that gap between human intelligence and machine intelligence, I think we are all pushing the frontier more and more possible, and we're seeing how that gap closes as we're scaling up our models and scaling up our data. I don't think anyone has a definite answer of how many dollars is it going to take from here to there.

Now, in the race towards more and more capable AI, closing that gap between human intelligence and machine intelligence, I think we are all pushing the frontier more and more possible, and we're seeing how that gap closes as we're scaling up our models and scaling up our data. I don't think anyone has a definite answer of how many dollars is it going to take from here to there.

If we knew that, we knew the outcomes. We're all on the frontier of what's possible right now.

If we knew that, we knew the outcomes. We're all on the frontier of what's possible right now.

If we knew that, we knew the outcomes. We're all on the frontier of what's possible right now.

i think we need to separate spend from getting the world's most possible capable ai by closing this gap getting to agi closing the gap between human intelligence and are they not the same thing they're not the same thing because if you look at these models as investments that we're making to get intelligence out on the other end that needs to be economically valuable to end users right with lots of layers and applications and things in between the model the creation of models is capex

i think we need to separate spend from getting the world's most possible capable ai by closing this gap getting to agi closing the gap between human intelligence and are they not the same thing they're not the same thing because if you look at these models as investments that we're making to get intelligence out on the other end that needs to be economically valuable to end users right with lots of layers and applications and things in between the model the creation of models is capex