Why Cerebras CEO Andrew Feldman Built The World's Largest Computer Chip

SPEAKER_2 (0:02)

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Joe Weisenthal (0:18)

Hello, and welcome to another episode of the Odd Lots Podcast. I'm Joe Weisenthal.

Tracy Alloway (0:23)

And I'm Tracy Alloway.

Joe Weisenthal (0:25)

Tracy, I have to say, unfortunately, I don't have AI psychosis. I'm certain of that.

Tracy Alloway (0:30)

Debatable.

Joe Weisenthal (0:32)

I'm pretty sure I don't have AI psychosis. I do have to say, unfortunately, like the amount of time now where it feels like AI-related questions, and there's many of them, are sort of like swallowing up the other thoughts that I have in my head, whether it's questions about which model is best and why, and what are the economics of inference, and how much training is pre-training versus post-training for each model. It's just sort of like this blob that's growing, that's taking up more and more of my thoughts.

Tracy Alloway (1:07)

What is your definition of AI psychosis? Because one would argue that maybe thinking about AI literally all the time would be a form of psychosis.

Joe Weisenthal (1:16)

Let's just say, I'm not the type who thinks that I don't think that the AI is a friend, for one thing. I'm not in love with the AI models. I don't think that in collaboration with ChatGPT that I'm stumbling on unified theory of physics and things like that.

Tracy Alloway (1:34)

But you do spend a lot of time inputting instructions, pressing the button and seeing what comes out.

Joe Weisenthal (1:40)

And seeing what comes out. I'm just saying, I think I'm aware that I'm talking to a machine and that we're not establishing any great breakthroughs of which we are collaborators and partners and friends.

Tracy Alloway (1:51)

Recognizing you have a problem is the first step towards healing, Joe. Seriously, though, there's a good reason to think about AI more and more, which is that a huge chunk of not just the market, but the real economy is now revolving around AI, right?

Joe Weisenthal (2:05)

Totally. So anyway, again, within the AI conversation, there are a lot of subcategories. One of the subcategories happens to be another Odd Lots favorite topic, which is chips. Of course, chips are used in multiple different ways. Chips are used in different parts of the AI supply chain, different types of chips of different roles. And so we have to learn more.

Tracy Alloway (2:25)

We have to learn more. And I have to say, I'm particularly interested in the company we're about to speak to, partly because the two things I know about them are, number one, they just had a huge IPO, right? Raising something like $5.5 billion at kind of insane multiple. I can't even do a price to earnings multiple because they're not profitable yet. But I think just on a sales basis, it was like 67 times forward earnings, which is pretty juicy, pretty hot. And the second thing I know about the company is they make giant wafers, which is just a fun image to have in your head.

Joe Weisenthal (3:02)

That's right. So if you were thinking it's like, okay, there is a hot entrant in this space. What is their differentiator? Well, one fact about them is their chips are just enormous about the size of the dinner plate. One might think you're reading an Onion article, but in fact, it's real and apparently it actually has some real technical advantages.

Tracy Alloway (3:22)

So and it's different to what everyone else is doing. So everyone else is, I guess, doing the sort of like modular networking thing where you get together a bunch of chips, you connect them together and that's how you get more compute, more memory, more power basically. But this company has done something different in the form of the giant wafer.

Joe Weisenthal (3:39)

The giant wafer and if you figure that to get maximum performance, you sort of want to lessen the distance between things, then put it all on one wafer. Anyway, we're going to learn a lot more. I'm very excited to say about giant wafer and more. I'm very excited to say we do have the founder and CEO of Cerebras on the podcast, Andrew Feldman, truly the perfect guest. Andrew, thank you so much for coming on the podcast on the week of your IPO.

Andrew Feldman (4:05)

Well, thank you so much for having me. What a pleasure.

Joe Weisenthal (4:07)

Absolutely. Why don't you just start us off the big giant chip? They're apparently real. They're as big as a dinner plate. What is the technical reason why this actually makes sense as a superior form of architecture for at least some aspect of AI?

Andrew Feldman (4:25)