Benchmark's Eric Vishria on the decade-long Cerebras bet: naivete, relentless grind, and a $23B SPV

Speaker 2: revenue 6.8% today, up 8.6% after hours. Congratulations to Intel. It

Speaker 1: says design matters more than ever. The Figma team continuing to execute Yeah. Incredibly well. Fantastic. Let's bring in

Speaker 2: Bring in Eric. To the show. Congratulations on the progress. Thank you so much for taking the time on such a busy day. Great to meet you.

Speaker 12: Great to meet you guys. Excited to be here.

Speaker 1: Long long overdue.

Speaker 2: Yeah. Crazy that this hasn't happened

Speaker 12: an opportunity Well, you guys like Ev, you know, so Oh, yeah. Have Ev on. You don't have to

Speaker 2: have He was a former colleague, but everyone is welcome here. But I would love to just hear the story from your perspective. We we we just heard it from obvious to you? Yeah.

Speaker 1: Was it the most obvious deal ever because I was we were talking with Andrew. Yeah. I was asking him for the story of those first couple rounds expecting him to be like, you know

Speaker 2: It was really hard.

Speaker 1: TBP would come out for for almost a decade. It was a slog. We kept getting we walked up and down San Hill Road. Got nosy. He's like, yeah, we got eight term sheets. So clearly it was a deal you had to win.

Speaker 2: Yeah. But take us through it.

Speaker 12: Well, you know what? The hilarious thing about it is in venture, it's very useful to be naive. And certainly, was so naive about how hard hardware actually is. Like, I just like I can't even I can't even describe to you guys how how naive I was and we were. You know, at the the the it was 2016, deep learning was clearly going to become a thing, which would obviously evolve and empower the AI that we have today. Mhmm. I was looking at all of these different applications. So I was looking at like deep learning for radiology and security and other things, and it was really hard to figure out where it was going to work, like which application was going to take off. And you guys have to remember, is 2016, right? The TPU hadn't been announced. The transformer paper hadn't come out yet. LLMs haven't hadn't been born yet and and obviously not ChatGPT or anything else. And so it's really early, but there was clearly something there.

Speaker 10: Mhmm.

Speaker 12: And when I first met Andrew, he came in and I was like, we hadn't we're not hardware investors typically. I think our last hardware investment before that one was Ambarella, which was ten years earlier. And he came in and he said, you know, was like the team slide, very impressive. And then, you know, the slide three was GPUs actually suck for deep learning. They just happen to be 100 times better than CPUs. And as soon as he said it, it's just like a light bulb went off. Like, of course, of course, like, why would a graphics processing unit be the right solution for deep learning? And then, of course, he proceeded to explain like why GPUs were so much better than CPUs for training and also what the like ideal ground up solution could look like. And they have their idea of the way for scale and everything else. And as soon as he said it, it's kind of like, oh, yes, that makes sense. And like, I should like, we don't know what application is going to work. We should invest in infrastructure. This is an amazing team and a really provocative idea. Fast forward, like that was 2016, 2016. You fast forward like six, seven years, and like we're still slogging it out and have raised so much money and have very little revenue. And it just hadn't all come together yet. And then, of course, over the last two years, inference is exploding. It turns out Cerebras switches from training to inference and really focusing on inference and making inference speed where speed matters, coding explodes where speed really matters. And so all these things kind of came together. And so a lot of luck, a lot of naivete on my part. But for the team, just relentless grind, never giving up, always taking feedback, but being persistent, being open minded about where the market was going. So, yeah, I'm I'm so so proud of them.

Speaker 2: Yeah. What was your role as an investor like over the journey of the company? Because obviously, Andrew and his core team, deep engineering bench, were you focused on how you position the company, the private markets, fundraising or management? Like, what were you focused on in terms of value add or just helping build the company alongside?

Speaker 12: I'm I'm really the algorithm specialist. Okay. I go in there and I do that. No. I'm just kidding. So I I I don't know anything.

Speaker 2: Oh. So I You're in fad. You're the one that made making the

Speaker 12: That's right. I was making

Speaker 2: it up. Clean up. Yeah.

Speaker 12: It there's you know, it it really changes a lot over the course of a company. Yeah. This is, I think, the the fourth company that I've worked with for more than ten years. Wow. And and so when you work on them a long time, the the companies evolve a lot. Right? You start out, it's just five people. It's just the five founders originally. So at different points in time, it's a lot of fundraising help. At points in time, it's like really helping build out the broader management team. And a lot of it is also just being someone for the founder to talk to. Know? There's there's being an entrepreneur is is very the highs are very high and the lows are very low. And and so someone you can talk to and be really open with that, like, helps moderate that. And I think that's a part of it. So it's just it's an evolving, you know, conciliatory kind of role, and I really love it. Actually, that's the part of the job that I love the most. And it's very it's rare and special to have these kinds of relationships. I've had a few of them. I'm very lucky to have a few of them where I just feel really like a lot of chemistry with the with the founder and and just feel like we have a really productive relationship.

Speaker 2: Where are you excited to invest over the next decade? Because, you know, it it feels like we're still in the semis. Boom. There's a lot of opportunity there. You could go deeper into that side of the business, but then there's so much software.

Speaker 1: I'm sure you've gotten pitches that look like the what what Yeah. Maybe would be the next gen and, you know Maybe like I already got my horse. Yeah. Well, yeah, that. But then, you know, talking to these teams that don't necessarily know what it'll actually take. Right? Know? Sure. Don't they don't really learn the hardware is hard lesson yet.

Speaker 12: Yeah. Totally. Totally. Well, you know, one of the funny thing and I ask myself this question all the time, obviously, is, this is a 20 for us, as early stage investors and looking for really big outcomes but willing to take big swings, you really do have to kind of look many years forward and try to see like what's going to ripen at the right time, right? So in 2016, you make an AI hardware investment. And Grok was, I think, 2017, for So like there were several contemporaries of them. Of course, Grock and Cerebras have ended up doing really well. And so you but you're trying to say like, okay, this fruit is going to ripen in like six years, right? And so there's kind of some mention of projection. Right now, I think I'm really excited and continue to be really excited about a lot of the AI applications. We're investors in Sierra and Ligora and a number of others that where, like, they're obviously booming, they're selling magic to their customers, and the companies are doing great. We also have these, like, infrastructure investments, like fireworks, for example, which is also riding this enormous inference demand. And then there are kind of things that are a bit more forward looking. We invested in Star Cloud. My partner, Chase, led our investment in Star Cloud, which space data centers. And we also we led the initial round in Sunday Robotics, which is a home robot. And so I think those things are going to take longer. Like they're not going to be massively scaling revenue like next year. Like that's not what they are. You So kind of have a combination of these different things which are but it's it's kind of trying to figure out when they ripen.

Speaker 2: Next time you come on, we gotta have you debate Delian because he came on and was debating Av and hardware versus software. But you got space, chips, you got everything Delian likes. Yeah. Doing well.

Speaker 12: It's nice to have a portfolio. And I think one of the beauties of Benchmark is each of the partners is attracted to different things and Yeah. Different types of founders. And so we you you put it together and it it works out really well.

Speaker 2: Yeah. Yeah. Makes sense.

Speaker 1: Walk us through fund seven and eight because there's chatter on the timeline as as those funds being some of the best in venture history. And although this is Cerebras' day, this is your first time on the show.

Speaker 2: Take your time.

Speaker 1: We do have a big gong here.

Speaker 12: Yeah. Well, I I you know, seven Fund seven has or had Uber, Snapchat, Elastic, Stitch Fix, WeWork. I mean, there were so many things. It was like it was such an embarrassment of riches. And I had nothing to do with that fund, just to be clear. Like I joined in 2014. That fund was already deployed, but and invested in but the team you know, that team at the time just did such an outstanding job with winner after winner. Discord is in there. I mean, it's like really like when you have you know, you guys look in venture, if you catch the trend right and obviously work hard and get lucky, but you have the sixth or seventh company in the portfolio delivering a multiple of the fund or something like that, like that you're in such rarefied air, and that's there's it's really special. So that's Fund VII. Fund VIII is a very enterprise. It's our 2014 vintage, I think. And it has it's a very enterprise y fund. And so we had Confluence, which returned a bunch and Amplitude has returned a bunch. And then we have Cerebras, obviously, which is big, but Chainalysis is in there and and several others. And so it's kind of interesting how these how they switch. I think that's actually more interesting to me, which is Fund VII was very consumer mobile, and Fund VIII is, like, very enterprise y, and they're, like, back to back, but they turn out to they both work. And so I think that tells you a little bit about what venture is and how we all have to be really open minded about what's happening and what's the right timing for these various ideas. And then fast forward in our 2022, I think, 2022 vintage has the first round of Sierra, the first round of Fireworks, the first round of Legora, Merkor. Reductor, Merkor. Yes, absolutely. LangChain. And so all those are in there. And so obviously, that's a totally different fund and has a different set of things, but also looks pretty interesting. So it it just it it evolves and it that's what's so hard and tough about this business is staying on your toes when you're in a very, very dynamic world.

Speaker 1: Yeah. Well, it's interesting. Something that, you know, this has been talked about on plenty of podcasts, but it's worth bringing up. You guys have stayed true to the strategy and you can count on the market changing and evolving and but a lot of funds are like having to deal with markets changing and evolving while having a fun strategy that is changing and evolving. And if you keep one of those things true, it seems at least from Benchmark's track record that it gives you some advantage and that like you're playing a very specific kind of game and not having to evolve your own game while dealing with changing technology trends and markets.

Speaker 12: Mhmm. You know, I've been at Benchmark twelve years and I've thought about this a lot. And, you know, you're watching your peers do all these different things and swimming and fees and all these like amazing things. And so you're like, wow, that's pretty that looks pretty cool. Like, you kind of like look at this stuff and but I'll tell you what I think it actually comes down to. It's what it actually comes down to is what do you love doing. And we're obviously in a very fortunate position, and I inherited an amazing platform. And so and very fortunate to have done that. And we're in this amazing position where you get to do what you really like doing. And at the end of the day, we really like partnering with early stage founders and working on these companies for a decade plus. And that's kind of what we like doing. So I think things have definitely evolved. The opportunity set is changing and evolving. And more recently, I mean, just in February, we raised an SPV, which we've never really done before, and to invest in Cerebras. And that was unusual, but it was you can also we've actually, a few years ago, we did public market investing when COVID first hit and then Nasdaq tanked. All of the early stage stuff just disappeared. We were like, wait a minute. These publics, there's interesting stuff in public, we started deploying a little bit in the public. So yes, we're really focused on the early stage and that's what we love doing. And then also, occasionally, like, we see these special opportunities and and we try to jump on them.

Speaker 2: Wow. Yeah. Well, thank you so much for coming on during a business day.

Speaker 11: Had to sneak

Speaker 1: in that the the SPV round of 23,000,000,000. So congratulations on on that investment. Fantastic. Another another little cheeky three x.

Speaker 2: I think you deserve a drink. Hopefully, you can find Andrew and cheers.

Speaker 12: Have some drinks tonight. Yeah.

Speaker 2: Have a great time.

Speaker 1: Great great to finally meet you and

Speaker 2: Yeah.

Speaker 1: Congrats to everyone.