Eric Vishria
speaker
163 appearances
1 recordings
1 series
first heard Sep 2024
last heard Sep 2024
Eric Vishria’s voice in public audio — every appearance, attributed to the second.
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I was talking to a team that had gone like a four-person team, zero to four million in four months. Amazing. Like just amazing kind of revenue trajectory. But I put like almost no value on that, like going zero to four million. And I think one of their things was like, well, like, why are you giving me credit for that? And I was like, well...
The thing that I take away from that is that whatever you're selling, and this is true for a lot of these AI companies, customers want to buy. Customers want to buy it. And I think part of it is just like the products to a lot of these customers, the products are magic. They feel like magic to the customers. So the customer and the ROI on those products is just tremendous.
And they know that they have to experiment with it or they have to try it or they want to try it because they see so much potential value in it and they feel it. So the demand side is very clear and it's just pulling. And I think that's probably the biggest thing that we can take away with these early stage companies and their traction, which is like, okay, there is demand.
And then you have to kind of evaluate and figure out like, okay, do we think that whatever the product the company is building, the entrepreneur, I mean, go back to the same things, like has sustainable advantage over time. And that's a really, you know, that's a really difficult judgment right now. But I think it's like one of these things that we have to do. But I totally agree with you.
The quickness of the scale is unlike, it's like three, four, five years of what SaaS company, like your traditional SaaS companies were doing. We're seeing in under a year. And we have a whole portfolio of companies that are like this. It's amazing.
I don't worry about the $600 billion thing.
No, I don't. I go back to my software engineer example. Forget about AGI for a second. The prize is so big even without AGI. The prize is so big. And so, yeah, the revenue will materialize. There's a lot to figure out. I was We had a dinner guest yesterday. We do these dinners as a partnership with the guests on Mondays.
And one of the kind of conversations around it was we were kind of unpacking is like if you think about search. So search, we started first seeing the search, the first search engines call it 1995 is when you started to see the first search engines. And then Google Series A was 1998. I believe. And immediately was a better search engine and a better trap and everything else.
What I think is lost in time is Google didn't figure out the monetization. Of course, they did it through an acquisition. They didn't actually figure it out themselves. They didn't figure out the monetization of search until 2001, I think, or late 2000. And so we had... Five or six years of these search engines, which anybody at that time was using them every day.
There were crappy display ads all over them and all kinds of stuff that was just totally like people. I think, sure, there were paid search engines. People tried to do all kinds of things to figure out the monetization model.
And so I don't know that we figured out the monetization model, but I think what we can say very clearly, customers perceive a lot of these products, not all of them, but a lot of these products as magic, which they are basically magic. And they want them. There's a bunch of monetization that needs to be figured out, but I kind of don't worry about it. It's like, we will figure it out.
That's just the delay. And so I feel like And the reason the parallel to search is interesting is because it's like, hey, there was a new technology that was really powerful, web search. And it took a while to figure out monetization. And we have a new technology, alums, that are really, really powerful. And we've got to figure out monetization on them.
And it's not going to be a $20 a month subscription. That's not the right way. And it's not going to be just bundled API. There's going to be much, much more sophistication and interesting models than that.
Foundational models are the fastest depreciating asset in human history, I think has turned out to be largely true.
I think that's a good question that is really interesting because if you think about OpenAI and Anthropic and Meta and Google, and then there's a whole bunch of others coming, XAI and Mistral and so forth, SSI now. I think the foundational model war benefits us all in a way.
It's really, really good for consumers and people around it because it's just like they're pushing the state of the art so much. In terms of value accrual, for Benchmark, we have no foundational model investments. And then two, we have a set of infrastructure investments available. which I think are really interesting.
So we have Cerebrus, which is a semiconductor and systems company for AI that we invested in and led their series A in 2016. So we've been working on it for eight years. We have companies like Fireworks, which are an inference service and others kind of off that infrastructure software layer.
And I think those like, you know, again, they're growing very, very quickly, like astoundingly quickly and doing really cool things. But
at the same time you kind of have to ask like okay what are the foundational models going to do and how are they going to move up the stack and so this is again where i go back to you need great entrepreneurs who are like constantly updating their mental models and re-navigating and um do you not think we just see all the foundation model companies just get acquired by the big players we've seen character inflection adapt i don't think all the foundational model companies will be acquired by the big players
Well, I think this is a question, right? And they're going to do it. But I think there's a set of people who certainly believe in the size of the prize. And so they continue to be able to raise really tremendous amounts of capital to train bigger and bigger models.
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