The Exchanges

Q and, you know, just kind of cementing New York as a figure in the tech world. There's always a debate. We love the debate. It's so much fun. But, um, so, you know, like, NYC is known for fintech and health tech, but I'd love for you to just break down the NYC AI angle and bring us all up to speed. What is the state of the market there?

A Well, I'm still hoping to get you back in New York, Molly. So I am optimistic that maybe the West Coast has not went out on you, but, uh, maybe, you know, after this podcast, you'll be like, you know what? Grace convinced me. I'm packing up my bags, uh, back to New York City. But, um, I really think New York is poised to be the next hub for AI. Um, and I, I think it's really simple. It's because the demand is here and the talent is here. Um, A few, like, stats, which, you know, folks may not know, right? 44 of Fortune 500 companies are headquartered here. Um, it is a center of major industries, like you mentioned, not just, you know, financial services, but also media, uh, fashion, et cetera, healthcare. Um, there's also a lot of really good research talent here. So NYU Silver Lab, that's like the top AI lab that feeds a ton of folks to Meta. It's led by Yann LeCun, who is Meta's chief scientist. The top labs from Columbia, they have excellent machine learning and biolab. Cornell Tech, which now is a massive campus in New York, which is affiliated with several Luxe portfolio companies too. Princeton, they have a great NLP Institute with Dante Chen and Karthik Narasimhan. Um, as well as just great international talent, startups moving to the US, whether it's from Europe or Israel, um, new grads, number one choice for new grads to live because they want to live here. Um, and so l…

AI assessment note: “I really think New York is poised to be the next hub for AI.”

Q Are there any particular companies or projects you're watching?

A Yeah. Um, a few in our Lux portfolio are crushing it, and I would plug four. Um, so I think like factory AI in the coding space is doing excellent. Maton is wonderful. Um, Maven AGI in the customer support space in Boston and New York, crushing it. And they have a really great underlying tech team. Both of them do have really great underlying tech teams, really understand the user workflow, pricing to value for their customers, and then are thinking about how do you actually keep things flowing, um, and automated for the customer. So it's a true seamless and autonomous resolution, uh, for, for those end users. Um, I'm also really excited about AI as it pertains to, like, the sciences and, like, areas where you've still seen very little penetration. So we're investors in evolutionary scale. They're a really cool company at the intersection of AI and biology. They actually spun out of Meta. Um, Alex Reeves used to run, kind of, the bio AI team there. He offered a paper card ESM Fold. To spare you the details, it's kind of like an open AI for bio. But there's going to be a huge potential to tap into big data sources, take a lot of key expertise in the sciences, whether it's physics, whether it's chemistry, whether it's material science, and then turn that with a great understanding of that workflow and with this data into really transformative outcomes. And so I think the impact o…

AI assessment note: “a few in our Lux portfolio are crushing it, and I would plug four.”

Q Right. And where have you seen the multiples and by valuations go? Have they normalized at all or are they still up in the hundred axes?

A I think AI is the industry right now that is receiving a premium. On pricing, um, across our whole portfolio. Um, and so if you're an AI portfolio company, uh, you're going to get a better premium. That could change, but we're still seeing, you know, high valuations and high multiples, um, hundred X range for companies that are earlier in revenue. That's not consistent actually across our portfolio because we have a lot of really, really awesome companies where we've seen those high multiples. Um, we've also seen though incredible growth. An incredible gathering of teams, right? And so I think what you're seeing right now from the investor perspective is, wow, AI is so transformative. Wow. This company is growing users, metrics, engagements, product shipment, revenue so quickly. Wow. I see the future is where the future is going. I'm going to give them forward credit for that because I think this could be super disruptive and create a lot of market value. So that's the framing I think people are doing. I think, of course, there's a lot of Questions of how people will get there. And I think at any tech hype cycle or even tech, you know, inflection point, there's always going to be a lot of hype. And so I think you will continue to see a little bit of this readjustment where companies who don't kind of hit those high valuation expectations and that high valuation excitement is ki…

AI assessment note: “we're still seeing, you know, high valuations and high multiples, um, hundred X range”

Q Yeah. You've had an amazing career thus far. Uh, you've worked at Canvas and since then you've made some pretty incredible investments into companies like Runway, Lang Chang, Sakana AI, Together Reflex. Could you just share more on your investment strategy and how you got into this category of computational sciences?

A Totally. Um, and thanks again for having me on. I've also been very impressed by everything that Sorcery has accomplished and honored to be one of your guests. It really does feel like we're coming full circle. And actually, I mean, I think you've followed my career for a while in some ways, so you kind of understand how the computational sciences all got started. But, um, how I got into it was really goes back to when I worked at Handshake. Uh, Handshake is kind of like a LinkedIn for college students. I actually worked there as part of this thing called the Mayfield Fellowship Program, which we did at Stanford, and that's like a work study program where you get to actually work at an early stage startup. Um, and when I worked at Handshake, we were a pretty small team, but we had a really sophisticated data and infrastructure stack. We were dealing with a lot of sensitive student data, helping curate that, right, on these profiles that were private, and then in turn working with them to get, you know, both career centers and also Kind of these enterprises on board to, for example, recruit a Stanford student, uh, to take your pick of, of major corporation. Um, and so I learned a ton there of, oh, machine learning is cool, but there's all these other systems and things that have to work, like an API, or like data reliability, or like a data warehouse. I learned what that was, ri…

AI assessment note: “how I got into it was really goes back to when I worked at Handshake”

Q to frame this question out a little bit more, like let's go through your sourcing strategy. Maybe how did you find this company? How did you find the other ones? But it's one particular company that I'm curious about because, you know, it's not NYC AI. It's Japan. So you invested into Sakana. Like, how did you find this company, and what kind of got you so excited about it?

A So the first thing I will say is we were not actually looking to have a Japanese investment, um, as much as there's a really cool full circle story on Sakana, because I actually lived for part of my childhood in Tokyo, Japan, and so it's been really special to now be going back there for, for board meetings. Um, the one thing I will say though, which does relate to New York, as I think Sakana is great proof, as is hugging face in our portfolio as well, that great talent is everywhere, And major metros are particularly great ways to attract awesome pockets of talent. And so I would expect to continue to see particularly great AI, but also just great engineering teams and talent in every great major metro, right? We've seen New York developing, as we'll talk about probably later. Obviously San Francisco has been great consistently. I think you're gonna, you've seen a lot of great stuff in London with the DeepMind team that kind of set foot and established there. Paris, between Mistral, Qtai, hugging face, large great engineering presences, and now Sakana in many ways is kind of like the deep mind for Japan. And so that's really exciting and cool. And it's a hundred million people. It's a huge economy, uh, where there's a lot of reasons why there could be a sovereign AI winner here. But to answer your question, um, we found Sakana a few different ways. Uh, the, the direct introduc…

AI assessment note: “the direct introduction came from another entrepreneur in the Lux portfolio”

Q Um, secondary question, but I just have to ask Grace. Hugging face. How do they make money? What is their business model?

A Hugging face is an incredible company. Uh, for those who are not familiar with it, I think most people probably are at this point. It's like a GitHub for machine learning, right? And so the most powerful thing that they have and they will continue to have and what really predicated our original investment was this incredible community. Their GitHub repo that took Advantage really of the key moment of the transformer paper unlock, productizing that, and then kind of becoming in many ways like the, the toll booth of, of AI in some way. And so that kind of relates a little bit to the business model. Um, they, they were monetized in a few ways. They have kind of like a freemium model and that's like, you know, live on their website where you could get a pro account. So basically it's just like access to the public hub, but with a lot of, Extra nice things. So things like higher rate limits or, you know, extra access controls or things like that. So for a power user, it's a small fee to pay for a lot of value of accessing and working with a lot of these open source models in a sandbox. Um, they have rev share partnerships and they have enterprise partnerships. Uh, but the company is doing awesome. Um, and I think is probably monetizing in an unconventional way, but in a way that's doing really well. Um, and I've been super impressed by what they've done.

AI assessment note: “They have kind of like a freemium model... rev share partnerships and they have enterprise partnerships.”