Lan Xuezhao has spent the last few months pulling together $136 million for her new machine intelligence-focused venture capital fund, Basis Set Ventures. I met Xuezhao for tea on a park bench in Potrero Hill earlier this week to chat about her strategy for the fund.
I spend a good portion of my time meeting with investors, but if you don’t know a lot about the scene, Potrero Hill is not a place you go to meet VCs. Hot spots for meetings generally range from opulent coffee shops in San Francisco to opulent offices on Sand Hill Road. So a park bench in a fairly residential, low-profile neighborhood stands out.
But even more than that, Xuezhao has a surprisingly laid-back demeanor and an apparent academic appreciation for technology. With a PhD in quantitative psychology, the former head of mergers and acquisitions for Dropbox can do something that most other investors cannot — relate to the incredibly talented founders of highly technical startups.
Breaking rank with increasingly flashy, services-focused AI studios like Yoshua Bengio’s Element AI, Xuezhao wants Basis Set to be the anti-VC. Everything blindly promised by AI-focused VCs gets a layer of realism. Data sets: What data, why and does it actually exist anywhere? Technical mentors: How about I just sit down and we both start by being honest with each other — then if we can’t come up with it, let’s text someone who can.
We spent about an hour talking about the state of AI startups and how Basis Set Ventures aims to capture the windfall from the burgeoning space. I’ve edited all remarks for brevity.
TechCrunch: Why did you feel $136 million was the right number to start with?
Lan Xuezhao: The number is more strategic than anything else. I feel like there’s a gap between Series A and smaller seed deals. There are a lot of smaller seed funds and it’s hard to compete with them because there are so many.
At Series A there are a lot of bigger names who do a very good job with those. But in-between, there’s a sweet spot for checks ranging in size between one and three million dollars. And not that many funds are able to do that.
TC: Can an AI focus still be a differentiator in a market that now seems saturated with AI-focused funds? What do you think is the real value a VC can add to a machine intelligence startup?
LX: Given my experience, I think go to market is the most important because algorithms are less defensible. Being able to help startups close larger clients is something I spend a lot of time on. Startups value me as a thought partner. You don’t have to be very formal with me…