Uber’s first head of data science just launched a new venture fund to back nascent AI startups – TechCrunch

Kevin Novak joined Uber as its 21st worker its seventh engineer in 2011, and by 2014, he was the corporate’s head of knowledge science. He transitioned out of the corporate in late 2017, after Travis Kalanick had been changed as CEO by Dara Khosrowshahi. However by then, he’d already begun spending weekends and evenings actively angel investing in what would in the end turn into a portfolio of greater than 50 startups (together with the fintech Pipe and the autonomous checkout firm Standard Cognition).

He additionally started advising each startups and enterprise corporations — together with Playground World, Costanoa Ventures, Renegade Companions and Knowledge Collective — and, realizing he wished to spend the remainder of his profession as an investor,  Novak determined this yr to launch his personal enterprise outfit in Menlo Park, Calif., Rackhouse Venture Capital. Certainly, Rackhouse simply closed its debut fund with $15 million, anchored by Uber’s first head of engineering, Curtis Chambers; Steve Gilula, a former chairman of Searchlight Footage, and the fund of funds Cendana Capital. (A whole lot of the VCs Novak is aware of are additionally buyers within the fund.)

We caught up with Novak late final week to speak out that new fund. We additionally talked about this tenure at Uber, the place, be warned, he performed a serious position in creating surge pricing (he prefers the time period “dynamic pricing.”) You possibly can hear that full dialogue or take a look at excerpts from it, edited calmly for size and readability, beneath.

TC: You had been planning to turn into a nuclear physicist. How did you wind up at Uber?

KN: As an undergrad, I used to be finding out physics, math and pc science, and once I received to grad faculty, I actually wished to show. However I additionally actually preferred programming and making use of physics ideas within the programming house, and the nuke division had the biggest allocation of supercomputer time, in order that ended up driving plenty of my analysis  — simply the chance to play on computer systems whereas doing physics. So [I] was finding out to turn into a nuclear physicist was funded very not directly by the analysis that ultimately turned the Higgs boson. Because the Higgs received found, it was superb for humanity and completely horrible for my analysis funds . . .

A buddy of mine heard what I used to be doing and form of knew my ability set and mentioned, like, ‘Hey, it is best to come take a look at this Uber cab firm that it’s like a limo firm with an app. There’s a really fascinating knowledge downside and a really fascinating math downside.’ So I ended up making use of [though I committed] the cardinal sin of startup purposes and wore a swimsuit and tie to my interview.

TC: You’re from Michigan. I additionally grew up within the Midwest so admire why you may suppose that individuals would put on a swimsuit to an interview.

KN: I received off the elevator and the buddy who’d inspired me to use was like, ‘What are you carrying?!’ However I received requested to affix nonetheless as a computational algorithms engineer — a title that predated the information science development — and I spent the following couple of years dwelling within the engineering and product world, constructing knowledge options and . . .issues like our ETA engine, mainly predicting how lengthy it will take an Uber to get to you. One in every of my very first initiatives was engaged on tolls and tunnels as a result of determining which tunnel an Uber went by and methods to construct time and distance was a standard failure level. So I spent, like, three days driving the Huge Dig in Boston out to Somerville and again to Logan with a bunch of telephones, amassing GPS knowledge.

I received to know plenty of very random details about Uber cities, however my large declare to fame was dynamic pricing. . . and it turned out to be a very profitable cornerstone for the technique of creating positive Ubers had been out there.

TC: How does that go over, once you inform folks that you simply invented surge pricing?

KN: It’s a really fast litmus take a look at to determine like folks’s underlying enthusiasm for behavioral econ and finance. The Wall Road crowd is like, ‘Oh my god, that’s so cool.’ After which lots of people are like, ‘Oh, thank you, yeah, thanks a lot, great, you purchase the following spherical of drinks’ sort of factor. . . [Laughs.]

However knowledge additionally turned the incubation house for lots of the early particular initiatives like Uber pool and plenty of the concepts round, okay, how would you construct a dispatching mannequin that allows totally different folks with pooled experience requests? How do you batch them collectively effectively in house and time in order that we are able to get the suitable match charge that [so this] mission is worthwhile? We did plenty of work on the speculation behind the hub-and-spoke Uber Eats supply fashions and pondering by how we apply our learnings about ride-share to meals. So I received the primary individual perspective on plenty of these merchandise when it was actually three folks scribbling on a notepad or riffing on a laptop computer over lunch, [and which] ultimately went on to turn into these large, nationwide companies.

TC: You had been engaged on Uber Freight for the final 9 months of your profession with Uber, so there with this business with Anthony Levandowski was blowing up.

KN: Yeah, it was it was very fascinating period for me as a result of greater than six years in, [I was already developing the] angle of ‘I’ve completed every little thing I wished to do.’ I joined a 20-person firm and, on the time, we had been closing in on 20,000 folks . . .and I sort of missed the small group dynamic and felt like I used to be hitting a pure stopping level. After which Uber’s 2017 occurred and and there was Anthony, there was Susan Fowler, and Travis has this horrific accident in his private life and his head is clearly not within the sport. However I didn’t need to be the man who was recognized for bailing within the worst quarter of the corporate’s historical past, so I ended up spending the following yr mainly conserving the band collectively and attempting to determine what I may do to maintain no matter small a part of the corporate I used to be working intact and motivated and empathetic and good in each sense of the phrase.

TC: You left on the finish of that yr and it appears you’ve been very busy since, together with, now, launching this new fund with the backing of outsiders. Why name it Rackhouse ? I see you used the model Jigsaw Enterprise Capital once you had been investing your individual cash.

KN: Yeah, even a yr in, I had fashioned an LLC, I used to be “marking” my portfolio to market, sending quarterly updates to myself and my accountant and my spouse. It was considered one of these workout routines that was a carryover from how I used to be coaching managers, in that I believe you develop most effectively and efficiently for those who can develop just a few expertise at a time. So I used to be attempting to determine what it will take to run my very own again workplace, even when it was simply shifting my cash from my checking account to my “investing account,” and writing my very own portfolio replace.

I used to be actually enthusiastic about the opportunity of launching my first externally dealing with fund with different folks’s cash beneath the Jigsaw banner, too, however there’s really a fund within the UK [named Jigsaw] and as I began to speak to LPs and was saying ‘Look, I need to do that knowledge fund and I would like it to be early stage,’ I’d get calls from them being like, ‘We simply noticed that Jigsaw did this Sequence D in Crowdstrike.’ I spotted I’d be competing with the opposite Jigsaw from a mindshare perspective, so figured earlier than issues go too large and loopy, I’d create my very own distinct model.

TC: Did you roll any of your angel-backed offers into the brand new fund? I see Rackhouse has 13 portfolio corporations.

KN: There are just a few that I’ve agreed to maneuver ahead and warehouse for the fund, and we’re simply going by the technicalities of doing that proper now.

TC: And the main target is on machine studying and AI.

KN: That’s proper, and I believe there are wonderful alternatives outdoors of the normal areas of trade focus that, to the extent that yow will discover like rigorous purposes of AI,  are additionally going to be considerably much less aggressive. [Deals] that don’t fall within the strike zone of practically as many [venture] corporations is the sport I need to be enjoying. I really feel like that that chance — no matter sector, no matter geography — biases towards area consultants.

TC: I’m wondering if that additionally explains the dimensions of your fund — your wanting to remain out of the strike zone of most enterprise corporations.

KN: I need to guarantee that I construct a fund that allows me to be an energetic participant within the earliest levels of corporations.

Matt Ocko and Zack Bogue [of Data Collective] are good mates of mine — they’re mentors, the truth is, and small LPs within the fund and talked with me about how they received began. However now they’ve a billion-plus [dollars] in belongings beneath administration, and he folks I [like to back] are two people who find themselves moonlighting and on the brink of make the leap and [firms the size of Data Collective] have mainly priced themselves out of the formation and pre-seed stage, and I like that stage. It’s one thing the place I’ve plenty of helpful expertise. I additionally suppose it’s the stage the place, for those who come from a spot of area experience, you don’t want 5 quarters of financials to get conviction.