Inspired with Alexa von Tobel
00:04:26 · Mikey Shulman, Alexa von Tobel
[00:04:26] S0: It's really it's really interesting. I always loved physics. I knew I loved it in in high school even. And I was trying to decide as an undergrad what I should do after. And it's like one of these, like, seems little at the time, but very serendipitous moments where there was a professor that I wanted to work for the summer after my junior year of college, and he said, I'm retiring. You can't really work for me. I'm gonna be closing down my lab. And then I went and I applied for an internship at Goldman Sachs. And then two months later, he said, you know, I'm actually gonna do one more year. Why don't you come work for me? And that was, like, this little thing that sent me down an entirely different career path where I was like, I really loved working for him, and I really loved the work, and it made me wanna do that. And then after that summer, said, okay. I'm gonna apply to grad school. Like, I I wanna do more of that. And I I suspect that if that hadn't happened, if I hadn't worked for him that summer, it would have been a very different path for me. And, yeah, you know, the rest is history. Actually, my PhD adviser is a former student of that undergrad advisor, and he told me just go work for your PhD advisor. He's the best student I ever had. [00:05:41] S1: That's amazing. You then went from... Instead of staying in academia, you jumped right into Kensho where you led machine learning for financial systems. And Kensho was really your first major step into applied AI. How'd you... How how how'd that happen? And also tell us what Kensho was.
00:05:41 · Alexa von Tobel, Mikey Shulman
[00:05:41] S1: That's amazing. You then went from... Instead of staying in academia, you jumped right into Kensho where you led machine learning for financial systems. And Kensho was really your first major step into applied AI. How'd you... How how how'd that happen? And also tell us what Kensho was. [00:06:00] S0: Yeah. You know, it's funny. So Kensho is and was an AI company in financial services. And I think very much the same thing. I didn't have a master plan at the end of my PhD. I met the Kensho people. The team was probably 12 when I joined, and I met all 12, and I liked all 12. And I said, I like working with you guys. Will you make me a job offer? Or I interviewed, and I actually didn't do very well in the interview, but they were kind enough to make me a job offer. And, you know, it's funny in a in a in a small company, you know, with 12 people, there's, like, no access controls on the on the applicant tracking system. And so, actually, after I joined, somebody just showed me what everyone wrote about me, and it wasn't it wasn't terribly kind. I actually did not do very well in those interviews, and it was very nice that they that they took a they took a flyer on me. [00:06:52] S1: You're an easy guy to take a flyer on, by the way.
00:06:52 · Alexa von Tobel, Mikey Shulman
[00:06:52] S1: You're an easy guy to take a flyer on, by the way. [00:06:55] S0: I'm not. I'm... You know, that's very kind of you to say. I I think, like, I... Yeah. And then I was hired as a software engineer, and very quickly, the the machine learning opportunities came along to the company. And this is back in 2014 and 2015 when AI was, like, a much less developed field. And I guess the the guy with the PhD in physics is what passes for machine learning engineer back then. And so I naturally gravitated toward those things. And I think I very quickly realized, a, I like it, but b, actually, where my... I think where my real talents lay were less in the day to day work, which I was, like, okay at, but more in building the team and identifying people who are excellent at it. And so I was honestly given a very long leash by Daniel, the founder, to go and build that team as I wanted and took full advantage of that, and kind of the rest is history. And, you know, I enjoyed every minute of it. [00:07:51] S1: Tell us a little bit about the outcome of Kensho and what happened, because it was a really successful outcome for you guys.
00:07:51 · Alexa von Tobel, Mikey Shulman
[00:07:51] S1: Tell us a little bit about the outcome of Kensho and what happened, because it was a really successful outcome for you guys. [00:07:57] S0: Yeah. It was... Look. It was it was a lot of fun, and I will say we're... I'm currently calling in from our headquarters in Cambridge, Massachusetts, which is the same office that Kensho's first office was, and that... That's somewhat by design. We were acquired in 2018 by S and P Global, a huge financial services company, after we were working together with S and P on various projects and realizing that there was a ton of really important work to do together around, at a very high level, bringing a lot more structure to the crazy world of unstructured documents in financial services. And so, you know, maybe just as an example, you read Nvidia just beat consensus for earnings, and, you know, maybe you never think what does that really mean. What does that consensus really mean? That's like people going and reading all of the broker research from 10 different banks and pulling out numbers from hundreds of pages of documents and averaging those numbers, and how messy of a process that is, and how much more structure can be brought to bear if you use the right set of set of tools. And so we kind of developed those with S and P first at arm's length, and then after we were acquired, not at arm's length. And I think ultimately ended up bringing a lot of speed and scale to that business. And so I think a successful outcome for both sides, which I'm told is, like, somewhat rare in the game of acquisitions.
00:09:22 · Alexa von Tobel
[00:09:22] S1: It is, by the way, having also built the company and sold it to Northwestern Mutual. I think for an acquisition years later for people to all feel good about it is is rare, and can... Congrats on being in the 1% of founders selling a company that goes really well. I think that really speaks to who you are. But before we go into Suno, alongside your work at Kensho, you were also a lecturer at MIT Sloan since 2018 teaching machine learning. In just a nugget, give us a sense of what you love to teach about machine learning. Make us all smarter. What sort of was your core concept as a as a professor?
00:10:02 · Mikey Shulman
[00:10:02] S0: Yeah. Totally bananas that they let me do this. You know? And So the course that I teach is a very applied course. It's in the business school, and it is for students who are largely going into quantitative trading. So it's meant to be very applied, it's meant to be very hands on. And the world of machine learning moves so quickly, but it's so particularly for natural language processing, as more and more documents get put out in the world, there is more and more edge to be had by understanding those. And there are tons and tons of classes in quantitative modeling, in econometrics, and just not enough very applied coursework in the nexus of machine learning and finance. And so with a professor at Sloan, of realized that this was like a gap and and made a very applied course. And I've actually, unfortunately, in the last year stopped doing it for lack of time, which actually bums me out greatly. But... Yeah. I I mean, I I loved every minute of it. Know, I'll tell you something personal. In 2020, the course went all remote, obviously. And it's like fine, I hate teaching over Zoom. And I remember in 2021, the first lecture back, and it's like fairly crazy draconian rules, you know, like everybody is like, we're in a big auditorium, everybody's six feet apart, everybody's wearing a mask. It's, like, not... And I remember at the end of that first class, I'm, like, so excited to be back in person. It's four to 7PM, so it's, like, an evening class. It's three straight hours of lecturing, and I come out of that class, and I'm like so energized after having been back in person with everybody after a year on Zoom. I couldn't fall asleep that night. I fell asleep at like three in the morning, and it's just like it's like... It's just an amazing data point for myself on, like, how fun it is to be around people when everybody is, like, into what you're doing.