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George Sivulka

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2025-01-22
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2025-01-22
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  1. I think that if $100 trillion of economic value will be created by AI and Agentic applications, that there will be so much room and so much opportunity for a ton of different players. I don't think that when Excel came out and then Mark released Salesforce and then people created TurboThese unravelings of Excel actually were produced later that that made Excel any less valuable. I actually think it made Excel more valuable. I view Hebia as this platform as something that will actually get better the more people get inspired by it and build increasingly vertical applications.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  2. There's all these stories, and you have like Klarna that's positioning for investors that they're firing half their staff, and no one really wants. And I think a lot I think it's BS. Yeah. There might be some reality to it, but I think that it's an amazing marketing story. And so anytime that I ever hear something that's put out as a marketing story, I almost negate it in my head to actually think about what the implications are. When you're saying something and screaming it from the rooftops that almost always means that internally you're freaking out about something, I look at that really loud behavior and I think that behavior itself really negates the content. That's maybe my positioning on this sort of stuff.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  3. The cognitive tasks that are lower in cognition, like more back office kind of middle office, maybe even some of the more junior front office tasks, I think we'll start to move into, okay, how can we manage AI juniors rather than actually do this ourselves by hand? But I don't think that just as Excel didn't end up taking away jobs from people, it just changed people to having to learn Excel, the exact same thing will happen with AI.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  4. Think that it will change the way that people do work, but I genuinely believe that it'll actually increase the AUM of the firms that use it. I think it will actually drive more employment. I think there will be some jobs that change. Hey, there's no more bookkeepers that do tabulations in spreadsheets on two sheets of paper

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  5. Premium to market. And I'm actually using more deals than you've ever seen because I know your name is on this many IC memos. And that type of structured thinking or that type of additional information that you can now give juniors in their career actually think makes better investors. I don't think that takes away.

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  6. What I mean by that is Yeah, I'm less worried about that. I think ultimately one of the best things about being, you know, having the years of experience is actually having the depth of knowledge about investing. So for example, if I'm a junior trying to price an asset, I haven't seen that many other companies that look like this company. And so I might say, hey, I think it should be priced at X, Y, or Z. And then someone in the IC meeting will be like, hey, no, I've seen 20 other companies in my 40 years of career that look exactly like this. And they all went nowhere. And I'm leaning on my prior experience. With Heavia, now juniors who are really smart themselves can say, okay, you might have remembered 20 deals, but I'm looking through every deal in our company's history in a giant matrix that anyone has ever seen. And I actually can tell you quantifiably that when a company is performing here, it's 90th percentile across all this investing criteria. We should actually pay 98%.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  7. He's my neighb It's a good point if you're cutting cost, which I think Daniel and UiPath are one of the best examples of using AI to make companies more efficient. Like if you look at finance and how fast Excel went to 90% market penetration in finance, 1985 to 1986, literally.

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  8. I ultimately genuinely believe that more than 50% of the GDP will be contributed by what you can call a gentic applications in the next few decades. I actually think it'll happen faster than the next few decades.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  9. I ultimately think that it will be a mix of all three. History doesn't repeat itself, but it often rhymes 60 years ago or even longer. foundational unit of compute, i.e. doing a calculation on a computer was effectively introduced to the enterprise. And there were plenty of people that were tallying things or bookkeeping in actual books, and their jobs changed. And there were apps for bookkeeping, and then there were platforms like Excel that let people build better apps for bookkeeping. And then Excel was unraveled again into better apps for bookkeeping. And I think that there's opportunity not only in verticals, but there's also opportunity in the entire industry in terms of building platforms, in terms of building corporatives, in terms of even building new types of quote-unquote agent employees. And I think that that opportunity is the exact same size. If there was a hundred trillion dollars of value that was created in the stock market from the introduction of the computer or the fundamental unit of compute, I actually think $100 trillion of value.

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  10. At the orchestration layer. And we think that an AGI system would prefer to use Heavy A matrix to diligence a company or to look through thousands of documents versus to read them all by hand in a really long context window.

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  11. I actually don't agree with that at all. I think he's completely wrong. I think it depends on how you define business apps, but I actually think that if the new business apps are platforms, you'll actually start to see those platforms really take hold. Like Heavy is a platform. It lets you build whatever agent that you'd like. And so here's a bit of a mindfuck. When building Hebia or when building all of these foundational primitives for how people use AI over the last four and a half years, Hebbia has always asked ourselves, what are the apps that AGI would want to use? Or what are the apps that agents would want to use themselves? i.e. what are the tools, because these AI applications are really good at using tools that we could build that would assist LLMs or these really smart foundation models, whatever they are in the future, to get to an answer more quickly. It's quite interesting, you know, heavy a matrix orchestrates lots of smaller LLM calls. It's actually scaling at inference, i.e. it's running massive amounts of compute.

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  12. I think it's incredibly clear. Yeah. And I think that we very much are capturing the agent, the high-level ambiguous decision-making and trying to trace it all the way down back to individual citations or individual characters that led the model to that decision.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  13. I actually am not a big believer in RPA. I think RPA is almost not an AI application in the new sense of AI. It's like AI in the old 10 years ago sense of AI where RPA is effectively very simple computation. But some of the things that people are asking Hebia are over 800 page credit agreements or 230 page SIMs, confidential information memorandums, this marketing material. They're not actually asking for things that like copying numbers. They're saying, hey, tell me what are inconsistencies in this document. Tell me where there's an event of default that we can trigger. There's almost this like open-endedness or this new level of computation that people can do.

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  14. Think like 90% of enterprise AI right now is almost like this vaporware. We swear it works like look at this amazing demo where we ask what does the CEO say about the investment? And then the minute that they actually go to try to use it in a real world example completely just fails. And so I actually think that the majority of AI usage, a lot of these usage statistics are all kind of one of my favorite phrases is fugazi fugazi. And one of the things that Hebia really tries to put forth in the market is to say, hey, change will take time, but we have a system that is actually starting to drive real measurable value over very specific defined use cases. And our taglines always, hey, stop experimenting with AI, which everyone's experimenting. They're all really excited about it. Start driving value, like getting value out of it.

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  15. Yeah. So we actually deploy it. Some of the largest finance firms in the world. We ended up going from zero to a million dollars of revenue sometime in 2021 or 2022 in Razor Series A also from index from Mike and Index, which is 30 million bucks. And we start to see that all these customers, okay, now they know what ChatGPT is. They know what LLMs are. Heavy has this really mature enterprise product in the market and we're by far the first to actually get there. And we just looked at all the queries that people were asking. And the questions that people were asking weren't ever, okay, find me the quote or find me the command F questions. They were actually more, okay, read all the documents and then tell me all the times they mention AI or what are exposure to Silicon Valley bank is during the regional banking crisis. And so all of these questions, it was actually almost 90% of the questions that people were asking these systems weren't answerable by a search through the documents, but rather they had to be work done on top.

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  16. That's a bit of a plot twist over here. I actually don't think Rag works at all. It's one of the most used AI architectures in the world pioneered at Hebia in a very meaningful way. I think every enterprise is experimenting with it, but it has a lot of different failures where a lot of the time the questions that people ask these systems aren't ever explicitly in the data. They're never explicitly stated. They're actually about the data. So for example, you know, if you're asking an AI system, is this company a good investment? Which is actually a very common thing that people ask Hebio over marketing materials. Maybe it'll say in a pitch deck, yeah, this company is a great investment as something that the CEO says or like a recording, et cetera. But what you actually want from that system isn't to search in the data. It's to answer about the data, hey, what's the customer concentration? What's the strength of the management team? What are X, Y, or Z criteria that are fundamental to our specific investing process? And that's a process.

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  17. We were one of the first people to productionize the idea of putting a search engine behind an LLM. So you'd ask a question and then instead of it just replying from its memory, it would actually go and do a search and then reply with that context. So in an enterprise where you have a lot of offline data, we were really the first people to hook up that offline data to large language model to answer that question.

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  18. Bragg is an acronym that stands for retrieval augmented generation. If you look at large language models today, they're really good at maybe thinking if you give it the right context, but they hardly ever have the right context. And so Rag was the first real attempt to give them the data to answer questions correctly.

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  19. So this is all in 2020. We end up building a product studio, which is the first to productionize rag, retrieve augmented generation also in 2020. We build the first semantic search engine. you actually go out and start

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  20. Got a million, and then two months later, Mike actually hears about Hebia from his daughter, who was a Stanford student. And I think I'd seen the product, was friends, and then Mike actually comes in and is like, hey, this is completely different than Elastic or all these other search technologies that I've seen and invested. Obviously, he's on the board of Elastic today. So he's like, well, let's just go add some fuel to the fire.

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  21. I mean, I think we were in late discussions with a lot of investors, and then everyone else was like, yeah, let's pile on in here. It's some of the best money that you can get. And that was a game changer for us.

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  22. There's two things. He is incredibly ontologically smart. And so he can build this worldview or this perspective of the world where he actually just knows how to pattern match to a variety of other things. But then he's also, I think, phenomenologically smart, which is the idea of like he understands processes and how humans behave really well. And so he's always thinking like, hey, you know, ex-ante, or like, you know, if I'm looking at something that's about to unfold, could I have predicted this ahead of time? And he always just asks himself that question. So he's built up a really rich perspective of the fallacies that human society has, memetic behavior that people kind of go out and copy each other with, et cetera, et cetera.

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  23. I got another conversation thinking I had just made a friend or was seen from someone who's incredibly, incredibly, incredibly bright. And I'm leaving his house. And I felt like I was inducted into the Illuminati. I was like, my whole body, drop top, the sun's shining. I was playing Kanye West. I drove out. It was like my first offer from a venture investor.

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  24. 45 minutes to an hour late. He's like just waking up, and I'm wired. I'm like sitting in my chair, you know, like ready to go. And it was supposed to be a 30 or 45 minute breakfast. I was like, all right, it's kind of already shot. But we ended up talking for, I think, like four or five hours about not only the company and all of the flaws that I had in my business model, but then also math and deep esoteric philosophy and just the world. And he said, you know, I'm not investing at the time because it was coronavirus and a variety of other factors, but I'd love to put in a check.

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  25. Well, so I was saying two months prior, again, I think I was at Stanford or just about the leave Stanford, and one of my friends had interned at Founder's Fund. And he's like, hey, I hear you're raising financing. You should talk to Peter. And I was like, well, I'm not going to say no to that. And so he introduces me on an email thread with me and Peter. And I'm like, hey, Peter, I would love to do a lunch or dinner. I'm not a morning person. So I was like, Peter would love to do a lunch or a dinner anytime soon. And Peter was like, I can do a breakfast. I was like, I really want to do a lunch or a dinner, you know, like, can we do a brunch? He's like, I'm going to do a breakfast. And so I said, well, that's fine. And he gave me a slot on a Saturday. And so got in my car. I was an old, like, beat up 2006 Audi convertible that I had like fixed up from Craigslist and bought for $4,000 at three in the morning and drank a bunch of coffee, like 18 cups of coffee, like a five-hour energy, like all the disgusting stuff, and drove from three to eight to his house to go and pitch this guy. And I think he showed up.

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  26. This is for our seed. So there's a follow on to the preced in like November of, I think, 2020. And I get on the Zoom call. And I've literally got clothes hanging behind me. And they're like, all of a sudden, Mike shows up and then four other partners and then 80 partners in the Zoom screen tessellates with, you know, hundreds of faces. And I'm like horrified at the fact. And Mike's like, look, he's living in a closet. And everyone's like, ah, great founder. And I was so embarrassed. And then I pitched my company. Honestly, hilarious. Yeah.

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  27. Yeah. Ultimately, I probably went too hard. My hind site's 2020. I think I definitely left nothing on the table to a point where it was detrimental to my health. But at the same time, I think that that was like a crucible where it helped form me. It's very hard to be a founder. And those are the moments where you're just like, you're eating microwave meals every single day. And like you're just like losing weight and you're trying to will something into existence. I actually was trying to pitch one of my former bosses at a professional services firm and he looked at me on the Zoom call and he almost cried and he was like, just come work here. Like, what are you doing to yourself? Like, just don't come back. We'll give you like a proper salary. Like, you don't have to do this. There's so many low points like that. And I think, you know, just kept on chewing through it. And yeah, raising money in the closet, I actually got on with, for we raised a precede from Peter Thiel and Floodgate and then our seed from Mike Vulpiet Index. And Mike was like, hey, we're going to do a partner.

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  28. Tables on the floor, and that was, I just sat there and worked all day, 16, 18 hours a day, go to sleep, wake up, do it again, no weekends. It's kind of like I turned into almost a monk where I was just obsessively building heavy. I was training models at the time. So I'd wake up in the middle of the night, check on them, you know, continue to use my GPU crate because I didn't want to spend any money.

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  29. No comment off the record I was on a PhD salary. You're making what $38,000 a year, I think $42 at the time if you had the Stanford graduate fellowship, which I had. And I said I was going to go and leave. And I actually originally went on leave and said, told my advisor, I'll be back in a year. You know, this coronavirus, just like, give me some time. And I didn't have anywhere to go. It was like a logical next step. And I wanted to work on this company. So I asked my friends who were renting out a house in East Palo Alto to let me rent a room the cheapest room they could possibly find and they were all fully booked and it was like I think over a thousand dollars of rent and they said I think it was actually you know $500 or $600 not $300 to give my broke self some credit here for not being able to afford the rent but they said you could rent out the master bedroom closet and so I bought in like a mattress from the dorms and I had a folding table from Home Depot nearby and I would basically rotate whether the mattress was on the floor or the full

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  30. Is pounds into your head the idea hey, you've got to start a company where there's a lot of pain. And I had a lot of my students or a lot of my friends would go into investment banking or private equity if they were really lucky and they would come back and basically be the least happy versions of themselves. They've lost 50. They just hated their lives. It seemed like there was more pain in financial services around processing unstructured data than anything I had ever seen. It's like, well, there's a great company to be had here. Let's give it a shot.

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  31. I'm one of the youngest PhD students in the history of my school. And I actually believe that I was working on, you know, at the time, one of the areas of research that was most interesting to me was meta-learning, this idea of teaching machines to learn to learn. And in June of 2020, Sam Altman, OpenAI came out with a GPT-3. And if you remember the title of that paper, it was large language models are multitask or meta-learners. And I'm sitting in my lab one day and playing around with this new technology. And I'm like, wow, they just stole the most important thing I could work out run under from my hands. And I said, well, if I can't build the most important technology, how can I build the most important product? And I think those are two very separate things. Obviously, at the time, GPT-3 was not a product. And I don't even think chatGPT is a really good product. It's like a calculator. It's got the technology in there encapsulated in very simple form, but it's not a product that like in Excel that lets you just build whatever you'd like with it. That's very human first. And Stanford.

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  32. On to the next one, you know, it's like, okay, that's done, and like the next day, I was like, okay, well, how do I become the youngest PhD student in my school's history? Not even a moment. I think I was excited for a moment, but it faded very, very quickly.

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  33. I think I have an unhealthy obsession with driving really hard. Yeah, I think you just can never give up. Like, I just don't think that's an option. You can look at every company ever, and some get to $100 million in revenue in whatever, like some span of time, which they probably their marketing team has hacked and some end up taking really, really long periods of time. The only thing that actually changes is the rate at which you get there. And so sometimes things go in your favor. Sometimes they don't. But if you're so persistent that you just continue, like you can bring a lemonade stand to a hundred million dollars in ARR. Like there's nothing that's actually stopped. You can brute force your way as a founder. You screw product market. You could literally brute force anything in the world. You just have to have that ship. You have to continue to just pound away at whatever is in your way.

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  34. Free. And then they paid me the next year, and then I publish internationally recognized research the next year. And by that time, I think that was impressive enough to let Stanford let me in, which is a life-changing moment.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  35. So, so, so cold. And I didn't know what to do. I started crying and I actually called my mother because I was like, well, I'm going to come home. And she's a salesperson. She works in medical sales. She picked up the phone and said, listen, no, you're not going anywhere. You sit your ass down and you call every single number that you can get into the building. And so I sat on the curb and I cold called every number on Google from my old phone. And finally, someone picked up. It was one of the only people in the office that day. And they came down, met me in the lobby, and I basically pitched them on myself for two hours. Gave me an interview. I interviewed, botched the interview because I didn't know anything about like kind of like linear algebra. I didn't know anything about physics. But I remember I memorized all of the titles of the posters on this professor's valley. Came back the next day, so showed up again cold and told them basically everything that I could possibly know about his specific research. And he was impressed enough to let me work for him.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  36. This is actually a very good story. I wanted to be an astronaut, like that was my number one goal, and I was hell-bent on that. And so by the time I was, I think around 15 years old, I was going to high school in New York City and all scholarship school where the alumna paid for everything. I was like, I was kind of tracking academically really strong. And I wanted a NASA internship. And they were offering them to college undergrads or graduate students. And so obviously I applied and got rejected five times. And then there was a snow day in February where my school was closed. I commuted into the city. I actually showed up in front of their New York City office, the NASA Goddard Institute for Space Studies. And I demanded that they let me in. And the front door security guard was like, you know, kid, get the heck out. Like, what are you doing? You don't have an appointment. Like, I was like, I printed my resume out on the nicest paper. I'm wearing a suit. You've got to let me up. And he kicked me to the curb. And so I actually sat outside. It's like 110th Street, Manhattan. And it was snowing. It was like...

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  37. What does your brother do now? He wants to meet me upstairs. That's what I'm talking about. There we go. Did you feel like a I think the answer is yes. I did. I felt like actually physically unable to do the things that I was wanted to do, or I thought that I was good at things that weren't valued or weren't actually.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  38. I'm happy to. I always joke around and say that you can bucket great founders into three backgrounds. I think probably the most common is that you had kind of a messed up childhood. The second most common would be you're gay. And the third most common would be you were adopted. Look at a list of the all-time greats. Elon Musk kind of messed up childhood. Jeff Bezos, Steve Jobs adopted, Peter Thiel, Sam Altman, you know, like publicly gay. And I think that all of these early life experiences end up giving you some desire, some like deeper passion to go out and prove yourself.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  39. I had a lot of friends who were incredibly nerdy. So we went to a public school. I was the type of kid that would hack the school tablets to put StarCraft on everyone's computer. And then, you know, we'd all like not be paying attention in public school playing. There was a large enough contingent of kids that were also not athletes before.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  40. Literally falling over while trying to dribble a basketball. And I think my whole child that I was really just a math kid, like not very out there, wasn't really talkative, only really good at math. And my parents barely even knew what Stanford was. So growing up, you know, you kind of have this whole misalignment of who I was and who I wanted to be with who they wanted me to be that gave me this drive and desire and passion to go out and prove myself in a way that was really tangible, maybe not only to them, but like hopefully to my own kids one day.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  41. It is fair, and I think the first time I met with Sangein, who's one of our investors at the Series B, it was like a 30 minute lunch that turned into almost two hours of us talking in depth about the dynamics that I think made me have a chip on my shoulder. But in short, I was born in Staten Island, New York City, which you already have a chip on your shoulder from that. Grew up kind of around New York City and New Jersey primarily, which a second chip. But my mom is probably like a mafia child born and raised Staten Island. My dad is an immigrant from Slovakia who grew up under the Iron Curtain and then immigrated, really escaped to the United States. Both of them actually fully intended to be professional athletes. They had four children, of which only one was a boy. And so, you know, you can imagine their dismay when I was chasing butterflies on the soccer pitch or like falling on my head many times, which I have plenty of stories of me.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source

  42. You can bucket great founders into three backgrounds. I think probably the most common is that you had kind of a messed up childhood. The second most common would be you're gay. And the third most common would be you were adopted. Look at a list of the all-time greats. Elon Musk kind of messed up childhood. Jeff Bezos, Steve Jobs adopted, Peter Thiel, Sam Altman, you know, like publicly gay. And I think that all of these early life experiences end up giving you some desire, some deeper passion to go out and prove yourself.

    2025-01-22 · The Twenty Minute VC · 20VC: Why All AI Companies Are Under-Valued | The Future of Foundation Models: Scaling Laws, Generalised vs Specialised, Commoditised? | From Unable to Afford Rent to Raising $130M From Index and Peter Thiel with George Sivulka @ Hebbia · IDENTIFIED FROM THE TRANSCRIPT · source