The Exchanges

Q Ah, it's a pleasure, but I'd love to start today, and maybe for those that didn't hear our first episode, how did you make your way into the world of startups and come to be a partner at YC and now founder of Pioneer?

A Well, thank you again for having me on. So my story is pretty weird, and it speaks to Why I'm doing what I'm doing today. I was born and raised in a small country called Israel in Jerusalem, right outside the old city, and I was very much born and raised into the life of Orthodox Jewry, which is quite different from the life I lead now here in the heart of Silicon Valley. When I was 18, I was getting ready to enlist in the Israeli army, and from the slow internet speeds of my Nokia phone, I applied to this organization called Y Combinator, which my dad sent me an article about. I wasn't really sure what I was doing at the time, but when I hit that submit button on that HTML page, I changed my life forever. And I came out to Silicon Valley. I ended up starting a company when I was 18. I think at the time I was the youngest person to get accepted into YC. And I ended up starting a company that raised a series A and a series B from Sequoia Capital and other investors. It was effectively a search engine that got acquired by Apple in 2013. I was 23 at the time leading a bunch of machine learning and the I teams across Apple, across iOS, iOS 10, the watch, and a bunch of other platforms. And when in 2017, I decided to leave out Apple. It's a wonderful company. I just had the opportunity to join Y Combinator and pay it forward for a year. Given the amount that organization has given m…

AI assessment note: “I just had the opportunity to join Y Combinator and pay it forward”

Q And then final question before we move into a quick fire. Do you get concerned investing now so heavily into the AI space that there seems to be kind of no foundational business model for, for the rise of ML technologies coming forward?

A Well, I, I would disagree. I think that there are going to be business models of taking AI and applying it to a vertical in the same way that you could literally take the advent of the database and apply it to a vertical. You know, software eats the world. Is a quote I think originally attributed to Marc Andreessen, and I think you could kind of rethink of it as machine learning enabled software eats the software that ate the world. So I think those will have healthy business models just like all the SaaS companies do. Second is for the platform companies, I do think there's a less obvious but likely business model as well. Less obvious because unlike the database analogy I provided, it's not immediately clear that there'll be An Oracle or a MySQL, that is to say, a company that empowers all the verticals, because I think the incumbents today, Google and Amazon, Microsoft and Apple, to some extent, are far less naive than the incumbents in Oracle's time, and so the companies are more forward-thinking, and as a result, I think it's going to be a little bit harder for a company to build something that TensorFlow won't do over time.

AI assessment note: “Well, I, I would disagree. I think that there are going to be business models”

Q And then final question before we move into a quick fire. Do you get concerned investing now so heavily into the AI space that there seems to be kind of no foundational business model for, for the rise of ML technologies coming forward?

A Well, I, I would disagree. I think that there are going to be business models of taking AI and applying it to a vertical in the same way that you could literally take the advent of the database and apply it to a vertical. You know, software eats the world. Is a quote I think originally attributed to Marc Andreessen, and I think you could kind of rethink of it as machine learning enabled software eats the software that ate the world. So I think those will have healthy business models just like all the SaaS companies do. Second is for the platform companies, I do think there's a less obvious but likely business model as well. Less obvious because unlike the database analogy I provided, it's not immediately clear that there'll be An Oracle or a MySQL, that is to say, a company that empowers all the verticals, because I think the incumbents today, Google and Amazon, Microsoft and Apple, to some extent, are far less naive than the incumbents in Oracle's time, and so the companies are more forward-thinking, and as a result, I think it's going to be a little bit harder for a company to build something that TensorFlow won't do over time.

AI assessment note: “I would disagree. I think that there are going to be business models”

Q Ah, it's a pleasure, but I'd love to start today, and maybe for those that didn't hear our first episode, how did you make your way into the world of startups and come to be a partner at YC and now founder of Pioneer?

A Well, thank you again for having me on. So my story is pretty weird, and it speaks to Why I'm doing what I'm doing today. I was born and raised in a small country called Israel in Jerusalem, right outside the old city, and I was very much born and raised into the life of Orthodox Jewry, which is quite different from the life I lead now here in the heart of Silicon Valley. When I was 18, I was getting ready to enlist in the Israeli army, and from the slow internet speeds of my Nokia phone, I applied to this organization called Y Combinator, which my dad sent me an article about. I wasn't really sure what I was doing at the time, but when I hit that submit button on that HTML page, I changed my life forever. And I came out to Silicon Valley. I ended up starting a company when I was 18. I think at the time I was the youngest person to get accepted into YC. And I ended up starting a company that raised a series A and a series B from Sequoia Capital and other investors. It was effectively a search engine that got acquired by Apple in 2013. I was 23 at the time leading a bunch of machine learning and the I teams across Apple, across iOS, iOS 10, the watch, and a bunch of other platforms. And when in 2017, I decided to leave out Apple. It's a wonderful company. I just had the opportunity to join Y Combinator and pay it forward for a year. Given the amount that organization has given m…

AI assessment note: “I applied to this organization called Y Combinator, which my dad sent me an article about.”

Q And so before everyone enters, Daniel, which I'm sure they will, the inner lawyer always taught me to ask about So what are the terms to joining pioneers and kind of what's involved from that perspective?

A Yeah, it's quite simple. I should first mention pioneer is not an incubator or an accelerator. We're fundamentally building almost a video game for productivity and happiness and self-actualization. That is our goal. And so our funding model looks different because we're not out here to take small companies and make them big. If you do that, you should apply to YC. But if you have a project that may not even turn into a company, you should apply to a pioneer. And the way it works is quite simple. If you get into Pioneer, you get a 5000 dollar grant immediately, and then you get the opportunity to get a 100,000 dollar investment into the company. Pioneer will basically follow any funding rounds that you end up getting afterwards and supplement it until it's put in up to a 100,000 dollars in your company. And honestly, if both parties want to invest more, we'll invest more. This is kind of a grand experiment. So we're just starting it and seeing how it goes. If you take that 5000 dollar grant and you end up working on research I'm not really turning it into a company. You owe us nothing, and we're very happy, and I'd be very happy dying knowing that Pioneer supported the creation of the next Einsteins and Marie Curie's and people that create a tremendous amount of value but don't capture it. All we're trying to do is experiment with ways where we can fund Pioneer in perpetuity, a…

AI assessment note: “If you get into Pioneer, you get a 5000 dollar grant immediately”

Q Well, Daniel, I'll just quash one there. I've had 2000 guests on the show, and you're one of the kindest. So I'm, I'm a little struggling with that KPI, but whatever. I'll let you run with it. I have to ask, what do you believe that most around you disbelieve? You're in the East of Silicon Valley. You hear a lot.

A Honestly, one I've been struggling with a little bit, and again, this is personal, but I don't mind sharing it, is I grew up being told to believe in God. I came out to Silicon Valley disbelieving in God, and I'm slowly coming back to it. I'm slowly coming back to the belief that there is some type of higher intelligence. And what I find really fascinating observing my own psychology around this is it's not a very rational thought process, but maybe that's okay. It basically stems from two factors. One is just a kind of constant awe of nature and it's just inability to comprehend how it could be all random. And maybe we're all ants when we're trying to understand the same way an ant is not going to understand what Harry Stepping's podcast is. I'm not going to understand the logic behind the universe and But I don't know. I struggle with that. So that's one. And the other is, I do think religion is an incredibly potent tool. I think it can be used like everything that's powerful. And I think it basically gets people playing an infinite game, and this will make sense once you read that book I recommend it. So that's one thing a lot of people around me disbelieve that I believe in.

AI assessment note: “I'm slowly coming back to the belief that there is some type of higher intelligence.”

Q the show the other day, and he said that specifically crypto, but also kind of the next frontier of, uh, categories, be it longevity, genomics, CRISPR, AI, will re-centralize talent into the valley. I'm interested, and so is Avichal. This is his question. I have to give him credit. He asks, do you think it will re-centralize the talent in Silicon Valley? If so, why? And if not, why not?

A Well, I think Silicon Valley is experiencing a temporary dip in quality of housing, somewhat akin to the kind of Manhattan struggles, New York City struggles in the 19 seventies before Giuliani came in and cleaned it up, where you've got kind of two things going on. One is prices are out of control, so it's just really tough for talent to come in, and two, just the quality of the city is in a slight decline, and so it seems like the situation's gotten a little bit worse, and so I think we need to fix that in order to ensure that we can have the opportunity to become the hub of all these future great ideas. I think we will. I think Silicon Valley has managed to produce significantly harder innovations than fixing housing, but I think that's the ticket to becoming the home for things like cryptocurrency and longevity, because ultimately people need to be able to afford rent, and right now that situation's, it's definitely not there, and I think if we don't afford it, we're at a real risk, but I'm quite optimistic that we'll fix it in time, and there are real solutions to these problems. The exciting thing, actually, about these problems is this is not cancer. No, this is something that we know how to solve. We just have to figure out how to align incentives so everyone agrees on how to solve it. This isn't something where we're just staring at a whiteboard and it's blank.

AI assessment note: “I think we will. I think Silicon Valley has managed to produce significantly harder innovations”

Q Well, Daniel, I'll just quash one there. I've had 2000 guests on the show, and you're one of the kindest. So I'm, I'm a little struggling with that KPI, but whatever. I'll let you run with it. I have to ask, what do you believe that most around you disbelieve? You're in the East of Silicon Valley. You hear a lot.

A Honestly, one I've been struggling with a little bit, and again, this is personal, but I don't mind sharing it, is I grew up being told to believe in God. I came out to Silicon Valley disbelieving in God, and I'm slowly coming back to it. I'm slowly coming back to the belief that there is some type of higher intelligence. And what I find really fascinating observing my own psychology around this is it's not a very rational thought process, but maybe that's okay. It basically stems from two factors. One is just a kind of constant awe of nature and it's just inability to comprehend how it could be all random. And maybe we're all ants when we're trying to understand the same way an ant is not going to understand what Harry Stepping's podcast is. I'm not going to understand the logic behind the universe and But I don't know. I struggle with that. So that's one. And the other is, I do think religion is an incredibly potent tool. I think it can be used like everything that's powerful. And I think it basically gets people playing an infinite game, and this will make sense once you read that book I recommend it. So that's one thing a lot of people around me disbelieve that I believe in.

AI assessment note: “I'm slowly coming back to the belief that there is some type of higher intelligence.”

Q ask, you mentioned some very exciting kind of potential themes and areas where we'll see some groundbreaking evolution and kind of breakthroughs. I'm intrigued, though, in terms of the companies being built around this, will we see an AI company, or do you think that kind of machine learning itself will be a sustaining innovation existing incumbents really use and kind of use to further themselves and their incumbent advantage?

A I think that's a really good question. So currently, the way you kind of look at the world today, there is yet to be an independent entity that you could really say is an AI company, or I think a better framework for this only exists because of the kind of latest and greatest machine learning technology. And And many different verticals inside Google and Apple and Facebook for incremental improvements, but nothing really breakthrough. I think there are two possible takes on this. One is that we're just early and that's going to happen. And I think that's fairly true. I mean, self-driving cars, it will be a great example of something that's not incremental. It's breakthrough. And there certainly are startups that are working on autonomy, literally with cameras and deep learning alone without the help of LIDAR. So that's one take. The second take is a slightly more dystopian one that I really hope doesn't come to bear, which is that, yeah, it's actually going to be a sustaining innovation for a lot of these large companies, and even if there are new products, they'll be made by large companies like the Amazon Echo, and this is something that I think if we in the industry don't take any corrective action may happen, because in the machine learning world, there are certain economies of scale that You only get to when you're a large company. In particular, there's three that really …

AI assessment note: “I think there are two possible takes on this.”

Q Where did you find great success in terms of this field?

A Well, I, I will credit a lot to meditation, in particular, over the course of The past three or four years, I've used the Headspace app almost every single day, and every time I mention this, I feel almost somewhat self-conscious describing it. It feels something so weird, foreign, that my rational, forward thinking, try to be as productive as possible mind should disagree with, but I found it really helpful for me to become just more self-aware and less immediately involved in my own line of thinking, and so The main thing to take away from this, if you're considering getting into meditation after listening to this podcast, is the advantage that you get is that you are able to kind of do what you want, not what you're in the mood to do, and I think that's a great skill.

AI assessment note: “I will credit a lot to meditation, in particular”

Q ask, you mentioned some very exciting kind of potential themes and areas where we'll see some groundbreaking evolution and kind of breakthroughs. I'm intrigued, though, in terms of the companies being built around this, will we see an AI company, or do you think that kind of machine learning itself will be a sustaining innovation existing incumbents really use and kind of use to further themselves and their incumbent advantage?

A I think that's a really good question. So currently, the way you kind of look at the world today, there is yet to be an independent entity that you could really say is an AI company, or I think a better framework for this only exists because of the kind of latest and greatest machine learning technology. And And many different verticals inside Google and Apple and Facebook for incremental improvements, but nothing really breakthrough. I think there are two possible takes on this. One is that we're just early and that's going to happen. And I think that's fairly true. I mean, self-driving cars, it will be a great example of something that's not incremental. It's breakthrough. And there certainly are startups that are working on autonomy, literally with cameras and deep learning alone without the help of LIDAR. So that's one take. The second take is a slightly more dystopian one that I really hope doesn't come to bear, which is that, yeah, it's actually going to be a sustaining innovation for a lot of these large companies, and even if there are new products, they'll be made by large companies like the Amazon Echo, and this is something that I think if we in the industry don't take any corrective action may happen, because in the machine learning world, there are certain economies of scale that You only get to when you're a large company. In particular, there's three that really …

AI assessment note: “I think there are two possible takes on this. One is that we're just early”

Q have to finish with kind of a full circle quote from, from Aaron, who said that the key to success in machine learning and AI is to, to have true ambiguity in your AI or machine learning. So I'm intrigued. How much would, to an extent, would you agree with this statement and kind of the importance of ambiguity in, in kind of investments moving forward within the ML space?

A Well, I think that is true in the sense that, and to really bring it back full circle to the point of a, of the, the audacious statement that this is all a scam, I think ambiguity could be a goal in the sense that when you don't have that much of it, you really wonder if simple Thinking techniques, or frankly, even simple stats, statistics techniques, could have solved the problem long ago, and the only reason this is kind of coming to your plate today as a potential investor is because of all the buzzwords, and really great machine learning engineers have the same characteristic that really great all engineers have, which is they're kind of lazy, and they want to find the kind of Occam's razor, the dumbest way to fix the problem, and the bad ones want to kind of over-apply AI, and To areas that don't have ambiguity. So I think in that sense, it is somewhat of a goal.

AI assessment note: “Well, I think that is true in the sense that... ambiguity could be a goal”

Q the show the other day, and he said that specifically crypto, but also kind of the next frontier of, uh, categories, be it longevity, genomics, CRISPR, AI, will re-centralize talent into the valley. I'm interested, and so is Avichal. This is his question. I have to give him credit. He asks, do you think it will re-centralize the talent in Silicon Valley? If so, why? And if not, why not?

A Well, I think Silicon Valley is experiencing a temporary dip in quality of housing, somewhat akin to the kind of Manhattan struggles, New York City struggles in the 19 seventies before Giuliani came in and cleaned it up, where you've got kind of two things going on. One is prices are out of control, so it's just really tough for talent to come in, and two, just the quality of the city is in a slight decline, and so it seems like the situation's gotten a little bit worse, and so I think we need to fix that in order to ensure that we can have the opportunity to become the hub of all these future great ideas. I think we will. I think Silicon Valley has managed to produce significantly harder innovations than fixing housing, but I think that's the ticket to becoming the home for things like cryptocurrency and longevity, because ultimately people need to be able to afford rent, and right now that situation's, it's definitely not there, and I think if we don't afford it, we're at a real risk, but I'm quite optimistic that we'll fix it in time, and there are real solutions to these problems. The exciting thing, actually, about these problems is this is not cancer. No, this is something that we know how to solve. We just have to figure out how to align incentives so everyone agrees on how to solve it. This isn't something where we're just staring at a whiteboard and it's blank.

AI assessment note: “I think we will... that's the ticket to becoming the home for things like cryptocurrency”

Q Where did you find great success in terms of this field?

A Well, I, I will credit a lot to meditation, in particular, over the course of The past three or four years, I've used the Headspace app almost every single day, and every time I mention this, I feel almost somewhat self-conscious describing it. It feels something so weird, foreign, that my rational, forward thinking, try to be as productive as possible mind should disagree with, but I found it really helpful for me to become just more self-aware and less immediately involved in my own line of thinking, and so The main thing to take away from this, if you're considering getting into meditation after listening to this podcast, is the advantage that you get is that you are able to kind of do what you want, not what you're in the mood to do, and I think that's a great skill.

AI assessment note: “I will credit a lot to meditation, in particular”

Q You mentioned the lost productivity there from people who maybe are able to achieve great things but don't have the opportunity, so to speak. What are some of the kind of stats around that, and really how wide a problem is it, Daniel?

A Well, there's a wonderful paper, actually, that Stanford put out called Lost Einsteins about this problem in particular. And there's a lot of other related papers. The interesting thing about all the academic literature on this front, some of it pointing to the fact that people of certain skin colors are achieving significantly more than others that don't, that have the same talent. There's no real great data set on this. A lot of the data set is measured based on patent filers and innovators, and I can tell you as someone who's filed a bunch of patents as a byproduct of working at Apple, that's not a great biomarker of creativity. It just means that you worked at a company that files patents for you, and so there's no real good ground truth for it, but One, you know, very obvious thing you could point to, or two very obvious things you could point to. One is, just if you look at the story of every great person that's come to exist in the world, they all seem to start from humble beginnings. You know, Sam Walton, founder of Walmart, his first job was at JCPenney, I think making 18 dollars a month. J.K. Rowling's manuscript getting rejected 22 times for writing it on the back of paper napkins as a homeless person in the United Kingdom. You know, all the way to John Rockefeller, You're starting out as a simple bookkeeper in a produce firm. And all of these people had peers, I bel…

AI assessment note: “There's no real great data set on this. A lot of the data set is measured”

Q And then talk to me. You are an incredibly productive guy. What's the big productivity tips for you? Um, I had to ask this. It wasn't in the schedule, but you just seemed so productive that I had to.

A Oh, I appreciate the compliment. Uh, I don't think I'm, I'm that productive. You know, I struggle a lot actually with a question I've been thinking about a lot is I am very self-critical of myself. And in many ways that propels me to work harder, but it's not clear to me that it's a great quality to have because I sometimes wonder if it's in contest with just being happy. So I think that's kind of a bad chip on my shoulder that I have that I wouldn't recommend others acquire other things that helped me quite a bit. I'll share, I'll share one funny one. I got in the habit a few years ago of rather than drinking coffee, which has one of the best drugs in the world, I drink a tremendous amount of decaf coffee, and the hack here is that coffee has two bad properties about it. One, it dehydrates you, and two, it's spiky. However, decaf coffee contains caffeine, and if you get very particular about the decaf coffee you use, you can actually get decaf coffee that has kind of the right amount of caffeine, and so what I try to do is It's just drink a continuous stream of decaf coffee throughout the day so that it can kind of maintain a consistent buzz rather than kind of getting stuck in the peaks and valleys. There are many other productivity hacks, but that's one funny one I thought I might share.

AI assessment note: “drink a continuous stream of decaf coffee throughout the day so that it can kind of maintain a consistent buzz”

Q I absolutely love that. And then let's finish then today, Daniel, on the next five years for you and for Pioneer, what does that roadmap look like?

A It's highly experimental. Look, if pioneer works and it ends up becoming a feeder for the next set of thinkers, innovators, everyone from John Lennon to Albert Einstein, then, you know, I will obviously continue to invest my time on it. I continue to be very interested in supporting people early on in life and joining them along for their journey and both helping them avoid the 10,000 common mistakes that I think everyone makes. I certainly made and helping them become, you know, the fully realized version of themselves. And the most important thing to note is throughout this process, I'm very interested in finding ways to do almost all of it entirely in software. I'm very interested in figuring out ways to build systems to do all of these things in a much more scalable way that's been done before. I think, again, gamification is an amazing model to maybe learn from, to try to build an online community or network of the next thousand or million great innovators around the planet.

AI assessment note: “finding ways to do almost all of it entirely in software.”

Q Can I ask, Daniel, this essentially could be the next generation of search engine for the kind of talent assessment and talent globally. How do you think about that as a spinoff company, and is that something that you'd love to run and pursue fully one day?

A Yeah, I mean, a lot of people kind of ask that question once I tell them about the project. We're going to be opportunistic. One of the differences between this and, of course, searching through statics Stuff is humans are the most interesting thing in the world, and they're dynamic, and they change a lot, and they need to be respected, and I don't exactly know what will come out of the woodwork. I can tell you that, you know, early signs are really promising. We're getting flooded with letters and emails and applications from people in the random pockets of the world, both in, you know, small cities in the U.S. and small cities in India and, you know, over 60 different countries, telling us that they finally feel like they found a door they could knock on. You know, I, I was just trading emails with someone who's a brilliant game engineer, but he's stuck working minimum wage, you know, in the middle of the United States. And he's just trying to find a way out. And so if it turns out that we've struck gold and we found a way to help people, not even people starting companies, but just people who are really smart, who are working on promising things, and we can find ways to encourage them to improve. I'm sure the universe will reward us, you know, from a karmic standpoint. So, you know, maybe it turns into something really big, but right now we're just getting started. And we're…

AI assessment note: “We're going to be opportunistic... maybe it turns into something really big”

Q at x.ai said, is that you can build your own kind of incumbency advantage through true specialization of data sets. For example, really diving into the kind of deep themes of calendar booking and scheduling. And that's one way to kind of get over the data incumbency through kind of Deep specialization and niches. To what extent do you agree with that in terms of kind of overcoming incumbency advantages?

A I think, I think that is probably true. Um, but I think that one of the great things Y Combinator did is it reduced the friction involved in starting a company to a level where it was counterfactual in the creation of a lot of these great companies. That is, I think it's an interesting question to ask the founders, but I think that It is less likely that Airbnb would have been created had Michael Seibel not recruited the founders to Y Combinator, introduced them to Paul Graham, the program had been set up in place, the investment been available, demo day being available, and so I think that the point that you can create specialization in a mode is true, but the challenge is that many folks may not even bother if it seems far too difficult or remote to even get access to the data, and I think this is very true for data sets that are Slightly more challenging to access than, say, calendar information. For example, medical data. Say And you want to build Dr. Watson, the AI doctor of the future. Well, it turns out getting access to, you know, a million electronic healthcare records is really challenging. And it turns out that data in the healthcare records is unstructured and difficult to deal with. And so this is an area where I think we, Y Combinator can be leveraged in terms of, again, just like we did in 2006 with kind of the basics of what you need for a company. Reducing the …

AI assessment note: “I think, I think that is probably true.”

Q at x.ai said, is that you can build your own kind of incumbency advantage through true specialization of data sets. For example, really diving into the kind of deep themes of calendar booking and scheduling. And that's one way to kind of get over the data incumbency through kind of Deep specialization and niches. To what extent do you agree with that in terms of kind of overcoming incumbency advantages?

A I think, I think that is probably true. Um, but I think that one of the great things Y Combinator did is it reduced the friction involved in starting a company to a level where it was counterfactual in the creation of a lot of these great companies. That is, I think it's an interesting question to ask the founders, but I think that It is less likely that Airbnb would have been created had Michael Seibel not recruited the founders to Y Combinator, introduced them to Paul Graham, the program had been set up in place, the investment been available, demo day being available, and so I think that the point that you can create specialization in a mode is true, but the challenge is that many folks may not even bother if it seems far too difficult or remote to even get access to the data, and I think this is very true for data sets that are Slightly more challenging to access than, say, calendar information. For example, medical data. Say And you want to build Dr. Watson, the AI doctor of the future. Well, it turns out getting access to, you know, a million electronic healthcare records is really challenging. And it turns out that data in the healthcare records is unstructured and difficult to deal with. And so this is an area where I think we, Y Combinator can be leveraged in terms of, again, just like we did in 2006 with kind of the basics of what you need for a company. Reducing the …

AI assessment note: “I think that is probably true. Um, but I think that”

Q No, I couldn't agree more in terms of that impact. The other element that maybe concerned some other people that I spoke to was the element of backing by Marc Andreessen and Stripe, and how you deal with maybe a conflict of interest Over their proprietary right and visibility and optionality into the talent and products created within the programs. How do you think about that?

A I'm so happy you brought that up. I mean, I think the reason Stripe and Mark wanted to back it is because they both have these stories where they came from, in Mark's case, middle of America, and Stripe's case, somewhere in Ireland that is not even in, in, in Limerick. It's like near Limerick. So, I mean, these people are truly coming out of nowhere and came into a tremendous degree of success, and so I think they Want to pay it forward, and I'm sure Stripe more broadly is products like Stripe Atlas is very interested in helping economic growth and progress across the world, but they have no rights into the data set of pioneer applicants. I would not be starting something that was like a feeder for Stripe Talent, and I don't think any of these folks would brand it that way, so the goal of this organization is to really find millions of potential lost Einsteins around the world, and I think those folks were interested in supporting it because They feel like they came from humble beginnings themselves. And again, I cannot embellish this more and more. If you're listening to this podcast, if you're on two 80 and you're already in Silicon Valley, great. Congrats. But if you're not, and you're just trying to figure out what to listen to, how to get ahead, you should realize everything big starts really, really small. I mean, SpaceX with all of its grand and glory was started as effe…

AI assessment note: “they have no rights into the data set of pioneer applicants.”

Q No, I couldn't agree more in terms of that impact. The other element that maybe concerned some other people that I spoke to was the element of backing by Marc Andreessen and Stripe, and how you deal with maybe a conflict of interest Over their proprietary right and visibility and optionality into the talent and products created within the programs. How do you think about that?

A I'm so happy you brought that up. I mean, I think the reason Stripe and Mark wanted to back it is because they both have these stories where they came from, in Mark's case, middle of America, and Stripe's case, somewhere in Ireland that is not even in, in, in Limerick. It's like near Limerick. So, I mean, these people are truly coming out of nowhere and came into a tremendous degree of success, and so I think they Want to pay it forward, and I'm sure Stripe more broadly is products like Stripe Atlas is very interested in helping economic growth and progress across the world, but they have no rights into the data set of pioneer applicants. I would not be starting something that was like a feeder for Stripe Talent, and I don't think any of these folks would brand it that way, so the goal of this organization is to really find millions of potential lost Einsteins around the world, and I think those folks were interested in supporting it because They feel like they came from humble beginnings themselves. And again, I cannot embellish this more and more. If you're listening to this podcast, if you're on two 80 and you're already in Silicon Valley, great. Congrats. But if you're not, and you're just trying to figure out what to listen to, how to get ahead, you should realize everything big starts really, really small. I mean, SpaceX with all of its grand and glory was started as effe…

AI assessment note: “they have no rights into the data set of pioneer applicants.”

Q Can I ask, Daniel, this essentially could be the next generation of search engine for the kind of talent assessment and talent globally. How do you think about that as a spinoff company, and is that something that you'd love to run and pursue fully one day?

A Yeah, I mean, a lot of people kind of ask that question once I tell them about the project. We're going to be opportunistic. One of the differences between this and, of course, searching through statics Stuff is humans are the most interesting thing in the world, and they're dynamic, and they change a lot, and they need to be respected, and I don't exactly know what will come out of the woodwork. I can tell you that, you know, early signs are really promising. We're getting flooded with letters and emails and applications from people in the random pockets of the world, both in, you know, small cities in the U.S. and small cities in India and, you know, over 60 different countries, telling us that they finally feel like they found a door they could knock on. You know, I, I was just trading emails with someone who's a brilliant game engineer, but he's stuck working minimum wage, you know, in the middle of the United States. And he's just trying to find a way out. And so if it turns out that we've struck gold and we found a way to help people, not even people starting companies, but just people who are really smart, who are working on promising things, and we can find ways to encourage them to improve. I'm sure the universe will reward us, you know, from a karmic standpoint. So, you know, maybe it turns into something really big, but right now we're just getting started. And we're…

AI assessment note: “maybe it turns into something really big, but right now we're just getting started.”

Q How did you come up with the idea for the gamification of talent assessment, essentially?

A In general, we underrate games. You're going to ask me later, maybe my favorite book, and it will be a good callback to this. I'll just mention that ominously for now. I think games are a fantastic way to both understand life and And a fantastic tool to learn from in terms of their motivational value. So on the first front, in terms of understanding life, I just find it a wonderful tool to really dig into, you know, certain things like, for example, why are people so interested in playing Fortnite or Age of Empires, and yet it's so hard to read a challenging book? What's going on? Well, effectively, the game of, say, reading that boring book, it wasn't providing you enough novelty. You were not getting enough Interesting variants in it. Whereas you think of what's going on in age of empires. It's quite fascinating. You're literally like opting in to solve problems for hours or civilization. You're opting in to solve fake problems for hours and hours and hours. You know, you're doing resource allocation for six or seven hours. And yet that's seen as somehow is not real work. It is real work. The reason why you do it is it's set up in a manner where it kind of drip feeds you novelty. So that step after step, There's a wonderful term, psychologist's name I'm blanking on, called the term of proximal learning, where it's never too easy or too hard. When something's too hard or too e…

AI assessment note: “In general, we underrate games. You're going to ask me later”

Q How did you come up with the idea for the gamification of talent assessment, essentially?

A In general, we underrate games. You're going to ask me later, maybe my favorite book, and it will be a good callback to this. I'll just mention that ominously for now. I think games are a fantastic way to both understand life and And a fantastic tool to learn from in terms of their motivational value. So on the first front, in terms of understanding life, I just find it a wonderful tool to really dig into, you know, certain things like, for example, why are people so interested in playing Fortnite or Age of Empires, and yet it's so hard to read a challenging book? What's going on? Well, effectively, the game of, say, reading that boring book, it wasn't providing you enough novelty. You were not getting enough Interesting variants in it. Whereas you think of what's going on in age of empires. It's quite fascinating. You're literally like opting in to solve problems for hours or civilization. You're opting in to solve fake problems for hours and hours and hours. You know, you're doing resource allocation for six or seven hours. And yet that's seen as somehow is not real work. It is real work. The reason why you do it is it's set up in a manner where it kind of drip feeds you novelty. So that step after step, There's a wonderful term, psychologist's name I'm blanking on, called the term of proximal learning, where it's never too easy or too hard. When something's too hard or too e…

AI assessment note: “In general, we underrate games.”