#62 Solving The Impossible With Arnav, Mikael and Aahaan Ft Arnav, Mikael and Aahaan
The Solving the Impossible Award for 14-18 year olds was recently taken out by IBM's youngest ever intern, Arnav. The top prize being a $1M trust fund powered by AuDeFi's core blockchain technology, Cryptium. Two of the finalists, Mikael and Aahaan joined Arnav in a fascinating episode about innovation, STEM role models and how they have accelerated their learning in neuroscience and artificial intelligence.
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Aahaan, Arnav, Mikael, Podcast Host
Podcast Host 00:05
Hi everybody, welcome to the top of the class podcast. It's awesome to be joined by Aahaan, Mikael and Arnav who all were finalists in the solving the impossible award. And a recent competition where enough took out the the top prize there a million dollar Trust Fund. It's obviously a pretty incredible competition that's open to 14 to 18 year olds, and the kind of level of problems that you guys were solving were pretty intense. So I would love to go around the room and for you guys to just introduce yourselves quickly. And then we can get into more meaty stuff about how you are approaching the competition. What kind of problem you decided to try and tackle. So let's start off with Aahaan. Aahaan, give us a bit of an intro to yourself.
Yeah, for sure. Well, thanks so much for having me on the podcast. I'm Aahaan, I actually lived in Europe before I came to Canada. Yeah, currently based in Canada. And I started out my journey last year looking into the medicine phase, doing some work and now technology and I moved over to AI/ML or we have a great time on my internship and that's where I really caught my inspiration to apply for the solving the impossible award.
Podcast Host 01:25
Awesome. Awesome. How about yourself Mikael?
everyone, my name is Mikael. I am actually based in Toronto, Canada, similar to Arnav and Aahaan. I have been working in the BCI industry for the best two years. So my sort of elevator pitch would be that I'm 16 year old brain computer interface developer working on actually building the tools necessary to read and write our neural code. Specifically, what that involves is iterating on functional ultrasound imaging, neuro imaging modalities, which is a type of neuroimaging modality that focuses on neurovascular coupling, which is like the correlation between hemodynamics and neural activation. And so what I'm personally doing is building the killer app of neuro tech by iterating on and improving this technology.
Podcast Host 02:12
Thanks Mikael, I will pretend to know exactly what you were talking about just then. All those things definitely know exactly what you're, you're talking about. But that's awesome. That's awesome. And Aranv?
Yeah, I'm just about to say I have absolutely no clue what you're saying either this. But hey, my name is Arnav, I'm 15 years old. I'm the youngest software developer intern in the world at IBM. And what I've been doing for the past couple of months, like six to eight months, is working in the space of machine learning, specifically in transfer learning. So figuring out how we can take what we currently have, which is these really narrow networks that are good at one thing, and then branch out to generally capable intelligent agents that are capable of doing multiple things and sort of read that Terminator level intelligence that movies like pre you know, prophesized, however, for the benefit of humanity, rather than the destruction of humanity.
Podcast Host 02:58
Yeah, don't go creating like the next Skynet or something like that man.
Oh, there's more research going towards stopping that than there is towards actually getting into that point. It's crazy. It's crazy.
Podcast Host 03:09
Okay. Well, that's interesting. Yeah. I mean, it's so interesting to kind of get an insight into what's happening in that field of robotics that is, you know, super advanced. What do you guys all have in common? As you know, you're all doing pretty crazy stuff in the STEM field. What do you see as being like a common link that you three have that perhaps other people don't have?
Yeah, so the thing that we I mean, we all come from very sort of like diverse backgrounds. But the maintenance work connects us all. The reason we all know each other is because we're part of the program, the notch society. And you're probably familiar, you're probably familiar with things like Sequoia Capital or Y Combinator, which are started, like accelerators. And they put like, lots of funding into companies and give them access to mentors that they become, they can become like, you know, really big unicorn companies or like billion dollar companies. So TKS is basically imagine like a startup accelerator book for humans, a human accelerator. And so they take, you know, kids are aged between 13 to 18, I believe, is the age range there. And they just about emerging technologies, about mindsets about some other real world skills, like presentations, one pagers, marketing, things of that, and then they expose us to some of the really interesting problems in the world and opportunities going on, and how we can actually make an introduction into into these sorts of things and change the world.
Podcast Host 04:28
Yeah, well, I'm going to get this the introduction that TKS makes and by the way, I will give myself just a tiny bit of credit because Crimson Education who powers the podcast is now a partner up with TKS trying to help students go from high school to then, you know, top universities like MIT, Stanford, trying to make that transition happen, which I'm sure you guys will be looking at doing in future but essentially, yeah, like when they make the introduction, I'm sure that there's some students who kind of take that introduction and then run with it right and then go really deep into particular field is that part of becoming really great in a program like TKS is your ability to then take an idea and run with it.
So basically, the value proposition of TKS is number one, its community, everyone wants to just really get better. Number two would be the directors. So we have various different directors spread across the world all have own diverse amount of experiences and things like that. And really, we're just learning more about about them. And then also, obviously, the curiosity factor. So which has led us to these individual experiences. So really what we we use the community, we use the directors in order to then follow our curiosity and then work on our individual paths.
Podcast Host 05:41
In terms of like, student life now as a high schooler. Is that super boring for you? And for like other students, when you know, you're going into maths class, and you're like, Oh, we're going to be learning about calculus, or, you know, going to be studying this book, and you're just no really wanting to get home and, you know, look into computer brain interfaces, all these other really cool things that sound a lot more interesting than what most people are learning at school.
Yeah, for sure. I think just before I answer going back to doubledown Macau's point is the real value property guess is that everybody comes in to you guys gives you the exposure and the tools and the access to all these big problems with technologies. And it's everybody's crossing everybody's drive to make an impact that takes them in different directions. So the directors, they've been the biggest help. They're some of the smartest people. And their main goal is just how can we help all these TKS students grow. And so once you have the exposure in TKS, like that, going back to school seems kind of boring, because you're doing research on like Macau, I was talking this weekend, how we do research on DCIS, and AI and improving AI. And you have to go and do like a bio test about same basic or learning something. So it's not always the most fun. But I think all the knowledge when you learn in school, it starts to add up as well, just the way they teach you, I think is much, it becomes a lot more faster, longer interesting if it's self driven. So for example, I know our nav yet to learn and may not ever have to learn the math to do some work in AI. And that makes learning math a lot more fun and interesting and haven't been taught due to school curriculum.
Podcast Host 07:12
Yeah, yeah, the the context around what you learn at school is often not there, right? Like, they just kind of say, this is the topic you're learning. And I used to always say to the teacher, like, when am I ever going to use it? And literally, her response at the time was, if you become a maths teacher, you will need to know this. And I'm like, no, no, that's a terrible answer. You know, give me something that I can actually work with you. And Aranv, you just put in the in the chat that the Canadian school system is terrible. I think a lot of high achievers tend to feel that their school system is a bit slow and a bit of a drag. Why do you particularly say that though?
Well, I think the main thing that makes it, but my main criticism for at least I wouldn't say it's like, you know, per se terrible. But my main criticism for it is that the way that it teaches kids like the way my friends think about it, is you're going to math class, and you'll memorize some formula, right? So for example, the formula for a circle is like we just did, this was like x squared plus y squared equals r squared, right? And people will memorize that formula, and you can write it down on your sheet for the test. But the issue is, they don't go through the intuition as to why that's the case. Like they don't go through usually the radius as a hypothesis and the triangle within that circle, right, you could think of as the polar graph. And the reason why I think that TKS really helps us sort of excel in school, even though we do basically no homework, like I don't know about Aahaan and Mikael, for me, I've done like zero minutes of homework this entire year, whereas like, our teachers are expecting us to do something between like, two, three hours, and I'm still getting really good grades. And the reason why is because from learning these really tough things, you kind of have to switch the way in which you learn stuff. And it goes from memorizing laws to basically making your mind or your learning mind at least, like an algorithm. And this algorithm takes in information and aims to understand it deeply. So that you can make the laws and math and you can understand the laws intuitively because you can understand the entire subject as a system holistically. And that's really, really useful because not only does it just assist in, you know, tremendously in learning way more complicated things, but for these sorts of pursuits, it's no longer just a endeavor of memorization, but it is truly an endeavor of thinking and, you know, basically pretending you're like Isaac Newton, for example, inventing math, or inventing calculus, sorry. And so it's definitely a very interesting way of thinking. And it's a shame that that isn't taught in the school system, I believe it's it's kind of an you know, an inevitability when you have to teach millions of kids every year. But approaching that sort of intuition based thinking, I think would tremendously profit any of these students in the school system.
Podcast Host 09:40
Completely agree. I think part of the problem is that the education system is often you know, one size fits all it's trying to suit everybody and so not everybody can get to that level of you know, creating an algorithm inside your head type of thing and approaching math that way, but you know, the fact that you wouldn't be able to do that in a place like TKS is fantastic. Aahaan, Mikael, do you have any thoughts on this way of thinking? Because it seemed like you guys had experienced something similar?
Yeah, so similar to our no of I actually haven't spent a lot of time on school as well. And I'm, I'm getting really good marks as well. And I think that what that really shows is that school is actually hackable, right? There are various different things that you can do in order to actually achieve high marks, while not putting a lot of input so that you can spend the remainder amount of time to actually work on the things that you're passionate about. So once you understand that, that's when you can really evaluate what where you should be putting most of your input on so that you can actually get the desired output.
Podcast Host 10:37
Yeah, 100%, Aahaan, do you have anything to say on like, the general way of how you think and approach problems, because I think this is like a super important part of how you guys are where you are in your lives right now. Right? And, you know, as I've been saying, like, my mom would be like, Oh, what's their, you know, what are their parents do? I'm like, no, no, sometimes it's an exposure to a program, or whatever it might be, that gives students access to a different part of their brain or a different way of thinking that it allows them to, you know, have this time where they're not studying, you know, because that's what a lot of parents assume. Right? Like, if you're, you know, researching, you know, blockchains, or brain interfaces, these are things, what about your homework? What about your studies, this kind of thing most parents have been like, how about your grades, you know, but if you ever said hackable these kinds of things, that there's ways around it, if you've got any experiences on on that kind of side of things.
Yeah, for sure. Think exactly what Mikael said. There's a something called the 80/20 principle, which basically identifies what are the 20% of actions you can take, that will lead you to get to 80% of results. I think that similar applies to school, when you look at, for example, you look at test prep, there are some really effective methods of studying like active recall, flashcards that are much better than just spending hours looking over your notes. Or even if you have an assignment, something great you can do is just actually reach out to your teachers. I know, if you talk to your teacher saying, Oh, I'm gonna be I'm doing this outside school, I have this internship. I'm still like, dedicated to getting good marks in your class, can you help me to understand where I should be focusing on to get better talk to your teachers, everybody's gonna be super friendly, very helpful. And then it's also just a major mindset shift where you're not always thinking that school is the end goal, we think was it's one in the first session, actually, if he gets exposed to most people go in their entire childhood life is that okay? Schools and goal getting 100% of this test, it means I succeeded, otherwise, I didn't. But it really exposures TKS. These other problems, and more important things in the world help you to show that school is a great way to learn, but it's not an goal, there's better things you can do. So don't over optimize and get worried if you don't do the best you can, because it's not the end of the world.
Podcast Host 12:48
Yeah, you guys remind me a bit about my occasional podcast co host, and the founder of crimson, Jamie Beaton, who basically very similar to what you just said, like, basically hacked away through self studying, and did the 20% to get the 80% result, like every single time, he was self learning, you know, entire subjects in the space of a couple of weeks, and then ace in the exam, because he knew the kind of study habits talking to the teachers, what do I actually need to know to get a good marks in the exam, don't give me all the fluff, don't give me all the background, just give me what I need to know for the exam. And he did really, really well and got into 25 of the world's top universities, I'll actually have to see if we can get you a copy of a new book that he wrote called accepted. He basically wrote a book on how to get into top colleges. Now let's talk about solving the impossible award because this is actually a really cool thing. I don't know a huge amount about it. I'm going to guess it's mainly like a US Canada type vibe. But yeah, how many students were part of it? How did you guys hear about it? Can you give us some kind of context or background as to how you got to where you are today as like finalists and winners and smashing this competition out?
So um, the idea of the competition was the, the guy that runs it, Patrick Poirier, his entire thing was like, okay, he's built all this capital in his career, right? Like he's, he's like, you know, a capital allocating machine, right? When it comes to making money. This guy's a God, basically, infinite money source, man. And so he's basically asking himself, like, how can we or how can I make the largest impact possible? And His thing was, let me invest in who I would think would be, you know, a very high potential prospect, like as a youth right now, then help them just completely exponential eyes, their trajectory in life. And so that way, they already they're already asking themselves this question, how can I make a large impact but they're only between the age of 14-18. So have the rest of their lives to go out and do that and his entire goal is like, how can I make it so that you don't have to deal with, you know, the the capitalistic part of society? How can I just allow you to keep working on your research? because it was specifically research oriented, and then hopefully you can go out and solve these important problems. And so I'm not sure how many people applied specifically, I know that they didn't spend any money on marketing. So they like, it was probably like less than you would think. But I know that I'm globally, like it was it was a competition for everyone. Because our idea is how can I get the, you know, the smartest person not the smart person from Canada, the smart person from United States? Um, but basically, the idea was like, How can I or his goal at least was making sure that we can work on something that doesn't necessarily get compensated in the free markets, for example, like, you know, the research that meno Han we're working on AGI is a very long term pursuit, right? Like it's 20 years, 30 years, that isn't really compensated in the free market, because you don't have a deliverable or like a something that is produced until the very end. And so his idea is like, How can I just make sure that you don't have to ever worry about getting a job or doing something like that, or doing something you don't want to do that's straying away from that goal, so that you can spend all your time becoming, you know, really, really smart in the field, and then, you know, eventually solve the problem. And I should preface, right, like, none of us here are really like, really extremely insane at any technology that we're working on. Like, we definitely have made substantial progress compared to you know, someone our age. Um, but we're, you know, we're not close, like Geoffrey Hinton, for example, in AI, or I don't know of any of the gods in BCI. But we're just on that, on that sort of trajectories that will be at that level, sooner or later.
Podcast Host 16:32
Yeah, I've always been intrigued on the show, like chatting to students who are doing some pretty intense research in these fields, like, how do you even access, you know, or where do you go to research these types of technologies when you are 14,15, 16? Because, you know, most of the time, I would think that that's a college level thing. Are you going to colleges and professors in life saying, hey, I want to research this thing? Can I spend some time or you might be going to companies like you're at IBM, at the moment? Are you asking those guys like, Hey, I'd love to know more about this site, you know, like, how do you even begin to research a field that most high schoolers would not even know about, let alone have access to in terms of like, no high school lab, I would think as, you know, equipment to, you know, robotically build these types of things that you guys are talking about, of course, there's the internet. I mean, that's obviously the first port of call probably YouTube, etc. But like beyond that, where do you go to start researching in depth these types of fields?
Ultimately, the two things that I've realized in the past year especially is that the internet and people are very powerful tools. Like, you can learn so much from a quick 15 minute conversation from someone that you actually look up to. And also, you can learn a lot from just various different research papers, various different textbooks, various different websites, that all are touching on information that you could get into college as a college level education. And so it's really just about how you approach these tools and how you use them to your advantage. For example, I'll give an example about me personally, I'm learning about how you can iterate on a specific neuroimaging tool. And so what I'm working on specifically, is just reading research papers for eight hours every single day, and just understanding the end to end pipeline of how this technology actually works. So then, in the next year, I can then go about iterating on this technology, and get to a level in which this technology has the ability to read our neural code at micro scale at one neuron or whatever it may be. And so that's really what the goal is.
Podcast Host 18:39
What is motivating? Why is these topics or the topics that you've chosen? Why are they a passion for you? I know that might be a kind of odd question to ask. But the idea of reading a research paper for eight hours a day is the last thing that I would ever think a teenager would be interested in, right? Like, that sounds a crazy thing for a teenager to be like, Yeah, I'm gonna dedicate myself to reading research papers like, especially for topics or goals that same as you guys are working on as well, Aahaan and Arnav, that is like 20-30 years in the future. So why are the topics that you guys have chosen? Do you see yourself as being an integral part of the development of these particular fields as well, I think is one of the other questions that I've got wrapped up in that. Aahaan, I'll throw to you for that.
Yeah, for sure. Okay, so you need to give a little bit of background. So I actually I did last year, I did, like I said, I talked about mostly focusing on technology. And the key aspect to your previous question, how I learned was just conversations like I tried to have a couple meetings each week instead of just reading an article online or a research paper if you just like send an email to the to the author of the paper and understand why did you do this? They'd be more than happy almost always to help you to spend some time helping you understand. And then actually, what am I to a serendipitous opportunity, one of my articles got read by the CEO of a applied AI company in downtown Toronto. And afterwards, the interview process began with him I got an internship in this company called Quantify, which is one of the leading machine learning companies in Toronto. And then so this, I found out, like I said, the dragon's vault competition, it was towards the end of August, and I was still working full time my summer internship and I was looking okay, which problems do I want to solve? So I initially talked I made a list is actually this simple. It's crazy. I made a list of all the different technologies that are being said in nanotech, virtual reality AI ml. And next, I made a list of all the different problems I wanted to solve. And then so I narrowed down pretty quickly to AI and ML as a technology. But when I realized it took me so long, and I couldn't narrow down about which problem they want to solve, there's climate change or things in physical technology, there's air pollution, there's even like different technical problems like improving machine learning models, I couldn't decide which problem because looked at, okay, what tool can I build to help me solve all these problems? And that's what got me to the field of AGI and I looked at it as a highly technical field. But just the love of the fear and love of learning and understanding. It's really what gets me excited, because I wake up like, damn, this is so cool. Let me spend as much time as I can trying to understand, but it really was that simple. I just looked at, made a list, and then went from there.
Podcast Host 21:25
That's pretty cool, actually, to hear that, that, that started at that list point and these things and these things, and then what can I do? And then you land on AGI. But yeah, I can see that like, once you've landed on the field, when you can see the potential of that field having the impact of you know, every I think every young person wants to have an impact these days. And I think you guys have certainly found that field that could have huge amounts of impact. Arnav, what about yourself, did you have a list approach? How did you start thinking about what the world's biggest problem was? Or the unsolvable problem might be?
Yeah, well, I mean, I have this whole journey is very long as I'll try and keep it concise. But basically, when I was 10 years old, I was diagnosed with a rare from a blood cancer. And this really was like, obviously a huge shock to me and my family, and definitely changed the trajectory of my life. But I had previously gone to India and Thailand, and I had seen extreme poverty firsthand. So I had seen, you know, kids without families, I saw like amputated kids on the street, that obviously wouldn't be getting any money. And what that made me realized, after I got cancer was like, I was still super privileged to be in a position that I was at. Because if I had been diagnosed with the same condition, and I was one of them, I would have died. But as you can see, I'm very much not dead. To quote, Black Panther. And so I was kind of fueled with motivation at that moment, right. I was like, How can I make my life now that I'm like, super, you know, awake about or, or aware of how important, you know, this opportunity is? How can I make my life the most impactful? And I switched around for many things like I started with extreme poverty, obviously very inspired by that entire experience. So I was working with a couple of my friends on problems like the water crisis, on open defecation on vaccine distribution. And then what I realized I was talking to a lot of professionals in the industry, or within this field called Effective Altruism, and especially concerned with, there's a lot of trees in the world, that one degree thing is there, a lot of people want to do great things, but not many people want to do great things actually do great things. And the reason why is because a lot of these charities and a lot of their approaches are either misguided, or just they're not executing properly. And so how can we make? Or how can we go about doing research in such a way that we create the highest impact possible with our efforts. And so I talked to a lot of professionals at these sort of companies is a company called Open philanthropy, which is right now like giving that they have a conference in England that my friend workshop is at, and they're giving away like $43 billion to organizations to work on these sorts of problems. I was talking to one of the guys there that was concerned, this research, Luke wall Hauser, and he's like, he's also like an AI guy. And I had a super enlightening conversation with them that made me realize that the highest point of leverage for us as individuals is technology. So the my sort of philosophy behind technology, and actually when I say my, it's kind of stolen from a guy Balaji Srinivasan, he used to be the CTO of Coinbase. But it's like technology is is kind of just a way for us as humans to remove or to reduce scarcity. And so technology serves as this thing that no other point in history, could individuals make the same level of impact that they can today, like the the team that runs Facebook, for example, they're a team of like 50 people, I think, or it might even be less than that impact 3 billion people around the world. And the ability now to make impact is very closely tied in the age that we live in the information age with ability rather than things like reasons versus or luck. I mean, obviously, there's there's an element of luck to everything, but far less than it was, for example, like the 1600s, I think you'd have to be high class mobility, you'd have to be either like an advisor to a king or be the king himself. And so technology, I think, serves as the leeway for our generation to make the most amount of impact possible. And AGI just I was just naturally gravitated towards AGI because it had the prospect of being the universal algorithm, like the algorithm that could solve any problem could learn anything. And yeah, I just fell in love with brains and simulating brains on computers, and figuring out how we can make these sort of agents it's very, it's very curiosity driven. It's very curiosity driven, but there's many elements that come into it, you know, the impact curiosity? All sorts of things.
Podcast Host 25:49
Yeah, obviously, a lot of life experience has gotten you to where you are today and gotten you super focused on achieving what you want to achieve in this particular space. So, and I think it's cool that a lot of you guys know, the kind of who's who in the technology space, you know, like the CTO of Coinbase, etc, etc. Whereas, like, a lot of teenagers are probably like, Oh, I know, you know, the, the starting lineup for the Lakers, or I know, like, the actors or whatever, right? Like the celebrities in the traditional sense, where you guys have like, the celebrities of the tech sector, which is, whoever they might be, but it's cool that you've got these role models. And, you know, I think it's worth for students to start looking into as a starting point, you know, who are the movers and shakers in the technology space? And how could I get to that kind of level as well. We'll end with Mikael on this, you know, how you got started in this motivational following the tech pathway. And you're starting to understand what you would do with the solving the impossible.
Yeah, for sure. So ever since I was a little kid, I've always been in love with the brain, then exploring various different concepts related to freewill, consciousness, etc, etc. And so ultimately, when, as a kid, I always had these big dreams of like achieving X or achieving y. But it was always like these brain related fields. So whether that could be like becoming a neurosurgeon or becoming a neuroscientist, or something along those lines, because I just wanted to really interface with the brain. And I want it to be as close to the brain as I possibly could. But it wasn't actually until two years ago that I finally realized that in order for us to really understand interface with and actually improve the brain, there must be some form of technological revolution. So I was listening to this, this specific video with Neil deGrasse Tyson and Ray Kurzweil, and they were talking about these nanobots that had the ability to increase the bandwidth of our brain. And it was like crazy to me, because what we would be able to do like right now, if we want to learn something, it could potentially take days, weeks, months, or even years to actually learn that specific thing. But by increasing our brain's bandwidth, we would be able to potentially have thoughts coming out of our brain and into our brain at an exponential rate. And so that's really what I wanted to focus on. And so now what I'm focused on is specifically is iterating on a specific neuroimaging tool, so that I can actually get us to that level in which we're actually getting specific neural activity out of our brain at an exponential rate and also into our brain. So really, just that overall idea of reading and writing or neural code.
Podcast Host 28:28
It makes me think of the matrix a little bit, you know, where he's like, I know kung fu after being downloaded with a disk of Kung Fu and how to do what type of thing where, which super cool. Now, let's talk about the actual competition. What was the competition asking of you guys? Like, what did you have to do? In terms of presenting your research? Did you have to do like a slide deck? What did you have to show something like, what was some of the, I guess, the rubric there that judges were using to determine you know, what you guys were actually working on?
Yeah, for sure. So I can set off still a day initial competition, it was you're looking for a essay in a video, there was no restriction, nothing to talk about. Just basically, whatever you supposed to be most authentic reflects your personality. So you can just try to exhibit that you are someone who has capability of making impact in someone because it's a directory of high potential. And that's it. So because we all made the video we did, Diaz and after that we had a quick interview is that's an interview more, it's a conversation with Patrick, where you talk to each of us about what our vision was what we were trying to solve, was it possible and it was actually a great conversation for me because me and Patrick, we scheduled for 15 minute interview, we talked for like, almost 3045 minutes just jamming out about different concepts and AI. And then for the final presentation, there was a couple of judges as well and they were just looking at presenting what your vision is and how you plan to accomplish.
Podcast Host 29:51
So it sounds like almost a shark tank kind of situation. Am I right?
The main thing though, is like it was a highly ambiguous process like you could Do really whatever you wanted. So for example, Mikael and Aahaan had a large focus on like their stories and their sort of plans, action plans to help them get to the point they want to be in their trajectory right now, me and Amy had more like talking about work we were currently working on. And then Brianna had the you know, good mix of both, really, it was up to us, whatever we want to do, you know, if we want to sing them a song, we I'm pretty sure we could do that as well. But it was just essentially illustrating to the judges or doing whatever we would take to convince them that we were, you know, high potential candidates and could solve some of these higher order problems in the future.
Podcast Host 30:39
What about your particular presentations Do you think enabled you to get to the final and you end up becoming a winner? In your case enough? Like, what is it that impress the judges so much about what you guys are working on do you think?
And I think it was, it was kind of unique for everyone, because, you know, with that ambiguity comes a level of idiosyncratic nature for the presentations. For me, I think the thing that was probably the most convincing of me on that as Patrick, but for me, I think it was, I was presenting like, you know, extremely, like novel research, you know, never really seen before. And I made like in two weeks a model after the different papers I was looking at, and connecting them together and seeing the broader implications of that. And so being able to accurately like to a very high level of depth explain an extremely technical subject that is like, you know, cutting edge was a big, convincing factor. I think, for me, that, you know, I knew what I was talking about, and that I would be high potential or high possibility of solving AGI.
Podcast Host 31:41
I think ultimately, for me, it was my conversation with Patrick because I think DSA there were, I'm not sure how often but probably a lot of applicants my video was it talks about my store, talk my vision. But ultimately, our conversation was when it was just me and him. And I could actually talk about very technical topics we talked about, what are the issues with even like capital allocation in today's startup ecosystem in research, if we talk about AI, why how people are training models the wrong way, same guy, as soon as I talked about that, he realized that I had the same level of technical depth that some of his previous colleagues had in AI, and I could be able to get that level. And then my presentation was more about what is my plan to get to that level? Because it's very long bridge that I haven't been working in the field as long as someone like Arnav, to just how do I plan to get to that level.
Podcast Host 32:29
And then Mikael?
For me, what I put a lot of bias on is discussing what my vision was, and then the quantifiable steps to get there. So whether that's, like I said, talking about the knowledge gaps, what do you actually have to address in order to get to this level? And then also, what would this overall vision look like. And then also, even just my journey before this, so like to give you some background, like in the past year, I've built like 15, plus projects, run it run and a bunch of academic papers, and done various different other things related to BCIs that could potentially make me the best candidate. And so I really put a bias on those two things, talking about my vision, and also talking about my journey to actually get to that level.
Podcast Host 33:10
With me, though, like, there's, I feel like most of my life now has basically just revolved around like the work that I do. Like I don't really go outside or do anything like that. I'm a very losery type of person. Now, I think from a third perspective,
Podcast Host 33:24
Well, at least you're aware of it. And you certainly getting a lot of LinkedIn love.
Oh, my homies, all my homies online, I have to say, LinkedIn has provided me with so much value, getting into work, like, I met one of the the big individuals that I met Savva (inaudible). He is a researcher at DeepMind. And he's been, you know, tremendously helpful to me, helping me navigate through the process of learning AI and all this stuff. And so I think that LinkedIn has been really, really useful for all sorts of things.
Podcast Host 33:31
Pretty much every episode of the top of the class feels like an advertisement for LinkedIn, because it's just like, students who are on LinkedIn. And you're right, you know, it's like my homies are on LinkedIn, whereas most students are like, well, you know, I spend most of my time on Instagram or Tik Tok, or whatever it might be. And then there is this small percentage of students who somehow often a guest on the show, who spend a considerable amount of time, you know, hustling on LinkedIn, and that's the way that they like to spend their social media time. But Aahaan. Yeah. Talk us through like what's going on in your kind of immediate circle immediate life? They can kind of paint a picture for some of our listeners.
Yeah, for sure. Um, before we do that, yeah. LinkedIn has been like LinkedIn and Twitter both have been incredibly valuable. I think I got my whole internship, because I posted my article on LinkedIn and a CEO ready and then Twitter is just great for building in public and just like spontaneously getting connections and meeting new people.
Podcast Host 34:48
I know that that is like a TKS thing building in public, right?
It started a while ago when you're looking you when you're building your startup for entrepreneurs to build in public, but then now it's sort of like you learn in public, you build a public you grow in public, just get gather community and see if you can connect with like minded individuals, not just physically do programs all over the world through things like LinkedIn and Twitter.
The intention there is kind of like with building and public is to foster serendipity. And so the idea is like with with a hunter example, he's a really good example of serendipity. The CEO of that AI company quantify literally reached out to him, you know, like, you know, you can go into a conversation at a conference and be like, oh, yeah, I'm 15. And I'm an intern on AI, internet, this company, quantify, but what's even cooler than that is like, oh, yeah, I'm 15. And they reached out to me to ask me to become an intern at their company, you know. And so the idea is, like, how can you do networking that like, networks, when you're not actively, you know, reaching out to people when you're working on your stuff instead? And so that was the intention I think behind that.
Podcast Host 35:53
Yeah. Well, yeah, it's that idea that, you know, if you're working on something, share it, because you never know who's going to read it, and who's going to reach out and be like, hey, the thing you're working on is really cool. Like a lot of people, as you know, I think, you know, build behind closed doors, and then eventually presented as a finished product, but you've missed like 100 opportunities along the way of your learning process and what you've done. And, you know, you can really extend your reach just by showing people what your interests are and what you're working on, rather than just the finished product. But yeah, I think that's like a very good tip for our listeners, for sure. Building public more is the general theme there. So, Aahaan, you were going to talk about what's going on in your room there as well?
Yeah, for sure. I think nothing crazy. You can see the basketball that my door that's like my number one source for all brainstorming when I'm taking a project articles, some random HaKadosh are always going to get my best ideas. And I have my Kindle on my desk right here, which is like summon archive, where have like, all my favorite books, and every time, if I'm bored and aren't bored, before I sleep, I'm just reading to find and then I have a notepad, which is always like, have like, sort of L shaped doesn't have a notepad, it's always when I have conversations with even just like reading the common art, if I get some cool thing or insight I want to write down or look into, I just noted down, so nothing crazy. I mean, but that's fine. I like my room.
Podcast Host 37:14
Yeah, for sure. For sure, and Mikael?
Yeah, for me, other than that huge brain poster, my desk is literally my temple, like I spend literally every second of my day outside of school, just like working at my desk. So I have a really nice setup. But the one thing that's on my desk at all times is this headset, which is like an EEG headset, and which in which I built all my projects with I used it every single day, last year, just building as many projects as I possibly could, and just jamming out with it. And and what it does, at a very high level is take my brain signals and then outputs it to the computer. And then I could like program and build a bunch of projects using that technical using that source of data. So yeah, so ultimately, that's the main thing I have on my desk. I think other than that, it's not not too much.
Podcast Host 38:01
Yeah, just got a random brain scanning interface thing. And we'd love sitting on your desk, which is cool. Not not everyone has that. But of course, you know, you guys are here for a reason. So that's some of the thing you'll find. I guess one of the final questions would be like, what advice would you have students who are at that level where they really love tech, they really love stem, but they are probably still stuck in the school bubble a little bit. Who would like to dive into that?
I have a couple of ideas about this actually, I've been thinking about this a lot lately, not just for this podcast, but because you know, it's obviously directly applicable to me and my friends. Um, the main thing that I would say so the the sort of thing that we have that is like tremendously different are the tremendous benefits that we have in comparison to all other generations. It's really the only generation to be born with access to the internet. And I think leveraging the internet is like the greatest thing you can do. There's like a source of basically unlimited knowledge. And so Naval Ravikant, as he said, It's not the means for knowledge that is rare, it is the desire to learn. And I think looking at vivid cases of people that became really, really smart, really young, we've there's people that are far smarter than us, I believe, that became smart when they were younger than us too. So I would say probably the biggest example of our worldview is Lauren Dunning. She was born in New Zealand and homeschooled there she taught herself, French literature and calculus before she was seven years old. She then became the youngest graduate of MIT, I think, either at 13 or 14. I remember how that went. And now she's working in the longevity space. She's a VC for longevity companies working to literally cure death. And so she is, you know, a super, super cool person. Another example in AI is Chris Olah. He is a bit older than us, but he dropped out of university to help his friend on a terrorist case, which is a bit of a weird thing there has his friends to commit terrorism or some you know, weird foreign thing, but he came back and without a university degree of single handedly came one of the most prolific AI researchers today, and has, you know, massive reach is really, really cool guy. And so I think the main thing, the main thing that you know, unifies all these sorts of different people, is the fact that fundamentally, like when you learn anything new, whether it's from a book, an article, a video, or a blog post, whatever it is, it's always coming from another individual or another, another source until you're at the very top of your game in which you were the person that's not producing that new knowledge, right, where you're at the top researcher. And so really, what you want to do is you want to optimize to find and meet these kinds of people. And I think like that the one piece of advice that I was thinking about this earlier as well, like during the podcast, the one thing I really want to take home for the you know, the children listening, or the ambitious children, is like people are everything, like all endeavors are human led, all endeavors are human directed, everything you could possibly learn is from other individuals. And all the greats are produced through that sort of apprenticeship. And so you want to optimize to find these people. And I should mention, like in the Chris Olah example, he wasn't like, obviously, he he dropped University, and I'm pretty sure he was in forestry as well. So he wasn't like some god AI researcher, before he was picked up by Michael Nielsen, who really provide him with that mentorship to get to that next stage from where he was at. He just happened to be a very curious individual, he happen to be very passionate about this field of research. And so Michael Nielsen, who is a very prolific AI, and quantum researcher, just picked them up as sort of like an advisor, like it wasn't really a PhD thing, because obviously, he wasn't university. But Michael Nielsen was running the seminar series on AI before he published his landmark textbook that I'm pretty sure a Han and I have read. And so he got that sort of individual experience there. I think that's really what you want to optimize for. If you want to reach that sort of next level, and become really, really good at something. It's really just to find your super smart people and get the advice to them, try to work with them in the lab, or whatever it may be. And just remember that, like people are everything.
Podcast Host 40:25
That's an awesome answer. You're a like an encyclopedia of cool people in the, in the tech industry, it feels like..
This is the thing, I follow my own advice, right? I just I just try and find the people. That's my new that's kind of my framework. Now for learning stuff. Like, I will just search out, for example, when I was learning calculus, right, like or linear algebra, I didn't trust try and find you know, the cheapest or most expensive or highest rated textbook, I tried to find, you know, the best teacher the best, or the guy, you know, leading linear algebra, research or whatever it may be. And then I learned from that guy, who, in that case, Gilbert Strang, you know, the legend, MIT. But that's basically I think, the best framework you can adopt for anything, if you want to become really good at anything.
Podcast Host 42:38
Awesome, awesome. I completely respect that approach. And that's pretty cool. responds to that question about, you know, advice for students. How about yourself, Aahaan? What would you, I know, you guys have kind of had variations of that as well in terms of learning from people and these kinds of things. But is there anything that you would say to students who are wanting to kind of level up their their game to reach those kinds of heights?
Yeah, for sure. I think Arna have basically covered everything as he tends to do with the knowledge of but would you do anything apart from just taking advantage the internet and just exploring cuz everybody starts somewhere, exploring to find I think it's super affordable also to try to get in one of these high growth communities. Because as one thing that like TKS pushed you to do when you have people around you are working at talking with big problems or excel as their main goals? How can they push themselves to the most growth? It inspires you in a way like you can imagine like, I know, I know, I speak for all of us and almost everybody in TKS a lot of the things who wouldn't be here if it wasn't for the community weren't for not just the guidance of physical ask people for help, which is also a big part but just when you're looking when you're like demotivated to do something everybody faces when you see like you're talking to some or you see five of your friends like Oh, Macau is out here doing DCI talking with like the top company, some other dudes working self driving cars, oh, guy got to get up, I gotta get to work so I can continue and it just really motivates you. And it definitely always gonna be people even in in school. It's not just like school like a place for everybody's there's some really smart people in schools where you can align that, okay, I want to work on this. I want to learn AI let's learn AI together two weeks, let's see how much we can learn and collaborate with them. I think that also having people in terms of not just reaching out for gain knowledge and people the community around you is a really undervalued aspect.
Podcast Host 44:20
Yeah, yeah, I, you know, it's that old saying that you're the average of the five people you spend the most time with. And that I think is a huge part of the inspiration. It's just to be thinking that life as a student doesn't stop at you know, doesn't start and stop at school type of thing. Like your learning doesn't stop and start at school either. But yeah, and Mikael?
Yeah, so in terms of advice for people who are getting into the STEM field, I think a lot of the time and I know I fell into this trap a lot was just, I continuously would read these papers continuously do all this thing and always consume information, do a bunch of courses, but I think that that's just an augmented and like a not an accurate representation of The knowledge that you have. And so ultimately, the best way to actually learn and exponentially grow in the STEM space is by just continuously building projects continuously learn by doing continue, like try to get maybe into a lab, like I think a Han said to like, just work and prone down on this type, the type of skills that you actually want to build to actually get that hands on experience. So really just learned by doing as opposed to just consuming information and not actively doing anything with that information obtained.
Podcast Host 45:29
as perfectly exampled by the fact that you've got like a brain headset thing sitting on your desk. Now, guys, just last question any particular direction for you college wise, obviously, like crimson helps students get into these top universities. So we'd love to hear if you had any ideas as to which colleges you were aiming for. I mean, like hearing what you guys are working on, and the people that you know, obviously, like MIT, Stanford, these types of universities might be one of the goals, but might not be anyone have any ideas?
Yeah, I mean, I'm asked this question. Often, I think, like, then I always get this answer, which is that it's like highly dependent. I think, on the work that I'm able to get done in the next like two years. There's obviously a lot of options for this sort of AI research stuff like there's Caltech, there's MIT, Stanford, there's also a lot of ones that you wouldn't think of. So for example, University of Alberta, here in Canada, is one of the best like universities with AI. Um, there's also a couple of stuff in Montreal, there's UCL and England, that's actually where the founders of DeepMind, which is, you know, my favorite AI company met. And then another thing is one of my really good friends, I met him recently, Dr. Wattenberg, he's a professor at Harvard used to head the Google Plus humanity initiative. And so he's no AI legend. He's a legend of everything. He's basically if I had to think about what God would be, he is basically God. And so he runs a lab at Harvard. So you know, I might, I might have to catch up and get into Harvard. So I can, you know, work with this guy, but it's highly dependent, I think on on what I get done and what opportunities arise. I'm also pretty sure Elon Musk said that he might open up a university in Texas, the Texas Institute of Science and Technology. And so yeah, there's a lot of options. Another one I forgot to mention is u of t. So like, arguably the world's best researcher in deep learning, which is the field of AI or that I specialize in, which is basically having multiple layers of of computation and neural networks hidden layers is what is called probably the best researcher, Geoffrey Hinton operates actually in University of Toronto. Now, I don't know if he's going to continue teaching because he's like, 85 years old by the time that I get into university, but as I was saying, Before, you know, if you just look at, like my, basically my history of progress, and like my plans for how I'm going to optimize the progress and everything, it all kind of revolves around this central idea that I was saying before, I've just like optimizing to find and meet and learn from the world's best people.
Podcast Host 47:49
Yeah, absolutely. Aahaan. Which college do you have in mind at this stage? If that is your thing? I mean, you could go the entrepreneurial path. Like, there's there's, the possibilities are endless.
I think it really depends. Similar to Arnav, what I'm working on what each university specializes in. Like, I know, Stanford is known for Neuroscience for things like they have top nurse on professors, the labs, the resources, it's probably looking at similar universities for AI AGI like Caltech, MIT, Stanford, haven't narrowed down that much hasn't really been a big priority, but really looking at where's the thing now give me the highest quality of education also just the best community, things like that.
Podcast Host 48:30
Yeah, absolutely. And finally, Mikael?
Yeah, so like a Han said, because I'm very focused on the brain and neuroscience specifically, definitely Stanford would be like, the end goal for college specifically, you know, you have like some of the awesome professors, David Eagleman, you have Andrew Huberman etc, etc. So like there's various different professors within Stanford are coming out of Stanford, that are just amazing. And, you know, having them at your disposal to talk about whether the specific neuro tech startup that I may have in uni would just be amazing. But the trap that I don't want to fall in is just like this hyper optimization trap. So like spending too much time optimizing for these schools, because I think, ultimately, that just takes away from your overall work in your specific passion, working on your passion and things like that. So really, I hope it's just a byproduct of what I'm working on.
Podcast Host 49:20
You've got a very good point there. I think a lot of students are so focused on you know, getting into college that they forget to work on their passions. A lot of the time, your passions will be the thing that gets you into college anyway. No, I think admission officers are very good at seeing authentic activity lists and not like modified ones to get into college, so to speak. But yes, certainly something to keep in mind there. But guys, it's been an absolute pleasure to have you on the show, but I know it's getting a little bit late there in Canada. So I really look forward to sharing this episode far and wide. Please send me any links that you want to share. There'll be in the show notes for students interested. Join our Slack group I heard like a little slack notification going off somewhere in the middle of this Tte podcast. So yeah, we've got a Slack community for top of the class at the moment as well. So I'll put that in the show notes too. But guys, thank you again so much for giving up your time and sharing your your experiences. It's been awesome to have you on the show.
Thank you for having us.