Transcription
Kyoto University RIMS, a common occurrence. Around 10 PM, if I was in the graduate student room, suddenly music would start blasting from the next room, and there would be someone intensely studying, which really gets me motivated.
And so, [sniff] um, it's been a very long time since my last video update, [sniff] and I apologize for neglecting my main job, YouTube. I've been quite busy with various things, and it was a situation where I wanted to release videos but couldn't. [sniff] Well, fortunately, I was able to enroll in RIMS, the Research Institute for Mathematical Sciences, and as you can see, I'm even filming this video now in the graduate student room I was assigned. As for the environment, well, if I only show my immediate surroundings, it looks something like this. You know, I even got a bookshelf, and I'm, well, proudly arranging my books, you see. [sniff]
When I had just enrolled, the sheer joy of finally having my own desk, of having made it this far, was immense. I even showed a rather endearing side, frequently coming to this room until late at night, even though I wasn't doing anything in particular, just fiddling with my smartphone. Yes, that's right. I've now become a graduate student, a mathematics graduate student, and I'm fortunate enough to be affiliated with this wonderful environment called RIMS. It's been almost three months now, but I imagine it's not often that people get to hear about RIMS, right? I think you all feel that way, and I do too. So, for high school students and university students who might want to pursue mathematics in the future, I'd like to briefly share what kind of life a graduate student here leads.
Hey, you over there, you probably thought, 'Why don't you just ask AI now?' You'd probably ask Gemini, right? I know, I get it. You can ask AI for a mathematics graduate student's daily schedule, their annual schedule. It'll tell you anything. Yeah. Because Gemini knows everything. So why not just ask it? Ask AI, right? No, that's not it. It's not that AI can't answer that. Of course, it can. But this video right now is without AI. It's a purely, purely authentic video, you see. Yeah. It's all human-made. [sniff]
I want that raw reality to be the value of this video. What I am speaking here, right now, what I am trying to convey, what I am trying to leave behind – that alone is its value. I want you all to, um, appreciate that this isn't AI, that there's a real person filming this. [sniff]
Um, and to be honest, I really wanted to do some editing and various other things, but, well, I just don't have the time for that anymore, so, um, I'll just speak in a rough, unpolished way. First, regarding the environment, Kyoto University is divided into two main entities: the Department of Mathematics, which is directly under the Faculty of Science, and, yeah, RIMS. RIMS is an institution of Kyoto University, but it's somewhat independent, you see.
And I'm over here, at RIMS. [sniff] Well, is there really a huge difference between the Department of Mathematics and RIMS? Not really. They're usually a bit separated, about a 500-meter walk from the Department of Mathematics. And since friends and people tend to gather, and classes are held, more often at the Department of Mathematics, RIMS can feel a little lonely sometimes, you see. But even here, well, in the graduate student room, for example, many people gather and study together for long periods, or go out to eat together, so, yeah. It's definitely not the case that there are no such connections here at all.
Yeah. Also, above all, RIMS has a lot of seminars. In this building, it feels like some kind of research meeting is held every single day, every week, you see. Yeah. For example, topics like quantum field theory, or topology, or numerical computation, or fluid dynamics – anyway, some kind of symposium is held every week. People from universities all over gather, and it's lively. Many people from overseas also come. There's a common room where you can drink tea and such, and no matter when you go, it's like ten people, 'Wow, wow,' everyone talking about mathematics. It's that kind of situation. So, it's an environment where you're exposed to mathematics whether you like it or not, you see.
Also, regarding the workload, the graduate school environment, compared to other departments within the Faculty of Science—like physics, chemistry, biology, or even engineering labs—all sorts of so-called science-related labs exist, but for mathematics, it feels like you can be quite flexible with your time. So, it's neither not busy nor overly busy. For instance, there are no core hours, so there's no requirement to be in the lab from this time to this time. If you want to make it completely un-busy, you can certainly take that time. However, for example, what I have to do now—or rather, what I must do—is attend a two-hour seminar with my professor every week. [sniff] In preparation for that, I spend about 10 to 15 hours preparing each week, sometimes more, sometimes less. So, if you only want to do the bare minimum, just that, you can technically get by. If you truly only dedicate your time to preparing for the seminar with your professor, you might have some free time. In reality, though, graduate students also take various classes, and along with that, there are quite a few assignments. And of course, those who are job hunting are much busier, with many things to do. So, um, as a result, I'm actually doing more mathematics now than when I was an exam student or an undergraduate. Yeah. What am I even doing, I wonder?
[Gasp] Well, why? Of course, I'm doing it because I want to. But honestly, I really think everyone here is a bit masochistic, you know? There are mathematicians who go running; they use their brains for math all day, and then they run at night to exhaust their bodies. I think that's a bit masochistic, don't you? Well, um, if you're going to really commit to doing mathematics, I think this is the best environment for it. Especially for first-year master's students, you see. When you were an undergraduate, you were probably busy with various classes, but if you're truly just focusing on mathematics in graduate school, then you really don't need many classes—one or so is fine. Yeah. So, you can dedicate any number of hours a week. Let's say you work from 9 AM to 5 PM, doing 7 or 8 hours every day, you can do that for five days. And what's more, the professors around you are, of course, extremely specialized, and your friends all have their own knowledge that you can share anytime. So, I think you can truly immerse yourself in mathematics as much as you want. That's why I wonder if it allows for such flexibility.
So, conversely, if you push yourself too hard and too much, for example, something like that will happen. Well, it might happen, or it might not, but, well, if you put it that way, you can commit to mathematics all the time, even on weekends and after returning home, right? And when a period comes where you don't really want to do it, even though you have to, um, if you keep doing it, driven by a compulsive feeling like, 'I don't want to do it but I have to,' well, that in itself, because there's no end to it, I think it will be painful. So, well, I think it's okay to give in to that. So, like, 'after 6 PM, I'll rest.' If you divide your time like that, making your own time your favorite time, well, I think that's good. Well, in terms of busyness, it's an environment where each person can flexibly decide how they want to use their time.
And regarding mathematics, well, having come to graduate school, of course, I'm doing mathematics. But, honestly, I feel both that I've grown and that I still have a long way to go, you know? And, um, well, it's not exactly a dream, but what I think is, the biggest reason I wanted to do mathematics, or rather, why I came to this current environment, is that I want to enhance my expertise. So, if I had to put it, it's like wanting to be the person who knows something best in the world, or wanting to become an elite in that field. Yeah, seeking something that only I can do, admiring having a lot of knowledge, experience, and ideas like that. I actually came in wanting to be like my seniors and professors after seeing them. Well, that's right, isn't it? If I had to say, it's not that your expertise increases just because you become a graduate student. Ultimately, it's something you have to do yourself. So, to be honest, the way you approach things, or what you do, hasn't changed since I was an undergraduate. In other words, it's about studying what you want to know and what you want to learn. Well, in mathematics, I think there are two types of learning: studying thoroughly by settling down, and then there's knowledge as knowledge, its application, or rather, the cutting edge, like just picking up bits and pieces. If you look at it from the perspective of picking up bits and pieces, this university offers many opportunities to hear discussions, with many graduate students around, seniors, and lectures. In that sense, the resolution of knowledge, or rather, you get to know deeper and deeper things. But ultimately, it's something you have to do yourself. But, well, what is it, I wonder? No, I'll talk about this a bit later. It's quite difficult. It's something I haven't been able to fully put into words yet, so.
And so, within that, I want to talk a bit about the issue of AI. AI is already amazing, and honestly, it can do more than I can. It can probably do it. [laughter] And this isn't necessarily a bad thing. Um, well, it might become a bit of a negative story, but it's certainly not entirely negative. For example, if I'm reading a book for an hour and I don't understand a certain famous theorem, and I think about it for about an hour, and still don't understand, even after researching various things, then I ask AI, and it just pops out the answer. So, it's become the case that asking AI gets you the answer much faster than me thinking for an hour. And when I experienced that, I was quite shocked. I had some kind of mysterious pride, you know, some strange pride or stubbornness against this latest technology. I used to think I didn't want to lose to AI, but that's because AI has an enormous amount of knowledge and input, you see. Simply put, AI has a vast amount of literature from the world in its head, and it summarizes related things and just pops them out. So, it's smarter than me. But because of that, I felt somewhat, what is it, some kind of frustration. But, well, among my peers, or rather, in the atmosphere of mathematicians, many people don't really care about AI. In other words, the fact that AI is smarter than oneself doesn't bother them. Well, that's true, isn't it? Indeed. Because being taught by AI is, well, the same as reading a book and studying by yourself, isn't it? Ultimately, reading a book is about, what is it, absorbing the theories that our predecessors discovered. And moreover, being taught by a teacher, or in class, or asking friends about things you don't understand—people in ancient times also did things like that, understanding and making it their own, right? Like reading various books. And if you think of AI as a new tool added to your learning toolkit, if using AI helps your studies, then it's perfectly fine, or rather, it's a normal thing, I think. So, what is it, well, it's also the feeling that what I ultimately do won't change.
In other words, in the process of enhancing your expertise, finding a research topic you want to pursue, and doing what you want to do, why not increasingly borrow the power of AI? If it answers what you want to know—for example, 'what good literature is there?' or 'please organize the overview of a new field'—it's incredibly useful. So, I think that's a good thing. But another thing I've been thinking about quite a lot recently is, well, this is something I don't have an answer for myself, and it's not really worth saying much about, so, well, it's more of a problem definition, or sharing what I'm thinking about. Yeah, research is difficult, you know. How should I put it? What is it, what point is it, I wonder? What is it? It's really that, yeah. What I've always thought is that I want to create something new in the world, or I had a feeling that I wanted to produce new value. But, honestly, to reach that level, my amount of knowledge and experience is very small. Still a long way to go. And, of course, professors, seniors, excellent friends, excellent people, juniors, etc.—they, well, know a lot, and there are many things they can do, of course, right? So, if I had to say, AI is also very much involved. I'm often told that mathematicians' jobs might not be needed anymore, like, 'Do I even need to do research?' if AI can solve everything. At that point, what will I do? Well, I often find myself thinking about that.
What is it? My most recent, well, my will or way of thinking is, after all, that pure interest in mathematics and that pure romance. Why not make these two your motivations? One is enjoying understanding interesting or unknown things by yourself. So, if you can enjoy understanding and absorbing things yourself, then you don't have to worry about AI or, what is it, you don't have to worry about what's around you. That's fine. That, and then, what is it, I wonder? Still, even though I know it's difficult, what is it, the romance I hold for being a mathematician—what kind of thing is it, if you ask? It's that groundbreaking work, or rather, pioneering uncharted territory that only that person can do. I've always felt that kind of pioneering coolness. So, like, um, how Andrew Wiles solved Fermat's Last Theorem, or how Perelman solved the Poincaré conjecture—there are so many examples, right? Like Professor Kashiwara becoming a D-module pioneer and winning the Abel Prize. And those kinds of things, well, what is it? What I've learned and understood up to this point is that, after all, each professor has their own unique themes and problem awareness they're thinking about. And each researcher, yeah, has something they want to discover. Well, it's not really that, yeah. It's not something super romantic, actually, in reality. In other words, it's not like everyone is burning with passion, doing it or wanting to do it. But within myself, somehow, potentially, faintly, there's an admiration, like wanting to do really groundbreaking work, really interesting things. I've always kept that flame burning, and if I can keep doing that, well, I think it would be a fun thing.
So, um, to summarize, where do I find motivation? It's simply the joy of understanding interesting things and sharing them. And also, that super top-tier, what is it, something incredibly brilliant. That I'm going to do amazing work. Well, if I had to say, it's like admiring Shohei Ohtani in baseball and aiming for that, or admiring Sota Fujii in Shogi and aiming for that level. That kind of aspiration, that kind of romantic ideal—it's not necessarily about being someone who has always held onto it, but rather, if you have it somewhat potentially, then I think that's perfectly fine, you see.
Um, that's how it is. These are my recent feelings. I really wanted to film for YouTube, and then do a lot of editing, and prepare various things properly before speaking, but I didn't really have the time for that. On the other hand, I wanted to release a video so badly that I was about to go crazy, so this is also a form of stress relief, you see. So everyone, um, if you have anything you want to ask RIMS, please say so. And, um, if there's anything you want me to research, please say so. Um, I'll think about it. Please leave it to me to somehow try to research it. That's, that's how it is.