Beginners are often focused on, like, what to do, and I think the focus should be more like how much you do. So I I am kind of, like, believer on the high level in this 10000 hours kind of concept where you just kinda have to just pick the things where you can spend time and you you care about and you're interested in. You literally have to put in 10000 hours of work. Mhmm. It doesn't even, like, matter as much, like, where you put it and you're you'll iterate and you'll improve and you'll waste some time. I don't know if there's a better way. You need to put in 10000 hours. But I think it's actually really nice because I feel like there's some sense of determinism about, being an expert at a thing if you spend 10000 hours. You can literally pick an arbitrary thing. And I think if you spend 10000 hours of deliberate effort and work, you actually will become an expert at it. It. And so I think it's kind of like a a nice thought. Mhmm. And so, basically, I would focus more on, like, are you spending 10000 hours? That's what I would focus on. So so and then thinking about what kind of mechanisms maximize your likelihood of getting to 10000 hours Exactly. Which for us, silly humans means probably forming a daily habit of, like, every single day, actually doing the thing. Whatever helps you. So I do think to a large extent, it's a psychological problem for yourself. Yeah. One other thing that I help that I think is helpful for the psychology of it is many times people compare themselves to others in the area. I think this is very harmful. Only compare yourself to you from some time ago. Mhmm. Like, say, a year ago. Are you better than you a year ago? It's the only way to think. And I think this then you can see your progress, and it's very motivating. That's so interesting that focus on the quantity of hours. Because I think a lot of people, in the beginner stage, but actually throughout, get paralyzed, by, the choice. Like, which one do I pick this path or this path? Yeah. Like, they'll literally get paralyzed by, like, which IDE to use. Well, they're worried yeah. They're worried about all these things. But the thing is some of the you you will waste time doing something wrong. Yes. You will eventually figure out it's not right. You will accumulate scar tissue. Mhmm. And next time, you'll grow stronger. Because next time, you'll have the scar tissue, and next time, you'll learn from it. And now next time you come to a similar situation, you'll be like, oh, I I messed up. I've spent a lot of time working on things that never materialized into anything. And I have all that scar tissue, and I have some intuitions about what was useful, what wasn't useful, how things turned out. So all those mistakes were, were not dead work. You know? Mhmm. So I just think you should they should just focus on working. What have you done? What have you done last week? That's a good question actually to ask for for a lot of things, not just machine learning. It's a good way to cut the the I forgot what the term we used, but the fluff, the blubber, whatever the, the inefficiencies in life. What do you love about teaching? You seem to find yourself often in the like, drawn to teaching. You're very good at it, but you're also drawn to it. I mean, I don't think I love teaching. I love happy humans, and happy humans like when I teach.