 We are going to start with the most difficult thing in the entire semester. It's about how to pronounce my name. Okay? Can you please find the lights for this spotlight because it's a bit hard to see? Oh, alright. I forgot this. Okay. This one? Yes. Okay. So, I am from Hungary and this is pronounced as Kaui Jone. Kaui is essentially the equivalent of Kaui in Deutsch or Charles in English. Jone is often there is no equivalent for that. So, I am sorry. So, it is pronounced as Kaui. If you imagine this as like an English word, then you forget the L and you just pronounce it like that. So, it's Kaui. Okay? So, I'd like to hear some examples of Kaui. Kaui. Okay? Kaui. Yes? Kaui. Excellent. Kaui. A bit louder? Kaui. It's the answer to the answer. So, it's Kaui. So, it's like a Y at the end. It's Kaui. One more time. Kaui. Lada. Kaui. Yes. Excellent. Kaui. Kaui. Wow. It's amazing. Okay. Now, how comes the hard part? So, this is pronounced as Jone. Okay? So, it's Hungarian. It's a weird language where Z and S is actually one letter. So, if you take a look at the Hungarian alphabet, there's a letter that is Z. There's a letter that is S. And there's a third letter that is Z and S together. So, it's pretty ridiculous, isn't it? So, this is pronounced as Jone. So, the Sch is the difficult part. Okay. Jone. Wow. Jone. Yes. It's a good word. Jone. Hi. Can you pronounce Jone? Jone. Yeah. It's just a common thing. You don't need to be meaning anything. Okay. Jone. Yes. Jone. Yes. Jone. Yes. Wow. Are you Hungarian? No, not really. I mean, Hungarian. Yes. Parents may be sicker than maybe. Mining, okay. Jone. Yeah. Wow. It's great. It's not Jone. Jone. Jone. Okay. Is there someone who I have forgotten? Or everyone knows what's up. Okay. So, this is what we're going to be doing. So, the amazing thing is that when you see images on the Internet like that, sometimes it's difficult to find out if this is computer graphics or is it a real photograph. And this is one of these examples. This is another example. And this is the work of amazing engineers and amazing artists. And we are going to be talking about how to compute images like that. And if you look at this, well, when you download the slides at home, you will see that on the lens, the dust is modeled. Here you can see just some small splotges, but you can actually see pieces of dust on the lens of the camera. And this is computed with the computer program. And by the end of the semester, you are going to know everything about this. How is this exactly computed? Every single pixel. Just a few things about organization. There's going to be assignments. They take up 40% of your grade. And these assignments will have, most of them will have theoretical parts, pen and paper, how to understand what's going on in nature. And there will be also programming exercises, but they are not really that programming exercises. It's mostly using programs, understanding what they are doing, and maybe modifying them here and there. But you are not going to write huge rendering engines and things like that. So don't worry about this. The 60% part is a world exam. And this is going to take place after the semester with me. So this is some friendly discussion about what you have learned. Or not so friendly discussion if you haven't learned anything. But that's never been case. So I'm just kidding. And this is going to take place with me. But you can choose. So if you would like to have the exam with Thomas, that's also fine. But I would like to note that I am an engineer. And he's a brilliant physicist. So if you choose who to try to deal with, I would choose the engineer. I don't know about you, but. Just a suggestion. And there can be some kind of individual contribution. So if you find some errors on the slides, if you add some figures that, hey, I don't like this figure, I've drawn something better than that. There's going to be programs that we work with. If you find some bugs in there, or if you can extend it in any way, you can get plus points. And this applies to basically any kind of contribution that you have. This is the book that we're going to learn from. So there is a trying to cover everything. And at some point, I will say that, yeah, please open the book if you would like to know more about this. But whatever I tell you here, it's going to be enough for an exam. So it's not going to happen that, hey, why haven't you read, I don't know, page 859. Don't you remember that? This is not going to happen. So this is to augment your knowledge. If you would like to know more, and this is a great place to do. And this has a website. This can be bought at different places. There is some sample chapters. And before buying, you can take a look whether you like it enough or not. So it's pretty cool that it has sample chapters. Let's start with what you shouldn't expect from this course. I'll just run through it. There's not going to be rigorous derivations of every imaginable equation that you have. So there are courses where there is this never ending infinite loop like in programming. An infinite loop of definition theorem, corollary definition theorem, theorem, lemma. Raise your hand if you've been to a course like that. I'm not going to tell anyone. I'm not going to tell anyone. So I've had a lot of these courses and I've had enough. So I'm trying to do it differently. There's not going to be endless derivations. There's not going to be an endless stream of formulae as well without explanation. There's going to be formulae, but with explanation we're going to play with all of them. And you are going to understand the core meaning of these things. And at the same time, please don't expect to understand everything if you open, for instance, the Luxrender source code. This is like a half a million line of code project. One of the best renders out there. But there's many. There's many really good renders. You will not understand every single thing that is there, but you will understand how the light transport part works. As thoroughly as possible. And the most important thing I've put it there in bold because this is what students love. You don't have to memorize any of the formulae. I will never tell you that, give me this formula and you will have to remember it off your head. I don't care. If you're an engineer at a company, you'll see that you need to solve a problem. Remember something, what you do. Google. And you look for it. It's not important to remember things. It's important to understand things. So if you look at the formula, you will have to understand what is going on. And that's intuition. This is what I would like you to have as much as possible, but you don't need to memorize any of these. Now, what you should expect from this course is how to simulate light in a simple and elegant way. This is going to be a surprise at first because things are going to look complicated. And by the end, we're going to derive really simple solutions for that that can be implemented in 200 lines of C++. So these 200 lines can compute something that's almost as beautiful as what you have seen here. And I have written this piece of code and every theorem that we learn about, you are going to see them in code. In fact, there's going to be an entire lecture on code review. Let's go through this renderer. And see there is Schlich's approximation. There is Snell's law. There is this and that. And everything you learn here, you are going to see in code. It's not just flying out and doing no. You will know why nature looks like as it does in real life. And you will be wondering that there's so many beautiful things and why haven't I seen them the way they are. Why are they looking the way they are? And you will know about also most of the state of the art in global illumination. This means that yes, we will start with algorithms from 1968. And we will end with algorithms from this year, like from two weeks ago, or in the next few weeks, because the C-graph is coming, like the C-graph paper, the biggest conference with the best of the bunch is coming in the next few weeks. And I'm going to read through it and the materials will be updated to the very latest works. And another thing is that really important is that you will be able to visualize and understand complicated formulae in a really intuitive way. So I would like you to learn something that's not only life transport specific, but you will be able to use this knowledge wherever you go, whatever kind of mathematical problems you have, this knowledge will be useful. And you will see from the very first lecture. And the most important thing is that you will see the world differently. There is lots of beautiful things in nature and you won't be able to stop looking at it. So you will perhaps like taking the train on public transport a bit more than before, because there's so many intricate, delicate things to see that you haven't seen before. You've looked, but you haven't seen them before. Stay up.