 Dear Fellow Scholars, this is Two Minute Papers with Dr. Karo Zsolnai-Fehir. Today we are going to simulate thousands of years of vegetation in a virtual world. And I am telling you, this paper is unbelievable. Now, normally, if we are building a virtual world, we don't really think about simulating a physics and biology-based ecosystem. Let's be honest, it's more like, yeah, just throw in some trees, and we are done here. But, in reality, the kinds of vegetation we have in a virtual world should be at the very least a function of precipitation and temperature. And here, at this point, we know that this paper means business. You see, if there is no rain and it's super cold, we get a tundra. With no rain and high temperature, we get a desert. And if we keep the temperature high and add a ton of precipitation, we get a tropical rainforest. And this technique promises to be able to simulate these and everything in between. See these beautiful little worlds here? These are not illustrations. No, no, these are already the result of the simulation program. Nice. Now, let's run a tiny simulation with 400 years and a few hundred plants. Step number one, the first few decades are dominated by these shrubs blocking away the sunlight from everyone else. But, over time, step two, watch these resilient pine trees slowly overtake them and deny them their precious sunlight. And what happens as a result? Look, they're downfall, brings forth a complete ecosystem change. And then, step three, screw trees start to appear. This changes the game. Why? Well, these are more shade tolerant and let's see. Yes, they take over the ecosystem from the pine trees. A beautifully done story in such a little simulation. I absolutely love it. Of course, any suffering-specting virtual world will also contain other objects, not just the vegetation, and the simulator says no problem. Just chuck them in there and we'll just react accordingly and grow around it. Now, let's see a mid-size simulation. Look at that. Imagine the previous story with the pine trees, but with not a few hundred, but a hundred thousand plants. This can simulate that too. And now comes the final boss, a large simulation. Half a million plants and more than a thousand years. Yes, really. Let's see the story here in images first and then you will see the full simulation. Yes, over the first hundred years, fast growing shrubs dominate and start growing everywhere. And after a few hundred more years, the slower growing trees catch up and start overshadowing the shrubs at lower elevation levels. And then more kinds of trees appear at lower elevations and slowly over 1400 years, a beautiful mixed-age forest emerges. I shiver just thinking about the fact that through the power of computer graphics research works, we can simulate all this on a computer. What a time to be alive. And while we look at the full simulation, please note that there is more happening here, make sure to have a look at the paper in the video description if you wish to know more details. Now about the paper. And here comes an additional interesting part. As of the making of this video, this paper has been referred to 20 times. Yes, but this paper is from 2019, so it had years to soak up some citations, which didn't really happen. Now note that one citations are not everything, and two, 20 citations for a paper in the field of computer graphics is not bad at all. But every time I see an amazing paper, I really wish that more people would hear about it, and always I find that almost nobody knows about them. And once again, this is why I started to make two-minute papers. Thank you so much for coming on this amazing journey with me. Perceptilebs is a visual API for TensorFlow carefully designed to make machine learning as intuitive as possible. This gives you a faster way to build out models with more transparency into how your model is architected, how it performs, and how to debug it. And it even generates visualizations for all the model variables, and gives you recommendations both during modeling and training, and thus all this automatically. I only wish I had a tool like this when I was working on my neural networks during my PhD years. Visit perceptilebs.com, slash papers, and start using their system for free today. Thanks to perceptilebs for their support, and for helping us make better videos for you. Thanks for watching and for your generous support, and I'll see you next time.