 Dear Fellow Scholars, this is 2 Minute Papers with Dr. Karajol Leifahir. I cannot tell you how excited I am by this paper. Wow! Today, you will see more incredible images generated by Google's newest AI called Party. Yes, this is not from OpenAI, but from Google. So, what is going on here? Just a few months ago, OpenAI's Image Generator AI called Dolly II took the world by storm. With that, you could name almost anything, Katnopolian, a teddy bear on a skateboard, on Times Square, a basketball player, dunking as an explosion of a nebula, and it was able to create an appropriate image for it. It is also good enough to be used in our own thumbnails. However, there was one interesting thing about it. What do you think the prompt for this must have been? Hmm, not easy, right? Well, it was a sign that says Deep Learning. Oh yes, this was one of the failure cases. Please remember this. Now, we always say that in research, do not look at where we are, always look at where we will be, two more papers down the line. That is the first law of papers. However, we didn't even make it to two more papers down the line. What's more, we barely made two months down the line, and scientists at Google came up with an amazing follow-up paper. It was called Imogen. Imogen was absolutely incredible as it could now finally synthesize text properly. It could also understand when we say a couple of glasses on a table, and one this little linguistic battle against OpenAI's Dolly II. And all this just two months after it. That is absolutely amazing. But hold on to your papers because you won't believe this one. I certainly didn't when I saw it first. Just about one month after Imogen, here is an even newer paper on AI image generation called Party. That is fantastic. Welcome to our world, little AI. But why does this exist? Well, this is why. I'll explain in a moment, but first, let's have a look at what it can do through three of my favorite examples, and then we'll discuss why it exists. One, let's start with the banger, and recreate the legendary Napoleon cat with the new method. This is Dolly II's solution, and let's see the new one. I cannot believe it. This is at least as good as Dolly II's legendary solution, and I have to say maybe even a touch better. What a time to be alive. Two, a crocodile made of water. As someone who has spent some time researching, controlling, fluid, and smoke simulations, this one is highly appreciated. Three, a detailed Athenian vase with Egyptian hieroglyphics. And more. I love how Party was able to bring all of these concepts together into one coherent solution. This may be subjective, but if someone told me that a person made this, I would say that person is quite creative. But creativity in a machine, how cool is that? Now, remember this image, I said that this is why Party exists. So, what is going on here? Well, look, the two previous techniques used a diffusion-based model. This means that when we ask it something, it starts out from noise and over time, it learns to organize these pixels to form a beautiful image that matches our description better. Now, look. Aha! This Party technique is not a diffusion-based model, it is an autoregressive model. What does that mean? It means that it uses no diffusion, it does not create a piece of noise and refine it into an image. Mm-hmm, no sir. Instead, it thinks of an image as a collection of little puzzle pieces. Why? Well, this hopefully helps with two other shortcomings of Dolly II. One is generating a specific number of objects that did not work too well before. And it can also deal with super long prompts, much longer than previous ones. You got me excited now? You know what? Let's test that right now together. Let's add this prompt. Oh my goodness, now that is a long prompt. Who can paint this? Almost nobody. In fact, it is the description of Van Gogh's Starry Night without saying that we are looking for Starry Night. I am itching to see this. And... Oh wow. All of them are lovely. Now, we have two more really spectacular things about this paper. One, we can witness how it learns to draw these beautiful images as we increase the model size, which roughly tells us how capable the AI is. We can take a smaller model and ask it to create a kangaroo with sunglasses and a sign that says hello friends and we get this. Well, that is a start. It can't really write yet and the details are lacking. But when we use the same architecture with the difference that we increase the model size to be about 50 times bigger, we get this. Oh my goodness. It not only learns to write, but the quality of the output is also leaps and bounds better. What do you think what results would another 50 fold increase result in? That must be something truly incredible. Let me know in the comments below. Alongside the paper, scientists at Google also released a bunch of prompts as a benchmark for testing future image generator AI's. And yes, there are some good ones in there, but if I may make some recommendations, I would love to see some of these prompts of mine in such a benchmark. For instance, the Fox scientists, the scholars and the cyber frog are very well received by you fellow scholars and it would be super cool to be able to compare how new, more elaborate AI models are able to deal with these. I also put a text version of these in the video description if someone is interested. So it's official. The age of beautiful AI generated images is now here. Does this get your mind going? What do you think? Let me know in the comments below. If you're looking for inexpensive cloud GPUs for AI, Lambda now offers the best prices in the world for GPU cloud compute. No commitments or negotiation required. Just sign up and launch an instance and hold on to your papers because with Lambda GPU cloud, you can get on demand a 100 instances for $1.10 per hour versus $4.10 per hour with AWS. That's 73% savings. Did I mention they also offer persistent storage, so join researchers at organizations like Apple, MIT and Caltech in using Lambda cloud instances, workstations or servers. Make sure to go to lambdalabs.com slash papers to sign up for one of their amazing GPU instances today. Thanks for watching and for your generous support, and I'll see you next time.