Google DeepMind's New AI Robot & AGI by 2027!

Google DeepMind just made a robot that can play ping pong against humans and even win some matches. Meanwhile, Boston Dynamics Atlas robot is showing off its strength, doing push ups and burpees like it's training for a marathon. On top of that, scientists are building a global network of supercomputers to speed up the development of artificial general intelligence, aiming to create AI that can think and learn more like humans. We're covering all these topics in this video, so stick around. But first let's jump into the story about the AI robot taking on table tennis. So Google DeepMind, the AI powerhouse that's been behind some crazy tech, has trained a robot to play ping pong against humans. And honestly, it's kind of blowing my mind. Alright, so here's the deal. Google DeepMind didn't just teach this robot to like casually hit the ball back and forth. No, they went all in and got this robotic arm to play full on competitive table tennis. And guess what? It's actually good enough to beat some humans. Yeah, no kidding. They had this bot play 29 games against people with different skill levels and it won 13 of them. That's almost half the matches, which for a robot is pretty wild. Okay, so let's break down how this all went down. To train this robot, DeepMind's team used a two step approach. First, they put the bot through its paces in a computer simulation where it learned all the basic moves, things like how to return a serve, hit a forehand topspin or nail a backhand shot. Then they took what the robot learned in the sim and fine tuned it with real world data. So every time it played, it was learning and getting better. Now to get even more specific, this robot tracks the ball using a pair of cameras which like capture everything happening in real time. It also follows the human player's movements using a motion capture system. This setup uses LEDs on the player's paddle to keep track of how they're swinging. All that data gets fed back into the simulation for more creating this super cool feedback loop where the bot is constantly refining its game. But guys, it's not all smooth sailing for our robotic ping pong player. There are a few things it still struggles with. For example, if you hit the ball really fast, send it high up or hit it super low, the robot can miss. It's also not great at dealing with spin, something that more advanced players use to mess with their opponents. The robot just can't measure spin directly yet, so it's a bit of a weak spot. Now, something I found really interesting is is that the robot can't serve the ball. So in these matches, they had to tweak the rules a bit to make it work. And, yeah, that's a bit of a limitation, but hey, it's a start, right? Anyway, the researchers over at DeepMind weren't even sure if the robot would be able to win any matches at all. But it turns out not only did it win, but it even managed to outmaneuver some pretty decent players. Panag Sanketti, the guy leading the project, said they were totally blown away by how well it performed, like they didn't expect it to do this well, especially against people it hadn't played before. And this isn't just a gimmick, guys. This kind of research is actually a big deal for the future of robotics. I mean, the ultimate goal here is to create robots that can do useful tasks in real environments, like your home or a warehouse, and do them safely and skillfully. This table tennis bot is just one example of how robots could eventually learn to work around us and with us, and maybe even help us out in ways we haven't even thought of yet. Other experts in the field, like Larel Pinto from nyu, are saying that this is a really exciting step forward. Even though the robot isn't a world champion or anything, it's got the basics down, and that's a big deal. The potential for improvement is huge. And who knows, we might see this kind of tech in all sorts of robots in the near future. But let's not get too ahead of ourselves. There's some still a long way to go before robots are dominating in sports or anything like that. For one, training a robot in a simulated environment to handle all the crazy stuff that happens in the real world is super tough. There are so many variables, like a gust of wind or even just a little bit of dust on the table that can mess things up. Chris Walte, who's a big name in robotics, pointed out that without realistic simulations, there's always going to be a ceiling on how good these robots can get. That said, Google, DeepMind is already thinking ahead. They're working on some new tech, like predictive AI models that could help the robot anticipate where the ball's going to go and better algorithms to avoid collisions. This could help the robot overcome some of its current limitations and get even better at the game. And here's the best part, at least for me. The human players actually enjoyed playing against the robot. Even the more advanced players who were able to beat it said they had fun and thought the robot could be a great practice partner. Like imagine having a robot you could play with any time time you wanted to sharpen your skills. One of the guys in the study even said he'd love to have the robot as a training buddy. Okay, now something interesting has surfaced about Boston Dynamics Atlas robot. The humanoid hub on Twitter recently shared a video of Atlas doing push ups and it's part of an eight hour long presentation. There's not much info available yet, but it's fascinating to see Atlas performing not just push ups, but even a burpee. The movements are incredibly fluid and almost human like. But here's the real question. Does it get stronger after each set? I hope not, because it looks like it could do push ups forever. Alright, now let's talk about something really fascinating that's happening right now. Scientists are working on building a global network of supercomputers to speed up the development of what's known as Artificial General intelligence or AGI for short. And we're not just talking about an AI that excels in one thing like playing table tennis or generating text. It's something that can learn, adapt and improve its decision making across the board. It's kind of scary, but also super exciting. Right? So these researchers are starting by bringing a brand new supercomputer online in September. And that's just the beginning. This network is supposed to be fully up and running by 2025. Now what's cool about this setup is that it's not just one supercomputer doing all the heavy lifting. It's actually a network of these machines working together, which they're calling a multi level cognitive computing network. Think of it as a giant brain made up of several smaller brains, all connected and working together to solve problems. Now what's really interesting is that these supercomputers are going to be packed with some of the most advanced AI hardware out there. We're talking about components like Nvidia L40s, GPUs, AMD Instinct processors, and some crazy stuff like 10 storage wormholes, server racks. If you're into the tech side of things, you know this is some serious muscle. Alright, so what's the point of all this? Well, according to the folks over at SingularityNET, the company behind this project, they're aiming to transition from current AI models, which are heavily reliant on big data, to something much more sophisticated. Their goal is to create AI that can think more like humans, with the ability to make decisions based on multi step reasoning and dynamic world modeling. It's like moving from An AI that just repeats what it's been taught to one that can think on its own. Ben Goertzel, the CEO of SingularityNET, basically said that this new supercomputer is going to be a game changer for AGI. He talked about how their new neural symbolic AI approaches could reduce the need for massive amounts of data and energy, which is a big deal when you're talking about scaling up to something AS complex as AGI. And if you're into the bigger picture, SingularityNET is part of this group called the Artificial Superintelligence alliance, or asi. These guys are all about open source AI research, which means they want to make sure that as we get closer to creating AGI, the technology is accessible and transparent. Oh, and speaking of timelines, we've got some pretty bold predictions here. Some leaders in the AI space, like the co founder of DeepMind, are saying we could see human level AI by 2028. Ben Goertzel, on the other hand, thinks we might hit that milestone as soon as 2027. And let's not forget Mark Zuckerberg. He's also in the race, throwing billions of dollars into this pursuit. We're so close to creating machines that could potentially surpass our intelligence. Whether that's a good or bad thing, we will soon find out. The next few years in AI are going to be absolutely insane. Alright, if you found this video helpful or interesting, don't forget to smash that like button, hit subscribe and ring the bell so you don't miss any of my future videos. Thanks for watching and I'll see you in the next one.