Google Deep Mind has developed an AI-powerd robot capable of playing and winning ping pong matches against human opponents.
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00:00Google DeepMind just made a robot that can play ping pong against humans and even win
00:06some matches.
00:07Meanwhile, Boston Dynamics' Atlas robot is showing off its strength, doing push-ups
00:11and burpees like it's training for a marathon.
00:13On top of that, scientists are building a global network of supercomputers to speed
00:17up the development of artificial general intelligence, aiming to create AI that can think and learn
00:23more like humans.
00:24We're covering all these topics in this video, so stick around.
00:27But first, let's jump into the story about the AI robot taking on table tennis.
00:31So Google DeepMind, the AI powerhouse that's been behind some crazy tech, has trained a
00:36robot to play ping pong against humans and honestly, it's kind of blowing my mind.
00:41All right, so here's the deal.
00:43Google DeepMind didn't just teach this robot to like casually hit the ball back and forth.
00:48No, they went all in and got this robotic arm to play full-on competitive table tennis.
00:54And guess what?
00:55It's actually good enough to beat some humans.
00:57Yeah, no kidding.
01:01They had this bot play 29 games against people with different skill levels and it won 13
01:06of them.
01:07That's almost half the matches, which for a robot is pretty wild.
01:10Okay, so let's break down how this all went down.
01:13To train this robot, DeepMind's team used a two-step approach.
01:16First, they put the bot through its paces in a computer simulation where it learned
01:20all the basic moves, things like how to return a serve, hit a forehand topspin, or nail a
01:25backhand shot.
01:27Then they took what the robot learned in the sim and fine-tuned it with real-world data.
01:31So every time it played, it was learning and getting better.
01:34Now, to get even more specific, this robot tracks the ball using a pair of cameras, which
01:38like capture everything happening in real time.
01:41It also follows the human player's movements using a motion capture system.
01:46This setup uses LEDs on the player's paddle to keep track of how they're swinging.
01:50All that data gets fed back into the simulation for more training, creating this super cool
01:55feedback loop where the bot is constantly refining its game.
02:00But guys, it's not all smooth sailing for our robotic ping pong player.
02:04There are a few things it still struggles with.
02:06For example, if you hit the ball really fast, send it high up or hit it super low, the robot
02:11can miss.
02:12It's also not great at dealing with spin, something that more advanced players use to
02:16mess with their opponents.
02:18The robot just can't measure spin directly yet, so it's a bit of a weak spot.
02:22Now, something I found really interesting is that the robot can't serve the ball.
02:27So in these matches, they had to tweak the rules a bit to make it work.
02:31And yeah, that's a bit of a limitation, but hey, it's a start, right?
02:35Anyway, the researchers over at DeepMind weren't even sure if the robot would be able to win
02:39any matches at all, but it turns out not only did it win, but it even managed to outmaneuver
02:44some pretty decent players.
02:46Panag Sankedi, the guy leading the project, said they were totally blown away by how well
02:50it performed.
02:52They didn't expect it to do this well, especially against people it hadn't played before.
02:55And this isn't just a gimmick, guys.
02:58This kind of research is actually a big deal for the future of robotics.
03:02I mean, the ultimate goal here is to create robots that can do useful tasks in real environments,
03:08like your home or a warehouse, and do them safely and skillfully.
03:12This table tennis bot is just one example of how robots could eventually learn to work
03:16around us and with us, and maybe even help us out in ways we haven't even thought of
03:19yet.
03:20Some experts in the field, like Lerol Pinto from NYU, are saying that this is a really
03:25exciting step forward.
03:27Even though the robot isn't a world champion or anything, it's got the basics down.
03:32And that's a big deal.
03:33The potential for improvement is huge.
03:36And who knows?
03:37We might see this kind of tech in all sorts of robots in the near future, but let's not
03:41get too ahead of ourselves.
03:42There's still a long way to go before robots are dominating in sports or anything like
03:48that.
03:49And getting a robot in a simulated environment to handle all the crazy stuff that happens
03:53in the real world is super tough.
03:55There are so many variables, like a gust of wind or even just a little bit of dust on
04:00the table, that can mess things up.
04:02Chris Walty, who's a big name in robotics, pointed out that without realistic simulations,
04:07there's always going to be a ceiling on how good these robots can get.
04:10That said, Google DeepMind is already thinking ahead.
04:13They're working on some new tech, like predictive AI models that could help the robot anticipate
04:18where the ball is going to go, and better algorithms to avoid collisions.
04:22This could help the robot overcome some of its current limitations and get even better
04:26at the game.
04:27And here's the best part, at least for me.
04:28The human players actually enjoyed playing against the robot.
04:32Even the more advanced players, who were able to beat it, said they had fun and thought
04:36the robot could be a great practice partner.
04:38Like imagine having a robot you could play with anytime you wanted to sharpen your skills.
04:44One of the guys in the study even said he'd love to have the robot as a training buddy.
04:49Okay, now something interesting has surfaced about Boston Dynamics' Atlas robot.
04:53The Humanoid Hub on Twitter recently shared a video of Atlas doing push-ups, and it's
04:58part of an 8-hour long presentation.
05:00There's not much info available yet, but it's fascinating to see Atlas performing
05:04not just push-ups, but even a burpee.
05:07The movements are incredibly fluid and almost human-like.
05:10But here's the real question, does it get stronger after each set?
05:14I hope not, because it looks like it could do push-ups forever.
05:17Alright, now let's talk about something really fascinating that's happening right now.
05:23Scientists are working on building a global network of supercomputers to speed up the
05:27development of what's known as Artificial General Intelligence, or AGI for short.
05:32And we're not just talking about an AI that excels in one thing, like playing table tennis
05:36or generating text.
05:37It's something that can learn, adapt, and improve its decision-making across the board.
05:42That's kind of scary, but also super exciting, right?
05:45So these researchers are starting by bringing a brand new supercomputer online in September.
05:50And that's just the beginning.
05:52This network is supposed to be fully up and running by 2025.
05:55Now what's cool about this setup is that it's not just one supercomputer doing all
05:59the heavy lifting.
06:00It's actually a network of these machines working together, which they're calling a
06:05multi-level cognitive computing network.
06:07Think of it as a giant brain made up of several smaller brains, all connected and working
06:12together to solve problems.
06:13Now what's really interesting is that these supercomputers are going to be packed with
06:16some of the most advanced AI hardware out there.
06:19We're talking about components like NVIDIA L40s GPUs, AMD Instinct processors, and some
06:25crazy stuff like Tenstorrent wormhole server racks.
06:28If you're into the tech side of things, you know this is some serious muscle.
06:32Alright, so what's the point of all this?
06:34Well, according to the folks over at SingularityNet, the company behind this project, they're aiming
06:39to transition from current AI models, which are heavily reliant on big data, to something
06:44much more sophisticated.
06:45Their goal is to create AI that can think more like humans, with the ability to make
06:50decisions based on multi-step reasoning and dynamic world modeling.
06:54It's like moving from an AI that just repeats what it's been taught to one that can think
06:58on its own.
06:59Ben Goertzel, the CEO of SingularityNet, basically said that this new supercomputer is going
07:04to be a game changer for AGI.
07:06We talked about how their new neural symbolic AI approaches could reduce the need for massive
07:11amounts of data and energy, which is a big deal when you're talking about scaling up
07:15to something as complex as AGI.
07:17And if you're into the bigger picture, SingularityNet is part of this group called the Artificial
07:22Super Intelligence Alliance, or ASI.
07:25These guys are all about open source AI research, which means they want to make sure that as
07:29we get closer to creating AGI, the technology is accessible and transparent.
07:34Oh, and speaking of timelines, we've got some pretty bold predictions here.
07:38Some leaders in the AI space, like the co-founder of DeepMind, are saying we could see human-level
07:43AI by 2028.
07:45Ben Goertzel, on the other hand, thinks we might hit that milestone as soon as 2027.
07:50And let's not forget Mark Zuckerberg.
07:52He's also in the race.
07:53Throwing billions of dollars into this pursuit, we're so close to creating machines that
07:57could potentially surpass our intelligence.
07:59Whether that's a good or bad thing, we will soon find out.
08:02The next few years in AI are going to be absolutely insane.
08:05Alright, if you found this video helpful or interesting, don't forget to smash that
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08:14Thanks for watching, and I'll see you in the next one.