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New episode tomorrow on the path to fully autonomous robots with Sergey Levine One question I had for him: why won't robotics be like self driving cars? Google started their self driving project in 2009. And for over a decade and half, we’ve had the kinds of cool demos... we sometimes now see for robotics, without any commercially viable and widely deployed machines. Sergey thinks we're in a different regime with robotics today, for 2 reasons: 1. Mistakes are way less costly (killing someone versus breaking a dish), so you can deploy much earlier and actually learn from those mistakes in deployement. 2. LLMs give robots a level of common sense which significantly boosts their generality. "You can say, 'Hey, there's a sign that says slippery floor. What's going to happen when I walk over that?' No autonomous car in 2009 would have been able to answer that question." Full episode out tomorrow!show more

Dwarkesh Patel

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A question I kept returning to was how soon robots will be ubiquitous in our daily lives. Sergey uses self-driving as an analogy, but explains why robotics may not follow the same path because the cost of mistakes is very different. Self-driving took over a decade and is still in its nascency, in part because even rare mistakes are unacceptable. Robots may deploy earlier, and improve faster, because some mistakes are tolerable. Breaking a dish is different from causing an accident.

A question I kept returning to was how soon robots will be ubiquitous in our daily lives. Sergey uses self-driving as an analogy, but explains why robotics may not follow the same path because the cost of mistakes is very different. Self-driving took over a decade and is still in its nascency, in part because even rare mistakes are unacceptable. Robots may deploy earlier, and improve faster, because some mistakes are tolerable. Breaking a dish is different from causing an accident.

Patrick OShaughnessy

57,780 Aufrufe • vor 4 Monaten

.Sergey Levine is one of the world's leading robotics researchers (and co-founder of Physical Intelligence). He thinks fully autonomous robots are much closer than people realize - when I pushed him on a prediction, he said 5 years to robots that can autonomously run your household). The big game changer, in his view, is that we finally have LLMs with common sense and prior knowledge that we can scaffold the robot models around. We get into all the reasons this might not happen, the data flywheel from deployment, architecture, simulation, manufacturing, and much more. Enjoy! 0:00:00 – Timeline to widely deployed autonomous robots 0:22:12 – Why robotics will scale faster than self-driving cars 0:32:15 – How vision-language-action models work 0:50:26 – Improvements needed for brainlike efficiency 1:02:48 – Learning from simulation 1:14:08 – How much will robots speed up AI buildouts? 1:22:54 – If hardware’s the bottleneck, does China win by default?

.Sergey Levine is one of the world's leading robotics researchers (and co-founder of Physical Intelligence). He thinks fully autonomous robots are much closer than people realize - when I pushed him on a prediction, he said 5 years to robots that can autonomously run your household). The big game changer, in his view, is that we finally have LLMs with common sense and prior knowledge that we can scaffold the robot models around. We get into all the reasons this might not happen, the data flywheel from deployment, architecture, simulation, manufacturing, and much more. Enjoy! 0:00:00 – Timeline to widely deployed autonomous robots 0:22:12 – Why robotics will scale faster than self-driving cars 0:32:15 – How vision-language-action models work 0:50:26 – Improvements needed for brainlike efficiency 1:02:48 – Learning from simulation 1:14:08 – How much will robots speed up AI buildouts? 1:22:54 – If hardware’s the bottleneck, does China win by default?

Dwarkesh Patel

211,158 Aufrufe • vor 11 Monaten

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing

My conversation with Sergey Levine (Sergey Levine). Sergey is the co-founder of Physical Intelligence -- a company building foundation models that can control any robot to do any task in any environment. The company's thesis is that generality is more scalable than specialization, meaning that a model trained across many different robots and tasks will ultimately outperform any system built to do one thing well (eg, just wash dishes). Sergey is a researcher by background, but I think you will appreciate how practical and commercially grounded this conversation is. We discuss: - Why changing a diaper will be the last task a robot masters - The simulation v. real-world data debate - How multimodal LLMs give robots common sense - Moravec's Paradox + Robot Olympics - Why robots can do long-horizon tasks now - A realistic timeline for robots in our homes I should note that I am an investor in Physical Intelligence -- I made the investment because I believe it is one of the most important companies tackling the problem of robotics. Enjoy! Timestamps: 0:00 Intro 2:39 Defining Physical Intelligence 5:19 The Challenge of Building General Models 6:34 The Stakes and Future of General Purpose Robotics 8:15 Pros and Cons of Humanoid Robots 10:12 Historical Milestones in Robotics Research 15:31 Combining Generative AI and Deep RL 21:24 Moravec's Paradox 25:33 Kitchen Robots 29:30 Simulation vs. Real-World Data 30:48 The Robot Olympics 36:31 The Physiological Reality of Embodiment 38:56 Controversies in the Robotics Community 44:18 What Makes a Great Researcher 48:27 How Businesses Should Prepare for Robotics 54:09 Tracking Progress Through Research Papers 57:02 The Next Step: Mid-Level Reasoning 1:02:00 The Kindest Thing

Patrick OShaughnessy

133,833 Aufrufe • vor 4 Monaten

Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”

Elon Musk in new interview on how Tesla’s Optimus robot will learn more quickly: "What we're going to need to do is build a lot of robots and put them in a kind of like a "Optimus Academy" so they can do self-play in reality. We're actually building that out. We're gonna have at least 10,000 Optimus robots, maybe 20,000 or 30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator. A physics-accurate reality generator that we made for the cars. We'll do the same things for the robots, and actually have done that for the robots. You can do millions of simulated robots in a simulated world, and you use the tens of thousands in the real world to close the simulation to reality gap.”

Sawyer Merritt

250,956 Aufrufe • vor 6 Monaten

FULL TRANSCRIPT OF ELON'S CYBERCAB AND ROBOVAN PRESENTATION 00:00 Welcome 01:16 Cybercab & Future of transportation 04:33 Cost 05:53 Timeline 07:13 Self-driving technology 10:05 Inductive charging 10:24 The cities of the future 11:04 Robovan 12:13 Optimus Welcome Welcome to the We, Robot party. We have quite a show for you tonight. I think you're going to like it. As you can see, I just arrived in the Robotaxi, the Cybercab. And there's 20 more where that came from. So they've been traveling, there's no people in them. As you can see, the car is just going by with no people. We have 50 fully autonomous cars here tonight. So you'll see model Y's and the Cybercabs, all driverless. You'll be able to take a ride in the Cybercab. There's no steering wheel or pedals. So I hope this goes well, we'll find out. You see a lot of sci-fi movies where the future is dark and dismal, where it's not a future you want to be in. So, you know, I love Blade Runner, but I don't know if we want that future. We want that duster he's wearing, but not the bleak apocalypse. We want to have a fun, exciting future that, if you could look in a crystal ball and see the future, you'd be like, yes, I wish I could be there now. That's what we want. Cybercab & Future of transportation So, when we think about transport today, there's a lot of pain that we take for granted, that we think is normal. Like having to drive around LA in 3 hours of traffic. Yeah, people that live in LA, I mean, you know, try to get from Pasadena to El Segundo during rush hour. You can fly to another city faster than you can get to LA. And you have to drive the whole way, unless you're in a Tesla. Of course, our Tesla already does quite well at this supervised self-driving. So, supervised full self-driving is actually working quite well. I'm sure there's people in the crowd who are using that. So, we'll move from supervised full self-driving to unsupervised full self-driving where the car, you could fall asleep and wake up at your destination. But there's also a challenge for a lot of people that cars cost too much. I mean, when you factor in everything that goes into a car and the car insurance and the car payments, storage of the car, it's very expensive. You say, like, how many hours a week are cars used? Your average passenger car is only used about 10 hours a week out of 168 hours. So, the vast majority of the time cars are just doing nothing. But if they're autonomous, they could be used, I don't know, five times more, maybe ten times more. So you could actually, for the same car, would have five times as much value, maybe ten times as much value. There's 168 hours in the week, and like I said, only ten of them are used for driving. And then, a bunch of those hours are looking for a parking spot, which can be pretty annoying at times. So, with autonomy, you get your time back. This is a very big deal. So it's not just, it'll save lives, like a lot of lives and prevent injuries. I think we'll see autonomous cars become ten times safer than a human. I mean, if you think of times past where there used to be an elevator operator in every elevator but once in a while, they get tired and accidentally shear somebody in half. Now, we have automated elevators. You just get an elevator and you press a button and you don't even think about it and it just takes you to the floor. And if you did see an elevator operator with a big relay switch, you'd be like, that's weird. That's how cars will be. And it's not just the lives saved in injuries, but if you think about the cumulative time that people spend in a car and the time that they will get back that they can now spend, well, I guess, on their phones or watching a movie or doing work or whatever you want to do you can think of the car in autonomous world as being like just little lounge. You're just sitting in a comfortable little lounge and you can do whatever you want while you're in this comfortable little lounge. And when you get out, you will be at your destination. So, yeah, it's gonna be awesome. Cost So, in fact, I think the cost of autonomous transport will be so low that you can think of it like individualized mass transit. The average cost of a bus per mile for a city, not the ticket price, because that is subsidized, but the average price is about a dollar a mile, whereas the cost of Cybercab we think probably over time, the operating cost is probably going to be around twenty cents a mile. Including taxes and everything else, it probably ends up being 30 or 40 cents a mile. And you will be able to buy one. And we expect the cost to be below $30,000. And I think there'll be an interesting business model where, let's say somebody is an Uber or Lyft driver today where they can actually sort of manage a fleet of cars and like, sort of manage, I don't know, 10, 20 cars and just take care of them. Like a shepherd tends their flock. You have a little flock of cars and you're the shepherd and you take care of your flock of cars. I think that would be pretty cool. I think it's going to be a glorious future. It's going to be really something special. Timeline We do expect actually to start fully autonomous unsupervised FSD in Texas and California next year. And that's obviously, that's with the Model 3 and Model Y. And then we expect to be in production with the Cybercab, which is really highly optimized for autonomous transport in probably, I tend to be a little optimistic with time frames, but in 2026. So, yeah, before 2027, let me put it that way. And we'll make this vehicle in very high volume. But well, before that, you will experience a robotic taxi via the Model 3 and Model Y program and model S and X, too. But the Model 3 and Y will achieve unsupervised full self-driving with permission, in wherever regulators essentially approve it. In the US, and then to follow outside the US. And Cybertruck, too. All our cars are basically, all cars that we make. Let's not get nuanced here. Self-driving technology One of the reasons why the computer can be so much better than a person is that we have millions of cars that are training on driving. It's like living millions of lives simultaneously and seeing very unusual situations that a person in their entire lifetime would not see. With that amount of training data, it's obviously going to be much better than what a human could be because you can't live a million lives. And it's also, it can see in all directions simultaneously and it doesn't get tired or text or any of those things. So, it will naturally be, like I said 10, 20, 30 times safer than a human, just for all those reasons. And I want to emphasize that the solution that we have is, AI and vision. So, there's no expensive equipment needed. The Model 3 and Model Y and S and X that we make today will be capable of full autonomy, unsupervised. And that means that our cost of producing the vehicle is low. Now, we are going to actually over-spec the computer for the Cybercab. So, our AI 5 computer will be somewhat over-spec'd because I think there's actually also an opportunity, sort of like an Amazon Web Services, where if the car is driving for 50 hours a week, there's still over 100 hours left and there's a potential there to have a massive amount of distributed inference compute, where if you've got like a fleet of 100 million vehicles and a kilowatt of efficient inference compute, you have 100 gigawatts of compute, which is really quite substantial. And if it's there, you might as well use it so that I think will make sense. So, our autonomous future is here. As I said, we've got 50 Teslas driving autonomously. We're trying to give you a sense of what cities will be like in the future. And when you get in, you'll see like, it's really quite a wild experience to just be in a car with no steering wheel, no pedals, no controls, and it feels great. So we have enough vehicles here, so everyone should be able to try it out and experience the set that we've built here. It's a very big set. So it's like really we've used I don't know, 20, 30 acres or something like that. It's really big. So, it goes on, the ride's long. And we set it up to feel like a ride, like a park ride. So, it'll be cool and you'll get to experience it tonight. Inductive charging Something we're also doing is and it's really high time we did this is inductive charging. So, the robotaxi has no plug. It just goes over the inductive charger and charges. So, yeah, it's kind of how it should be. The cities of the future One of the things that is really interesting is how will this affect the cities that we live in. And when you drive around a city, or when the car drives you around the city, you'll see there's a lot of parking lots. There's parking lots everywhere, parking garages. What would happen if you have an autonomous world is that you can now turn parking lots into parks. And so, from we're taking the inglot out of parking lot. You're welcome. So, there's a lot of opportunity to create green space in the cities that we live in. So, like, that would be quite fantastic. Robovan Oh, and also, what happens if you need a vehicle that is bigger than a Model Y? The Robovan. We're going to make this and it's going to look like that. Now, can you imagine going down the streets and you see this coming towards you? That'd be sick. So this can carry up to 20 people, and it can also transport goods. You can configure it for goods transport within a city. Or transport of up to 20 people at a time. The Robovan is what's gonna solve for high density. If you want to take a sports team somewhere or you're looking to really get the cost of travel down to, I don't know, 5, 10 cents a mile, then you can use the Robovan. One of the things we want to do, and we've seen this with the Cybertruck, is we want to change the look of the roads. The future should look like the future. Optimus Speaking of robots. Everything we've developed for our cars, the batteries, power electronics, the advanced motors, gearboxes, the software, the AI inference computer, it all actually applies to a humanoid robot. The same techniques. It's just a robot with arms and legs instead of a robot with wheels. We've made a lot of progress with Optimus. And as you can see, we started up with someone in a robot suit. And then, we've progressed dramatically, year after year. So, if you extrapolate this, you're really going to have something spectacular, something that anyone could own. So, you can have your own personal R2-D2-C3PO. And I think at scale, this would cost something like, I don't know, $20,000, $30,000, probably less than a car is my prediction, long-term. It'll take us a minute to get to the long term. But fundamentally, at scale, the Optimus robot, you should be able to buy an Optimus robot for, I think, probably $20,000 to $30,000, long-term. And what can it do? It'll basically do anything you want. It can be a teacher or babysit your kids, it can walk your dog, mow your lawn, get the groceries, just be your friend, serve drinks whatever you can think of, it will do. And, yeah, it's going to be awesome. I think this will be the biggest product ever of any kind, because I think everyone of the 8 billion people of Earth, I think everyone's going to want their Optimus buddy. And there's going to be maybe two. And then, they'll be producing products and services. I predict, actually, provided we address risks of digital superintelligence, 80% probability of good outcome, look on the bright side, the cup is 80% full, the cost of products and services will decline dramatically. And basically, anyone will be able to have any products and services they want. It will be an age of abundance the likes of which people have not, almost no one has envisioned. It will be something special. So now, one of the things we wanted to show tonight was that Optimus is not a canned video. It's not walled off. The Optimus robots will walk among you. Please, please be nice to the Optimus robots. You'll be able to walk right up to them and they'll serve drinks at the bar. I mean, it's a wild experience just to have humanoid robots and they're there, you're just in front of you. So yeah, with that, let's party!

FULL TRANSCRIPT OF ELON'S CYBERCAB AND ROBOVAN PRESENTATION 00:00 Welcome 01:16 Cybercab & Future of transportation 04:33 Cost 05:53 Timeline 07:13 Self-driving technology 10:05 Inductive charging 10:24 The cities of the future 11:04 Robovan 12:13 Optimus Welcome Welcome to the We, Robot party. We have quite a show for you tonight. I think you're going to like it. As you can see, I just arrived in the Robotaxi, the Cybercab. And there's 20 more where that came from. So they've been traveling, there's no people in them. As you can see, the car is just going by with no people. We have 50 fully autonomous cars here tonight. So you'll see model Y's and the Cybercabs, all driverless. You'll be able to take a ride in the Cybercab. There's no steering wheel or pedals. So I hope this goes well, we'll find out. You see a lot of sci-fi movies where the future is dark and dismal, where it's not a future you want to be in. So, you know, I love Blade Runner, but I don't know if we want that future. We want that duster he's wearing, but not the bleak apocalypse. We want to have a fun, exciting future that, if you could look in a crystal ball and see the future, you'd be like, yes, I wish I could be there now. That's what we want. Cybercab & Future of transportation So, when we think about transport today, there's a lot of pain that we take for granted, that we think is normal. Like having to drive around LA in 3 hours of traffic. Yeah, people that live in LA, I mean, you know, try to get from Pasadena to El Segundo during rush hour. You can fly to another city faster than you can get to LA. And you have to drive the whole way, unless you're in a Tesla. Of course, our Tesla already does quite well at this supervised self-driving. So, supervised full self-driving is actually working quite well. I'm sure there's people in the crowd who are using that. So, we'll move from supervised full self-driving to unsupervised full self-driving where the car, you could fall asleep and wake up at your destination. But there's also a challenge for a lot of people that cars cost too much. I mean, when you factor in everything that goes into a car and the car insurance and the car payments, storage of the car, it's very expensive. You say, like, how many hours a week are cars used? Your average passenger car is only used about 10 hours a week out of 168 hours. So, the vast majority of the time cars are just doing nothing. But if they're autonomous, they could be used, I don't know, five times more, maybe ten times more. So you could actually, for the same car, would have five times as much value, maybe ten times as much value. There's 168 hours in the week, and like I said, only ten of them are used for driving. And then, a bunch of those hours are looking for a parking spot, which can be pretty annoying at times. So, with autonomy, you get your time back. This is a very big deal. So it's not just, it'll save lives, like a lot of lives and prevent injuries. I think we'll see autonomous cars become ten times safer than a human. I mean, if you think of times past where there used to be an elevator operator in every elevator but once in a while, they get tired and accidentally shear somebody in half. Now, we have automated elevators. You just get an elevator and you press a button and you don't even think about it and it just takes you to the floor. And if you did see an elevator operator with a big relay switch, you'd be like, that's weird. That's how cars will be. And it's not just the lives saved in injuries, but if you think about the cumulative time that people spend in a car and the time that they will get back that they can now spend, well, I guess, on their phones or watching a movie or doing work or whatever you want to do you can think of the car in autonomous world as being like just little lounge. You're just sitting in a comfortable little lounge and you can do whatever you want while you're in this comfortable little lounge. And when you get out, you will be at your destination. So, yeah, it's gonna be awesome. Cost So, in fact, I think the cost of autonomous transport will be so low that you can think of it like individualized mass transit. The average cost of a bus per mile for a city, not the ticket price, because that is subsidized, but the average price is about a dollar a mile, whereas the cost of Cybercab we think probably over time, the operating cost is probably going to be around twenty cents a mile. Including taxes and everything else, it probably ends up being 30 or 40 cents a mile. And you will be able to buy one. And we expect the cost to be below $30,000. And I think there'll be an interesting business model where, let's say somebody is an Uber or Lyft driver today where they can actually sort of manage a fleet of cars and like, sort of manage, I don't know, 10, 20 cars and just take care of them. Like a shepherd tends their flock. You have a little flock of cars and you're the shepherd and you take care of your flock of cars. I think that would be pretty cool. I think it's going to be a glorious future. It's going to be really something special. Timeline We do expect actually to start fully autonomous unsupervised FSD in Texas and California next year. And that's obviously, that's with the Model 3 and Model Y. And then we expect to be in production with the Cybercab, which is really highly optimized for autonomous transport in probably, I tend to be a little optimistic with time frames, but in 2026. So, yeah, before 2027, let me put it that way. And we'll make this vehicle in very high volume. But well, before that, you will experience a robotic taxi via the Model 3 and Model Y program and model S and X, too. But the Model 3 and Y will achieve unsupervised full self-driving with permission, in wherever regulators essentially approve it. In the US, and then to follow outside the US. And Cybertruck, too. All our cars are basically, all cars that we make. Let's not get nuanced here. Self-driving technology One of the reasons why the computer can be so much better than a person is that we have millions of cars that are training on driving. It's like living millions of lives simultaneously and seeing very unusual situations that a person in their entire lifetime would not see. With that amount of training data, it's obviously going to be much better than what a human could be because you can't live a million lives. And it's also, it can see in all directions simultaneously and it doesn't get tired or text or any of those things. So, it will naturally be, like I said 10, 20, 30 times safer than a human, just for all those reasons. And I want to emphasize that the solution that we have is, AI and vision. So, there's no expensive equipment needed. The Model 3 and Model Y and S and X that we make today will be capable of full autonomy, unsupervised. And that means that our cost of producing the vehicle is low. Now, we are going to actually over-spec the computer for the Cybercab. So, our AI 5 computer will be somewhat over-spec'd because I think there's actually also an opportunity, sort of like an Amazon Web Services, where if the car is driving for 50 hours a week, there's still over 100 hours left and there's a potential there to have a massive amount of distributed inference compute, where if you've got like a fleet of 100 million vehicles and a kilowatt of efficient inference compute, you have 100 gigawatts of compute, which is really quite substantial. And if it's there, you might as well use it so that I think will make sense. So, our autonomous future is here. As I said, we've got 50 Teslas driving autonomously. We're trying to give you a sense of what cities will be like in the future. And when you get in, you'll see like, it's really quite a wild experience to just be in a car with no steering wheel, no pedals, no controls, and it feels great. So we have enough vehicles here, so everyone should be able to try it out and experience the set that we've built here. It's a very big set. So it's like really we've used I don't know, 20, 30 acres or something like that. It's really big. So, it goes on, the ride's long. And we set it up to feel like a ride, like a park ride. So, it'll be cool and you'll get to experience it tonight. Inductive charging Something we're also doing is and it's really high time we did this is inductive charging. So, the robotaxi has no plug. It just goes over the inductive charger and charges. So, yeah, it's kind of how it should be. The cities of the future One of the things that is really interesting is how will this affect the cities that we live in. And when you drive around a city, or when the car drives you around the city, you'll see there's a lot of parking lots. There's parking lots everywhere, parking garages. What would happen if you have an autonomous world is that you can now turn parking lots into parks. And so, from we're taking the inglot out of parking lot. You're welcome. So, there's a lot of opportunity to create green space in the cities that we live in. So, like, that would be quite fantastic. Robovan Oh, and also, what happens if you need a vehicle that is bigger than a Model Y? The Robovan. We're going to make this and it's going to look like that. Now, can you imagine going down the streets and you see this coming towards you? That'd be sick. So this can carry up to 20 people, and it can also transport goods. You can configure it for goods transport within a city. Or transport of up to 20 people at a time. The Robovan is what's gonna solve for high density. If you want to take a sports team somewhere or you're looking to really get the cost of travel down to, I don't know, 5, 10 cents a mile, then you can use the Robovan. One of the things we want to do, and we've seen this with the Cybertruck, is we want to change the look of the roads. The future should look like the future. Optimus Speaking of robots. Everything we've developed for our cars, the batteries, power electronics, the advanced motors, gearboxes, the software, the AI inference computer, it all actually applies to a humanoid robot. The same techniques. It's just a robot with arms and legs instead of a robot with wheels. We've made a lot of progress with Optimus. And as you can see, we started up with someone in a robot suit. And then, we've progressed dramatically, year after year. So, if you extrapolate this, you're really going to have something spectacular, something that anyone could own. So, you can have your own personal R2-D2-C3PO. And I think at scale, this would cost something like, I don't know, $20,000, $30,000, probably less than a car is my prediction, long-term. It'll take us a minute to get to the long term. But fundamentally, at scale, the Optimus robot, you should be able to buy an Optimus robot for, I think, probably $20,000 to $30,000, long-term. And what can it do? It'll basically do anything you want. It can be a teacher or babysit your kids, it can walk your dog, mow your lawn, get the groceries, just be your friend, serve drinks whatever you can think of, it will do. And, yeah, it's going to be awesome. I think this will be the biggest product ever of any kind, because I think everyone of the 8 billion people of Earth, I think everyone's going to want their Optimus buddy. And there's going to be maybe two. And then, they'll be producing products and services. I predict, actually, provided we address risks of digital superintelligence, 80% probability of good outcome, look on the bright side, the cup is 80% full, the cost of products and services will decline dramatically. And basically, anyone will be able to have any products and services they want. It will be an age of abundance the likes of which people have not, almost no one has envisioned. It will be something special. So now, one of the things we wanted to show tonight was that Optimus is not a canned video. It's not walled off. The Optimus robots will walk among you. Please, please be nice to the Optimus robots. You'll be able to walk right up to them and they'll serve drinks at the bar. I mean, it's a wild experience just to have humanoid robots and they're there, you're just in front of you. So yeah, with that, let's party!

Mario Nawfal

241,051 Aufrufe • vor 1 Jahr

Elon Musk: We can have a future where nobody's in need. “A future of abundance for all sounds impossible. But what I'm here to tell you is that it will indeed be the case. What's key to that is robotics and AI: Self-driving cars and autonomous humanoid robots that can be your own personal robot buddy [...] and enable the production of goods and services, basically with no limit. When you combine that with sustainable energy from the sun and batteries, we can at the same time also maintain a great environment. I think that's the future that we want. A future where nobody's in need, you can have what you want. But we still have the beautiful parts of nature that we like. And also space travel—let's not forget that.” Tesla All-Hands Meeting, March 20, 2025

Elon Musk: We can have a future where nobody's in need. “A future of abundance for all sounds impossible. But what I'm here to tell you is that it will indeed be the case. What's key to that is robotics and AI: Self-driving cars and autonomous humanoid robots that can be your own personal robot buddy [...] and enable the production of goods and services, basically with no limit. When you combine that with sustainable energy from the sun and batteries, we can at the same time also maintain a great environment. I think that's the future that we want. A future where nobody's in need, you can have what you want. But we still have the beautiful parts of nature that we like. And also space travel—let's not forget that.” Tesla All-Hands Meeting, March 20, 2025

ELON CLIPS

1,330,456 Aufrufe • vor 1 Jahr

Fei-Fei Li on what simulation can do for robotics that real-world data can't: "You play out events that haven't happened, or cannot happen... And while you play it out, you learn how to act in it." "That's really important in robotics, because we cannot possibly have enough real-world data for that." "Here is a real life example: the industry of self-driving cars. Waymo has officially said they use billions of hours of simulation." "Cars are the simplest kind of robots. So clearly simulation plays a huge role in robotic learning." Fei-Fei Li Yunzhu Li World Labs martin_casado

Fei-Fei Li on what simulation can do for robotics that real-world data can't: "You play out events that haven't happened, or cannot happen... And while you play it out, you learn how to act in it." "That's really important in robotics, because we cannot possibly have enough real-world data for that." "Here is a real life example: the industry of self-driving cars. Waymo has officially said they use billions of hours of simulation." "Cars are the simplest kind of robots. So clearly simulation plays a huge role in robotic learning." Fei-Fei Li Yunzhu Li World Labs martin_casado

a16z

35,480 Aufrufe • vor 28 Tagen

Was especially curious to ask Andrej Karpathy why self-driving cars took a decade+ from stellar demo rides to even somewhat deployed. Andrej led AI at Tesla for 5 years. I really wanted to know whether these frictions should lengthen our AGI timelines, or whether they were idiosyncratic to self driving. Driving has a really high cost of failure. Humans are surprisingly reliable drivers - we have a serious accident every 400,000 miles/7 years. And self-driving cars need to match or beat this safety profile before they can be deployed. But are most domains like this? Before the interview, it seemed to me that almost every domain we would want to plug AGI into has a much lower cost of failure. If fully autonomous software engineers weren’t allowed to make a mistake for 7 years, deployment would indeed be super slow. Andrej made an interesting point that I hadn’t heard before: compared to self driving, software engineering has a higher (and potentially unbounded) cost of failure: > If you’re writing actual production-grade code, any kind of mistake could lead to a security vulnerability. Hundreds of millions of people’s personal Social Security numbers could get leaked. > In self-driving, if things go wrong, you might get injured. There are worse outcomes. But in software, it’s almost unbounded how terrible something could be. > In some ways, software engineering is a much harder problem [than self driving]. Self-driving is just one of thousands of things that people do. It’s almost like a single vertical. Whereas when we’re talking about general software engineering, there’s more surface area. There’s potentially another reason why the LLM -> widely deployed AGI transition might happen much faster: LLMs give us perception, representations, and common sense (to deal with out of distribution examples) for free, whereas these had to be molded from scratch for self-driving cars. I asked Andrej about this: > I don’t know how much we’re getting for free. LLMs are still pretty fallible and they have a lot of gaps that still need to be filled in. I don’t think that we’re getting magical generalization completely out of the box. > The other aspect that I wanted to return to is that self-driving cars are nowhere near done still. The deployments are pretty minimal. Even Waymo has very few cars. They’ve built something that lives in the future. They’ve had to pull back the future, but they had to make it uneconomical. > Also, when you look at these cars and there’s no one driving, there’s more human-in-the-loop than you might expect. In some sense, we haven’t actually removed the person, we’ve moved them to somewhere where you can’t see them.

Dwarkesh Patel

135,020 Aufrufe • vor 10 Monaten

Robotics is entering the mainstream! 👀 Let's accept this fact. Consumptionism – stonks. Possibilities (HW + SW) – stonks. Demographics - not stonks. Modern robots are often designed to interact with our legacy world, whether it's a household, a factory, or a shipyard. That means they often need to work with existing machines, tools, and spaces. In short: retrofitting. Improving old machines with new technologies without major interference in their operation. Modern way of integrating things. You don't have to change the entire environment to deploy a robot. The robot will adapt, just as human would when freshly hired. The promise is to have an army of robots to help with the world designed for us. I also believe that general purpose robots, are not a direct competition for single purpose machines (like a highly efficient specialized packaging machine, for example). It's like adding a robot to this carriage. Specialized machine could be a car ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Robotics is entering the mainstream! 👀 Let's accept this fact. Consumptionism – stonks. Possibilities (HW + SW) – stonks. Demographics - not stonks. Modern robots are often designed to interact with our legacy world, whether it's a household, a factory, or a shipyard. That means they often need to work with existing machines, tools, and spaces. In short: retrofitting. Improving old machines with new technologies without major interference in their operation. Modern way of integrating things. You don't have to change the entire environment to deploy a robot. The robot will adapt, just as human would when freshly hired. The promise is to have an army of robots to help with the world designed for us. I also believe that general purpose robots, are not a direct competition for single purpose machines (like a highly efficient specialized packaging machine, for example). It's like adding a robot to this carriage. Specialized machine could be a car ;) ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

14,396 Aufrufe • vor 6 Monaten

ELON: TESLA IS THE WORLD’S BIGGEST ROBOT MAKER AND AI SAFETY LEADER "Tesla is arguably the world's biggest robot maker, because we have basically semi-autonomous cars that will ultimately be fully autonomous. And we are building a humanoid robot that will be basically like the car, but with legs. I kind of held open doing that for a while because I certainly don't want to hasten the AI apocalypse. But clearly, when you look at Boston Dynamics and these humanoid robots, they're going to happen with or without Tesla. So with Tesla, I've got a lot more ability to ensure robotics safety and AI, and I'll try my best to do that." Source: ELON CLIPS

ELON: TESLA IS THE WORLD’S BIGGEST ROBOT MAKER AND AI SAFETY LEADER "Tesla is arguably the world's biggest robot maker, because we have basically semi-autonomous cars that will ultimately be fully autonomous. And we are building a humanoid robot that will be basically like the car, but with legs. I kind of held open doing that for a while because I certainly don't want to hasten the AI apocalypse. But clearly, when you look at Boston Dynamics and these humanoid robots, they're going to happen with or without Tesla. So with Tesla, I've got a lot more ability to ensure robotics safety and AI, and I'll try my best to do that." Source: ELON CLIPS

Mario Nawfal

62,961 Aufrufe • vor 9 Monaten

🚨 BREAKING: German robot maker NEURA Robotics has raised €120 million in Series B funding to advance its cognitive robotics technology. Good to see the Europe robotics market moving! 🇪🇺 And yes I know this is news from mid-January, sometimes you have to be like Internet Explorer! Their product lineup includes collaborative arms, autonomous mobile robots, and humanoids. The funding will support new product development and the growth of its Neuraverse ecosystem, an operating system and marketplace for robotic skills. David Reger believes cognitive robots could become bigger than smartphones, with NEURA leading the way as Germany’s only humanoid robotics company. You can meet this and many other robots at the internationalhumanoidforum in Biel on the 20th & 21st of February! 🇨🇭 I also will be there, and I am happy to talk about the future of robotics!

🚨 BREAKING: German robot maker NEURA Robotics has raised €120 million in Series B funding to advance its cognitive robotics technology. Good to see the Europe robotics market moving! 🇪🇺 And yes I know this is news from mid-January, sometimes you have to be like Internet Explorer! Their product lineup includes collaborative arms, autonomous mobile robots, and humanoids. The funding will support new product development and the growth of its Neuraverse ecosystem, an operating system and marketplace for robotic skills. David Reger believes cognitive robots could become bigger than smartphones, with NEURA leading the way as Germany’s only humanoid robotics company. You can meet this and many other robots at the internationalhumanoidforum in Biel on the 20th & 21st of February! 🇨🇭 I also will be there, and I am happy to talk about the future of robotics!

Lukas Ziegler

46,521 Aufrufe • vor 1 Jahr

ELON: MANUALLY-DRIVEN CARS WILL BE LIKE HORSES IN THE FUTURE “Tesla in a few months will release unsupervised full self-driving. So, the cars that people are driving right now, the cars that you can buy from the factory will be driving around by themselves with no people in them. We call that unsupervised full self-driving. There's literally no one in the car on public roads. We'll start that in Austin in a few months, in June, and then we'll rapidly expand that to the rest of the country. Anyone who has Tesla now, if they try self-driving, it should work very well. It should be rare that you need any intervention. In fact, in the future, I think it'll be unusual to see a manually-driven car. It'll be like seeing a horse.” Source: Interview with Lara Trump, May 2025

ELON: MANUALLY-DRIVEN CARS WILL BE LIKE HORSES IN THE FUTURE “Tesla in a few months will release unsupervised full self-driving. So, the cars that people are driving right now, the cars that you can buy from the factory will be driving around by themselves with no people in them. We call that unsupervised full self-driving. There's literally no one in the car on public roads. We'll start that in Austin in a few months, in June, and then we'll rapidly expand that to the rest of the country. Anyone who has Tesla now, if they try self-driving, it should work very well. It should be rare that you need any intervention. In fact, in the future, I think it'll be unusual to see a manually-driven car. It'll be like seeing a horse.” Source: Interview with Lara Trump, May 2025

Mario Nawfal

39,736 Aufrufe • vor 1 Jahr

"I worked for the Speaker of the House. I worked for the President of the United States. One of the things you learn in those jobs is that ultimately no one is fully in charge of anything, and the world is very, very complex. I would read in the Washington Post how Republican leaders had all these plans and they were going to pull things this way or that way. And then I'd get to work and to say that no one had a plan would be a gross understatement. No one had any idea what was going to happen that afternoon. The idea that in a free society somebody is pulling the strings and someone has a nine-step plan and you're just a pawn in it is just very, very implausible. Our society doesn't really work that way. Our elites now are not ultra-competent. You can say a lot of things about them, but I would not say that we have ultra-competent leaders of any institution. I can see the appeal of wanting to believe that it's all a false flag or a plan. But when you actually see the system work—it's both good news and bad news—but nobody's in charge of everything."

"I worked for the Speaker of the House. I worked for the President of the United States. One of the things you learn in those jobs is that ultimately no one is fully in charge of anything, and the world is very, very complex. I would read in the Washington Post how Republican leaders had all these plans and they were going to pull things this way or that way. And then I'd get to work and to say that no one had a plan would be a gross understatement. No one had any idea what was going to happen that afternoon. The idea that in a free society somebody is pulling the strings and someone has a nine-step plan and you're just a pawn in it is just very, very implausible. Our society doesn't really work that way. Our elites now are not ultra-competent. You can say a lot of things about them, but I would not say that we have ultra-competent leaders of any institution. I can see the appeal of wanting to believe that it's all a false flag or a plan. But when you actually see the system work—it's both good news and bad news—but nobody's in charge of everything."

Michael Shermer

128,362 Aufrufe • vor 2 Jahren

On today’s episode of “How dumb can you be” 🙄 this lady works for a car rental company, she is driving one of their cars, she’s doing 53 in a 35, gets pulled over…and her instinct is to fight with the cops…she put a little FAFO on her calendar for that day. 👀 🎥 👮‍♂️ 🚔 Part 2 in comments!

On today’s episode of “How dumb can you be” 🙄 this lady works for a car rental company, she is driving one of their cars, she’s doing 53 in a 35, gets pulled over…and her instinct is to fight with the cops…she put a little FAFO on her calendar for that day. 👀 🎥 👮‍♂️ 🚔 Part 2 in comments!

🇺🇸 𝓓𝓪𝓻 🇨🇦

211,794 Aufrufe • vor 8 Monaten

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

World Labs CEO Dr. Fei-Fei Li & SceniX Co-Founder Yunzhu Li on the data bottleneck in robotics and how world models help: "The lack of data in training, the lack of data in evaluation, this is very, very different from language models, where data is abundant on the internet." "And we know that in order for robotics to work, we have to somehow unlock the power of scaling law. But where does that come from?" "It's a profound problem that everybody's battling with in robotics." "We see a lot of unlock in being able to do this whole process through the modeling of the environments." "Being able to create these digital worlds... that's just going to unlock so much more potential for being able to replace all the costly and the unsafe data in the real environments with the data generated from the worlds for robots to be able to do scalable learning and evaluations." Fei-Fei Li Yunzhu Li martin_casado

a16z

75,232 Aufrufe • vor 29 Tagen

Sunday Robotics' Tony Zhao runs a fully autonomous robot demo live and unscripted, and it corrects itself every time you mess with it: brexton: "I want to confirm for the audience right now that this is fully autonomous. There's no teleoperation, no one behind the curtain, and this is real time. And we did not prepare this demo before. Why do you think seeing real-time demos is so rare for robotics? What the audience is seeing right now is not that common." Tony Zhao: "In order for a live demo to work, it's really stressing all parts of the system. From the bottom is the reliability of the hardware, then the software system, then the model. Because we're a full-stack company, we're able to do excellent work across all of them. We have these robots running pretty much every day, and it just keeps getting better as they practice." brexton: "So kids can bump into Memo, people can drop clothes, and it will correct itself just on the fly." Tony Zhao: "Act Two is the first robotic policy that can handle the diversity of homes in a way that is this reliable. You can see as I'm twisting it, if I twist it in again, it will keep doing it. So Memo has infinite patience." Sunday

Sunday Robotics' Tony Zhao runs a fully autonomous robot demo live and unscripted, and it corrects itself every time you mess with it: brexton: "I want to confirm for the audience right now that this is fully autonomous. There's no teleoperation, no one behind the curtain, and this is real time. And we did not prepare this demo before. Why do you think seeing real-time demos is so rare for robotics? What the audience is seeing right now is not that common." Tony Zhao: "In order for a live demo to work, it's really stressing all parts of the system. From the bottom is the reliability of the hardware, then the software system, then the model. Because we're a full-stack company, we're able to do excellent work across all of them. We have these robots running pretty much every day, and it just keeps getting better as they practice." brexton: "So kids can bump into Memo, people can drop clothes, and it will correct itself just on the fly." Tony Zhao: "Act Two is the first robotic policy that can handle the diversity of homes in a way that is this reliable. You can see as I'm twisting it, if I twist it in again, it will keep doing it. So Memo has infinite patience." Sunday

MTS

133,191 Aufrufe • vor 27 Tagen