00:03:28 · Chris Walti
[00:03:28] S8: So I joined Tesla in 2014. I think this is after the dual motor Model S was launched or was announced. You know, there's a lot of skepticism. Are electric vehicles going to be successful? Is fully battery electric vehicle or plug in hybrid, you know, Tesla versus Fisker? A lot of uncertainty in the market then, but, you know, I joined Tesla to to solve a very clear problem. I was working on more traditional wheeled automation and, of course, a lot of the fixed infrastructure projects that we had at Tesla beforehand. And then, you know, this challenge of let's build a humanoid robot was given to our team because we had an integrated robotics team, but the challenges of a humanoid are very different than building a wheeled robot on the floor, legged locomotion, grasping in the manipulation, the kinds of of of decisions that this robot has to process. A perception systems are are wildly different. And so first, Tesla had precisely zero expertise of humanoid robotics at the time. So I had to go and figure out who the experts were, meet with them, try to establish a recruiting pipeline, try to find the internal experts within Tesla who were willing and able and also had the foundational skill sets to be able to solve this problem, I had to give myself a two month crash course in humanoid robotics. So that was really an interesting time. But, you know, I think one of the things that Tesla teaches you to be very resourceful, that wasn't the first time I've been asked to solve a problem, which I had no really like deep or meaningful background in. But you structure the problem, you go find the information you need, hop on a plane to meet with the experts as you need. So you do what it takes to figure it out. You know, Elon laid a mandate out that we needed to get some robot walking in three months. And so between internal experts and talking with some folks outside the company, have to get... Accomplish that goal. I think as a whole, though, all robots are not created equal. All robot challenges are not equal. Anytime you're talking about legged locomotion or just advanced grasping, the perception that the type of data and the consistency of data, the frequency of the refresh rates, like I'm not just looking at a hand, like I need to understand like the forces and there's literally infinite ways I could grab something.
00:05:38 · Chris Walti, S0
The difficulty of repeating that and making that some sort of industrial process is many orders of magnitude more difficult than driving a bot around the floor of a factory. You know, if we think about how difficult it has been to do full self driving cars or autonomous vehicles, you know, you could argue that that problem is not a solved problem yet because we don't have ubiquitous cars, you know, driving highways and and surface streets yet. Right? You do have companies that are driving... Like, you can walk outside of this building. You will see a car, unmanned car drive by this this facility. Ad[00:06:12] S0: This episode is brought to you by Google Chrome. You think you know a browser, but Gemini in Chrome? That's new. It can help you with practically anything on the web, like restoring a vintage motorcycle from a 50 page restoration block or finally break down that long article you've had open for weeks. Gemini in Chrome is here for it. Ready to make anything online make sense? There's no place like Chrome. Check responses, setup required, compatibility, and availability varies 18 plus.
00:06:12 · S0, S1, S2
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00:07:37 · S2, S3, S9, S4, S5
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00:08:19 · S5, Chris Walti
Ad[00:08:19] S5: Pricing participation may vary. Promotion pricing may be lower than meal pricing. [00:08:22] S8: Probably in thirty minutes, but it's not ubiquitous. Right? Hasn't been adopted. Building a humanoid to operate at full scale in a factory or a home at the comparable productivity of a human is a very, very challenging problem to solve. I'm confident it will be solved. I think the timing is everything. Right? Is this a one year problem? Is this a five year? Is this a ten year? Is this a thirty year problem? Unclear. So after spending a year there, it was it was a fascinating problem where, again, was able to work with some of the best and brightest at Tesla and and beyond Tesla. I was fortunate to be able to to hire some wonderful people to work on these huge challenges. But, ultimately, I joined Tesla to ship, you know, millions of products to the public to make real impact, And I felt that most of the impact that a humanoid is dependent on solving effectively some research problems. With what we're doing at Mytra, this is not in the research domain. This is a very... Like, we're solving tangible problems with technology that doesn't require moonshot levels of of innovation to have meaningful impact on the economy.
00:09:26 · Ahmad Baitalmal
[00:09:26] S7: After Tesla, I I tried to just focus a little bit away from manufacture. Let me think a little bit, you know, do something else. Derivatives trading and try to learn more about AI and financial systems, but the bug of manufacturing, working on hardware, got me again. And the things I did at Tesla were very applicable to Rivian. And I thought I really wanted to help one more US auto manufacturer get off the ground. I was really excited about Rivian, trying to help them out. So I went and spent time at Rivian, helping them scale their manufacturing systems as well. That's the journey. After that, I was at a beach in Hawaii. I still had the video while I'm recording the beach and I was going like, wonderful, this is great, I'm done, I don't want to do anything else. I've solved every problem I want to solve. As I'm recording the video, I get a call from Walti and he's asking me about, hey, do you remember the problems we went into at Tesla during manufacturing? Let's really solve it. At the beginning, I was like, I don't wanna do this, I don't wanna do manufacturing again, I wanna stay at the beach. But the more we talked about how we would solve this problem, go back to the fundamentals, let's not just build another automation company, let's do something completely different. The more we talked about it, the more I got excited, because it wasn't just another implementation. It's a complete rethink. And that was very exciting. So I said, okay, yes, let's start this company. Let's find the best people that we can find from our network and tackle this problem.