Lenny's Podcast: Product | Career | Growth
01:03:29 · Caitlin Kalinowski
[01:03:29] S0: If you're talking about robots building robots that are different than them usually, yes, I think that that's going to happen, but it's like the terms matter. I don't think there's going to be one robot that's going to build itself. I don't think that that's what it's going to look like. If you could say, "Hey, I want to build this thing and I want it to do this and this is kind of how I want it to look and here's a picture," the idea that you could, even as a hobbyist, go from a 2D picture to complex 3D CAD to assemblies to communication with vendors of how to make those parts and getting their feedback to iterating on that and doing a couple builds, that is possible, I think, in the future. Will it be good as good in the beginning as us doing it? No, but it will happen. The biggest challenge here, Lenny, is actually the data. This CAD data is some of the most valuable IP that anybody has, and Samsung or Matic, to pick on Matic, they're not going to want to give their 3D CAD to a model vendor, to a model maker, somebody making an AI model to teach it how to make great CAD. This is proprietary. This is like the secret sauce. And so, where is this data going to come from is a big question I have, which is why I think hobbyists are a more interesting place to start where they're not concerned about the sanctity of their CAD and where it goes. They don't care. They want to make something and they want help making it faster. So this is kind of where I'm interested in this starting, which is maybe a hobbyist isn't an expert in printed circuit board design. Maybe they don't care. They just want their drone to be fast and to beat this other guy's drone or whatever. This is where I think you're going to start seeing all this start, and then probably, the big incumbents are going to be slower because they have dedicated tools and a lot of IP privacy.
01:05:18 · Lenny Rachitsky, Caitlin Kalinowski
[01:05:18] S1: It's really interesting, this idea of what data AI models need to train on. I've been hearing that labs are buying code like GitHub repos pre 2021 because that's before AI has impacted the code because there's less and less of human-written code. And these are data labeling companies like Mercor and Surge and Handshake and things like that. It feels like this is a big opportunity that might emerge as them selling data, creating these CAD files. [01:05:46] S0: Absolutely. And one really great idea I think would be to have an AI system that can go on prem, so be inside of a data center that the company owns and then train it with their data. That, I think, could work eventually in the future, but you need a lot of this CAD data. So you're going to need a base model that has a lot of CAD data. We'll have to figure out how to do that. That's going to be very interesting. And then, we're going to have to figure out how to put it safely inside essentially the walls of companies and have them then train it on their own data. I don't know if that's going to be the equivalent of an MCP layer or what that's going to be, but this seems doable in the long term. [01:06:23] S1: I want to ask you a question that my sister suggested. She's actually been a longtime VR person. She was at Oculus. She joined with the acquisition. She helped create a lot of content within VR. She's just been in the VR world for a long time, and now, she's working on other things. She wanted me to ask you, what does it take to create a robot that feels human and that humans feel connected to?
01:06:45 · Caitlin Kalinowski
[01:06:45] S0: It's a great question. I'm new relatively speaking to robotics. And so, I had to learn as much as I could as fast as I could. One of the researchers that helped me the most, her name's Leila Takayama. She's an expert at this. What she explained to me is that humans have a certain expectation about how other beings are going to respond when they enter a space. When someone walks into a room, you kind of acknowledge them. You might not talk to them, but you kind of look up. There is a lot of very complex nonverbal cues that we give to each other. And if you walk into a room and a robot's just like, it's creepy, and it's easy to be creepy. I'm a little surprised with some notable exceptions how creepy a lot of these humanoids are right now. You want, I think, these devices to be non-threatening, generally speaking. You want them to appear soft, you want them to appear reactive to you. You want to have a sense that they know that you're there, that they're attentive to you, that they're there to help you and make your work life easier, and you also expect them to intentionally or to show their intent before they do something. And so, one of the things I learned is if a robot just suddenly turns and does all this stuff, it scares you. But if a robot looks before it turns and then goes, it's much less alarming. So there's all these little pieces, and I recommend anyone to go look at her work. There's a lot of great research here about how to, not necessarily with a humanoid, but how to have any robot both respond properly in a social context with someone entering a room or exiting a room, but also transmit its intent physically so it doesn't surprise you.
01:08:43 · Lenny Rachitsky, Caitlin Kalinowski
[01:08:43] S1: It feels like there's a lot we can learn from Pixar and animation studios that have thought about this a long time. [01:08:49] S0: Yeah. I actually think Pixar, Disney are probably the world's best at doing this type of design work even though they haven't done as much in physical in volume. If you look at what they do and how they show emotion, intent, approachability, engagement with their characters, they're really world-class. [01:09:16] S1: I don't know about you, but I'm so excited to have a robot at home doing things. These videos that they're starting to put out where they're doing your... They can do dishes, at least the prototypes, they can fold laundry, they can do... It's like, yes, please come do this for me. How do you feel about robots in your house? [01:09:32] S0: So I'm into it. My partner, not so much. So I'm very lucky to have a partner who's got a high bar, which means was like never going to take Waymo, took one Waymo, and now, never wants to take anything else. So definitely willing to update her position, but it has to be pretty good. So she's in love with the Matic. It's amazing, but the bar is pretty high. So I think in order to have a home robot, it's going to have to be pretty incredible for her to be willing to have it in our home. But I take that as a challenge.
01:09:32 · Caitlin Kalinowski, Lenny Rachitsky
[01:09:32] S0: So I'm into it. My partner, not so much. So I'm very lucky to have a partner who's got a high bar, which means was like never going to take Waymo, took one Waymo, and now, never wants to take anything else. So definitely willing to update her position, but it has to be pretty good. So she's in love with the Matic. It's amazing, but the bar is pretty high. So I think in order to have a home robot, it's going to have to be pretty incredible for her to be willing to have it in our home. But I take that as a challenge. [01:10:04] S1: My wife is exactly the same way. She's like, "I don't want this thing in our house with Matic. Oh, wow, this is so cute." A recent example, a self-driving Tesla. She used to be so like, "No, don't do that." It was not that great originally, and now, she's like, "I don't want to drive any other car. This just feels like absurd to drive your car. I don't want to do that anymore." It's crazy how quickly that changes.
01:10:04 · Lenny Rachitsky, Caitlin Kalinowski
[01:10:04] S1: My wife is exactly the same way. She's like, "I don't want this thing in our house with Matic. Oh, wow, this is so cute." A recent example, a self-driving Tesla. She used to be so like, "No, don't do that." It was not that great originally, and now, she's like, "I don't want to drive any other car. This just feels like absurd to drive your car. I don't want to do that anymore." It's crazy how quickly that changes. [01:10:27] S0: So there's a big difference in my mind. This is a big categorical difference. There's a big difference between a car that is safer that drives itself versus a car that a human drives because you have an existence proof of the human driving car and you have the data. When you talk about homes, what is the delta? You have now a thing that you didn't have before doing things. So if it's bad at it, what are you relating it to? And if it's unsafe in any way, what are you relating that to? It's a much harder equation in my mind to get to a lot of people than a car where you can say, "Hey, Waymo save lives." You're going to have a fraction of the deaths using a Waymo, whether you're a passenger or you're not. When you already see people in San Francisco adapting how they respond around a Waymo versus any other car, so you're seeing behavioral changes that are based on trust, which is really cool. When you're talking about a new product that hasn't existed yet and is not essentially replacing something, that's a harder sell and you have to have a different story.