00:11:25 · Bernt Øivind Børnich, Ty Morse
And in the end, you read across your fingers that you're gonna you're gonna run out of problems. If you just fix enough of them, you're gonna run out of problems. Do you still believe? Yeah. I still believe. But, like, since that's kinda the only way to do it, then you just need to be able to really benchmark yourself on, like, how quickly can I iterate? Because that's how quickly I can kinda, like, churn through these problems. And we see less and less problems. So there's... Seems to be going in the right direction. So sooner or later, we'll run out of the problems. [00:11:54] S0: When you're, like, starting to put these in people's homes that aren't inside of the company, I think the bot at the beginning of next year is going to look significantly different than the bot at the end of next year. And the feedback that you get from January customers are gonna be very diff... You know, you can incorporate that for the December people. How do you kind of, as quickly as possible, incorporate new information and new feedback from the robots in the field, and then basically spin up new manufacturing lines in order to scale that?
00:11:54 · Ty Morse, Bernt Øivind Børnich
[00:11:54] S0: When you're, like, starting to put these in people's homes that aren't inside of the company, I think the bot at the beginning of next year is going to look significantly different than the bot at the end of next year. And the feedback that you get from January customers are gonna be very diff... You know, you can incorporate that for the December people. How do you kind of, as quickly as possible, incorporate new information and new feedback from the robots in the field, and then basically spin up new manufacturing lines in order to scale that? [00:12:23] S1: There's a lot you can do now with just, like, fleet monitoring and data and analytics. That was very... Really harder to do before. So I think that that's a very important part of it. But there's nothing really that replaces the need to just, like, stay close to your customer and really listen to your customer and get that feedback. And then also, like, when we talk about iteration here, right, you you you iterate on the entire fleet. So we do have a big goal in the beginning, at least, for, like, the first units that we will do a lot of remanufacturing also. So, like, if you find things that we need to fix, then we fix it not just for new robots. We should also fix it for the existing robots. [00:13:00] S0: Would that be, like, literally, like, quote, unquote, recall recall back end?
00:13:00 · Ty Morse, Bernt Øivind Børnich
[00:13:00] S0: Would that be, like, literally, like, quote, unquote, recall recall back end? [00:13:05] S1: Well, but not necessarily recall. Right? Most of it is... Like, the the product is pretty small and light, so, like, generally, you can service it in the field. And, like, if you if you figure out that, like, we... You left feet on a robot. Right? We we we replace... Place the left field in the field. We we don't necessarily recall the robot, but, technically, you could call it a recall. [00:13:26] S0: I was looking at the hand video, and I was thinking to myself, this reminds me of this idea from Steve Jobs, where if you look at the inside of, like, an Apple computer, it's gorgeous, and people were kind of wondering to themselves, like, why is this? And it's like, because Steve wanted to design something that was both beautiful on the inside and the outside and also functional. And I think when I look at your robot, it's that... Has that same feel where it's, like, beautiful to look at even when it doesn't have its, like, clothes on or skin on. What's your kind of, like, philosophy on designing something where even the internals look good?
00:13:57 · Bernt Øivind Børnich, Ty Morse
[00:13:57] S1: I... I'm I'm I'm I'm probably, like, blunted here in, like, a special way because I think sufficiently advanced engineering is art, and this is clearly advanced engineering. But I think the beauty of the machine kinda comes from the simplicity, not the complexity. So you take something that's extremely complex, and you manage to boil it down to something is like, it is the simplest form, the simplest implementation that can fully solve the problem. And there's a real beauty to that. I think often you can see this in systems. You can kinda see that, like, oh, first principles wise. This is just, like, the minimum implementation of the system. And there's a real beauty to that simplicity, and that's really hope... What I hope we can deliver. That kinda comes from itself. Right? You don't need to design for it to be beautiful in inside. If you've done your job on, like, how do you design the system, then this just automatically happens because it should always be the minimum complexity implementation that solves the problem. That's how you achieve scale. [00:14:58] S0: Do you ever have a feeling where you're looking at something and you say to yourself, like, it is clearly not there yet because it doesn't look simple, it doesn't look beautiful?
00:15:05 · Bernt Øivind Børnich
[00:15:05] S1: Oh, yeah. And and, like, every day, every time I look at a robot, all I see is everything that's wrong. So I'm not that lucky in that sense. Like, everyone else sees something as, this is beautiful. I'm like, no. No. No. No. Like, this is wrong. This is wrong. This is wrong. And I think that's probably gonna be like that forever. So I'm not the right person to ask that. But I I do think, like, I I find beauty in every time we can do simplifications. And I think the biggest simplification that's happened over the last year is, for example, wire harnessing and just ensuring, like, the complexity of the cabling really going down tremendously, like minimum number of connectors, minimum number of wires. And this is just something we drive top down. Like, we literally have, like, a cable and connector budget, for example. There's a certain number of connectors that you have to have from, like, a first principles point of view, but it's not that many. And every connector that you have more than that, that's an exception that really needs to be defended and needs to be approved because it shouldn't be there, and we should have a plan for how to get rid of it. And this is the same for moving parts. Right? Like, you want the number of parts in your robot to be the number of moving parts. If two parts don't move with respect to each other, like, why are there two parts? Like, they should be one part. You can't always achieve this, but you should absolutely know what is the first principle's minimum complexity and how far away are you and how are you driving it down towards that. Because the ultimate goal should be to reach that.
00:16:36 · Ty Morse, Bernt Øivind Børnich
[00:16:36] S0: Has there been any specific example where there was, like, a very obvious this should just be one part that you can think of? [00:16:43] S1: This is very niche. But my favorite is actually how the rotational part and shaft on the motor is now one part less than what it's always been, because some very smart people figured out how to do the bearing assembly of the shaft without needing two parts, which usually it's always two parts because you kinda, like, need to sandwich it in, but it's actually one part. As... To me, that's that's very beautiful. It's half the number of parts for that. [00:17:07] S0: If you took Bernt from five years ago and you teleported him to today or teleported yourself back, would you make any decisions drastically differently than you have?