Caitlin Kalinowski: prediction

Transcript context

…Okay, ever. Right. So if you're building hardware, you redesign it in CAD for every major build and then you have to release it. And once it's released, you compile it the last time you release it for mass production. If it's a mass production device, that's it. You're done. You can't ship over their updates. So we have a different approach. We have to have a different approach, which is more conservative. You have to do more of the reliability checks and tests in line with the program because once you compile that last time, you're done. You make all the parts, you put them together, they're out in the world. The only alternative is to ship something new to replace it a couple years later. And so we have to be more conservative and we have to take our time because if you think about it, a product that sells millions, if you have a graph of all the parts put together on any different part of the device, you have a curve, you're in the plus and minus three sigma or more. So meaning if you have two parts that go together, you're going to get the smallest version of this one and the largest version of this one and you're going to have to put those together across the board. People don't think about this that much, but the part variance is pretty high. And so we've got to solve for that last half a percent in the process of building so that when we compile our last time, when we build our last time, it's done and we're going to have a high yield, we're going to be able to make them and make money on them effectively and we won't have very many returns. And so that's kind of the game that we're playing. It sounds so hard and complicated. They're just like, "Software is so nice, you just write some code, ship it. It's great." Why do you think people are getting so into robots and hardware now? What's the driving trend?…

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