How to Build a Successful Robotics Company - Colin Angle, iRobot CEO | AI Podcast Clips

Foreign.

So I gotta ask you, I think this is a fundamental and fascinating question because iRobot has been a successful company and a rare successful robotics company. So Anki Jibo, Mayfield Robotics with a robot curry. Sci Fi Works, Rethink Robotics. These were robotics companies that were founded and run by brilliant people. But all very unfortunately, at least for us roboticists, all went out of business recently. So why do you think they didn't last longer? Why do you think it is so hard to keep a robotics company alive?

You know, I say this only partially in jest that back in the day before Roomba, you know, I was a high tech entrepreneur building robots, but it wasn't until I became a vacuum cleaner salesman that we had any success. The point is, technology alone doesn't equal a successful business. We need to go and find the compelling need where the robot that we're creating can deliver clearly more value to the end user than it costs. This is not a marginal thing where you're looking at the scale and you're like, it's close. Maybe we can hold our breath and make it work. It's clearly more value than the cost of the robot to bring in the store. And I think that the challenge has been for finding those businesses where that's true in a sustainable fashion. When you get into entertainment style things, you could be the cat's meow one year, but 85% of toys, regardless of their merit, fail to make it to their second season. It's just super hard to do. So. That's just a tough business. And there's been a lot of experimentation around what is the right type of social companion. What is the right robot in the home that is doing something other than tasks people do every week that they'd rather not do. And I'm not sure we've got it all figured out right. And so that you get brilliant roboticists with super interesting robots that ultimately don't quite have that magical user experience. And thus the that value benefit equation remains ambiguous.

So you, as somebody who dreams of robots, you know, changing the world, what's your estimate? Why? How big is the space of applications that fit the criteria that you just described where you can really demonstrate an obvious significant value over the alternative non robot robotic solution?

Well, I think that we're just about none of the way to achieving the potential of robotics at home, but we have to do it in a really eyes wide open, honest fashion.

Another way to put that is the potential is infinite because we did take a few steps. But you're saying those steps are just very initial steps. So the Roomba is a hugely successful product. But you're saying that's just the very, very beginning?

That's just the very, very beginning. It's the foot in the door. And I think I was lucky that in the early days of robotics, people would ask me, when are you going to clean my floor? It was something that I grew up saying. I got all these really good ideas, but everyone seems to want their floor clean. And. And so maybe we should do that. Yeah. Your good ideas earn the right to do the next thing after that.

So the good ideas have to match with the desire of the people, and then the actual cost has to like the business. The financial aspect has to all mash together.

Yeah. During our partnership back a number of years ago with Johnson Wax, they would explain to me that they would go into homes and just watch how people lived and try to figure out what were they doing that they really didn't really like to do. But they had to do it frequently enough that it was top of mind and understood as a burden. Hey, let's make a product or come up with a solution to make that pain point less challenging.

And sometimes we do certain burdens so often as a society that we actually don't even realize, like, it's actually hard to see that that burden is something that could be removed. So it does require just going into the home and staring at, wait, how do I actually live life? What are the pain points?

Yeah. And getting those insights is a lot harder than it would seem it should be in retrospect.

So how hard on that point? I mean, one of the big challenges of robotics is driving the cost to something, driving the cost down to something that consumers, People would afford. So people would be less likely to buy a Roomba if it cost $500,000.

Right.

Which is probably sort of what a Roomba would cost several decades ago. So how do you drive? Which I mentioned is very difficult. How do you drive the cost of a Roomba or a robot down such that people would want to buy it.

When I started building robots, the cost of the robot had a lot to do with the amount of time it took to build it. And so that we would build our robots out of aluminum, I would go spend my time in the machine shop, on the milling machine, cutting out the parts and so forth. And then when we got into the toy industry, I realized that if we were building at scale, I could determine the cost of the rope instead of adding up all the hours to mill out the parts, but by weighing it. And that's liberating. You can say, wow, the world has just changed as I think about construction in a different way. The 3D CAD tools that are available to us today, operating at scale, where I can do tooling and injection mold an arbitrarily complicated part and the cost is going to be basically the weight of the plastic in that part is incredibly exciting and liberating and opens up all sorts of opportunities. And for the sensing part of it, where we are today is instead of trying to build skin, which is like really hard, for a long time I spent creating strategies and ideas around how could we duplicate the skin on the human body because it's such an amazing sensor. Instead of going down that path, why don't we focus on vision? And how many of the problems that face a robot trying to do real work could be solved with a cheap camera and a big ass computer? And Moore's law continues to work. The cell phone industry, the mobile industry is giving us better and better tools that can run on these embedded computers. And I think we passed an important moment maybe two years ago where you could put machine vision capable processors on robots at consumer price points. And I was waiting for it to happen. We avoided putting lasers on our robots to do navigation and instead spent years researching how to do vision based navigation because you could just see where these technology trends were going. And between injection molded plastic and a camera, with a computer capable of running machine learning and visual object recognition, I could build an incredibly affordable, incredibly capable robot. And that's going to be the future. SA.