Lex Fridman: uncertainty

Transcript context

…Yes. Okay. Is there some more practical engineering lessons from TensorFlow Quantum? Just organizationally too, like the humans involved and how to get to a product, how to create good documentation? I don’t know. All of these little subtle things that people might not think about. I think working across disciplinary boundaries is always a challenge, and you have to be extremely patient in teaching one another. I learned a lot of software engineering through the process. My colleagues learned a lot of quantum physics, and some learned machine learning through the process of building this system. And I think if you get some smart people that are passionate and trust each other in a room, and you have a small team- Are passionate and trust each other in a room, and you have a small team, and you teach each other your specialties, suddenly you’re kind of forming this sort of model soup of expertise, and something special comes out of that, right? It’s like combining genes, but for your knowledge bases, and sometimes special products come out of that. And so I think, even though it’s very high friction initially to work in an interdisciplinary team, I think the product at the end of the day is worth it. And so, learned a lot trying to bridge the gap there. And I mean, it’s still a challenge to this day. We hire folks that have an AI background, folks that have a pure physics background, and somehow we have to make them talk to one another. Right?…

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