CVPR Daily - Wednesday

Andrew Fitzgibbon leads the All Data AI theme at Microsoft Research in Cambridge and has worked for Microsoft for the past 15 years. He also teaches at Cambridge University and has a PhD student there. Andrew, do you feel more of a teacher, or a business technologist? I really enjoy trying to be clear about things, so teaching is a chance to try to very clearly explain something that’s happening. I like teaching Fourier transforms to undergraduates because it’s fun to keep one’s hand on the mathematics. The fantastic thing about students, especially undergraduates, is they have no idea what’s difficult and what’s easy. They just try to understand and if they don’t understand, they tell you. They spot bugs in your reasoning, in your descriptions, very, very quickly. Were you like this when you were in their place? Good question. That’s what I’m here for! I notice when something is a bit wrong, and in fact, it’s almost a way I generate research ideas. I find things that are weird or annoying. Is there anything that your generation should learn from the current generation of students? Yes. Oh, that’s a great question. Thank you, that’s the second time that you’ve told me that. I will start to believe it! I like that they’re self-confident. Well, they were trained to be more self-confident than we were. We were trained to accept discipline and authority, while they’re actually used to challenge it. Yes. Which is obviously very useful. One thing that’s good about being old, because I’m just over 50, is I’ve just got better at predicting what an algorithm will do without having to run it. So, it’s better intuition? Is it intuition? I don’t know. It’s definitely to do with experience. You’ve just seen enough things tried in different ways. I’ve definitely learned to try to prove myself wrong. I think it was Oscar Wilde who said: experience is the name that people give to their failures. Maybe the fact that we did something many times leads us to know where it will lead to. That’s right, and easier to predict when things will fail, or to predict how to break things, which is just as important. Andrew Fitzgibbon 10 DAILY CVPR Wednesday Guest