So I choose to look at visual intelligence and my PhD and my early professor years, my students and I are very committed to a north star problem, which is solving the problem of object recognition because it's a building block for the perceptual world, right? We go around the world interpreting reasoning and interacting with it more or less at the object level. We don't interact with the world at the molecular level. We don't interact with the world as... We sometimes do, but we rarely, for example, if you want to lift a teapot, you don't say, "Okay, the teapot is made of a hundred pieces of porcelain and let me work on this a hundred pieces." You look at this as one object and interact with it. So object is really important. So I was among the first researchers to identify this as a north star problem, but I think what happened is that as a student of AI and a researcher of AI, I was working on all kinds of mathematical models including neural network, including Bayesian network, including many, many models.
So I was among the first researchers to identify this as a north star problem, but I think what happened is that as a student of AI and a researcher of AI, I was working on all kinds of mathematical models including neural network, including Bayesian network, including many, many models.