Transcript

In chemistry computational methods, computational concepts have been used to actually invent new molecular structures that would have desired chemical properties. In physics, (this is one of my favourite examples), I am going to labour on this a little bit in quantum computing. There is a very young professor in MIT who works in quantum computing, he’s actually in the Computer Science department but he works as a physicist. In computer science, there is a kind of quantum computer where you can represent the problem in terms of a, let’s call it a graph, but you can solve the problem if you can morph this graph into some other representation/other graph. You can solve it more easily in this second representation, and so the idea is then how can you get this graph to be morphed into this graph. There is a procedure that you can use that would allow you to make manipulations of each graph until you finally come in the middle, and have that intermediate. Physicists know about this kind of quantum computer. So, the question that quantum scientists asks, is how fast you can do this? This is something that computer scientists ask all the time, how fast can you do it, right? I already said that is the question they always ask about efficiency in terms of space and time. The physicist never asks that question of themselves, they just know that there exists some path such that you can do that, but they didn’t ask, how fast can you do it? Now again, for the computer scientists in the audience, the reason this was such a tantalising question to answer, is, if it turns out that the convergence is polynomial it means that you might have an answer to the P=NP question. So you can see why this young computer scientist at MIT would very much like to know the answer to that convergence question, and it turns out that it goes really, really, really fast until this very small window where it is exponential. Even so it was a very interesting question to pose and now he tells me that the physicists are going around asking how fast on all their convergence questions. This to me is a deep way of computational thinking influencing other people’s thinking because you ask these basic questions that we would ask, and had the answer being polynomial then wow!, what a break through in computer science. We see it in Mathematics, we see it in Engineering and I think we are going to see more of it in all other fields. In society like Economics, right now, in fact tomorrow and Friday there is a workshop at Cornell on computer science and economics that an assessor is helping to sponsor and we are seeing a lot of the theories of economics and models of economics. In fact, we already know that some of them are not applying to our real world, but they are certainly not necessarily applicable to say to the internet and internet economics, and so there is all of a sudden this new interest, completely new interest, in revisiting economic models and theories in terms of computing models and vice versa. So for instance we are very much using game theoretic models in looking at lots of problems in computer science, game theory from economics, but many of the direct relationships between economics and computer science has to do with things like added placement and keyword auctions and so on. So for instance when you type into Google and you do a search, maybe you realise to the right of your search you have all these ads, well companies actually bid on where they want their company to be listed in that list of ads. You pay a lot to be listed number 1. But maybe it doesn’t matter to be listed number 1 or 2, you pay a little less to be listed number 2, you are still number 2, you are up there, right so that the kind of game theoretic thinking that people are doing in computer science. In Law we are seeing computational thinking and in the Humanities. Again in the sense of digging into the data challenge is analysing lots and lots of data.