So it makes sense to use chess as a measuring stick for the development of artificial intelligence. What was your role specifically on the Deep Blue team? I was the AI expert.
Deep Blue was a chess-playing computer developed by IBM. It is known for being the first computer chess-playing system to win both a chess game and a chess. Deep Blue may refer to: Deep Blue (chess computer), a chess-playing computer developed by IBM that defeated world champion Garry Kasparov in
AI was quite different in and early The dominant part in those days was what we now called good old-fashioned AI, or symbolic AI, which was based less on machine learning. Certainly machine learning was a serious field in those days but nothing like what it is today, where we have massive data sets and large computers and very advanced algorithms to churn through the data and come up with models that can do some amazing things.
When I started with IBM, machine learning methods for game-playing programs were fairly primitive and not able to help us much in building Deep Blue. We worked on algorithms for efficient search and evaluation of the possible continuations, which we knew Deep Blue would need in order to compete. What were the most significant limitations on AI back then? So, we made do with much smaller data sets.
How useful was your own chess expertise in building Deep Blue? Not as useful as you might think.
I was able to, in the early stages, identify problems with the system and suggest approaches that I felt would be able to fix one problem without creating a host of other problems. That was probably good enough to get us to a certain point. When we got closer to the point where we would actually be playing against a world champion we brought in grand masters— Joel Benjamin , in particular—to help us. There were two parts to how they helped.
One, in particular, was to help with the opening library, which every chess program uses in order to save time and make sure it gets into reasonable positions.
Humans have been studying chess openings for centuries and developed their own favorite [moves]. The grand masters helped us choose a bunch of those to program into Deep Blue. They also were, you could say, sparring partners for Deep Blue. They would play against the computer and try and pinpoint weaknesses of the system.
lastsurestart.co.uk/libraries/spouse/1425-mobile-tinder.php And then we would sit around with them and with the rest of the Deep Blue team and try to articulate what that weakness actually was and if there was a way to address it. But often there was some way we could improve its ability to deal with a problem we had identified. How did Deep Blue decide which moves to make? Deep Blue was a hybrid.
But reportedly, about surfers from beaches around Byron Bay, held a meeting on Monday night in which 95 per cent supported a limited cull focussing on great white sharks which have been regularly spotted in the area. The thing is, what price do we put on a [human] life? Although the future of shark protection on Australia's East Coast seems uncertain, we're pleased to see a large white shark belie the myth of a blood-thirsty predator intent on hunting humans.
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