Artificial Intelligence Asked by datdinhquoc on July 21, 2020
Everybody is implementing and using DNN with, for example, TensorFlow or PyTorch.
I thought IBM Deep Blue was an ANN-based AI system, however, it says in the following URL that IBM Deep Blue was symbolic AI:
https://analyticsindiamag.com/understanding-difference-symbolic-ai-non-symbolic-ai/
Any special features in symbolic AI that it was used by IBM Deep Blue instead of ANN?
ANNs as used today need 1. a lot of data 2. a lot of computational power. Before we had any of the above two, we didn't really know how to properly build ANNs since we didn't quite have the means to train the network, and thus couldn't evaluate it.
"Symbolic AI" on the other hand, is very much just a bunch of if-else/logical conditions, much like regular programming. You don't need to think too much about the whole "symbolic" part of it. The main/big breakthrough is that you had a lot of clever "search algorithms" and a lot of computation power relative to before.
Point being, is just that symbolic AI was the main research program at the time, and people didn't really bother with "connectionist" methods.
Correct answer by k.c. sayz 'k.c sayz' on July 21, 2020
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