3 ms·
> they actually can freely introspect their thought process as part of their thought process. Do you mean that they can in principle? I don't know existing sys
by red75prime 8y ago
> they actually can freely introspect their thought process as part of their thought process.
Do you mean that they can in principle? I don't know existing systems, which can inspect their own weights and output a vector of confidence scores that they can recognize classes A, B, C, ...
- deleted 8y ago[deleted]
- p1esk 8y agooutput a vector of confidence scores that they can recognize classes A, B, C, ... This is literally what neural networks do when classifying patterns.
- red75prime 8y agoThey classify patterns, not their own ability to classify patterns.
- p1esk 8y agoAgain, they literally produce confidence scores - probabilities that each prediction is correct. For example, say there are 3 classes, and the network is shown two different examples of class 2. Say it outputs a class probability distribution {0.02, 0.45, 0.43} for the first example, and {0.02, 0.9, 0.08} for the second. Even though in both cases it correctly identifies class 2, it's a lot more confident in its prediction in the second case.
- red75prime 8y agoI just say that there's no introspection in existing networks. There's no part, which can take the weights of a convolutional part of a network and images of a certain class, and then output confidence score of the convolutional part classification ability for that class. I don't say that it is possible or useful. I said that I don't know of any deep learning systems, which "[...] can freely introspect their thought process as part of their thought process."