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The biggest counter-example is with "hack" to AI. If you can change two pixels in an image, in imperceptible ways to a human, and an AI chooses "cat" instead of
by speedplane 8y ago
The biggest counter-example is with "hack" to AI. If you can change two pixels in an image, in imperceptible ways to a human, and an AI chooses "cat" instead of "dog", it shows there is something terribly different between how an AI operates compared to a human.
Perhaps "bugs" like that can be fixed with more/less neurons, training data, or neuron organization, but it doesn't change the fact that fundamentally, a neural network's definition of understanding is quite different from our own.
Based on this, I suspect that even if neural networks are the long-term answer, we're nowhere close to any sort of general AI that mimics human understanding.
That said, we can certainly make many useful tools in the interim.
- taeric 8y agoMeh, look at how many people see visions in shadows and whatnot. The very constellations can almost be seen this way. That is, yes, you can fool machines. But you can also fool people. That you fool the two in different ways isn't that surprising. Nor is the fact that you would want to. Just look at camouflage. Basically the same exact thing, just in the physical world. (And, notably, not something monopolized by humans.)
- speedplane 8y agoIf you need different methods to fool machines and humans, it means that they aren't really thinking in the same way.
- taeric 8y agoAh, I think I'm arguing a different point, then. I fully grant they are thinking in different ways. For that matter, though, so do different humans. There is a great Feynman story about how he and a colleague both counted "in their heads" using completely different methods. To surprising results. So, I am not arguing that they think the same way. I just don't know if that really matters. Regardless of if they think the same or another way, there will be ways to fool them. They could still be "thinking", though.