Comment by TeMPOraL
8 years ago
The mouse reacts to stimuli and environment in a qualitatively different way than our programs do. It does continuous and essentially free-form learning of the environment around it, and engages in what looks to us as dynamic formulation and achievement of goals. In "AI" we have today, the learning is very shallow (despite the "deep learning" buzzword), it's usually neither free-form nor continuous, and goals are set in stone.
The goals for a mouse are also set in stone and simple: maximize brain dopamine. Almost everything a mouse does can be described in terms of maximizing that 'reward', and that can lead to a host of other emergent behavior.
I don't see much difference between that and Open AI's engine: https://openai.com/five/. Watch some of those games and you definitely see the same dynamic formulation and complex decision-making, none of which was directly programmed.
You are applying what you know about the learning process in current AI. But if you simply observed behavior between a real mouse and an AI mouse, especially if the latter was trained to mimic the behavior of the former, can you tell that they react in a completely different way?
If your AI mouse would behave like the real mouse for couple hours of observation, I'd conclude you've done a good job.
I'm not trying to make a Chinese room argument (which I don't buy), implying there's some hidden "spark" needed. I'm just saying that currently existing "AI" programs are pretty far from mouse brain, both in individual capabilities and the way they're deployed together (i.e. they're not). For instance, deep learning is to mice brains what a sensor/DSP stack is to a processor. We seem to be making progress in higher-level processing of inputs, but what's lacking is the "meat" that would turn it into a set of behaviors giving rise to a thinking entity.