| > We can determine by looking at certain problems (The Halting Problem is one such example) what the outcome will be without actually having to execute that code. No, we definitely can't do that in general, and that lack of generality is the halting problem. > Take time to observe the interactions that occur and think about how little [training] is involved here. Apart from "all of evolutionary history", (though everyone agrees AI are slow learners when counting how many examples they need if that's your point?), there's continuous feedback from pleasure and pain and probably a lot more emotions that don't necessarily map onto any human qualia. > I think that when you think about how we program our various artificial stupidity systems that we are still at the caveman stage in our computational systems. We have barely discovered fire so to speak. I'd use a different analogy; dinosaur perhaps. > As for [GPT-3 is about as complex as the brain of a rodent], I don't think GPT-3 has even reached a single bacterium cell state of intelligence. I think my Roomba-clone does that: touch an obstacle, back off, rotate a few degrees, go forward again. Now that, I'm fairly sure was programmed rather than learned (in the robot; still learned in the bacteria via evolution). > I would like you to try the following: Using your index finger on your left hand, touch the tip of your nose. > Now think about this: How did you do that very simple task? When did you learn and how did you learn to do that simple task? How: a network of neurons, if I remember right about 40 deep, integrating mostly proprioceptor input as it's continuously updated when my muscles move. When: unclear, either as an infant before and autobiographical memories, or genetic (which is arguably "not me"). I'm not sure this matters, either way though, as we do have robots which are navigating entirely by proprioception, and which again learned by training rather than being programmed. > What programming do we need to do to achieve this task? basically: """
from FooLibrary import AiModel model = AiModel() model.learn(input, expected_output)
""" With a lot of optional parameters in the constructor for different hyperparameters like "learning rate" and neurons/layers… > We can build very useful tools that we can use to good purpose. But no tool is ever more than a tool for us. When tools stops being mere tools — regards of this is mere perception, or when peasants and slaves revolt, or when (Australia) pest-control animals themselves become pests — we generally have big problems. I agree the world is more fragile; I don't know if AI will help or not. |