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This is just wrong. First of all, you're rejecting teleological anthropomorphizing (saying it's weird to act as if "the weights have some goal") but then in t
by MarkusQ 3y ago
This is just wrong.
First of all, you're rejecting teleological anthropomorphizing (saying it's weird to act as if "the weights have some goal") but then in the very next line you talk about the optimizer making "an attempt" to accomplish a goal. All of which misses the point, since the question is about _explanations_ not goals and intentions.
Then you reject out of hand any other level of explanation than the one you favor, saying "it's not more or less than that" when in fact it is both more and less than that; you can climb the ladder of abstraction either way to build more or less abstract explanations. We can dig down and talk about how the optimizer adjusts weights, or how tensor math works and how it's used in this case, or about how GPUs work, or gates, or transistors, etc. Or we could climb up and talk about (as this article does) and talk about what attention heads do, and why they work, when they work, when they don't, etc.
- danielmarkbruce 3y agoThe optimizer has a goal. The weights in the model do not. The optimizer isn't the model. There is no contradiction if you know how it works. Climbing the layer of abstraction from model weights doesn't seem to work in this field. Just saying it's so doesn't make it so.
- MarkusQ 3y ago> Just saying it's so doesn't make it so. Does that apply to you as well?
- danielmarkbruce 3y agoOf course. You shouldn't take my word for it. You can learn the basics of AI/ML from a number of good texts. Simon Prince just released a very approachable text, although it doesn't cover much in the way of history to see the move to "more data/more compute, less human lead abstraction". I think Norvig's book covers that but I haven't read the latest version.
- MarkusQ 3y agoYou sure like to make assumptions, don't you? :)