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This is a silly point. Just because the size of these things is too large for our tiny brains, it doesn't mean we have no idea why it does what it does. If you
by danielmarkbruce 1mo ago
This is a silly point. Just because the size of these things is too large for our tiny brains, it doesn't mean we have no idea why it does what it does. If you run a physics simulation of a weather system, you have a situation that is unpredictable for a human - but it's not fair to say "we have no idea why the outputs are what they are!!"
- auggierose 1mo agoThat is not a silly point at all. You confuse understanding the mechanics of it with having a theory of why it works. For the physics simulation, physics provides us with the theories which give us the equations underlying the physics simulation. For neural networks, why is next word prediction giving us AI that can do math? We don't really know!
- danielmarkbruce 1mo agoThere is no "theory" of tomorrow's weather. We understand the math of every single individual equation of an LLM (for example), just like we understand every single equation in the physics simulation. It's the entirety of the system that we don't understand (and hence can't predict) in our heads. From a biology perspective - we have a good understanding of the carbon atom and how forces influence it. We really don't know much about a cell.