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I see what you're saying, but I don't really think understanding how they work is the problem. We do understand how they work. You can go read the many papers t
by sanderjd 9d ago
I see what you're saying, but I don't really think understanding how they work is the problem. We do understand how they work. You can go read the many papers that have been published as the technology has been developed. It is not mysterious. We don't need to understand the "clever algorithm", we already understand that. The sense of mystery is because the results of the algorithm are non deterministic, and because the number of parameters that determine the outcome is so large that it appears to exhibit emergent behavior.
I guess I agree with your general premise that tools we use should not be treated as magic. But I don't think this is a problem to be solved, it's possible to learn how these things work, and people should definitely do that.
- js8 9d agoI disagree we understand LLMs, your view is quite reductionist. It's like saying we understand human brain because we understand physics and evolution, or that we understand some program because it's just a binary code in a known instruction set. I think Dennett's theory of intentionality (see https://en.wikipedia.org/wiki/Intentional_stance https://en.wikipedia.org/wiki/Intentional_stance) applies here. We do understand LLMs from physical stance (ML algorithm and inference), but we don't fully understand them from design stance (it's internal workings have been evolved so it's hard to tell the functional units) and from the intentional stance they are a complete mystery. And I talk about obstacles to this understanding elsewhere in this thread.
- sanderjd 9d ago[dead]