alt Hacker NewsCall me a conspiracy theorist, and granted much of this could be attributed to the fact that the majority of code in existence is shit, but im convinced that these models are trained and encouraged to produce code that is difficult for humans to work on. Further driving and cementing the usage of then when you inevitably have to come back and fix it.
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This could be the case even without an intentional conspiracy. It's harder to give negative feedback to poor quality code that's complicated vs. poor quality code that's simple.
Hence the feedback these models get could theoretically funnel them to unnecessarily complicated solutions.
No clue has any research been done into this, just a thought OTTOMH.
Or it takes a lot of time effort and intelligence to produce good code and IA is not there yet…
It is a mathematical, averaging model after all
I don't think they would be able to have an LLM withouth the flaws. The problem is that an LLM cannot make a distinction between sense and nonsense in the logical way. If you train an LLM on a lot of sensible material, it will try to reproduce it by matching training material context and prompt context. The system does not work on the basis of logical principles, but it can sound intelligent.
I think LLM producers can improve their models by quite a margin if customers train the LLM for free, meaning: if people correct the LLM, the companies can use the session context + feedback to as training. This enables more convincing responses for finer nuances of context, but it still does not work on logical principles.
LLM interaction with customers might become the real learning phase. This doesn't bode well for players late in the game.