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Nah, this is just an early example of many "this is too easy it doesn't count" defensive human arguments against AI. Parallel to the "you use copilot so your c
by elif 3y ago
Nah, this is just an early example of many "this is too easy it doesn't count" defensive human arguments against AI.
Parallel to the "you use copilot so your code quality is terrible and you don't really even understand it so it's not maintainable" human coping we are familiar with.
If there is any shred of truth to these defenses, it is temporary and will be shown false by future, more powerful AI models.
Consider the theoretical prompt that allows one of these models to rapidly improve itself into an AGI. Surely you'd want to read that paper right?
- jdefr89 3y agoId much rather see a PoC…
- daveguy 3y agoNo prompt will cause an LLM to rapidly improve itself, much less into an AGI. Prompts don't cause permanent change in the LLM, only differences in output.
- elif 3y agoYou're talking about how GPT functions in 2023. I am discussing such a point where when LLM outputs become valuable LLM modifications. AI recursing on itself progressing toward an AGI.
- Intralexical 3y ago> AI recursing on itself progressing toward an AGI. Inbreeding LLMs will result in an "AGI"? In this universe, if you try to get something from nothing, you just end up with noise.
- daveguy 3y agoNo matter how many times you feed the output of an LLM back to itself, the underlying model does not change. Online training (of actual model weights not just fine-tuning) would be hugely resource intensive and not guaranteed to do any better than the initial training. Interference will happen whether catastrophic or simply drift. We can fantasize about future architectures all day long, but that doesn't make them capable of AGI or even give us a path forward.