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LLM failure modes are caused by the lack of external context - they perform poorly on visual tasks because they have no sense of vision for example. Hallucinati
by Jack000 3y ago
LLM failure modes are caused by the lack of external context - they perform poorly on visual tasks because they have no sense of vision for example. Hallucinations are another aspect of this - as embodied agents, humans and animals have a strong bias for counterfactual reasoning because it is needed to survive in a complex information-rich environment (if you believe in something that is false, you tend to get eaten)
The real solution to these problems is to train transformers on a more human-like information context rather than pure text. Hallucinations should naturally decrease as LLMs become more "agentic"
- nomel 3y agoIn my mind, I have a "confidence" in my memories and what I know, which seems to be based on how much "context" I can tie it to. This is how I can identify false memories, and say "I don't know". Is there some "confidence" coefficient that we can extract from AI? I would claim that hallucinations are required for creativity and problem solving. A "novel" answer is a hallucination to the existing dataset. For a simple example, have ChatGPT-4 come up with a new words that combine two concepts. I imagine this wouldn't be possible if hallucinations weren't allowed.