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by Agraillo
240 days ago
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> Today's "artificial intelligence" analyzes words (tokens) based on an input (prompt) to come up with an output. It's predictable. It's fast. But, imho, it lacks creativity ... I would have agreed with you at the dawn of LLM emergence, but not anymore. Not because the models have improved, but because I have a better understanding and more experience now. Token prediction is what everyone cites, and it still holds true. This mechanism is usually illustrated with an observable pattern, like the question, "Are antibiotics bad for your gut?" which is the predictability you mentioned. But LLM creativity begins to emerge when we apply what I’d call "constraining creativity." You still use token prediction, but the preceding tokens introduce an unusual or unexpected context - such as subjects that don't usually appear together or a new paradoxical observation (It's interesting that for fact-based queries, rare constraints lead to hallucinations, but here they're welcome) I often use the latter for fun by asking an LLM to create a stand-up sketch based on an interesting observation I noticed. The results aren’t perfect, but they combine the unpredictability of token generation under constraints (funny details, in the case of the sketch) with the cultural constraints learned during training. For example, a sketch imagining doves and balconies as if they were people and real estate. The quote below from that sketch show that there are intersecting patterns between the world of human real estate and the world of birds, but mixed in a humorous way. "You want to buy this balcony? That’ll be 500 sunflower seeds down, and 5 seeds a day interest. Late payments? We send the hawk after you."
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