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Can you list some examples where free-associations from LLM were useful to you?
Assume free-associations = hallucinations. Assume hallucinations are exactly what makes LLMs useful and your question can be rephrased as "Can you list some examples where LLMs were useful to you?"
A group of PhD students at Stanford recently wanted to take AI/ML research ideas generated by LLMs like this and have teams of engineers execute on them at a hackathon. We were getting things prepared at AGI House SF to host the hackathon with them when we learned that the study did not pass ethical review . I think automating science is an important research direction nonetheless.
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Assume free-associations = hallucinations. Assume hallucinations are exactly what makes LLMs useful and your question can be rephrased as "Can you list some examples where LLMs were useful to you?"
Hallucinations are lies. So not the same thing.
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Assume free-associations = hallucinations. Assume hallucinations are exactly what makes LLMs useful and your question can be rephrased as "Can you list some examples where LLMs were useful to you?"
Hallucinations are lies. So not the same thing.
Cool idea. Never gonna work. LLMs are still generative models that spits out training data, incapable of highly abstract creative tasks like research. I still remember all the GPT-2 based startup idea generators that spits out pseudo-feasible startups.
I have asked chat GPT to generate hypotheses on my PhD topic that I know every single piece of existing literature about and it actually threw out some very interesting ideas that do not exist out there yet (this was before they lobotomized it).
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Ignoring the “spits out training data” bit which is at best misleading, it’s interesting that you use the word “abstract” here. I recently followed Karpathy’s GPT-from-scratch tutorial and was fascinated with how clearly you could see the models improving. With no training, the model spits out uniformly random text. With a bit of training, the model starts generating gibberish. With further training, the model starts…
If we keep extrapolating eventually GPT will be omniscient. I really can't think of any reason why that wouldn't be the case, given the exponential curve we find ourselves on.
Cool idea. Never gonna work. LLMs are still generative models that spits out training data, incapable of highly abstract creative tasks like research. I still remember all the GPT-2 based startup idea generators that spits out pseudo-feasible startups.
I have asked chat GPT to generate hypotheses on my PhD topic that I know every single piece of existing literature about and it actually threw out some very interesting ideas that do not exist out there yet (this was before they lobotomized it).
Of course, of course. Because god forbid anyone be able to reproduce your suggestion. Funnily enough I tried the same and have the exact opposite experience.
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If we keep extrapolating eventually GPT will be omniscient. I really can't think of any reason why that wouldn't be the case, given the exponential curve we find ourselves on.
This has the form of a religious belief.