this post was submitted on 16 Dec 2023
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Training one AI with the output of another AI will just make an even crappier AI.
There is actually a whole subsection of AI focused on training one model with the output of another called knowledge distillation.
Depends how it's done. GAN (Generative Adversarial Network) training works with exactly that, having networks train against each other, each improving the other over time.
Works kinda neat with stable Diffusion tho
Like photocopying a picture of a terd
I've watched Multiplicity enough times to know you get a slightly less functional copy.
She touched my peppy Steve.
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Sounds like what you'd get if you ordered a ChatGPT off of Wish dot com. Cheap knock-offs that blatantly steal ideas/designs and somewhat work are kinda their thing.
Not necessarily: there have been recent works that indicate that filtering effects of fine tuned LLMs greatly improves the data efficiency (e.g phi-1). Further, if you have e.g. human selection on top of LLM generated content you can get great results as the LLM generation can be used as a soft curriculum, with the human selection biasing towards higher quality.