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If these things get put on specialized hardware for inference with much lower energy costs, the world will never be the same.
the biggest problem first of all might be the memory requirements given so many parameters. It couldn't be as cheap as a high end computer in the foreseeable future.
Earlier quoted context omitted.
Imagine any diffusion-style text-to-image model on specialized ASIC hardware.
That’s what an ANE/TPU is. If you mean putting the model weights into gates directly, it’d be useless because users would get bored of the model as soon as they figured out what its style looked like. Also, large models can memorize their training data so eventually you’ll get it to output something copyrighted.
I understand I can query such a model, one query at a time. But are there way to query these models with several queries in a row such that the N+1-th query benefit from the knowledge that was used to answer the N first questions ? Basically, following a conversation. For example, youtube subtitles can badly translate some terms but if "it" had in mind the overall subject of the video, then it'd probably pick the cor…