Whenever I see them described as “plagiarism machines”, odds are about 99% that the person using the term have no idea how these models work. Like with humans, they can overfit, but most of what they output will have have far less in common with any individual work than levels of imitations people engage in without being accused of plagiarism all the time.
As for the environmental effects, it’s a totally ridiculous claim - the GPUs used to train even the top of the line ChatGPT models adds up to a tiny rounding error of the power use of even middling online games, and training has only gotten more efficient since.
E.g. researchers at Oak Ridge National Labs published a paper in December after having trained a GPT4 scale model with only 3k GPUs on the Frontier supercomputer using Megatron-DeepSpeed. 3k GPUs is about 8% of Frontiers capacity, and while Frontier is currently fastest, there are hundreds of supercomputers at that kind of scale publicly known about, and many more that are not. Never mind the many millions of GPUs not part of any supercomputer.
Whenever I see them described as “plagiarism machines”, odds are about 99% that the person using the term have no idea how these models work. Like with humans, they can overfit, but most of what they output will have have far less in common with any individual work than levels of imitations people engage in without being accused of plagiarism all the time.
As for the environmental effects, it’s a totally ridiculous claim - the GPUs used to train even the top of the line ChatGPT models adds up to a tiny rounding error of the power use of even middling online games, and training has only gotten more efficient since.
E.g. researchers at Oak Ridge National Labs published a paper in December after having trained a GPT4 scale model with only 3k GPUs on the Frontier supercomputer using Megatron-DeepSpeed. 3k GPUs is about 8% of Frontiers capacity, and while Frontier is currently fastest, there are hundreds of supercomputers at that kind of scale publicly known about, and many more that are not. Never mind the many millions of GPUs not part of any supercomputer.