100x is an assumption. LLMs can hit a ceiling (already prohibitively expensive to train), GPUs can hit a ceiling (we are not far from silicon semiconductor limits) and we might end up with a decade of "almost there, but not yet".
There is still relatively low-hanging fruit because this is a very specific application that suddenly has a huge amount of attention. So there are software improvements, model improvements, and hardware improvements. Probably before we even start a truly new paradigm, Nvidia can get close to 10X by focusing on GPT. Model improvements can likely get another order of magnitude.
There are also radically different compute-in-memory paradigms in the pipeline.
Things like high-bandwidth senses tied to a body, stream of subjective experience, control seeking, self-centeredness, self-preservation, reproductive instincts, emotions. Also GPT doesn't have certain types of adaptivity yet. Or anything else that is part of being alive.
I asked Bard for help, and it allucinated the fictional "The Last Human" by Isaac Asimov, and even described the plot when asked.
ChatGPT allucinated that Ken Liu's story called "The Perfect Match" was about personal assistants named "Jorges", after Dr. Jorge Luis Borges, who volunteered for the mind-uploading experiment.
Crowdsourcing to the right subreddit would likely bring the correct answer, so at least we know it doesn't help if AIs think faster than humans, if they don't learn to think as different personas.
I just wanted to quote the story, but this got me sidetracked.