> but that also involves an exponential increase in costNot necessarily. For training, yes. But there surely will be custom hardware specialized for the inference of "1-bit" quantized models, which could be orders of magnitude more energy-effective than GPUs.
Hell, you probably can even bake trained models in silicon. Maybe instead of digital logic, use analog circuits. Photonics?
I believe there's so much room for improvement and I feel that GPUs are just the "training wheels" (lol, quite literally) — there will be exponentially more effective hardware for running LLMs.