Comment by levocardia

There's a Stephen Boyd quote that's something like "if your optimization problem is too computationally expensive, just go on vacation to Greece for a few weeks and by the time you get back, computers might be fast enough to solve it." With LLMs there's sort of an equivalent situation with cost: how mindblowing would it be able to train this kind of LLM at all even just 4 years ago? And today you can get a kindergartener level chat model for about $100. Not hard to imagine the same model costing $10 of compute in a few years.

There's also a reasonable way to "leapfrog" the training cost with a pre-trained model. So if you were doing nanochat as a learning exercise and had no money, the idea would be to code it up, run one or two very slow gradient descent iterations on your slow machine to make sure it is working, then download a pre-trained version from someone who could spare the compute.