[Ukv]

I'm relatively optimistic, on the grounds that:

1. Diminishing returns on a model's capability with respect to scale means that, even if big tech datacenters grow at a faster rate than infrastructure available to individual researchers, the gap in performance between their models will narrow - with big tech needing to invest increasing resources even just to gain a shrinking lead

2. Many applications of AI don't need the latest massive LLMs. Some defect detector may reach 99.9% accuracy at which point further work gives negligible improvement, and the hardware cost to reach that point is steadily decreasing - putting it in range of more individuals/small companies/etc.