Earlier quoted context omitted.
The current crop of LLMs is like Paleozoic megafauna, or like Egyptian Pyramids. It takes a few relatively simple approaches and stretches them wildly, using colossal computing resources. Live systems in nature seem to solve similar problems with way less compute available. There should be better architectures. Also, as somebody said, every exponential growth curve is a lower part of a sigmoid. LLMs will plateau at s…
>Live systems in nature seem to solve similar problems with way less compute available Do they really? They're certainly more energy-efficient in business-as-usual mode, but a human brain has 86 billion neurons, 600+ trillion synapses(!), and each instance takes 15-20+ years to train to do complex logical tasks. Even if the per-cell work is tiny (and, is it? cells are amazingly complex), 86 billion (or 600+ trillion)…
Show me a humanoid robot that can do that.