> It’s still fairly safe to argue that the best LLMs today are not yet thinking, at least not in a way a human does. But in another generation or two? It will b

> It’s still fairly safe to argue that the best LLMs today are not yet thinking, at least not in a way a human does. But in another generation or two? It will become much harder to deny. Current LLMs have a hard division between training and inference time; human brains don’t-we train as we infer (although we probably do a mix of online/offline training: you build new connections while awake, but then pruning and consolidation happens while you sleep). I think softening the training-vs-inference division is a necessary (but possibly not sufficient) condition for closing the artificial-vs-human intelligence gap. But that softening is going to require completely different architectures from current LLMs, and I don’t think anyone has much of an idea what those new architectures will look like, or how long it will take for them to arrive