> that doesn't require re-running the same conversation sixteen bajillion times in a row Lets assume the dog visual systems run at 60 frames per second. If it

> that doesn't require re-running the same conversation sixteen bajillion times in a row Lets assume the dog visual systems run at 60 frames per second. If it takes 1 second to flip a bowl of food over then that's 60 datapoints of cause-effect data that the dog's brain learned from. Assuming it's the same for humans, lets say I go on a trip to the grocery store for 1 hour. That's 216,000 data points from one trip. Not to mention auditory data, touch, smell, and even taste. > ability to reason [...] Transformer models do not Can you tell me what reasoning is? Why can't transformers reason? Note I said transformers not llm's. You could make a reasonable (hah) case that current LLMs cannot reason (or at least very well) but why are transformers as an architecture doomed? What about chain of thought? Some have made the claim that chain of thought adds recurrence to transformer models. That's a pretty big shift, but you've already decided transformers are a dead end so no chance of that making a difference right?