A language model is also capable of one shot learning. Try it in the chat, you tell it something, once, and it incorporates it for the rest of the chat. :-) Yo

A language model is also capable of one shot learning. Try it in the chat, you tell it something, once, and it incorporates it for the rest of the chat. :-) You may think I don't know what "one shot learning" means, but I do know, I'm just saying it's a problem of our perspective, not of the model's capability. Aside from it having no long term memory (by design) from the chat. Yet. Our high-level learning is absolutely nothing like how we learned as toddlers. It took us DECADES to understand complex concepts from "few shots". Only pretrained models can do that, and you're also one, in your adulthood. What you say about extra complexity from neuron types and neurotransmitters combining with one another to modulate even simple networks is true of course. But it's also true you don't need to replicate all those organic details in a NN, because they're equivalent to just a few more "regular" parameters. Think of an artificial neuron in a network as a Turing machine. A Turing machine can do everything with just some more tape, and a neural network can do everything with just some more parameters. And yet, our models show that we don't need AS many parameters as we thought. And that's exciting.