[infgeoax]

Plus it's unclear if the amount of data used to "train" a human brain is really less than what GPT4 used. Imagine all the inputs from all the senses of a human over a lifetime: the sound, light, touches, interactions with peers, etc.

[alchemist1e9]

Don’t forget all the lifetimes of all ancestors as well. A lot of our intelligence is something we are born with and a result of many millions of years of evolution.

[Jensson]

But that is of little help when you want to train an LLM to do the job at your company. A human requires just a little bit of tutorials and help, an LLM still require an unknown amount of data to get up to speed since we haven't reached that level yet.

[infgeoax]

Yeah humans can generalize much faster than LLM with far fewer "examples" running on sandwiches and coffee.

[logicchains]

>Yeah humans can generalize much faster than LLM with far fewer "examples" running on sandwiches and coffee.

This isn't really true. If you give an LLM a large prompt detailing a new spoken language, programming language or logical framework with a couple examples, and ask it to do something with it, it'll probably do a lot better at it than if you just let an average human read the same prompt and do the same task.

[infgeoax]

Hmm, but is it really "generalizing" or just pulling information from the training data? I think that's what this benchmark is really about: to adapt to something it has never seen before quickly.