[famouswaffles]

>There’s every reason to believe that AGI is meaningfully different from LLMs because humans do not take anywhere near this amount of training data to create inferences

The human brain is millions of years of brute force evolution in the making. Comparing it to a transformer or any other ANN really which essentially start from scratch relatively speaking doesn't mean much.

[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.