I guess the challenge here is that the human mind is not a blank slate, and has been optimized first by billions of years of evolution.

If it takes all the data on the internet (or more) to bootstrap AGI, but that system is then capable of leveraging its knowledge to solve new out-of-distribution tasks, that seems like a fair test to me.

I agree with the article that we see "sparks" of this generality with GPT4.

   become more creative with a fraction of the data consumed by GPT-4

not if you understand the input stream of vision as an equivalent input stream of semantic tokens as in multimodal models. under that definition people looking around for 10 years receive much more training data than large language models and thus perform a bit better at zero shot inference.

Not sure I would call constant real-time perceptual stimuli since before birth "a fraction of the training data."

or better yet, chuck it in an open plain and see how long it takes to figure out how to attach a rock to a stick and fight a gazelle to refuel it's energy supply.