What's the human baseline? How many cats does a human need to see to learn what a cat is, vs an AI?

Maybe not quite a fair comparison since my human brain has been "learning" for half a billion years before I was born.

I wonder if there's an equivalent of that for AI. Evolving the architectures?

The human genome contains around 1.5GB of information and DeepSeek v3 weighs in at around 800GB, so it's a bit apples-to-oranges. As you say, what's been evolved over hundreds of millions of years is the learning apparatus and architecture, but we largely learn online from there (with some built-in behaviours like reflexes). It's a testament to the robustness of our brains that the overwhelming majority of humans learn pretty effectively. I suspect LLM training runs are substantially more volatile (as well as suffering from the obvious data efficiency issues).

If you'd like an unsolicited recommendation, 'A Brief History of Intelligence' by Max Bennett is a good, accessible book on this topic. It explicitly draws parallels between the brain's evolution and modern AI.

	▲	jack_pp 3 hours ago \| parent \| next [-]
		And that same information contained in an LLM is a compression of how many terabytes of training data? Maybe in the future there will be models an order of magnitude smaller and still better performing. What I'm saying is you can't judge the data in the genome by purely counting the bytes of data.
	▲	idiotsecant an hour ago \| parent \| prev [-]
		The human genome isn't its own thing, the genome as a static sequence is really just an abstraction. What actually functions as the heritable unit includes epigenetic marks, non-coding RNA regulation, 3D chromatin structure, and mitochondrial DNA. In the real biological world there are very few sharp edges - systems bleed into one another and trying to define something like 'the number of bits in the human genome' is very difficult, but it's undoubtedly way bigger than you posit here.

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jamilton 3 hours ago | parent | prev | next [-]

Also interesting to consider how much "compute" has to be spent by humans are learning something like that. Like, do we need to see more examples if learning from pictures of cats and dogs than seeing them in person? How many more examples? What if we're seeing them all in sequence, or spread out across hours or days?

I've probably seen... at least a dozen pictures of aardvarks and anteaters and maybe even see one of them at the zoo but I don't think I could reliably remember which was which without a reminder.

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SatvikBeri 3 hours ago | parent | prev | next [-]

I think my toddler saw roughly 100 dogs and cats before she was able to reliably tell the difference.

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sdpmas 5 hours ago | parent | prev [-]

i think evolution meta-learns the architecture, hyperparams. some domain knowledge too (for ex, we all perceive the world as 3d) but not much. if you compare the text consumed by human vs AI (and i think this is fair b/c even with evolution text is a pretty recent invention for humans), the gap is many orders of magnitude.

	▲	throwaway894345 4 hours ago \| parent [-]
		Tangentially, some scientists think humans may have hardwiring for detecting snakes https://en.wikipedia.org/wiki/Snake_detection_theory