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Comment by dsalfdslfdsa | Hacker News Reader

"Efficient" and "better" are very different descriptors of a learning algorithm.

The human brain does what it does using about 20W. LLM power usage is somewhat unfavourable compared to that.

You mean energy-efficient, this would be neuron, or synapse-efficient.

I don't think we can say that, either. After all, the brain is able to perform both processing and storage with its neurons. The quotes about LLMs are talking only about connections between data items stored elsewhere.

Stored where?

You tell me. Not in the trillion links of a LLM, that's for sure.

I'm not aware that (base) LLMs use any form of database to generate their answers- so yes, all their knowledge is stored in their hundreds of billions of synapses.

Fair enough. OTOH, generating human-like text responses is a relatively small part of the human brain's skillset.

I don't know - it's about the best I can manage some days...

Hm. I've always commented on my (temporarily) non-retrievable memories as, "The data is still in there, it's the retrieval mechanism that degrades if not used." And, sure enough, in most cases the memory returns in a day or so, even if you don't think hard about it. (There are cases where the memory doesn't come back, as if it was actively erased or was never in long term memory in the first place. Also, as I pass eighty, I find it increasingly difficult to memorize things, and I forget recent events more readily. But I remember decades old events about as well as I ever did.)

So, my first response to your comment about the memory not being in the synapses was to agree with you. But I also agree with your respondent, so, hm.

The "knowledge" of an LLM is indeed stored in the connections between neurons. This is analogous to real neurons as well. Your neurons and the connections between them is the memory.

Also, these two networks achieves vastly different results, per watt consumed. A NN creates a painting in 4s on my M2 MacBook; an artist in 4 hours. Are their used joules equivalent? How many humans would it take to simulate MacOS?

Horsepower comparisons here are nuanced and fatally tricky!

What software are you using for local NN generation of paintings? Even so, the training cost of that NN is significant.

The general point is valid though - for example, a computer is much more efficient at finding primes, or encrypting data, than humans.

The cost of training a human from birth is pretty high, especially if you consider their own efforts over the years. And they don't know a fraction of what the LLMs know. (But they have other capabilities!)

Humans aren't able to project an image from their neurons onto a disk like ANNs can, if they could it would also be very fast. That 4 hour estimate includes all the mechanical problems of manipulating paint.

It is using about 20W and then a person takes a single airplane ride between the coasts. And watches a movie on the way.

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