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Animats ◴[] No.41890003[source]
This is an important result.

The actual paper [1] says that functional MRI (which is measuring which parts of the brain are active by sensing blood flow) indicates that different brain hardware is used for non-language and language functions. This has been suspected for years, but now there's an experimental result.

What this tells us for AI is that we need something else besides LLMs. It's not clear what that something else is. But, as the paper mentions, the low-end mammals and the corvids lack language but have some substantial problem-solving capability. That's seen down at squirrel and crow size, where the brains are tiny. So if someone figures out to do this, it will probably take less hardware than an LLM.

This is the next big piece we need for AI. No idea how to do this, but it's the right question to work on.

[1] https://www.nature.com/articles/s41586-024-07522-w.epdf?shar...

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jebarker ◴[] No.41891228[source]
> What this tells us for AI is that we need something else besides LLMs

Not to over-hype LLMs, but I don't see why this results says this. AI doesn't need to do things the same way as evolved intelligence has.

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awongh ◴[] No.41891547[source]
One reason might that LLMs are successful because of the architecture, but also, just as importantly because they can be trained over a volume and diversity of human thought that’s encapsulated in language (that is on the internet). Where are we going to find the equivalent data set that will train this other kind of thinking?

Open AI O1 seems to be trained on mostly synthetic data, but it makes intuitive sense that LLMs work so well because we had the data lying around already.

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1. BurningFrog ◴[] No.41892004[source]
Videos are a rich set of non verbal data that could be used to train AIs.

Feed it all the video ever recorded, hook it up to web cams, telescopes, etc. This says a lot about how the universe works, without using a single word.