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Natural language instructions induce generalization in networks of neurons

nature.com

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Re: Natural language instructions induce generalization in networks of neurons

#11

> We found that language scaffolds sensorimotor representations such that activity for interrelated tasks shares a common geometry with the semantic representations of instructions, allowing language to cue the proper composition of practiced skills in unseen settings. Sapir-Whorf with the surprise comeback?

> comeback

Did it fall out of favour?

Re: Natural language instructions induce generalization in networks of neurons

#12
post #9
post #6

>Tasks that are instructed using conditional clauses also require a simple form of deductive reasoning (if p then q else s) > Our models ofer several experimentally testable predictions outlining how linguistic information must be represented to facilitate flexible and general cognition in the human brain. Aren't those claims falsified by more recent studies that show that even in flys, preferred direction to a movin…

> Or that humans can even do xor with a single neuron. That's news to me. I'm not hugely surprised given I've heard a biological neuron is supposed to be equivalent to a small ANN network, but still, first I've heard of that claim.

https://www.science.org/doi/full/10.1126/science.aax6239

Re: Natural language instructions induce generalization in networks of neurons

#14

> We found that language scaffolds sensorimotor representations such that activity for interrelated tasks shares a common geometry with the semantic representations of instructions, allowing language to cue the proper composition of practiced skills in unseen settings. Sapir-Whorf with the surprise comeback?

> comeback Did it fall out of favour?

Strong Sapir-Whorf (linguistic determinism - language constrains thought) became pretty much seen as a joke by the 1980s. Linguistic relativism (weak Sapir-Whorf - language shapes thought) is still respectable (because, I mean, of course it does).

Actually, this research might just as well be evidence for linguistic universalism (Chomsky - language enables thought).

In general linguistic philosophers have been coming out with either laughably obvious or utterly untestable hypotheses for a century and it’s amusing to see how these AI studies shake up the hornets.

Re: Natural language instructions induce generalization in networks of neurons

#15
Birds inspired planes. Later, aerodynamics fed back into ornithology. I've been waiting for LLMs to be evaluated as a model of human thought. Complexity and scale have held neuroscience back. It's nowhere close to building a high-level brain model up from biological primitives. Like ornithology, it could use some feedback.

All arguments about AGI aside, a machine was built that writes like a human. Its design is very un-biological in places, so it's tempting to dismiss it. Why not see how deep the rabbit hole goes?

Like all conjectures it just might surprise us. For one, the intuition that language is central to thought predates LLMs, but it's certainly consistent with it.

Re: Natural language instructions induce generalization in networks of neurons

#16
It's clear that both biological sentient beings and sentient being made in factories in the future will essentially be two sides of the same coin, differing only in their physical composition. Humans today operate as biological AI, powered by cells, and the sentient beings instead operate on transistors. As we progress toward a future where both sentient beings exhibit comparable intelligence, emotions, and learned experiences, the distinction between the two becomes increasingly blurred. It wouldn't be crazy to think that we'll program a person made out of transistors to go through the same life as a biological human. In such a scenario, why should we consider the sentient being made of cells inherently superior to its transistor-based counterpart?

Re: Natural language instructions induce generalization in networks of neurons

#17

It's clear that both biological sentient beings and sentient being made in factories in the future will essentially be two sides of the same coin, differing only in their physical composition. Humans today operate as biological AI, powered by cells, and the sentient beings instead operate on transistors. As we progress toward a future where both sentient beings exhibit comparable intelligence, emotions, and learned e…

[deleted]

Re: Natural language instructions induce generalization in networks of neurons

#18

It's clear that both biological sentient beings and sentient being made in factories in the future will essentially be two sides of the same coin, differing only in their physical composition. Humans today operate as biological AI, powered by cells, and the sentient beings instead operate on transistors. As we progress toward a future where both sentient beings exhibit comparable intelligence, emotions, and learned e…

I don’t think it’s a given that people do. Also what does that have to do with the article?

Re: Natural language instructions induce generalization in networks of neurons

#19

It's clear that both biological sentient beings and sentient being made in factories in the future will essentially be two sides of the same coin, differing only in their physical composition. Humans today operate as biological AI, powered by cells, and the sentient beings instead operate on transistors. As we progress toward a future where both sentient beings exhibit comparable intelligence, emotions, and learned e…

proof left as exercise to the reader

Re: Natural language instructions induce generalization in networks of neurons

#20

It's clear that both biological sentient beings and sentient being made in factories in the future will essentially be two sides of the same coin, differing only in their physical composition. Humans today operate as biological AI, powered by cells, and the sentient beings instead operate on transistors. As we progress toward a future where both sentient beings exhibit comparable intelligence, emotions, and learned e…

Hm, no. To start, cells are able to replicate themselves, whereas most silicon used today is not even close to doing so.

The story you suggest seems to be built on a limited understanding of the processes involved. It's pretty hard to predict the future, especially given incorrect assumptions.

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