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Comment by nradov | Hacker News Reader

I read that pre-print Microsoft paper. Despite the title, it doesn't actually show any real "sparks" of AGI (in the sense of something that could eventually pass a rigorous Turing test). What the paper actually shows is that even intelligent people have a bias towards perceiving patterns in randomness; our brains seem to be wired that way and this is likely the source of most superstition.

https://arxiv.org/abs/2303.12712

While there is no scientific evidence that LLMs can reach AGI, they will still be practically useful for many other tasks. A human mind paired with an LLM is a powerful combination.

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>What the paper actually shows is that even intelligent people have a bias towards perceiving patterns in randomness

I'm not saying that you're wrong, but...

you'd have to provide a more rigorous rebuttal to be taken seriously.

AGI can exist without sapience and intelligence is a continuum. you can't just hand wave away GPT's capabilities which is why the sharpest minds on the planet are poking this new machine to work out wtf is going on.

human intelligence is a black box. we judge it by its outputs from given inputs. GPT is already producing human-like outputs.

a common rebuttal is: "but it doesn't *really* think/understand/feel", to which my response is: ...and? ¯\_(ツ)_/¯ what does that even mean?

I was just demonstrating its capabilities to a client. I asked GPT 4 to summarise a cloud product in the style of Encyclopaedia Dramatica, and it came up with a unique phrase not seen on the Internet when talking about auto-scale: “It’ll take your wallet on a roller coaster ride.”

What’s brilliant about this is that typically auto scaling metrics look like a stereotypical roller coaster track with the daily ups and downs!

That’s a genuinely funny, insightful, bespoke, and stylistically correct joke.

Tell me that that is not intelligence!

There's a certain amount of cosmic irony involved whenever someone calls LLMs 'stochastic parrots' or whatever.

How do you know this was unique and not picked up in its training set?

I searched Google for a few variations and turned up nothing.

Agreed.

Here’s the thing: the authors of that paper got early access to GPT-4 and ran a bunch of tests on it. The important bit is that MSR does not see into OpenAI’s sausage making.

Now imagine if you were a peasant from 1000 AD who was given a car or TV to examine. Could you really be confident you understood how it worked by just running experiments on it as a black box? If you give a non-programmer the linux kernel, will he/she think it’s magical?

Things look like magic especially when you can’t look under the hood. The story of the Mechanical Turk is one example of that.

>Could you really be confident you understood how it worked by just running experiments on it as a black box

the human brain is a black box, we can certainly learn a lot about it by prodding and poking it.

>Things look like magic especially when you can’t look under the hood.

imagine we had a 100% complete understanding of the mechanical/chemical/electrical functioning of the human brain. Would knowing the magic make it any less magical? in some sense, yes (the mystique would be gone, bye bye dualism), but in a practical sense, not really. It's still an astonishingly useful piece of grey matter.

I don't think static LLMs could reach AGI tbh. An LLM is like slicing out the language processing portion of our brain.

Well realistically it's like independently evolving the language processing part of our brain without forming the rest of the brain, there seems to be extra logic/functions that emerge within LLMs to handle these restrictions.

I think we'll see AGI when we finally try to build one up from various specialised subcomponents of a "brain". Of course GPT can't "think", it only knows how to complete a stream of text and has figured out internal hacks during training to pass the tests they set for it.

The real difference will be when we train a model to have continuous, connected abstract thoughts - an LLM can be used to communicate these thoughts or put them into words but it should not be used to generate them in the first place...

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