[somewhereoutth]

Nothing points to this I'm afraid. All we have with LLMs is a probabilistic word salad generator that is realistic enough to get people who should / should not know better very excited.

It is better than Google search because it puts the results into a realistic sounding piece of text. It is worse than Google search because it does not provide sources or context. Both will steal the information you feed in.

Exactly no progress has been made in understanding or creating real intelligence in any meaningful sense, and we should have no expectation of any progress anytime soon while everyone is so focused on purely syntactical learning environments. Nobody learns anything by feeding them a dictionary.

[cubefox]

The leading neuroscientific theory of the brain says that, at it's core, it predicts experiences. It's called predictive coding. LLM's don't predict real time sensory data, they predict just text, and not a real time stream. But the conceptual similarity is still remarkable, both are at their core predictors.

[dwaltrip]

> probabilistic word salad generator

> Exactly no progress has been made in understanding or creating real intelligence in any meaningful sense

Strong words…

The thing has understanding. It may be alien and imperfect, with strange failure modes and quirks. But it has significant understanding of the real world. At this point, there are countless compelling examples demonstrating this.

The only way the model could so effectively predict the next token of such an immense and diverse collection of texts is by acquiring some level of understanding of the circumstances that gave rise to those texts.

The more I use gpt-4, this clearer this is to me, despite its limitations.

Edit: Removed unnecessary snark.

[somewhereoutth]

But it is being given only those texts, not the circumstances. All that is can do is associate and surface patterns in the texts - very complex though those patterns may be. It should not be surprising that those patterns are recognizable, and even that they appear 'real', as they are derived from text about our world. However there cannot be any understanding beyond that, just as with the shadows on the wall of Plato's cave.

[dwaltrip]

Are you arguing the humans are not merely looking at the shadows on the cave wall but LLMs are? Or that the shadows that the LLMs sees are fundamentally different / worse than ours?

> All that is can do is associate and surface patterns in the texts - very complex though those patterns may be

One of the more interesting ideas I’ve heard is that text contains embedded world models that are far richer that we previously imagined. We missed this because it is something we take entirely for granted and couldn’t imagine it any other way, like a fish who doesn’t realize they are swimming in “water”. This seems like a very plausible explanation for the performance of gpt-4 and the like.

[somewhereoutth]

We humans see and digest much much more than just texts we have been given to read. Indeed, and texts are exactly the shadows on the cave wall that we create and share to describe and remember the world around us - but without direct experience of that world around us they can only be shadows.

Yes quite plausible that extraordinarily complex models are embedded in the text corpus, but these can only relate to the texts themselves, as that is all that exists as far as the LLM is concerned. Again, it should not be a great surprise that they correlate to our real world to some extent, but they cannot go beyond those input texts.

[ThrowawayTestr]

> It is worse than Google search because it does not provide sources or context.

Try Bing chat. It provides sources for it's responses.