OpenAI, Google and Anthropic are struggling to build more advanced AI

> The AGI bubble is bursting a little bit

I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

I thought maybe they were on the right track until I read Attention Is All You Need.

Nah, at best we found a way to make one part of a collection of systems that will, together, do something like thinking. Thinking isn’t part of what this current approach does.

What’s most surprising about modern LLMs is that it turns out there is so much information statistically encoded in the structure of our writing that we can use only that structural information to build a fancy Plinko machine and not only will the output mimic recognizable grammar rules, but it will also sometimes seem to make actual sense, too—and the system doesn’t need to think or actually “understand” anything for us to, basically, usefully query that information that was always there in our corpus of literature, not in the plain meaning of the words, but in the structure of the writing.

I see takes like this all the time and its so confusing. Why does knowing how things work under the hood make you think its not on the path towards AGI? What was lacking in the Attention paper that tells you AGI won't be built on LLMs? If its the supposed statistical nature of LLMs (itself a questionable claim), why does statistics seem so deflating to you?

Because it can't apply any reasoning that hasn't already been done and written into its training set. As soon as you ask it novel questions it falls apart. The big LLM vendors like OpenAI are playing whack-a-mole on these novel questions when they go viral on social media, all in a desperate bid to hide this fatal flaw.

The Emperor has no clothes.

>As soon as you ask it novel questions it falls apart.

What do you mean by novel? Almost all sentences it is prompted on are brand new and it mostly responds sensibly. Surely there's some generalization going on.

Novel as in requiring novel reasoning to sort out. One of the classic ways to expose the issue is to take a common puzzle and introduce irrelevant details and perhaps trivialize the solution. LLMs pattern match on the general form of the puzzle and then wander down the garden path to an incorrect solution that no human would fall for.

The sort of generalization these things can do seems to mostly be the trivial sort: substitution.

Why is your criteria for "on the path towards AGI" so absolutist? For it to be on the path towards AGI and not simply AGI it has to be deficient in some way. Why does the current failure modes tell you its on the wrong path? Yes, it has some interesting failure modes. The failure mode you mention is in fact very similar to human failure modes. We very much are prone to substituting the expected pattern when presented with a 99% match to a pattern previously seen. They also have a lot of inhuman failure modes as well. But so what, they aren't human. Their training regimes are very dissimilar to ours and so we should expect some alien failure modes owing to this. This doesn't strike me as good reason to think they're not on the path towards AGI.

Yes, LLMs aren't very good at reasoning and have weird failure modes. But why is this evidence that its on the wrong path, and not that it just needs more development that builds on prior successes?