zlacker

>>mef+(OP)
The level of intellectual engagement with Chomsky's ideas in the comments here is shockingly low. Surely, we are capable of holding these two thoughts: one, that the facility of LLMs is fantastic and useful, and two, that the major breakthroughs of AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution.

That may change, particularly if the intelligence of LLMs proves to be analogous to our own in some deep way—a point that is still very much undecided. However, if the similarities are there, so is the potential for knowledge. We have a complete mechanical understanding of LLMs and can pry apart their structure, which we cannot yet do with the brain. And some of the smartest people in the world are engaged in making LLMs smaller and more efficient; it seems possible that the push for miniaturization will rediscover some tricks also discovered by the blind watchmaker. But these things are not a given.

>>atdt+SZ
> the major breakthroughs of AI this decade have not, at least so far, substantially deepened our understanding of our own intelligence and its constitution

People's illusions and willingness to debase their own authority and control to take shortcuts to optimise towards lowest effort / highest yield (not dissimilar to something you would get with... auto regressive models!) was an astonishing insight to me.

>>rf15+Rh1
Well said. It's wild when you think of how many "AI" products are out there that essentially entrust an LLM to make the decisions the user would otherwise make. Recruitment, trading, content creation, investment advice, medical diagnosis, legal review, dating matches, financial planning and even hiring decisions.

At some point you have to wonder: is an LLM making your hiring decision really better than rolling a dice? At least the dice doesn't give you the illusion of rationality, it doesn't generate a neat sounding paragraph "explaining" why candidate A is the obvious choice. The LLM produces content that looks like reasoning but has no actual causal connection to the decision - it's a mimicry of explanation without true substance of causation.

You can argue that humans do the same thing. But post-hoc reasoning is often a feedback loop for the eventual answer. That's not the case for LLMs.

>>Occams+Fq1
> it doesn't generate a neat sounding paragraph "explaining" why candidate A is the obvious choice.

Here I will argue that humans do the same thing. For any business of any size recruitment has been pretty awful in recent history. The end user, that is the manager the employee will be hired under is typically a later step after a lot of other filters, some automated some not.

At the end of the day the only way is to measure the results. Do LLMs produce better hiring results than some outside group?

Also, LLMs seem very good at medical pre-diagnosis. If you accurately portray your symptoms to them they come back with a decent list of possible candidates. In barbaric nations like the US where medical care can easily lead to bankruptcy people are going to use it as a filter to determine if they should go in for a visit.