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Artificial Intelligence is the name of the research field that this stuff comes out of. It was coined in 1956: https://en.wikipedia.org/wiki/Dartmouth_workshop

Researchers have been using "AI" as a term to describe their work for nearly 70 years at this point.

I don't see why we should throw away six decades of nomenclature just because "LLMs aren't actually intelligent".

It's a perfectly cromulent term.




And we have had numerous cycles of things that were once referred to as AI being no longer referred to as such...


But that's an indicator of success, not failure. https://en.wikipedia.org/wiki/AI_effect

"AI is whatever hasn't been done yet." — Larry Tesler


I would say it's an indicator of us realizing in the computing community that the technique in question is, while perhaps a valuable form of computing, not actually intelligence.

For example, we no longer consider beating people at chess to be an benchmark of "intelligence" - it's just a program. Which seems to me to what the OP is arguing.


The comment read like a criticism to me, so I thought I'd share the link and quote in case not everyone knew that this was pretty common for most widely operationalized AI technologies.


Not actually intelligence. So an artificial simulacrum of intelligence, you say?


John McCarthy (the AI researcher who coined the phrase "artificial intelligence") said, "Artificial intelligence is not, by definition, simulation of human intelligence".

His definition of the "I" in AI was, "the computational part of the ability to achieve goals in the world".


The term "Artificial Intelligence" was explictly not used in these fields for long stretches of time because the term got overhyped. The winter is coming.

https://en.m.wikipedia.org/wiki/AI_winter


A new winter is never coming, the last few years have shown the potential of machine learning and its use is only going to increase


Machine learning has taken huge leaps but the expectations for it are getting blown out of proportion. The use is going to increase for sure but there are many weaknesses in the technology that tend to be overlooked.

E.g. autonomous driving already proved too hard a task for ML for the foreseeable future. Also "hallucination" is a problem with no clear solution in sight.


>autonomous driving already proved too hard a task for ML for the foreseeable future

Has it? Seems like Waymo is still making good progress. They became generally available in SF recently IIRC.


I've seen hints of this in the past month or so: people who were acting like true general AI happened a year ago now just talking about it as "word generators".

Gemini felt like the tipping point where the flaws became obvious, which they then started noticing in the others.


Considering the amount of carbon being pumped out to power all this, you may be right.


Do you have any further reading on the idea that the term was explicitly avoided in those fields as a result of the AI winter?

I thought the academics kept on using the term, while commercial interests backed away during winter and came rushing back as soon as it was fashionable again.


The Wikipedia article mentions it: "Many researchers in AI in the mid 2000s deliberately called their work by other names, such as informatics, machine learning, analytics, knowledge-based systems, business rules management, cognitive systems, intelligent systems, intelligent agents or computational intelligence, to indicate that their work emphasizes particular tools or is directed at a particular sub-problem."

Also when I studied these things in the 2000s the program was called "Informatics".


That makes sense, thanks! My university had a course on "intelligent agents" back in ~2002.


> cromulent

Thanks for the new word of the day!


One could argue that it is not actually a word https://www.merriam-webster.com/wordplay/what-does-cromulent...




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