Do you consider a basic algorithm to be artificial intelligence?
You are right though, you van go back further than LLMs and find misuses of the term "artificial intelligence." That doesn't contradict my main point though, that the word has been so redefined as to be pretty meaningless to the understanding of what intelligence is.
If we want to consider even basic algorithms to be intelligence, are we boiling down the entire concept of intelligence to mathematical equations?
If it's been the way the field has used it for decades, it's not really a misuse.
> that the word has been so redefined
It's not been redefined though, other than people now wanting to moan about PR and things not being "real" AI when we've had AGI as a term to use right there.
> If we want to consider even basic algorithms to be intelligence, are we boiling down the entire concept of intelligence to mathematical equations?
Massive side argument, but I think we obey physical laws and are not magical and so fundamentally I can't see another answer.
Not really - machine learning, whether SVMs or ANNs, was called just that until relatively recently when the popular press started to first call ANNs AI, then LLMs. At first there was pushback from ML researchers, but particularly with LLMs they are now embracing it since investors want to invest in "AI".
LLMs are really just fancy (deep) pattern recognizers/predictors, conceptually not so different than rule-based expert systems like CYC, which was never called AI. Of course LLMs learn their own rules, which is extremely useful.
Other than the pop press wanting to talk about futuristic AI, and investors wanting to invest in it, what also provides cover for LLMs as "AI", is that they are trained to predict/copy human training data, and so appear as smart/dumb as that is, even if they are really no smarter than Searle's Chinese room.
> machine learning, whether SVMs or ANNs, was called just that until relatively recently when the popular press started to first call ANNs AI,
That is absolutely not the case. These things have been in the field of AI for decades. Frighteningly it's nearing two decades since I started my degree in AI and it wasn't a new reference then.
I remember taking Andrew Ng's Coursera ML course (incl. neural nets and SVMs) when it came out in 2011, and nobody, including him, was calling it AI at that time. I think it was sometime after neural nets really took off after ImageNet 2012 that the press started to call everything AI.
The field of ai is far older than that, my degree was in artificial intelligence starting in 2005 so before the dnn boom with rbms (I was replicating them only in my masters, I think it was more 2008ish that became a bigger topic?)
Yes, although the use of the label AI comes and goes as people get their hope up that a particular type of solution (e.g. various GOFAI approaches) is the answer, until it proves not to be, when the technologies go back to being called by their descriptive name (general problem solver, expert system, etc).
There was certainly a time when ANNs were widely just considered as part of ML, then rebranded as "deep learning", before the "AI" label was slapped on anything ANN-related. I guess it makes sense that an AI degree, encompassing many prior/current approaches might use that as a catch-all term for the field as opposed to any specific technology.
