Yes, the point is LLMs are AI.

So, we’ve gone full circle. LLMs is a sub-category within the collection of ML techniques within the collection of AI techniques. Point is, AI is just a term here. A label, that indicates nothing about the abilities of LLMs to exert any form of intelligence or reasoning. In other words, the whole field of AI could (should?) have been named “computational statistics” or “mathematics applied to numerical datasets” (or whatever else you want, really…), and LLMs would absolutely belong to “CoStats”/“MAND” fields, for the same reason we say they relate to “AI” today, it’s just that nobody would be silly enough to call them “artificially intelligent”.

ML is AI too. But sales didn’t call it that because AI had the reputation of “just brute force with some heuristics”.

What sales are you even thinking about? What do even presume the market for ML algorithms to be? Nobody was shopping for support vector machines as a service, or spending tokens on linear regression, or using convolutional neural networks via API before the current LLM craze. What the field is experiencing right now is unheard of. Never before did the private sector jump gun on a niche technique and spent trillions to package, anthropomorphise and market it as if “AI has finally been figured out, and we happen not only to own it, but also to sell it to you”. This deceptive rhetoric would be a much tougher sell if some early computer scientists hadn’t happened to name their field “AI”.

Was there even a point you wanted to make? I’m not sure exactly where you are heading with all this.

I mean, “machine learning” was a marketing term invented exactly to avoid the A in AI.

No, it’s not. ML is a sub-category within the collection of AI techniques that describes those algorithms whose behaviour is the result of fitting a training data-set to a pre-defined model by minimising an agreed-upon error function. For the longest of times, we were just calling that “statistics”, and many ML techniques and algorithms predate computers by centuries. Your mean-squares curve fitting? …qualifies as ML. That is to say, ML is all AI, but not all AI is ML.

LLMs are no different than function fitting with mean-squares. They are not magical, they are not black-boxes: they are fully described and completely predictable.

I mean, have fun re-defining artificial intelligence to suit your narrative. Here’s what the scientific consensus stands at: https://en.wikipedia.org/wiki/Artificial_intelligence

It’s also no secret that the companies involved in the LLM craze (OpenAI, Anthropic, Microsoft, …) diligently muddy the waters as a marketing trick to sell their product for more than what it is, that’s precisely what I’m calling out here: we can collectively do better/know better than that.

Also, LLMs are not AI (in the sense that most people would deem meaningful): there’s no reasoning involved, just a convincing illusion of it, served by extensive knowledge compaction and next token prediction. That is not to say that LLMs are useless, or that the sort of all-powerful AI people fantasize about cannot exist (I really don’t know, no people do). That is to say that it’s not for now, and that before it happens, we will see another long AI winter before the emergence of something fundamentally more convincing than LLMs.

LLMs are not the tool for a recommender job