Every algorithm is now called AI, unfortunately. 'AI' is being used 'exponentially'.

Under current usage of the term, I think the bimetallic switch in my office thermostat qualifies as an AI.

Random forests are absolutely AI as the term has been used for a very long time in academia and in public.

I fear this kind of retconning will become more commonplace as new entrants to the space who are unfamiliar with the history of the field put words in the mouths of academics that academics themselves would vociferously reject.

Academics have long pushed back against the labeling of everything as "AI", and only the most public-facing ones with more than a buck to make on the hype treadmill ever stoop so low.

In academia, "AI" is usually reserved as a synonym of "AGI" in large part because of the fuzziness and lack of consensus around a good definition of "intelligence". The term is simply not applied to actual outputs of research because there's no way to justify calling anything "intelligence".

As the saying goes, what's the difference between ML and AI? ML is what the PhDs call it, AI is what the MBAs call it.

> In academia, "AI" is usually reserved as a synonym of "AGI"

Now this is retconning. I did my uni course called AI almost twenty years ago. The same processes had been called that for a long time.

Agree completely, particularly with the smirk I can see in the final word! As an academic, "AI" means "fund me". It's the new "big data". And "exponential" is the new "rising" (or, sometimes, "falling").

The AI term has been coopted by Hollywood notions of synthetic human-level intelligence but it really is just referring to the academic discipline which Random Forests definitely falls under and has for decades.

Yes I agree, but OP's link is not aimed at academics, it's aimed at the general public. And you can't expect the general public to know that distinction: they see 'AI', they think 'ChatGPT', not Random Forests

AI has been discussed in public for years and was attached to huge numbers of things well before chatgpt. Chatgpt only came out less than a year ago.

We've also been using the term Machine Learning for a long time to try to avoid this. Using "AI" where "ML" would suffice is just trying to cash in on recent hype for clicks.

Still an interesting result of course.

My understanding is "ML" came into existence after the term "AI" became an untouchable and disrespectful dirty word in academia after a previous hype cycle went bust. Statisticians wouldn't be caught dead working on "AI". See also xkcd purity scale (435).

It looks like machine learning took over in the 2010s after a long convergence starting in the 2000s.

https://books.google.com/ngrams/graph?content=artificial+int...

This is from published books, so probably less affected by popular narratives. For that, we have Google Trends!

It looks like they trade places repeatedly when constrained to news searches: https://trends.google.com/trends/explore?cat=5&date=all_2008...

Right. ML is less likely to arouse emotions in either direction.

It's also a refinement on the term. AI can include a lot while ML is much more specific.

Not really though it may seem that way. Not all AI is ML. There are a ton of things within AI such as planning algorithms or Expert Systems. Again those are under the academic discipline of AI but not in the subfield of ML.

* * *

A random forrest classifier is a classic example of AI, quite popular before hardware caught up with the computational needs of neural networks.

Random forests of significant size also suffer some of the same inexplicability problems that neural networks suffer from, so it makes even more sense to make the comparison.

At a job where the company specialized in mathematical optimizations (think operations research, logistic planning, timetable optimization, etc.) we jokingly called the solvers with heuristics "A.I. technology, short for Advanced If technology". Some customers got the joke, some didn't, but they were generally content with the results :)

Now the question is, could this be done for stuff like marine immune genomes?