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by _delirium 3844 days ago
Quibble with the timeline: AI as a field has included a big chunk devoted to machine learning research pretty much continuously, especially since the '80s or so. The specific methods in vogue do change: decision trees, neural networks, SVMs, boosting, association-rule learning, genetic algorithms, Bayesian networks, etc. go through periods of waxing and waning in popularity. A few years ago boosting/bagging and other ensemble methods were very hot and neural networks were out of fashion; now neural networks are hot and the boosting hype has quieted down a bit. But ML is pretty much always there in some form, since learning from data is an important component of AI.
1 comments
johann28 3844 days ago
ML was there but at least when I started learning about these things around 8 years ago, the label "AI" was mostly used for symbolic stuff. Courses named "AI" taught from the Russell-Norvig book. Things like resolution, planning in the block world, heuristic graph search, min-max trees, etc. ML existed but it wasn't really under the label of "AI" as far as I can remember. I think it's something of a marketing term that big companies like Google and Facebook reintroduced due to the scifi connotations. But that's just my guess.
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_delirium 3844 days ago
I can see that for intro courses, especially because of the book, though it varies a lot by school and instructor. On the research side it's been a big part of the field, though. The proceedings of a big conference like AAAI [1] are a decent proxy for what researchers consider "AI", and ML has been pretty well represented there for a while.

[1] http://www.aaai.org/Library/AAAI/aaai-library.php

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auvrw 3844 days ago
> I think it's something of a marketing term

you're not alone in thinking so

https://news.ycombinator.com/item?id=10483846

i get the impression that terminology bifurcated into "AI" and "cognitive science" around the time Marr published Vision in the 80's.

quibbles and q-bits aside, i was glad to see the announcement from the perspective of a if-not-free-then-at-least-probably-open-source-ish software appreciator.

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