He meant ML as in Standard ML and other variants, ML here means modular language or something else, and isn’t related to machine learning at all.
Suffice it to say no one has really explored doing ML in an ML. :)
Suffice it to say no one has really explored doing ML in an ML. :)
> Suffice it to say no one has really explored doing ML in an ML. :)
Learned Standard ML in college. Never did anything with it in the corporate and don't know anyone who has either. Though I think it is something everyone should learn. One thing I agree with the author: "Standard ML was the first functional language I learned well, so I still remember being shocked by its expressiveness." If you come from C/C++/Java/etc world, just pattern matching by itself is mind-blowing.
To be fair, the precedeeing sentence doesn't read like the author is about to give an argument about why Haskell is good for "artificial intelligence, natural-language processing or machine-learning research".
It just reads like he merely expands his preference of Haskell for what he does, and just mention in passing how he thinks it suit him also in those other domains.