[nsrahmad]

by Leon Bottou (one of the original authors).

Yann Lecun posted on twitter yersterday https://twitter.com/ylecun/status/1628386056641847296?cxt=HH...

>Hotter take: ML would have advanced faster if another front-end language had been available and widely adopted instead of Python. One that is interactive yet fast & compilable, multithreaded (no GIL), isn't bloated, doesn't care about white spaces,... E.g. Julia or some Lisp.

[mturmon]

Yes, that’s the news item that probably promoted the submission.

Yann’s later chaser to the above take (https://twitter.com/ylecun/status/1628390522892025860) —

> Even hotter take: the fact that ML and Computer Vision researchers were largely using Matlab held back progress for years, mostly because implementing something like a ConvNet in 2005 Matlab would have been a total nightmare.

And there are arguments back and forth about that. It’s funny, though, because a lot of the leading 1990s-2000s ML work was default-Matlab and people mostly loved it. Kevin Murphy used to advise Mathworks on bayes net implementation, and a lot of researchers from that time really liked the “numerical shell” that the Matlab REPL offered.

But of course one can see Yann’s point that the lack of clean capability for abstractions (I think struct’s came in the later 90s, lambda’s in the mid 2000s?) and licensing costs did hold the field back.

[ramblerman]

I did the original machine learning coursera course from Andrew ng, the homeworks in matlab were a horrible experience, seared into my memory till this day.

fwiw, I'm not a researcher though.