That's weird, a physicist that deals with the empirical world, how does the rest of your tribe feel about you? I promise you we can treat you better in engineering, but the initiation might be a little hard for you. It includes a lot of chanting "pi is 3", "what good is science if you don't apply it", and "that's a weird parameter, I'll just try setting it to one"
If you want to code like MATLAB but keep the leather elbow patched sports jacket and cozy office, maybe try getting plastered and code Visual Basic, it has the same feeling to it.
What if you don't have a favorite programming language? I'm a firm believer that each language offers a specific set a features that makes each one uniquely suck and I often find myself at the crossroads of continuing to use this garbage or to learn a new language only to find it sucks in a different way. (/s another way of saying each language has its niche... (but sucks outside of it))
It's like how some infinite are greater / less than others, sure you might say that each one uniquely sucks, but spend a month trying to build something with say, Salesforce's language, and you'll come to appreciate how there are still tiers to it... much, much lower tiers.
that's not really true anymore is it though? in my limited experience now that nearly all AI is statistical, it's mostly implemented in python, R, matlab, or the low level languages that implement their stats libraries like C and fortran
Sure, but as far as I'm aware, no other large group of LISP users exists. My contention isn't that most AI researchers use LISP now, but that most LISP programmers are (were?) AI researchers.
I've been trying to learn about early AI work, and I'm finding that to get any practical details you're almost guaranteed to have to wade through LISP code, although at least it's usually pretty well commented.