I was going to say the same. In my experience I can say without hesitation green field projects is how you advance your career, become visible and get promoted.
You say this because you are on HN, very senior and/or living in a bubble.
In the vast majority of programming jobs out there you are not paid to solve problems: you are told very clearly what to do, how to do it and what technology you have to use for the job.
People don't hire analysts they hire "Java programmers".
If you've ever lead a team, you know how much more valuable people are if they don't need to be told how to do things. Even more if they don't need to be told what to do! But having to explain in detail the "how".. can be really a big time sink and only worth it if you are training someone to level up.
The thing is that the poster I responded to also is those three things. And I am just pointing out that his job was never to keep up with the frameworks.
Or, you could have been suddenly cheated on and exposed, or divorced and recently entered the dating market, or thinking about opening up your relationship after decades of monogamy.
But the number of such people is low, it would not be easy to find candidates for the trial. Just because there are some doesn't mean there are enough to make it worthwhile for the drug company to do the testing to be able to market it to such groups.
Maybe this is just me and my experiences but when I encounter people in the wild that seem dull I often assume they just have fringe interests that are kinda problematic to share with regular people they haven't built rapport with yet.
Like they're probably into something weird or niche that doesn't translate well in casual conversation so they just keep it surface level until they figure out if you're their type of person.
Yeah I don't get it either. Lisp is perfectly fine for this task although probably makes less sense now that Julia is a thing.
Reminder that before Python was used for data science, people used things like BioPerl and PDL and that didn't stop people from working on pandas and the like.
Lispers might not like that it's not a Lisp, but I remember Luke Tierney also making a statement to the effect that the statisticians have spoken and they don't prefer the Lisp syntax.
So Julia is a happy middle ground - MATLAB-like syntax with metaprogramming facilities (i.e., macros, access to ASTs). Its canonical implementation is JIT, but the community is working on allowing creation of medium-sized binaries (there has been much effort to reduce this footprint).
Julia isn't a lisp, but I think it's the most lispy non-S-expression based language around these days. The language creators took the lessons from lisp very seriously, and it shares a lot of functionality and philosophy with lisps.
Well I think the original author was a fan of Lisp and implemented the first Julia parser in femtolisp, IIRC. (And femtolisp was a lightweight Lisp of his own.)
Yeah, I think every programmer experiences the "I should write a language" moment when the solution to the problem is abstracted to be the language itself.
He probably means Allegro CL which is in my experience the best one.
All the OS Lisp GCs are stuck in the 80s and honestly not very good. The one in LispWorks is pretty good though but I wouldn’t call it state of the art. It just works.