I don't know. If you're writing Java you may not be working on the same types of problems.

This comment would seem to address the point of that joke

I had a similar-ish project a while ago. I enjoy doing the "Spelling Bee" game in The NY Times Games section. In the comments someone worried that there weren't enough arrangements to keep the game going very long. I used an open source dictionary to generate all possible puzzles restricted by some basic heuristics like never using the letter S, having the total number of possible words in some reasonable range, etc. I found about 23,000 possible puzzles. My next idea was to use google's n-gram statistics to add some sort of "commonly known" heuristic, but my energy for the project petered out.

In any event these languages are great for exploring data in projects like these.

The readme has links to various resources including tutorials: https://codeberg.org/ngn/k

Oh, sorry. I misunderstood the question.

Chet Baker - Let’s get lost Gerry Mulligan - Night Lights

Also check out Bossa Nova by João Gilberto for a similar vibe but a different style.

Any detail whatsoever would make this a more credible claim. I haven’t met many people, including those skeptical of the performance claims, who have called K _slow_. Maybe for particular domains but I’d doubt that includes the kind of quant work that gets done at Millennium.

I've heard plenty of complaints over the years, and only within quant, unsurprisingly since that is the only field you'll get paid to use K.

A brilliant programmer I met who came from DE Shaw said he reimplemented a K-based portfolio optimization pipeline because the performance hit a wall once the dataset got large enough. He was able to beat K with Java of all things.

Columnar and timeseries dbs have continued to evolve, K is the same tech it was in the 2000s. The only reason it gets used at a Millennium is that whatever trade is still printing money, not any tech advantage.

I appreciate it's probably not possible to share too many details but I wouldn't be surprised if the choice of Java wasn't simply preference. It may have been a problem with the pipeline rather than with K. I.e. a fix might have been available using K but it can be easier (and harder) to just use some out-of-the box solution. I agree that columnar and time series dbs may have caught up with K over the years, but most of the complaints I've heard about K aren't technical.

It’s not at all clear where you read pretentiousness. Is it the mere fact of its existence?

Ngn/k is GPL and thus more restrictive. https://codeberg.org/ngn/k/src/branch/master/LICENSE

Don’t. Feel inspired. Nothing worth learning comes easy.

Using a debugger is basically out of the question. The theory is that the conciseness and lack of fluff makes it easier to reason about once you’ve mustered the requisite focus.