That’s changed, of course, but it remained true for at least another 15 or 20 years after this article was written and then changed rather quickly, perhaps cemented with deep neural networks and GPUs.
Other than running the emacs ecosystem, what else is Lisp being used for commonly these days?
I know a lot of people classify "Clojure" and "Lisp" in different categories, but I'm not 100% sure why.
[1] Usual disclaimer: It's not hard to find my job history, I don't hide it, but I politely ask that you don't post it here.
It mostly boils down to Clojure not having CONS cells. I feel like this distinction is arbitrary because the interesting aspect of Lisps is not the fact that linked-lists are the core data-structure (linked-lists mostly suck on modern hardware), but rather that the code itself is a tree of lists that enables the code to be homoiconic.
> what else is Lisp being used for commonly these days?
Anything that runs on Clojure - Cisco has their cybersec platform and tooling running on it; Walmart their receipt system; Apple - their payments (or something, not sure); Nubank's entire business runs on it; CircleCI; Embraer - I know uses Clojure for pipelines, not sure about CL, in general Common Lisp I think still quite used for aircraft design and CAD modeling; Grammarly - use both Common Lisp and Clojure; Many startups use Clojure and Clojurescript.
Fennel - Clojure-like language that compiles to Lua can handle anything Lua-based - people build games, use it to configure their Hammerspoon, AwesomeWM, MPV, Wez terminal and things-alike, even Neovim - it's almost weird how we're circling back - decades of arguing Emacs vs. Vim, and now getting Vim to embrace Lisp.
It is being used for formal verification in the semiconductor industry by companies like AMD, Arm, Intel, and IBM: https://www.cs.utexas.edu/~moore/acl2/
Yann LeCun developed Lush, which is a Lisp for neural networks, during the early days of deep architectures. See https://yann.lecun.com/ex/downloads/index.html and https://lush.sourceforge.net. Things moved to Python after a brief period when Lua was also a serious contender. LeCun is not pleased with Python. I can't find his comments now, but he thinks Python is not an ideal solution. Hard to argue with that, as its mostly a thin wrapper over C/C++/FORTRAN that poses an obvious two-language problem.
In addition to REPL and macros, I think two other Lispy features are essential:
nil is not just the sad path poison value that makes everything explode: lisp is written so that optionals compose well.
Speaking of composing, Lisps tend to be amazing with regard to composability. This is another line that cuts between CL, Scheme and Clojure on one side, with Python and Javascript firmly on the other side in my experience.
Lisps are as dynamic a languages ever go, unapologetically.
QVM, a Quantum Virtual Machine https://github.com/quil-lang/qvm
Quilc, an "advanced optimizing compiler" for Quil https://github.com/quil-lang/quilc
Coalton, "a statically typed functional programming language built with Common Lisp." https://coalton-lang.github.io/20211010-introducing-coalton/
I would guess it's by far the most active Guile project.
https://www.grammarly.com/blog/engineering/running-lisp-in-p...
present companies (that we know about): https://github.com/azzamsa/awesome-lisp-companies/
I dunno, there's Nyxt, Google Flights, MediKanren, there's some German HPC guys doing stuff with SBCL, Kandria,... I believe there's also a HFT guy using Lisp who's here on HN. LispWorks and Franz are also still trucking, so they prolly have clientele.
There are fewer great big FLOSS Lisp projects than C or Rust, but that doesn't really tell the whole story. Unfortunately proprietary and internal projects are less visible.
Apparently it didn’t make the transition to 64-bit machines well? But I haven’t really looked.
It's a shame things took the course they did with preferred languages.
Bit by bit, more people got used to doing data analysis and AI research in Python. Some projects were even written for Python first (e.g. Tensorflow or Keras). Eventually, Python had so many high-quality packages that it became the de facto for modern AI.
Is it the _best_ language for AI, though? I doubt. However, it is good enough for most use cases.
Perhaps the macro facilities are also convenient but that is not the part that makes Lisp mathematical, it's the higher order programming.
And it needn't even be something fancy, just being able to have a data table of tests and have the test functions generated and executed from the table is the power demonstrated.
Beware though, that there are today more than one flavor of Clojurescript, nbb for instance still acts just like JS in this regard.
The last time I did ClojureScript in serious capacity was for a school project in 2021, specifically because I wanted to play with re-frame and the people who designed the project made the mistake of saying I could use "whatever language I want".
It makes sense, but I guess I didn't realize that ClojureScript generates some nice runtime wrappers to ensure correctness (or to at least minimize incorrectness).
I guess that means that if you need to do any kind of CPU-intensive stuff, ClojureScript will be a bit slower than TypeScript or JavaScript, right? In your example, you're adding an extra "if" statement to do the type check. Not that it's a good idea to use JS or TypeScript for anything CPU-heavy anyway...
In rare cases, sure, it can add some overhead, and might not be suitable I dunno for game engines, etc., but in most use-cases it's absolutely negligible and brings enormous advantages otherwise.
Besides, there are some types of applications that simply really difficult to build with more "traditional" approach, watch this talk, I promise, it's some jaw-dropping stuff:
SpreadSheesh! talk by Dennis Heihoff https://www.youtube.com/watch?v=nEt06LLQaBY