←back to thread

Hofstadter on Lisp (1983)

(gist.github.com)
372 points Eric_WVGG | 7 comments | 16 Oct 24 13:44 UTC | HN request time: 0s | source | bottom
Show context
waffletower ◴[16 Oct 24 15:54 UTC] No.41860593[source]▶
I find this article to be quaint -- remember reading it decades ago and feeling more receptive to its perspective. Ironically, I prefer using Clojure (though some here challenge its status as a Lisp lol) to interface with Large Language Models rather than Python. Clojure in particular is much better suited, for some reasons that Hofstadter details, and if you can interact with an LLM over a wire, you are not beholden to Python. But what we use to interface to these massive digital minds we are building, including the Bayesian sampling mathematics we use to plumb them, may have their elegance, but they are orthogonal to the nearly ineffable chaos of these deeply interconnected neural networks -- and it is in this chaotic interconnectedness where artificial intelligence is actually engendered.
replies(2): >>41861555 #>>41861844 #
1. iLemming ◴[16 Oct 24 17:58 UTC] No.41861844[source]▶
> Clojure in particular is much better suited

Clojure in general is far better suited for manipulating data than anything else (in my personal experience). It is so lovely to send a request, get some data, and then interactively go through that data - sorting, grouping, dicing, slicing, partitioning, tranforming, etc.

The other way around is also true - for when you need to generate a massive amount of randomized data.

replies(2): >>41865001 #>>41867456 #
2. troupe ◴[16 Oct 24 23:40 UTC] No.41865001[source]▶
> when you need to generate a massive amount of randomized data.

Even faster than Clojure: Open VIM for a VS Code user and ask them to exit.

replies(1): >>41865109 #
3. iLemming ◴[16 Oct 24 23:56 UTC] No.41865109[source]▶
There's no such thing as a "VS Code user", VS Code is the one that uses you, not the other way around.

btw. this isn't some kind of an FP joke, there's no 'fun' in it, only sad truth.

4. lenkite ◴[17 Oct 24 08:12 UTC] No.41867456[source]▶
Clojure doesn't have a standard, well-maintained dataframe library - so it is not suitable for any medium to large data science.
replies(1): >>41870440 #
5. iLemming ◴[17 Oct 24 15:15 UTC] No.41870440[source]▶
I don't do "true" data science, so my voice of "expertise" in the matter is limited. This is the extent of what I've heard. In my opinion, neither of the clauses in your statement are true.

Clojure is very well suited for data science of all shapes and sizes. There's a great meetup lead by Daniel Slutsky where they regularly discuss this topic, and there's #data-science channel in Clojurians Slack where they regularly post interesting findings. As for the libraries, anything used in Java/Javascript can be directly used. Besides, there is TMD, https://github.com/techascent/tech.ml.dataset - it's a well-regarded lib and provides solid functionality for data manipulation.

replies(1): >>41871042 #
6. lenkite ◴[17 Oct 24 16:16 UTC] No.41871042{3}[source]▶
Interesting. This is new library that certainly wasn't present when I last checked Clojure's offerings - the first commit was in March 2023. It still appears a work in progress to me, but I look forward to checking it to see how it compares to pandas/dplyr.
replies(1): >>41871450 #
7. iLemming ◴[17 Oct 24 17:02 UTC] No.41871450{4}[source]▶
Like I said - with or without TMD, Clojure does not lack tooling for DF, anything JVM/JS can be used and even Python libs, if you're inclined to do so. You can always ask in Clojurians Slack for guidance, people are incredibly nice and always eager to help.