frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

The Unstoppable Green Revolution: Adam Tooze [video]

https://www.youtube.com/watch?v=BEmYzxc97K4
1•verdverm•3m ago•0 comments

"8-pinski" – EIGHT() bytes intro for MSDOS [video]

https://www.youtube.com/watch?v=9A-XJjnU5Oo
1•vok•3m ago•0 comments

A Good DIY Solder Stencil Begins with a Cleanly-Sliced Soda Can

https://hackaday.com/2026/10/03/a-good-diy-solder-stencil-begins-with-a-cleanly-sliced-soda-can/
1•whiteblossom•3m ago•0 comments

Show HN: AgentiLoop Agent Mac GUI Agent Loop for macOS 14.6 or Later

https://agentiloop.ai/
1•macOS26•7m ago•0 comments

AI will not make mathematicians obsolete

https://inference-review.com/article/ai-will-not-make-mathematicians-obsolete
2•marojejian•10m ago•0 comments

Second Chances

https://www.nybooks.com/articles/2026/10/22/second-chances-office-politics-wilfrid-sheed/
3•samclemens•13m ago•0 comments

AI share of US market cap

https://theinference.org/indexes/ai-share?range=max
1•magus_stoopr•15m ago•0 comments

PL research is dead, the age of PL exploration is just beginning

https://kirancodes.me/posts/log-end-of-pl.html
2•azhenley•15m ago•0 comments

Declaring a Bird Extinct: The Median Wait Is 36 Years After the Last Sighting

https://birdshistory.com/how-long-to-declare-a-bird-extinct/
2•Heidi_70•18m ago•1 comments

The Mulleted, Meme-Loving Billionaire Behind Meta's Hit AI App

https://www.wsj.com/tech/ai/alexandr-wang-muse-meta-efae7659
2•nradov•23m ago•0 comments

Self-Documenting Atmospheric Breakbeat

https://johnoestmannmusic.com/0010-a-shrine-of-teaching/
2•soundworlds•29m ago•0 comments

Pen vs. keyboard vs. Newton vs. Graffiti vs. Treo vs. iPhone (2010)

https://www.gyford.com/phil/writing/2010/01/18/input/
3•colinprince•31m ago•0 comments

First Hour of My Deposition – Ann Altman vs. Sam Altman [video]

https://www.youtube.com/watch?v=akjrfwYPvy8
4•sensanaty•33m ago•0 comments

Postgres 19: What's New with Monitoring?

https://clickhouse.com/blog/postgres-19-monitoring-whats-new
1•saisrirampur•35m ago•0 comments

Show HN: PeerYeet – P2P file transfer or fail

https://peeryeet.com/
1•dicroce•35m ago•0 comments

Gutsy: Tiny model for typed decisions on CPU (Jev style)

https://github.com/kouhxp/gutsy
2•mrkn1•37m ago•1 comments

Show HN: I built an inverse kinematics robot arm you can play with

https://www.kanishksachdev.com
1•kanishksachdev•38m ago•0 comments

Sam Altman's sister amends lawsuit accusing OpenAI CEO of sexual abuse

https://www.reuters.com/legal/government/judge-now-dismisses-lawsuit-by-sam-altmans-sister-accusi...
6•sensanaty•39m ago•2 comments

Show HN: Docker Desktop Alternative for WSLC in Rust

https://github.com/ricardoborges/rcdesktop
2•r2ob•43m ago•0 comments

Independent Music Report 2026

https://dittomusic.com/en/independent-music-report-2026
1•rishikeshs•46m ago•0 comments

Can AI read pain in your cat's face?

https://tailstory-app.com/en/blog/can-ai-read-pain-in-a-cats-face
2•Mohsentr•48m ago•0 comments

Kushner's financial stake in Israeli defence firms conflict of interest concerns

https://www.middleeasteye.net/news/jared-kushner-has-sprawling-financial-stakes-israeli-defence-f...
13•Betelbuddy•53m ago•1 comments

Show HN: Cliproxy-rs, a Rust port of the CLIProxyAPI LLM subscription proxy

https://github.com/vayungodara/cliproxy-rs
1•vayungodara•58m ago•0 comments

Big Balls Now Exposed to Serious Criminal Charges in at Least Six States

https://medium.com/@carmitage/big-balls-now-exposed-to-serious-criminal-charges-in-at-least-six-s...
46•sans_souse•59m ago•0 comments

Spinifex: The open, AWS-compatible cloud you run yourself

https://github.com/mulgadc/spinifex
2•santiago-pl•1h ago•1 comments

Merging With An LLM: Can an LLM reconstruct my values from small data?

https://chillphysicsenjoyer.substack.com/p/merging-with-an-llm
2•crescit_eundo•1h ago•0 comments

Writing code by hand is over, forever

https://eliocapella.com/blog/writing-code-by-hand-is-over/
17•aray07•1h ago•22 comments

Scorched Planets: "Scorched Earth" but in space with planetary gravity effects

https://www.scorchedplanets.com
4•hexer303•1h ago•1 comments

When Does Automating AI Research Produce Explosive Growth? [pdf]

https://basilhalperin.com/papers/singularities.pdf
1•marojejian•1h ago•1 comments

Building the Human Layer of AI

https://publicai.io/
1•measurablefunc•1h ago•0 comments
Open in hackernews

Ask HN: Is there a general, multi-PL programming task dataset?

1•quartztz•1y ago
Hello!

Being a student interested in PL design, I have had this idea floating around for a while: the gist is finding out what programming languages LLMs might be the most proficient in, to study their design choices and syntactic features with the goal of designing the perfect language for LLMs. This is, of course, gimmicky, but I entertained the idea for a while as a fun afterschool project.

The challenge is: what would be the best way to evaluate programming performance _in specific languages_? There are two main hypotheses here:

1. There are intrinsic syntactic/structural features that the transformer architecture is uniquely able to parse/reproduce/understand best, leading to higher quality code generated. For example: Lisp dialects make parsing code structure and blocks very easy, so one could assume an LLM can "understand their code better" 2. There is so much Python/JS out there that the question isn't even worth asking, and the performance in those will beat whatever other language you throw at it. This is probably not as much of a point thanks to newer transformer architectures but the question is still up.

I suspect the answer can be made somewhat interesting by considering performance relative to language popularity, but the ground question is: is there a general dataset containing different programming challenges, of varying difficulty, in multiple languages, with standard solutions? I couldn't find anything when I looked around, but I might have missed something obvious. It wouldn't be impossible to build a simple website to crowdsource, but I'm thinking that if I missed something obvious I'd rather find out early than late. Also, if you have any input on the project itself, I'd love to hear your ideas!

Comments

Someone•1y ago
> For example: Lisp dialects make parsing code structure and blocks very easy, so one could assume an LLM can "understand their code better"

I would expect the reverse: lisp has no syntactic sugar, making it harder for a LLM to glue code fragments together in a way that produces valid lisp code. Even guaranteeing that parentheses are correctly nested already can be a challenge.

As to a set of programs: they aren’t exactly what you’re looking for, but I would consider https://projecteuler.net (does not contain solutions, but searching for project Euler solutions” finds some) or https://benchmarksgame-team.pages.debian.net/benchmarksgame.

sargstuff•1y ago
Very open ended questions. Geeks for Geeks loosely organized around computer science topics of study : https://www.geeksforgeeks.org/

nit-pick details:

Ignoring hardware differences, "performance" comparisons can be based on differences between algorithm(s) used vs. how algorithm is implimented. For a given language, "algorithm implimentation performance" can be defined as the trade-offs on how a a given algorithm is implimented in a language (compared to other programming languages, but also easy use/flexibility based on 'language generation level -> https://www.geeksforgeeks.org/generation-programming-languag... )

----------------------

1) General computation language specialty 'modules' not withstanding; "languages" are built/optimised around core algorithmic concepts / anticipated area/concentration of targeted professional environment. aka opencl (gpu), R (statistics), Lisp (engineering design), C (OS level), sql (data selection), jasper reports, cobol (business), etc. Languages tend to be 'popular' because of the ecosystem provided around/for a given language.

snarky side note -> can always write a more standard language that compiles to an esolang & provide appropriate emacs/vim/sed/spacemacs ide support.: https://esolangs.org/wiki/Main_Page

  LLM's are very useful at curating information and recognizing/summarizing "statisical" relevance. aka apl is great for engineering mind set, not so good for business use cases aka cobal.  LLM might recognize a language for a given user that combines commonly used 'apl' aspecs of user and commonly used 'cobal' aspecs of user and recommend a language(s) with suitable commonalities for given user. 


2) Search engine topic 'coding challenges' 'algorithmic coding challenges' brings up many types of answers/sites for honing one's coding skills (various languages, beginner to expert, etc). Coding 'algorithms' vs. coming up with algorithm(s) to code is sort of a side aspect. Also differences in 'competition' challenges vs. 'technical challenges' (aka 512 c64 vs. 1 raspberry pi) ; vs. "computer science coding challenges" vs. 'computational genomic challenges'

     ?? how easy / hard based on 'profession' aka artist vs. software designer 20 years experience programming in scheme; environment -- NASA vs. google vs. insurance company.

   ?? from scratch : https://synoptek.com/insights/it-blogs/10-challenges-every-software-product-developer-faces/

   ?? based on industry standards ?? ; just trying to keep skills honed ??