frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

Dark Hours

https://darkhours.io
1•jparise•43s ago•0 comments

Nirmal Purja, Renowned Mountaineer, Dies at 43 After Pakistan Avalanche

https://www.nytimes.com/2026/08/01/world/asia/nirmal-purja-dead-pakistan-avalanche.html
1•whack•5m ago•0 comments

Plants and their ants: When flora and fauna team up

https://knowablemagazine.org/content/article/living-world/2026/ants-and-plants-keep-symbiotic-par...
2•marojejian•8m ago•1 comments

the death of uppercase: a bet I made around 20 years ago (that i lost)

https://thepeoplesrepublicofcouch.org/the-bet/
1•gaws•9m ago•0 comments

AI will always find a difference

1•ghassenfaidi•9m ago•0 comments

China's tech advances are causing chaos from Silicon Valley to the White House

https://www.theguardian.com/technology/2026/aug/01/china-silicon-valley-white-house
1•Teever•10m ago•0 comments

Suffering

https://www.aaronbergman.net/p/on-suffering
1•barry-cotter•13m ago•0 comments

Jaron Lanier and DeGrasse Tyson on "There Is No AI"

https://www.youtube.com/watch?v=a_ZKYH8v_do
2•lifeisstillgood•22m ago•1 comments

The brief life and sudden death of Zyzz

https://www.theguardian.com/film/2026/aug/02/the-brief-life-and-sudden-death-of-zyzz-why-did-the-...
2•mellosouls•26m ago•1 comments

Walsh: Multi-agent research pipeline with risk manager that can veto trades

https://github.com/ats4321/walsh
1•atshu21•27m ago•0 comments

Dreamup+|+Dang.ai

https://dang.ai/tool/ai-art-generation-dreamup
1•thestbyguy•30m ago•0 comments

Ask HN: I still don't understand why AI agents need "skills"

2•skeptic_ai•32m ago•2 comments

Ablative Software

https://conikeec.substack.com/p/ablative-software
1•conikeec•33m ago•0 comments

Send and Pretend: Exploiting Transcript Consistency Issues in E2EE Group Chats

https://arxiv.org/abs/2607.27510
1•sbulaev•34m ago•0 comments

The Greenhouse and the Lens: Two Modes of Agentic AI Work

https://www.brethorsting.com/blog/2026/08/the-greenhouse-and-the-lens-two-modes-of-agentic-ai-work/
2•aaronbrethorst•35m ago•0 comments

Android SystemUI Crash-loop from a single Google Drive one link (STA whitepaper)

https://lostmon.blogspot.com/2026/07/resilience-gaps-in-android-ipc.html
1•Lostmon•39m ago•0 comments

Kobuk the Destroyer – Tales from the Wild, Unseen World of Test Engineering

https://wwnorton.com/books/9781324051299
2•ripe•39m ago•1 comments

Why Is Europe Burning?

https://www.newyorker.com/news/the-lede/why-is-europe-burning
2•littlexsparkee•40m ago•0 comments

European Search Perspective: Creating a new foundation for digital pluralism

https://www.eu-searchperspective.com/
1•TMWNN•41m ago•1 comments

Genomic findings and their implications for the evolutionary social sciences

https://www.sciencedirect.com/science/article/pii/S1090513824000722?via%3Dihub
2•geneticdrifts•48m ago•0 comments

A Uiua Type System

https://www.uiua.org/blog/a-uiua-type-system
2•xyzsparetimexyz•51m ago•1 comments

The Kurzgesagt Situation is Insane [video]

https://www.youtube.com/watch?v=OX1yHmeLPy8
3•julkali•52m ago•3 comments

RFC 10015: Deprecating Obsolete Key Exchange Methods in TLS 1.2 and DTLS 1.2

https://www.rfc-editor.org/rfc/rfc10015.html
6•Jimmc414•56m ago•0 comments

Ask HN: Anyone still do work on Intel Macs?

3•senor_digimon•57m ago•2 comments

Moore's Law for Everything (2021)

https://moores.samaltman.com/
3•eatitraw•57m ago•0 comments

Nomophobia

https://en.wikipedia.org/wiki/Nomophobia
2•andersonmvd•1h ago•1 comments

Surface – KDL Specification Format – Experimental

https://github.com/etoxin/surface
2•etoxin•1h ago•1 comments

New Rule: Commie by Your Name – Real Time with Bill Maher [video]

https://www.youtube.com/watch?v=dRIjYHVh5kI
3•Bender•1h ago•2 comments

A Taxonomy of R&D Orgs

https://analogue.press/p/a-taxonomy-of-r-and-d-orgs
2•arbesman•1h ago•0 comments

Show HN: I made 70K+ hand-drawn icons using AI

https://koboyo.com/icons
1•kamranahmedse•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 ??