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Keeping video layers in place across aspect ratios

https://blog.breatic.ai/layers-across-aspect-ratios/
1•Ubiquition•58s ago•0 comments

Elon should hire Jensen to run Terafab

1•spottedmarley•1m ago•0 comments

What Are Metal Organic Frameworks (MOFs)?

https://www.ossila.com/pages/what-are-metal-organic-frameworks
1•peter_d_sherman•1m ago•0 comments

Searching for exotic scalars at fusion reactors (2025)

https://arxiv.org/abs/2502.12314
1•greesil•3m ago•0 comments

Pax Silica

https://en.wikipedia.org/wiki/Pax_Silica
1•jonbaer•4m ago•1 comments

Run Cloudflare Workers Anywhere

https://openorange.dev/
1•madars•4m ago•0 comments

Dusk OS Sales Pitch

https://duskos.org/why.html
1•vermilingua•6m ago•0 comments

Ask HN: What use are the non-major cryptocurrencies?

1•otohp•9m ago•0 comments

Neuron turns model into conspiracy theorist

https://x.com/StationhouseAI/status/2121393278407123388
1•stationhouse•12m ago•0 comments

MathHelm: A Place to discuss AI-generated papers

https://mathhelm.org/
2•iLuddite•13m ago•0 comments

Israel's VCs see opportunity for challengers in Nvidia's turmoil

https://techcrunch.com/2026/11/13/israels-vcs-see-opportunity-for-challengers-in-nvidias-turmoil/
3•sjdh76•13m ago•0 comments

An open letter to the Nvidia Board of Directors

https://standwithjensen.com/#letter
3•gmays•14m ago•1 comments

Agent Distraction

https://developers.googleblog.com/agent-distraction/
2•pykello•15m ago•0 comments

Faster Scientific Simulations with New FP64 Algorithms in Nvidia cuBLAS

https://developer.nvidia.com/blog/faster-scientific-simulations-with-new-fp64-algorithms-in-nvidi...
1•qainsights•18m ago•0 comments

Show HN: Back endskills – agent skills for safer auth, data and migration code

https://github.com/globalmpc/backendskills
1•bayarkhuu5155•31m ago•0 comments

Cancer society issues updated prostate cancer screening guidelines

https://abcnews.com/GMA/Wellness/cancer-society-issues-specific-prostate-cancer-screening-guideli...
4•gmays•31m ago•0 comments

Ask HN: OpenAI Astra post-launch slump?

1•iJohnDoe•35m ago•2 comments

Obscura is so obscure it is practically unique

https://chronicles.mad-scientist.club/tales/obscure-obscura-is-actually-unique/
2•CqtGLRGcukpy•38m ago•2 comments

Show HN: Browserr – An MCP-first browser for AI agents (one Rust binary)

https://browserr.dev
1•Omodaka9375•40m ago•0 comments

MathHelm: A Place to discuss AI-generated papers

https://terrytao.wordpress.com/2026/11/13/introducing-mathhelm-a-place-to-discuss-ai-generated-pa...
2•smilelamp•42m ago•0 comments

Show HN: Geocode the planet(630M addresses), indexed in 5h on a 9 GB RAM budget

https://github.com/open-geocode-rs/open-geocode
2•abhigyaan•45m ago•0 comments

Martin van den Brink: His contributions in ASML [video]

https://www.youtube.com/watch?v=HEr90oVa758
1•pillars•45m ago•0 comments

App Basics for Firefox OS (2013)

https://web.archive.org/web/20160316133358/https://mozilla.github.io/app-basics-videos/
1•gurjeet•49m ago•0 comments

Quahuru: An original dice strategy board game

https://quahuru.com
1•trecht•51m ago•1 comments

A Financial Timeline of Jensen's Ousting

https://nvidia.cool.computer/
2•warthog•55m ago•0 comments

Pax Silica

https://www.nationalreview.com/the-morning-jolt/greta-thunberg-s-next-big-thing
2•fortran77•1h ago•1 comments

Before His Ouster, Jensen Huang Belittled the Executive Replacing Him

https://www.wsj.com/tech/jensen-huang-colette-kress-nvidia-ceo-eb289097
7•alsetmusic•1h ago•3 comments

Microsoft 365 Crawls Back to Life After a 24-Hour Outage

https://www.wired.com/story/microsoft-365-crawls-back-to-life-after-a-24-hour-outage/
9•ksec•1h ago•3 comments

Nvidia Allegedly Engineered Scarcity by Funding AI Startups to Buy Its GPUs

https://www.techpowerup.com/354814/nvidia-allegedly-engineered-scarcity-by-funding-ai-startups-to...
56•speckx•1h ago•20 comments

Beating the Frontier on NetHack

https://antithesis.com/blog/2026/nethack/
2•nwjsmith•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 ??