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Kessler Syndrome Has Started [video]

https://www.tiktok.com/@cjtrowbridge/video/7602634355160206623
1•pbradv•57s ago•0 comments

Complex Heterodynes Explained

https://tomverbeure.github.io/2026/02/07/Complex-Heterodyne.html
1•hasheddan•1m ago•0 comments

EVs Are a Failed Experiment

https://spectator.org/evs-are-a-failed-experiment/
1•ArtemZ•12m ago•2 comments

MemAlign: Building Better LLM Judges from Human Feedback with Scalable Memory

https://www.databricks.com/blog/memalign-building-better-llm-judges-human-feedback-scalable-memory
1•superchink•13m ago•0 comments

CCC (Claude's C Compiler) on Compiler Explorer

https://godbolt.org/z/asjc13sa6
1•LiamPowell•15m ago•0 comments

Homeland Security Spying on Reddit Users

https://www.kenklippenstein.com/p/homeland-security-spies-on-reddit
2•duxup•18m ago•0 comments

Actors with Tokio (2021)

https://ryhl.io/blog/actors-with-tokio/
1•vinhnx•19m ago•0 comments

Can graph neural networks for biology realistically run on edge devices?

https://doi.org/10.21203/rs.3.rs-8645211/v1
1•swapinvidya•31m ago•1 comments

Deeper into the shareing of one air conditioner for 2 rooms

1•ozzysnaps•33m ago•0 comments

Weatherman introduces fruit-based authentication system to combat deep fakes

https://www.youtube.com/watch?v=5HVbZwJ9gPE
2•savrajsingh•34m ago•0 comments

Why Embedded Models Must Hallucinate: A Boundary Theory (RCC)

http://www.effacermonexistence.com/rcc-hn-1-1
1•formerOpenAI•36m ago•2 comments

A Curated List of ML System Design Case Studies

https://github.com/Engineer1999/A-Curated-List-of-ML-System-Design-Case-Studies
3•tejonutella•40m ago•0 comments

Pony Alpha: New free 200K context model for coding, reasoning and roleplay

https://ponyalpha.pro
1•qzcanoe•44m ago•1 comments

Show HN: Tunbot – Discord bot for temporary Cloudflare tunnels behind CGNAT

https://github.com/Goofygiraffe06/tunbot
1•g1raffe•47m ago•0 comments

Open Problems in Mechanistic Interpretability

https://arxiv.org/abs/2501.16496
2•vinhnx•52m ago•0 comments

Bye Bye Humanity: The Potential AMOC Collapse

https://thatjoescott.com/2026/02/03/bye-bye-humanity-the-potential-amoc-collapse/
2•rolph•57m ago•0 comments

Dexter: Claude-Code-Style Agent for Financial Statements and Valuation

https://github.com/virattt/dexter
1•Lwrless•58m ago•0 comments

Digital Iris [video]

https://www.youtube.com/watch?v=Kg_2MAgS_pE
1•vermilingua•1h ago•0 comments

Essential CDN: The CDN that lets you do more than JavaScript

https://essentialcdn.fluidity.workers.dev/
1•telui•1h ago•1 comments

They Hijacked Our Tech [video]

https://www.youtube.com/watch?v=-nJM5HvnT5k
1•cedel2k1•1h ago•0 comments

Vouch

https://twitter.com/mitchellh/status/2020252149117313349
36•chwtutha•1h ago•6 comments

HRL Labs in Malibu laying off 1/3 of their workforce

https://www.dailynews.com/2026/02/06/hrl-labs-cuts-376-jobs-in-malibu-after-losing-government-work/
4•osnium123•1h ago•1 comments

Show HN: High-performance bidirectional list for React, React Native, and Vue

https://suhaotian.github.io/broad-infinite-list/
2•jeremy_su•1h ago•0 comments

Show HN: I built a Mac screen recorder Recap.Studio

https://recap.studio/
1•fx31xo•1h ago•1 comments

Ask HN: Codex 5.3 broke toolcalls? Opus 4.6 ignores instructions?

1•kachapopopow•1h ago•0 comments

Vectors and HNSW for Dummies

https://anvitra.ai/blog/vectors-and-hnsw/
1•melvinodsa•1h ago•0 comments

Sanskrit AI beats CleanRL SOTA by 125%

https://huggingface.co/ParamTatva/sanskrit-ppo-hopper-v5/blob/main/docs/blog.md
1•prabhatkr•1h ago•1 comments

'Washington Post' CEO resigns after going AWOL during job cuts

https://www.npr.org/2026/02/07/nx-s1-5705413/washington-post-ceo-resigns-will-lewis
4•thread_id•1h ago•1 comments

Claude Opus 4.6 Fast Mode: 2.5× faster, ~6× more expensive

https://twitter.com/claudeai/status/2020207322124132504
1•geeknews•1h ago•0 comments

TSMC to produce 3-nanometer chips in Japan

https://www3.nhk.or.jp/nhkworld/en/news/20260205_B4/
3•cwwc•1h ago•0 comments
Open in hackernews

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

1•quartztz•9mo 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•9mo 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•9mo 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 ??