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England set to be one of the first countries to eliminate hepatitis C

https://www.bbc.com/news/articles/c75gk620r22o
398•stevekemp•6h ago•286 comments

Apple Silicon and macOS VMs: 11–16× Faster LLM Inference with Llama.cpp

https://github.com/trycua/cua/blob/main/blog/gpu-passthrough-macos-vms.md
202•frabonacci•3h ago•32 comments

OpenSSH 10.5 released, AI assistance now welcome

https://www.openssh.org/releasenotes.html#10.5
20•voxadam•54m ago•8 comments

Stealing Reasoning Traces from Proprietary LLM APIs

https://stolen-thoughts.com/
276•quantumgarbage•5h ago•99 comments

Why Go Is an Ideal Language for AI-Assisted Software Engineering

https://developers.googleblog.com/why-go-is-an-ideal-language-for-ai-assisted-software-engineering/
97•0xedb•1h ago•89 comments

Show HN: iPhone app takes simultaneous images from 2 lenses, fuses into 1 photo

https://photosynthesis.camera
59•sajomes•2d ago•31 comments

Manus will return to operating as an independent company

https://manus.im/blog/a-note-to-our-users
87•thm•4h ago•39 comments

Jolt: Clojure compiler implemented with Chez Scheme

https://jolt-lang.github.io
70•mark_l_watson•3d ago•22 comments

Nvidia's Risky Business

https://stratechery.com/2026/nvidias-risky-business/
206•jonbaer•8h ago•83 comments

As AI eats the web, the internet’s collective memory is disappearing

https://thewalrus.ca/google-search-is-dying/
772•awnird•20h ago•788 comments

France to ban unsolicited telemarketing calls

https://www.lemonde.fr/en/france/article/2026/08/06/france-to-ban-unsolicited-telemarketing-calls...
935•aziaziazi•10h ago•448 comments

Show HN: Git-knife – edit commit messages, authors, and dates like a spreadsheet

https://github.com/TheRealYT/git-knife
75•YonathanTesfaye•3h ago•57 comments

Archive of Animal Photography Reveals 18,000 Species and Counting

https://www.smithsonianmag.com/science-nature/this-amazing-archive-of-animal-photography-reveals-...
15•pseudolus•2d ago•2 comments

Launch HN: Keet (YC S24) – An app to create video courses on anything

https://www.trykeet.com/
22•zackashen•3h ago•30 comments

H3-metal – Native MiniMax-H3 inference for Apple Silicon

https://github.com/antirez/h3.c
400•swyx•17h ago•93 comments

What I learned by putting GitHub Copilot behind a MitM proxy

https://www.lighthousenewsletter.com/p/i-put-github-copilot-behind-a-mitm
104•j0selit0•8h ago•12 comments

Federal vendor with $50M in contracts leaves portal broken for a month

https://www.propublica.org/article/foia-requests-responses
87•ams1•4h ago•18 comments

Mojo 1.0 Is Here

https://www.modular.com/blog/modular-26-5-mojo-1-0-is-here
27•dayanruben•1h ago•4 comments

Show HN: Needle2: 14MB agentic LLM for phones, wearables, smart home and robots

https://cactuscompute.com/needle
489•HenryNdubuaku•1d ago•162 comments

Halcyon Video – a 3D video store for your media server

https://github.com/halcyon-video/halcyon-video
54•Gander5739•4d ago•13 comments

Mark Zuckerberg attacks 'closed' AI rivals as Meta returns to open models

https://www.ft.com/content/4e3957f8-ea7c-4c46-a3de-cdce8e526878
610•root-parent•1d ago•569 comments

Chicken Scheme 6.0

https://code.call-cc.org/releases/6.0.0/NEWS
280•eatonphil•18h ago•44 comments

LFM2.5 2.6B model competitive with 4x larger models

https://huggingface.co/LiquidAI/LFM2.5-2.6B
147•nateb2022•6d ago•38 comments

Show HN: Scroll through all 43252003274489856000 Rubik's Cube states

https://everycube.alen.is/
273•Alen123•19h ago•108 comments

How Claude marks AI-generated content

https://support.claude.com/en/articles/16266773-how-claude-marks-ai-generated-content
381•mfiguiere•21h ago•352 comments

Stowaway – Take the window seat on any plane or satellite overhead

https://stowaway.live/
408•thunderbong•4d ago•50 comments

Nvidia Nemotron 3.5 Lightning

https://huggingface.co/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4
101•beklein•5h ago•23 comments

The “mechanical miracle” that ruined Mark Twain’s life

https://resobscura.substack.com/p/the-mechanical-miracle-that-ruined
213•benbreen•6d ago•107 comments

Faster floating point math with Rust's new API

https://pythonspeed.com/articles/faster-float-math-rust/
92•subset•5d ago•31 comments

Sonic Pi v5

https://www.patreon.com/samaaron/posts/sonic-pi-v5-166001392
420•samaaron•4d ago•103 comments
Open in hackernews

The Fastest Way yet to Color Graphs

https://www.quantamagazine.org/the-fastest-way-yet-to-color-graphs-20250512/
62•GavCo•1y ago

Comments

tonyarkles•1y ago
In case you haven't looked at the article, this is looking specifically at the Edge Coloring problem and not the more commonly known Vertex Coloring problem. Vertex Coloring is NP-complete unfortunately.
erikvanoosten•1y ago
You can convert edge coloring problems into vertex coloring problems and vice versa through a simple O(n) procedure.
meindnoch•1y ago
Wrong. You can convert edge-coloring problems into vertex-coloring problems of the so-called line graph: https://en.m.wikipedia.org/wiki/Line_graph

But the opposite is not true, because not every graph is a line graph of some other graph.

erikvanoosten•1y ago
Indeed. Thanks, I stand corrected.
tonyarkles•1y ago
Hrm... right. It's been a while. And it looks like both Vertex Coloring and Edge Coloring are both NP-complete (because of the O(n) procedure you're talking about and the ability to reduce both problems down to 3-SAT). I've started looking closer at the actual paper to try to figure out what's going on here. Thanks for the reminder, I miss getting to regularly work on this stuff.

Edit: thanks sibling reply for pointing out that it's not a bidirectional transform.

mauricioc•1y ago
For the edge-coloring problem, the optimal number of colors needed to properly color the edges of G is always either Delta(G) (the maximum degree of G) or Delta(G) + 1, but deciding which one is the true optimum is an NP-complete problem.

Nevertheless, you can always properly edge-color a graph with Delta(G) + 1 colors. Finding such a coloring could in principle be slow, though: the original proof that Delta(G) + 1 colors is always doable amounted to a O(e(G) * v(G)) algorithm, where e(G) and v(G) denote the number of edges and vertices of G, respectively. This is polynomial, but nowhere near linear. What the paper in question shows is how, given any graph G, to find an edge coloring using Delta(G) + 1 colors in O(e(G) * log(Delta(G))) time, which is linear time if the maximum degree is a constant.

Syzygies•1y ago
Yes. The article ran through this point as follows:

"In 1964, a mathematician named Vadim Vizing proved a shocking result: No matter how large a graph is, it’s easy to figure out how many colors you’ll need to color it. Simply look for the maximum number of lines (or edges) connected to a single point (or vertex), and add 1."

I keep wondering why I ever read Quanta Magazine. It takes a pretty generous reading of "need" to make this a correct statement.

JohnKemeny•1y ago
phkahler•1y ago
Is this going to lead to faster compile times? Faster register allocation...
john-h-k•1y ago
Very few compilers actually use vertex coloring for register allocation
isaacimagine•1y ago
Totally. The hard part isn't coloring (you can use simple heuristics to get a decent register assignment), rather, it's figuring out which registers to spill (don't spill registers in hot loops! and a million other things!).
NooneAtAll3•1y ago
and this post isn't even about vertex coloring
DannyBee•1y ago
No.

In SSA, the graphs are chordal, so were already easily colorable (relatively).

Outside of SSA, this is not true, but the coloring is still not the hard part, it's the easy part.

Not really. Coloring a graph is almost always talking about proper coloring, meaning that things that objects that are related receive different colors.

If you read the introduction, you'll also read that the goal is to "color each of your lines and require that for every point, no two lines connected to it have the same color."

Ps. "How many colors a graph needs" is a very well established term in computer science and graph theory.

mockerell•1y ago
I think the comment referred to the phrase „a graph needs X (colors or whatever)“. For me, this can be read two ways: 1. „a graph always needs at least X colors“ or 2. „a graph always needs at most X colors“.

Personally, I would interpret this as option 1 (and so did the comment above I assume). In that case, the statement is wrong. But I’d prefer to specify „at most/ at least“ anyways.

Or even better, use actual vocabulary. „For every graph there exists a coloring with X colors.“ or „any graph can be coloured using X colors“.

PS: I also agree with the sentiment about quanta magazine. It’s hard to get some actual information from their articles if you know the topic.

JohnKemeny•1y ago
What about this statement:

No matter how large a car is, it is easy to figure out how much money you'll need to buy it. Simply look at the price tag.

(From: No matter how large a graph is, it’s easy to figure out how many colors you’ll need to color it. Simply look for the maximum ...)

mauricioc•1y ago
Parent's point is that sometimes (but not always) the store is perfectly fine selling you a car for $1 less than what the "price tag" of Delta(G)+1 dollars asks for, so "need" is a bit inaccurate.