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Jensen Huang resigns

https://apnews.com/article/nvidia-megaspeed-china-singapore-huang-5403f152a601cf82ce939f1d24fffa0f
2868•lldb•10h ago•2718 comments

Rust 1.100

https://blog.rust-lang.org/2026/11/12/Rust-1.100.0/
381•mbStavola•6h ago•160 comments

Gemini 4 Hydrogen and Orchestrator

https://antigravity.google/blog/gemini-4-hydrogen-in-google-antigravity/
281•jonbaer•5h ago•63 comments

Foundation Models framework

https://developer.apple.com/foundation-models-framework/
110•kermatt•3h ago•13 comments

Dwarf planet candidate appears which takes roughly 280 years to orbit our sun

https://www.smithsonianmag.com/smart-news/astronomers-found-a-mysterious-object-orbiting-far-beyo...
188•cybermango•5h ago•92 comments

Show HN: My $300 embroidery machine needed a subscription, so I built my own app

https://github.com/simpsoka/zigzag
307•simpsoka•7h ago•128 comments

Richard Posner has died

https://www.law.uchicago.edu/news/senior-lecturer-richard-posner-law-and-economics-pioneer-and-fo...
25•sebg•1h ago•3 comments

Service degradation on Microsoft 365

https://status.cloud.microsoft/
464•dkpk•6h ago•431 comments

22-Year-Old PostgreSQL Bug Turned into Remote Code Execution

https://mehmetince.net/part-3-6-how-i-ended-up-turning-a-22-year-old-postgresql-type-confusion-pr...
138•ozirus•6h ago•17 comments

AI is turning Apple's app review process into a nightmare for synth developers

https://synthanatomy.com/2026/11/ai-is-turning-apples-app-review-process-into-a-nightmare-for-dev...
71•anigbrowl•3h ago•68 comments

I'm making LLMs work on small and old devices

https://github.com/hyperionaidev/smolmaxxing/
275•mrashad74•9h ago•92 comments

Edge0-145B: Frontier AI Capabilities on Your Own Computer

https://edge0.ai/blog/introducing-edge0-145b-frontier-ai-capabilities-on-your-own-computer
18•sroussey•1h ago•4 comments

Abandoned Quake 4 expansion finished by modders and now playable

https://www.moddb.com/mods/openq4/downloads/openq4-0141-windows-x64
235•klaussilveira•10h ago•81 comments

Relax: JIT compiler for Rust to reduce build times

https://makepad.github.io/relax/
110•adamnemecek•1d ago•46 comments

Gemini 4 Hydrogen

https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-4-hydr...
451•dvaplima•6h ago•292 comments

Why writing correct software is hard and why math (alone) won’t help us (2016)

https://pron.github.io/posts/correctness-and-complexity
351•AriFordsham•14h ago•166 comments

Before Pixels: Speed-Minder

https://unsung.aresluna.org/before-pixels-speed-minder/
11•surprisetalk•1d ago•0 comments

Talking Zen 6 with Mike Clark at AMD In-Depth

https://chipsandcheese.com/p/talking-zen-6-with-mike-clark-at
183•dverlaeckt80•10h ago•2 comments

Chinese frontier AI models carry the fingerprint of export-controlled GPUs

https://unemploymentlabs.com/checkpoint-forensics
134•firloop•2h ago•38 comments

Fortune Telling and Speculative Design

https://maggieappleton.com/fortune-telling
4•saikatsg•2d ago•0 comments

Show HN: Kapso – Iterative learning from enterprise data

37•alirezamshi•7h ago•9 comments

Safety in Algae Home Experiments

https://chillphysicsenjoyer.substack.com/p/algae-safety-in-home-experiments
26•surprisetalk•2d ago•2 comments

Anthropic IPO

https://ipo.anthropic.com/us/
804•josephljohnston•13h ago•799 comments

Distributed Ray Tracer

https://ray.hatchet.run
35•juliusgeo•5h ago•12 comments

Show HN: AgentRun – open-source, Self-improving Managed Agents

https://github.com/Parcha-ai/agentrun/blob/main/README.md
74•miguelrios•6h ago•16 comments

Adapting CPython for Yk

https://tratt.net/laurie/blog/2026/adapting_cpython_for_yk.html
41•frostbyte7•12h ago•2 comments

Words of warning about radiocarbon dating medieval human bones

https://www.nature.com/articles/s40494-026-02958-x
53•gumby•1d ago•8 comments

ExcalidrawZ: Local Native Excalidraw on macOS/iOS

https://github.com/chocoford/ExcalidrawZ
106•Qision•9h ago•24 comments

Our software engineering interviews are changing a little

https://blog.janestreet.com/software-engineering-interviews-are-changing-a-little/
166•maitland•10h ago•162 comments

Show HN: Cerulion – ROS 2-compatible robotics runtime with multi-process replay

https://github.com/cerulion-inc/cerulion
7•lakshays•3h ago•2 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.