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Fujitsu launches made-in-Japan next-generation CPU FUJITSU-MONAKA

https://global.fujitsu/en-global/pr/news/2026/09/14-02
230•my123•1d ago•84 comments

Rate limits on GitLab.com are changing

https://about.gitlab.com/blog/rate-limit-change-2026/
18•darkwater•28m ago•4 comments

One Year of Sponsored Servo Development

https://servo.org/blog/2026/09/15/one-year-of-sponsorship/
268•AshleysBrain•7h ago•113 comments

LLM Classification Is Feature Engineering

https://minimallysufficient.com/posts/llm-classification-is-feature-extraction/
9•minsufficient•21m ago•1 comments

Nvidia announces native GPU programming in Rust

https://developer.nvidia.com/blog/introducing-cuda-rust-two-tracks-for-writing-gpu-kernels/
872•nonmaskable•1d ago•344 comments

CCC invites all model citizens to 40C3

https://events.ccc.de/en/2026/09/12/40c3-model-citizens/
190•antonly•7h ago•51 comments

Artificial intelligence now beats some of the best human forecasters

https://www.economist.com/science-and-technology/2026/09/16/artificial-intelligence-now-beats-som...
6•ddp26•48m ago•2 comments

OpenAI's Misalignment Framework: A Tactical Bid to Preempt Global AI Governance

https://asiaai.fyi/openai-misalignment-framework-global-governance/
8•ghernando•35m ago•7 comments

My temporary PHP fix from 2014 has nearly 20M installs. Today I'm deprecating it

https://jakeasmith.com/blog/http-build-url/
254•jakeasmith•1d ago•64 comments

Show HN: Share your AI Setup, Learn from others

https://mysetup.ai/
38•steveybrown•3h ago•19 comments

Keys Not Included: recovering the signing keys for US driver's license barcodes

https://ryan.science/blog/keys-not-included
244•Ryan5453•12h ago•107 comments

The Relation Between Mathematics and Physics by Paul Dirac (1939)

https://www.damtp.cam.ac.uk/events/strings02/dirac/speach.html
124•rramadass•3d ago•33 comments

GLM Built Its Own Inference Infrastructure

https://z.ai/blog/glm-built-its-inference-infrastructure
225•whiteros_e•7h ago•181 comments

Better Vector Search for Long Documents: Chunking Inside Manticore Search

https://manticoresearch.com/blog/auto-chunking/
61•GloriaVinogrado•5h ago•10 comments

Lucasart's Afterlife

https://togameforlife.wordpress.com/2023/12/09/on-lucasarts-afterlife/
79•Bondi_Blue•1d ago•36 comments

Xiaomi Mimo 2.6 live post-training dashboard

https://mimo.xiaomi.com/rl/
511•krackers•19h ago•146 comments

Show HN: I built a new version of my fun spatial 3D online meeting app

https://flat.social
71•pawelwentpawel•3h ago•42 comments

Online Z3 Guide

https://microsoft.github.io/z3guide/
49•Bluestein•2d ago•14 comments

Cloudflare/Security-Audit-Skill

https://github.com/cloudflare/security-audit-skill
157•donk8r•11h ago•32 comments

Show HN: An e-ink frame that hears birds and draws them as 1800s illustrations

https://github.com/arnegiacomo/fugleramme
2241•arnemunthekaas•2d ago•247 comments

Comparison of Malloc() Algorithms

https://egbert.net/blog/articles/comparison-of-arena-architecture-in-malloc.html
115•egberts1•1d ago•31 comments

Backups Aren't Simple

https://filipovski.net/2026/09/16/backups-arent-simple.html
311•afilipovski•19h ago•187 comments

Breaking the 1.58-bit Barrier for Ternary LLMs

https://arxiv.org/abs/2609.16338
230•matt_d•19h ago•36 comments

HarnessTax: How Much Does the Harness Matter for Coding Agents?

https://harnesstax.github.io/
197•matt_d•17h ago•74 comments

Developing provably correct Rust code with Verus

https://www.amazon.science/blog/developing-provably-correct-rust-code-with-verus
143•Betelbuddy•2d ago•39 comments

Mastering Layout Engines in Graphviz: Dot vs. Neato vs. Twopi vs. Circo

https://guides.visual-paradigm.com/mastering-graphviz-layout-engines-dot-neato-twopi-circo/
4•vismit2000•2d ago•1 comments

The engineering behind the US Strategic Petroleum Reserve

https://johnjwang.com/post/2026/09/15/engineering-behind-us-strategic-petroleum-reserve
254•johnjwang•1d ago•102 comments

Training a 4B model to produce 81% faster query plans than Postgres

https://rohanbansal.com/qorl
647•polyphilz•21h ago•130 comments

Performance Improvements in .NET 11

https://devblogs.microsoft.com/dotnet/performance-improvements-in-net-11/
330•soheilpro•2d ago•100 comments

OpenSpec – A lightweight and configurable AI spec framework

https://openspec.dev/
176•etoxin•16h ago•87 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.