frontpage.
newsnewestaskshowjobs

Open Source @Github

fp.

GLM-5.3: Frontier coding with emergent cyber capabilities

https://z.ai/blog/glm-5.3
541•pella•5h ago•239 comments

DeepSeek peak/off-peak pricing update

https://api-docs.deepseek.com/news/news260813/
25•fagnerbrack•1h ago•7 comments

For the love of god stop using CPU limits in Kubernetes

https://github.com/inevolin/k8s-cpu-limits-analyzed
18•iljanevo•20m ago•4 comments

Gemini 3.7 Flash

https://blog.google/innovation-and-ai/models-and-research/gemini-models/introducing-gemini-3-7-fl...
867•thisisauserid•17h ago•441 comments

Major oil slick washes up on Iran coast after Hormuz ship strike

https://www.bbc.com/news/articles/cr7kpdkg13zo
18•binyu•51m ago•3 comments

Accelerating GPT-5.6 Sol Ultrafast

https://www.cerebras.ai/blog/accelerating-gpt-5-6-sol-ultrafast-with-openai
621•pr337h4m•16h ago•247 comments

Hello, me. It's been a while

https://themech.net/2026/08/hello-me-its-been-a-while/
238•somesoftdev•16h ago•127 comments

Show HN: C# Game Engine with its own scripting language and IDE

https://github.com/ArcadeMakerSources/ArcadeMaker
52•am-gm•2d ago•18 comments

Show HN: Lumabri – Run Moe Models on a P2P Swarm with Colibri

https://github.com/JustVugg/lumabri
28•vforno•10h ago•8 comments

Differential Heuristics

https://www.redblobgames.com/blog/2026-08-08-differential-heuristics/
19•ibobev•4d ago•0 comments

Ruby 4.0 Universal RCE Deserialization Gadget Chain

https://www.elttam.com/blog/ruby-4-0-universal-rce-deserialization-gadget-chain
36•pentestercrab•4h ago•9 comments

DeepSeek Harness developer preview

https://deepseek.com/harness/en/
674•bjin•22h ago•276 comments

Spaghettifying DRAM

https://github.com/xoreaxeaxeax/skitter-creek-bath-salts
637•matt_d•20h ago•164 comments

Mistral OCR 4.1

https://docs.mistral.ai/models/ocr-4-1
363•spelk•17h ago•144 comments

Bluesky Protocol Services

https://atproto.com/blog/introducing-bluesky-protocol-services
167•danabramov•10h ago•37 comments

Understanding is the new bottleneck

https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck
348•sebg•16h ago•181 comments

We're not done with point clouds

https://claytonwramsey.com/blog/mvt/
10•claytonwramsey•3d ago•1 comments

Choose Boring Technology (2015)

https://mcfunley.com/choose-boring-technology
357•tosh•17h ago•193 comments

Donkey.bas is 45 Years Old – 131 line of Glory

https://donkeybas.com/
244•jkrauska•17h ago•110 comments

Nine PBS sues Iron Mountain over blocked access to archival data

https://current.org/2026/08/nine-pbs-sues-iron-mountain-over-blocked-access-to-archival-data/
320•vinayakborkar•21h ago•183 comments

What an improv stage can teach you about leading cross-cultural teams in Tokyo

https://www.tokyodev.com/articles/yes-and-what-an-improv-stage-can-teach-you-about-leading-cross-...
15•pwim•1w ago•3 comments

How Compaction Works in Pi

https://earendil.com/posts/compaction-in-pi/
173•tosh•17h ago•69 comments

Why does Opus 5 feel worse to work with?

https://mun-logadan.github.io/why-does-opus-5-feel-worse/
57•numeri•48m ago•54 comments

Single log line is 49KB+ (ext4) / 110KB+ (btrfs) of systemd-journald disk writes

https://github.com/systemd/systemd/issues/40262
223•ValdikSS•16h ago•153 comments

Credibility is the barrier to entry in silicon

https://www.siliconimist.com/p/credibility-is-the-barrier-to-entry
30•johncole•3d ago•9 comments

The Library of Ashurbanipal (2025)

https://www.historytoday.com/archive/feature/library-ashurbanipal
36•samizdis•3d ago•9 comments

Blog about things you don't understand yet

https://www.seangoedecke.com/blog-about-things-you-dont-understand-yet/
111•gfysfm•11h ago•34 comments

Where did the old web go? We followed 657,607 links to find out

https://0.mk/blog/link-rot
192•tdx•17h ago•182 comments

How Organizations Use AI: Evidence from ChatGPT [pdf]

https://cdn.openai.com/pdf/how-organizations-use-chatgpt.pdf
114•malshe•15h ago•74 comments

NP-overrated

https://gruhn.me/blog/2026-08-13/
219•theanonymousone•14h ago•155 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.