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An OpenAI model has disproved a central conjecture in discrete geometry

https://openai.com/index/model-disproves-discrete-geometry-conjecture/
1173•tedsanders•15h ago•857 comments

GitHub confirms breach of 3,800 repos via malicious VSCode extension

https://www.bleepingcomputer.com/news/security/github-confirms-breach-of-3-800-repos-via-maliciou...
845•Timofeibu•20h ago•350 comments

Show HN: Rmux – A programmable terminal multiplexer with a Playwright-style SDK

https://github.com/helvesec/rmux
16•shideneyu•49m ago•9 comments

Haskell Foundation 2026 Update

https://discourse.haskell.org/t/haskell-foundation-2026-update/14136
120•azhenley•7h ago•32 comments

Show HN: I reverse engineered Apple's video wallpapers

https://github.com/kageroumado/phosphene
285•kageroumado•10h ago•65 comments

Vivaldi 8.0

https://vivaldi.com/blog/vivaldi-on-desktop-8-0/
132•OuterVale•2h ago•59 comments

New features in GCC 16: Improved error messages and SARIF output

https://developers.redhat.com/articles/2026/04/28/gcc-16-improved-error-messages-sarif-output
83•siteshwar•2d ago•12 comments

The Letter S, by Donald Knuth (1980) [pdf]

https://gwern.net/doc/design/typography/1980-knuth.pdf
171•bambax•10h ago•21 comments

DOS Zone

https://dos.zone/
260•rglover•11h ago•57 comments

Typewise (YC S22) Is Hiring an AI Growth Engineer (Zurich or Remote)

https://www.ycombinator.com/companies/typewise/jobs/HmCzfBK-ai-growth-engineer
1•janisberneker•2h ago

Flipper One Tech Specs

https://docs.flipper.net/one/general/tech-specs
376•gregsadetsky•15h ago•133 comments

Anthropic is expanding to Colossus2. Will use GB200

https://twitter.com/nottombrown/status/2057194829986300375
203•aurareturn•13h ago•189 comments

All the bugs they found

https://andreapivetta.com/posts/all-the-bugs-they-found.html
29•ziggy42•1d ago•4 comments

How fast is N tokens per second really?

https://mikeveerman.github.io/tokenspeed/
417•hexagr•3d ago•83 comments

Archaeologists find Egyptian mummy buried with the 'Iliad'

https://www.openculture.com/2026/05/archaeologists-discover-ancient-egyptian-mummy-buried-with-pa...
139•diodorus•5d ago•95 comments

Simulating Infinity in Conway's Game of Life with Modern C++

https://ryanjk5.github.io/posts/GOLDE/
35•HeliumHydride•2d ago•6 comments

What is a Demand Coop

https://cahootzcoops.com/blog/what-is-a-demand-coop
65•DeonRob•8h ago•64 comments

OpenAI Is Preparing to File for an IPO Soon

https://www.wsj.com/tech/ai/openai-is-preparing-to-file-for-an-ipo-very-soon-0ec95af5
92•louiereederson•17h ago•228 comments

Saying goodbye to asm.js

https://spidermonkey.dev/blog/2026/05/20/saying-goodbye-to-asmjs.html
378•eqrion•22h ago•147 comments

Your Most Improbable Life

https://kevinkelly.substack.com/p/your-most-improbable-life
107•jger15•2d ago•73 comments

Reviving old scanners with an in-browser Linux VM bridged to WebUSB over USB/IP

https://yes-we-scan.app/details
75•gmac•3d ago•27 comments

Show HN: I made a tactical map-based WWII submarine simulator (public beta)

https://silentshark.app/alpha/
46•epaga•2d ago•15 comments

Recreate famous water profiles using supermarket bottled water

https://www.waterdictionary.net
45•smugglerFlynn•2d ago•25 comments

The famous O3 "GeoGuessr" prompt did not work

https://www.seangoedecke.com/the-o3-geoguessr-prompt-did-not-work/
18•ingve•1h ago•8 comments

Google’s AI is being manipulated. The search giant is quietly fighting back

https://www.bbc.com/future/article/20260519-google-tackles-attempts-to-hack-its-ai-results
313•tigerlily•23h ago•193 comments

Intuit to lay off over 3k employees to refocus on AI

https://techcrunch.com/2026/05/20/intuit-to-lay-off-over-3000-employees-to-refocus-on-ai/
192•wapasta•9h ago•141 comments

Qian Xuesen: The missile genius America lost and China gained (2025)

https://www.usni.org/magazines/naval-history/2025/december/missile-genius-america-lost-and-china-...
176•thnaks•16h ago•93 comments

The Interview That Ships to Production: replacing whiteboards with pull requests

https://www.angellist.com/blog/the-interview-that-ships-to-production
28•asimov4•2d ago•8 comments

Numexpr: Fast numerical array expression evaluator for Python, NumPy, Pandas

https://github.com/pydata/numexpr
8•tosh•2d ago•0 comments

Why is Inkwell stuck in review

https://www.manton.org/2026/05/19/why-is-inkwell-stuck-in.html
142•speckx•16h ago•46 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
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.
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.