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Muse – Meta’s personal AI agent

https://ai.meta.com/muse/
267•yks•5h ago•257 comments

Large language models develop novel social biases through adaptive exploration

https://openreview.net/challenge?redirect=%2Fforum%3Fid%3Dpc7fqaOcAH
78•paimapi•3h ago•43 comments

AlphaGenome Atlas: a high-resolution map of human DNA

https://blog.google/innovation-and-ai/models-and-research/google-deepmind/alphagenome-atlas/
483•utiiiD•10h ago•115 comments

How to build a printer

https://nishantjosh.dev/blogs/how-to-build-a-fking-printer/
116•cat-whisperer•3h ago•25 comments

Navier-Stokes – Tristan Buckmaster [pdf]

https://cims.nyu.edu/~tristanb/statement.pdf
1211•procedurecall•19h ago•531 comments

On the Navier–Stokes Millennium Prize Problem

https://openai.com/index/navier-stokes-solution/
1085•tedsanders•7h ago•944 comments

A Topological Picture Book, Rendered

https://e-infinity.space/picture-book/
40•mathgenius•2h ago•4 comments

DaVinci Resolve 21.1

https://www.blackmagicdesign.com/media/release/20260908-03
345•tosh•11h ago•154 comments

The Microeconomics of Artificial Intelligence (2025)

https://direct.mit.edu/books/oa-monograph/6067/The-Microeconomics-of-Artificial-Intelligence
21•neehao•2d ago•6 comments

Benchmarking Qwen3.8 27B quantizations: 4-bit holds up, 1-bit collapses

https://quesma.com/blog/qwen38-27b-quantizations-benchmarked/
207•stared•10h ago•104 comments

Kimi K3 (2.8T) at 1 token/s on a MacBook Pro, streamed from four SSDs

https://github.com/argonautlabsai/deltafin
202•Argonautlabs•4h ago•103 comments

I-have-ADHD: A skill to stop coding agents from burying the answer

https://github.com/ayghri/i-have-adhd
305•domhudson•10h ago•241 comments

Animation in Bevy: The Big Picture

https://glocq.com/en/blog/20260827/
41•ibobev•4h ago•2 comments

Mercury 2.5

https://www.inceptionlabs.ai/blog/introducing-mercury-2-5
118•Topfi•4h ago•15 comments

Implementation of GCC's Nested Functions (vs. C++ Lambdas)

https://uecker.codeberg.page/2026-09-05.html
54•uecker•3d ago•9 comments

Getting phpBB 1.4.4 working in Docker

https://www.thran.uk/writ/devlog/2026/09/phpbb-144-in-docker.html
16•HeckFeck•1d ago•4 comments

Show HN: LLM Attention Visualization

https://ishamf.dev/p/llm-attention-visualizer/
117•ifz•7h ago•19 comments

Replacing a Rust Enum with a 64-Bit Word Made My Interpreter 17% Faster

https://pointersgonewild.com/2026-08-25-replacing-a-rust-enum-with-a-64-bit-word/
78•metrofun•3d ago•37 comments

Tracing np.add, all the way down

https://blog.veitheller.de/numpy.html
34•luu•4d ago•2 comments

Ask HN: 3.5 inch diskette read errors, would a period correct drive do better?

6•rietta•1d ago•5 comments

The Helicopter with Radioactive Blades

https://hackaday.com/2026/09/07/the-helicopter-with-radioactive-blades/
146•zdw•1d ago•43 comments

Show HN: Copperhead – Cursor for circuit boards

https://copperhead.sh/
204•animeshchouhan•11h ago•78 comments

We built our house for LAN parties (2024)

https://lanparty.house/
406•fittingopposite•3d ago•307 comments

Reverse Engineering an ASIC

https://kjartanvandriel.github.io/asic/
25•burekqueen•1d ago•4 comments

Tao: Open math problems being non-renewably mined by AI

https://mathstodon.xyz/@tao/117237320796901560
107•_alternator_•3h ago•78 comments

The two Christian saints who are the Buddha

https://signoregalilei.com/2026/08/30/the-two-christian-saints-who-are-secretly-the-buddha/
215•surprisetalk•10h ago•149 comments

The 92-Year-Old Mathematician and the Teenage Apprentice

https://www.nytimes.com/2026/09/06/science/92-year-old-mathematician-apprentice.html
136•robinhouston•2d ago•11 comments

C*: Unifying Programming and Verification in C (2025)

https://arxiv.org/abs/2504.02246
69•rramadass•8h ago•41 comments

Connecting the machines

https://herdr.dev/blog/connecting-the-machines/
76•collinmanderson•8h ago•26 comments

AlphaGenome Atlas predictive map of every DNA letter change in the human genome

https://deepmind.google/blog/alphagenome-atlas-a-predictive-map-of-every-possible-dna-letter-chan...
78•fady0•10h ago•11 comments
Open in hackernews

Computational Complexity of Air Travel Planning [pdf] (2003)

http://www.demarcken.org/carl/papers/ITA-software-travel-complexity/ITA-software-travel-complexity.pdf
76•rochoa•1y ago

Comments

buildsjets•1y ago
This is well over 20 years old and is based on pre 9/11 flight data. I would suspect that a lot has changed since then. So proceed with no caution at all.
gwern•1y ago
Since these sorts of things usually only get more and more complex over time, I would guess that it's all still true, but much more so.
throw0101b•1y ago
(2003)
throw0101b•1y ago
The PDF was produced by ITA, which famously used Common Lisp:

* https://en.wikipedia.org/wiki/ITA_Software

From 2001, a message from the same author as the linked paper:

> (Here's an email Carl de Marcken of ITA Software sent to a friend, describing their experiences using Lisp in one of the software industry's most demanding applications.)

* https://www.paulgraham.com/carl.html

Qem•1y ago
Are there any public, open, comprehensive datasets on flights?
dieselerator•1y ago
> Are there any public, open, comprehensive datasets on flights?

Airlines and commercial aviation operators schedule their own flights. That is a dynamic schedulle. So, perhaps there is no "comprehensive data set".

However, FlightAware makes publicly available scheduled and completed flight data over many routes in the USA. You can search by route and get a list of flights.

Flight information includes filed departure time, route of flight, and speed. For completed flights actual time, altitude, and route is shown. For example, a search on the route Dallas/Fort Worth to Austin lists 45 flights.

I hope that helps.

foundart•1y ago
A very interesting dive into, as the title says, the computational complexity of air travel planning. Graph algorithms with lots of complexity added due to the wide variety of fare conditions that airlines have dreamt up over the years.

The article may be from 2003 but I would call it an evergreen. While I imagine some of the details have changed since then, I suspect that the complexity has only grown since then.

foundart•1y ago
It makes me wonder: Would an airline that drastically simplified its fares be more likely to appear in flight search results?

Simplifying the fares would make it less computationally expensive and, in theory, could take fewer steps to answer a flight planning query.

Imagine a flight search planner that, say, fanned out N airline-specific workers when handling a planning query and then displayed to the user whatever results it got back within some time limit. If FooAir had simple fares, the FooAir searcher would likely run faster than searchers for other airlines. Thus it would be more likely to return results for more queries, assuming the deadline is fairly tight because of usability metrics. (People don't tend to stick around waiting for slow results.)

sjburt•1y ago
At least a few years ago (~2014), the fare search was actually nearly instant, but all major airfare search sites added a delay because customers had the impression they were getting a better deal when they had to wait. It seems like the delay has been dialed back lately.
teleforce•1y ago
This is a very popular article that get submitted every now and then (nearly every year) [1].

I think this kind of problem would be a very nice for logic, optimization and constraint programming that probably can be solved with modern tools like Google OR-Tool or Monash University MiniZinc [1],[2],[3].

[1] Past:

https://hn.algolia.com/?query=Computational%20Complexity%20o...

[2] Logic, Optimization, and Constraint Programming: A Fruitful Collaboration - John Hooker - CMU (2023) [video]:

https://www.youtube.com/live/TknN8fCQvRk

[3] Google OR-Tools:

https://developers.google.com/optimization

[4] MiniZinc:

https://www.minizinc.org/