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AI;DR (AI; Didn't Read)

https://www.rickmanelius.com/p/aidr-ai-didnt-read
53•mooreds•20m ago•11 comments

A Preview of DuckDB v2.0

https://duckdb.org/2026/08/17/duckdb-20-highlights
417•ibotty•6h ago•65 comments

GPU Offload in Rust: Portable, Safe, and Fast

https://arxiv.org/abs/2608.13759
45•linggen•2h ago•8 comments

AI-Generated GitHub Copilot “Autofix” Allowed Compromise of Snowflake's Jira

https://www.wiz.io/blog/red-agent-snowflake-copilot-cicd-bug
243•galnagli•5h ago•108 comments

Incident with Github.com

https://www.githubstatus.com/incidents/zkxwbgr0cnmx
377•SpyCoder77•6h ago•784 comments

How to disable or avoid intrusive AI

https://www.librarian.net/notoai/
188•ColinWright•5h ago•93 comments

Sun Clock

https://sunclock.net/
78•Gecko4072•3h ago•31 comments

GPT 5.6 Sol is the best "vision" model OpenAI ever released

https://blog.roboflow.com/openai-gpt-5-6/
252•plurby•7h ago•132 comments

Launch HN: Speko (YC S26) – OpenRouter for Voice AI

https://speko.ai/
73•abdik•4h ago•45 comments

Judge sets framework for Nine PBS to retrieve archival data

https://current.org/2026/08/judge-sets-framework-for-nine-pbs-to-retrieve-archival-data/
65•qingcharles•3h ago•22 comments

Roboflow Playground: Try and Compare 30 Computer Vision Models

https://blog.roboflow.com/roboflow-playground/
12•Bluestein•1h ago•1 comments

Olo (Color)

https://en.wikipedia.org/wiki/Olo_(color)
189•inigyou•5d ago•46 comments

AirTag reveals Amazon is trashing rare books to train AI

https://arstechnica.com/tech-policy/2026/08/hidden-airtag-reveals-amazon-is-trashing-rare-books-t...
63•jefurii•1h ago•28 comments

How I Over-Engineered My Book

https://ben.balter.com/2026/08/17/how-i-over-engineered-my-book/
30•benbalter•1h ago•23 comments

The Oldest Bar in Every US State

https://www.businessinsider.com/oldest-bar-every-state
28•NaOH•4d ago•4 comments

Qwen3.8 27B scores 52 on Artificial Analysis

https://artificialanalysis.ai/models/qwen3-8-27b
183•anana_•2h ago•90 comments

Ask HN: Alternatives to GitHub

388•dhruv3006•6h ago•252 comments

The Lonely Men Who Work in Patagonia, at the End of the World

https://www.newyorker.com/culture/photo-booth/the-lonely-men-at-the-end-of-the-world
56•bookofjoe•1h ago•21 comments

Marketers are Addicted to Bad Data (2020)

https://www.jacquescorbytuech.com/writing/marketers-addicted-bad-data
11•zbentley•4d ago•13 comments

How to put 170 atoms in an atom

https://signoregalilei.com/2026/08/02/how-to-put-170-atoms-in-an-atom/
78•surprisetalk•5h ago•15 comments

India built the biggest digital payments miracle: Now comes the bill

https://www.bbc.com/news/articles/c8xnwqe00v1o
3•monkey_monkey•42m ago•0 comments

Anthropic's ‘watermark’ text adulteration in Claude is a perversion of writing

https://daringfireball.net/2026/08/anthropics_watermark_text_adulteration_in_claude_is_a_perversi...
731•ropbear•22h ago•640 comments

Amazon, which started off selling books, is destroying rare texts to train AI

https://techcrunch.com/2026/08/17/amazon-once-an-online-bookseller-is-destroying-rare-books-to-tr...
62•rzk•1h ago•31 comments

How I developed an Am29000 C compiler and web browser

https://nanochess.org/am29000_c_compiler_web_browser.html
61•nanochess•23h ago•9 comments

We Are Forking dotenvy into dotenv-ng

https://secretspec.dev/blog/we-are-forking-dotenvy-into-dotenv-ng/
15•linggen•2h ago•16 comments

A particle made of force: physicists say they've found mysterious 'glueball'

https://www.nature.com/articles/d41586-026-02498-1
46•Brajeshwar•5d ago•2 comments

Show HN: Sokoban AI Solver

https://mkornreich.me/projects/sokoban/
58•enjoyyourlife•7h ago•33 comments

On AI regulation and messaging

https://twitter.com/DarioAmodei/status/2088758816376807762
218•jacquesm•18h ago•456 comments

Show HN: Learn Flags Quiz

https://flagquizzes.com/
33•artiomyak•5h ago•18 comments

Show HN: Saggar, a Mac terminal that keeps sessions and your attention organized

https://saggar.marginalutility.dev/
35•mcclowes•5h ago•33 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/