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OpenCiv3: Open-source, cross-platform reimagining of Civilization III

https://openciv3.org/
601•klaussilveira•11h ago•178 comments

The Waymo World Model

https://waymo.com/blog/2026/02/the-waymo-world-model-a-new-frontier-for-autonomous-driving-simula...
908•xnx•17h ago•545 comments

What Is Ruliology?

https://writings.stephenwolfram.com/2026/01/what-is-ruliology/
23•helloplanets•4d ago•19 comments

How we made geo joins 400× faster with H3 indexes

https://floedb.ai/blog/how-we-made-geo-joins-400-faster-with-h3-indexes
97•matheusalmeida•1d ago•23 comments

Unseen Footage of Atari Battlezone Arcade Cabinet Production

https://arcadeblogger.com/2026/02/02/unseen-footage-of-atari-battlezone-cabinet-production/
28•videotopia•4d ago•0 comments

Show HN: Look Ma, No Linux: Shell, App Installer, Vi, Cc on ESP32-S3 / BreezyBox

https://github.com/valdanylchuk/breezydemo
204•isitcontent•12h ago•24 comments

Monty: A minimal, secure Python interpreter written in Rust for use by AI

https://github.com/pydantic/monty
204•dmpetrov•12h ago•96 comments

Show HN: I spent 4 years building a UI design tool with only the features I use

https://vecti.com
314•vecti•14h ago•137 comments

Sheldon Brown's Bicycle Technical Info

https://www.sheldonbrown.com/
359•ostacke•17h ago•93 comments

Microsoft open-sources LiteBox, a security-focused library OS

https://github.com/microsoft/litebox
353•aktau•18h ago•178 comments

Hackers (1995) Animated Experience

https://hackers-1995.vercel.app/
463•todsacerdoti•19h ago•231 comments

Delimited Continuations vs. Lwt for Threads

https://mirageos.org/blog/delimcc-vs-lwt
24•romes•4d ago•3 comments

Show HN: If you lose your memory, how to regain access to your computer?

https://eljojo.github.io/rememory/
261•eljojo•14h ago•156 comments

An Update on Heroku

https://www.heroku.com/blog/an-update-on-heroku/
395•lstoll•18h ago•268 comments

Dark Alley Mathematics

https://blog.szczepan.org/blog/three-points/
80•quibono•4d ago•20 comments

PC Floppy Copy Protection: Vault Prolok

https://martypc.blogspot.com/2024/09/pc-floppy-copy-protection-vault-prolok.html
54•kmm•4d ago•3 comments

Was Benoit Mandelbrot a hedgehog or a fox?

https://arxiv.org/abs/2602.01122
7•bikenaga•3d ago•2 comments

Jeffrey Snover: "Welcome to the Room"

https://www.jsnover.com/blog/2026/02/01/welcome-to-the-room/
3•kaonwarb•3d ago•1 comments

How to effectively write quality code with AI

https://heidenstedt.org/posts/2026/how-to-effectively-write-quality-code-with-ai/
235•i5heu•14h ago•178 comments

Vocal Guide – belt sing without killing yourself

https://jesperordrup.github.io/vocal-guide/
5•jesperordrup•2h ago•1 comments

Introducing the Developer Knowledge API and MCP Server

https://developers.googleblog.com/introducing-the-developer-knowledge-api-and-mcp-server/
47•gfortaine•9h ago•14 comments

Female Asian Elephant Calf Born at the Smithsonian National Zoo

https://www.si.edu/newsdesk/releases/female-asian-elephant-calf-born-smithsonians-national-zoo-an...
27•gmays•7h ago•8 comments

I spent 5 years in DevOps – Solutions engineering gave me what I was missing

https://infisical.com/blog/devops-to-solutions-engineering
137•vmatsiiako•16h ago•60 comments

Why I Joined OpenAI

https://www.brendangregg.com/blog/2026-02-07/why-i-joined-openai.html
124•SerCe•7h ago•105 comments

Show HN: R3forth, a ColorForth-inspired language with a tiny VM

https://github.com/phreda4/r3
68•phreda4•11h ago•13 comments

Understanding Neural Network, Visually

https://visualrambling.space/neural-network/
271•surprisetalk•3d ago•37 comments

I now assume that all ads on Apple news are scams

https://kirkville.com/i-now-assume-that-all-ads-on-apple-news-are-scams/
1048•cdrnsf•21h ago•431 comments

Learning from context is harder than we thought

https://hy.tencent.com/research/100025?langVersion=en
171•limoce•3d ago•92 comments

Zlob.h 100% POSIX and glibc compatible globbing lib that is faste and better

https://github.com/dmtrKovalenko/zlob
14•neogoose•4h ago•9 comments

FORTH? Really!?

https://rescrv.net/w/2026/02/06/associative
60•rescrv•19h ago•22 comments
Open in hackernews

New updates and more access to Google Earth AI

https://blog.google/technology/research/new-updates-and-more-access-to-google-earth-ai/
150•diogenico•3mo ago

Comments

diogenico•3mo ago
It shifts from map layers to answer “what/where/why now?” rather than just “show me X.”

And the Gemini-in-Google Earth bit could lower the barrier for non-GIS folks.

chrisshroba•3mo ago
> Bellwether, a moonshot at Alphabet's X, is using Earth AI to provide hurricane predictions insights for global insurance broker McGill and Partners. This enables McGill's clients to pay claims faster so homeowners can start rebuilding sooner.

Hm, I'm quite skeptical about this claim.

tencentshill•3mo ago
Could be a nice expensive contractor option for replacing the NOAA's public data that we lost. But it probably wont be picked up because it has to study the climate, which is a bad word now.
CobrastanJorji•3mo ago
You can totally create a private version of NOAA so long as you keep the messaging about insurance intelligence and never, ever speculate out loud about the causes of hurricanes. And if that's not enough, just do what Meta did and hire some shmuck like Robby Starbuck to signal that you're on the right team.
mrtesthah•3mo ago
I see the humor in this but you'd still need to operate your own satellites.
wlesieutre•3mo ago
What they want is for the government to run the satellites and provide the data on the taxpayers' dime, but only let private companies interpret that data so they can sell their forecasting

https://www.cnn.com/2017/10/14/politics/noaa-nominee-accuwea... (note: old news)

vineyardmike•3mo ago
Google (with partner companies) launched a climate-monitoring satellite last year. Thanks to SpaceX, it’s cheaper than ever for private organizations to launch satellites.
apples_oranges•3mo ago
Haha yeah. Perhaps a marketing gimmick with an asterisk..
moffkalast•3mo ago
> McGill and Partners

Hi, I'm Saul Goodman. Did you know that you have hurricanes? The constitution says you do! And so do AI.

Legend2440•3mo ago
Seems plausible to me. It would allow them to start contracting CAT adjusters as soon as a hurricane is expected, before other insurers start bidding for them.

Will this actually pay off for them? Who knows. But insurers are quite into ML for claims/underwriting these days, so I'd believe they're giving it a try.

KRAKRISMOTT•3mo ago
Wdym by 'bid for them'? Won't the MGA want to get rid of their contracts in an area that's about to be hit by a hurricane ASAP?
piperswe•3mo ago
They want to pay adjusters and contractors the least amount possible - that's what they're bidding on
Legend2440•3mo ago
You need a large workforce of adjusters to handle big events like a hurricane, but you don’t need them all the time. So catastrophe adjusters are often independent contractors.

Pay is good but hours are long, and you are often deployed far away from home.

olq•3mo ago
More like booking them for the availability and likely a fixed non-hurricane-panic price.
notatoad•3mo ago
quicker approvals probably also means quicker denials, if you want to look at the negative side of it.
giobox•3mo ago
A quicker denial is still better than a long drawn out one, even if it isn't the outcome you might want.
citizenpaul•3mo ago
Sorry but our AI said your home destroyed in the hurricane was not in fact destroyed by a hurricane. Claim denied. We accept no further inquiries on the matter.

100% of claims paid out instantly, so its kinda true.

I suspect you don't have an MBA /s

Jordan-117•3mo ago
I have some old screenshots of interesting locations from Google Earth circa 2006-2012 that I've never been able to track down. I wonder if something like this would be capable of geolocating them somehow -- like reverse image search for landscapes.
tom1337•3mo ago
Out of interest: have you already tried using GPT 5 (reasoning / thinking) for that? I've had quite some success in the past using them to track down such places.
Jordan-117•3mo ago
Yeah, that and Gemini 2.5. They actually were able to help identify a handful based on context clues, or at least narrow it down enough that I could find it myself. But there were three I couldn't crack -- even a forum dedicated to solving GE puzzles came up empty:

https://googleearthcommunity.proboards.com/thread/10731/ulti...

howenterprisey•3mo ago
Maybe Geoguessr players would be good at identifying them as well?
theletterf•3mo ago
First photo could be Namibia? 29°40'04"S 18°11'12"E
Jordan-117•3mo ago
Hmm, plausible... though I'll have to go back in time and kick myself if it turns out I captioned it with the wrong continent!
theletterf•3mo ago
Gemini says:

"This looks almost certainly like a satellite view of a region in Western Australia, such as the Pilbara or the Hamersley Range. The dark areas are likely ancient, iron-rich rock formations (ironstone), and the surrounding soil is iconic of what's known as Australia's "Red Centre."

0x00cl•3mo ago
Hey Jordan,

I gave it a try and look for the locations, specially the 3rd one that does indeed look like it could be in Chile.

For the 2nd picture I found an island in the French Polynesia that has very similar colors and characteristics, might be its around that area, 8°56'10.8"S 139°34'41.2"W (-8.936304553977038, -139.57811272908305)

For the 3rd picture I found many locations that look like your picture but really couldn't find one. The first one is around Mexico, though it probably isn't 27°32'39.0"N 114°45'00.5"W (27.544166, -114.750130). And the second one are islands close to Morocco 28°01'54.4"N 17°16'22.9"W (28.03198233652239, -17.27306308433365) though the angle is not the same... As a bonus for the 3rd picture, I did find in the Andes mountain something that looks like your picture: 33°38'11.7"S 70°07'01.4"W (-33.636446, -70.116968). So maybe you should also look around mountains.

At least from what I've seen in Chile the coast is usually very rocky and the water is usually lot of waves, and in the picture it looks really smooth. (Though I don't know how zoomed out the picture is)

Jordan-117•3mo ago
Thanks! That's not it, but they're very beautiful landscapes.
nomel•3mo ago
There's a whole community (with world tournaments [1]) around finding places from pictures: geoguessers. The top people are absolutely incredibly [2]. There are also AI trained for this purpose. Although, the perspective they use is usually from street level.

[1] https://www.youtube.com/watch?v=u3sVtwexp0o

[2] https://www.youtube.com/@georainbolt

Jordan-117•3mo ago
A few people recommended Geoguessr (and people like Rainbolt are definitely amazing), but yeah I reckon they're hyperspecialized on reading clues in actual street view imagery, not natural satellite footage like this.
1d22a•3mo ago
Rainbolt often finds locations for people who have old photos of friends/family who have passed away etc., so the skills definitely seem to extend past just street view.
lacoolj•3mo ago
Once Zillow and Redfin start doing this, that will be game-changing
ecommerceguy•3mo ago
In 2001 we used Erdas Imagine to do this type of work. It required humans to train the software using heads-up digitizing. Dare I say machine learning on Pentium workstations?

edit, looks like they have ai too now. could be neat to play with after how long has it been. jeesh.

polyomino•3mo ago
I have found that using LLMs to generate queries for Overpass (Open street map query language) works really well. Great alternative if you don't care to deal with corporate nonsense.
macNchz•3mo ago
I've been able to do really cool stuff that I would never have otherwise bothered with by having an LLM generate Overpass queries + walk me through complex setup steps with QGIS.
groby_b•3mo ago
The flipside is that QGIS and overpass are so complicated that only with LLM assistance they're truly usable.

(Applies more to QGIS than to overpass, though both could stand to improve a lot in terms of usability)

Mashimo•3mo ago
Mhh, don't we already have conventional ways of telling where a flodding might happen?
kittikitti•3mo ago
Guess which corporation just announced they're profiting off of the government shutdown of vital environmental and climate agencies? I wonder why they failed to mention any of that in this press release.
Reubend•3mo ago
Instead of all this stuff, I'd like to see Google use their ML chops to "solve" weather forecasting and deliver ultra accurate predictions a few days ahead.
elpakal•3mo ago
But then who’s gonna spend all day Googling stuff when the weather changes their plans again?
NocturnalWaffle•3mo ago
They are working on this and have had really good results: https://deepmind.google/science/weathernext/ https://deepmind.google/discover/blog/gencast-predicts-weath...
jasongill•3mo ago
Just tested and while it seems interesting, there doesn't seem to (yet) be any intelligence about the imagery itself from what I can tell. For example, it can give me insights about vegetation data overlayed on a map (or try to), but it can't "find the most fertile grassland in this radius".

When there is a way to actually "search" satellite images with an LLM, it will be a game changer for businesses (and likely not to the ultimate benefit of consumers, unfortunately)

Demiurge•3mo ago
How would you even define “most fertile grassland”? What does “fertile” mean - soil nutrients, water availability, or productivity for a specific crop? And what counts as “grassland”? Are you talking about a 1 acre parcel, something for sale, or land next to a road?

There’s already data for all of this: SSURGO soil maps, vegetation indices, climatology datasets, and more — that could help you find the “most something” in a given radius. But there are too many variables for a single AI to guess your intent. That’s not how people who actually farm, conserve, or monitor land tend to search; they start from a goal and combine the relevant data layers accordingly.

In fact, crop-specific fertility maps have existed for decades, based on soil and climate averages, and they’re still good enough for most practical uses today.

jasongill•3mo ago
It was just an example, but you are correct. A more "imagery required" example would be "Find all the houses with roofs that have been damaged in the last 6 months" or something like that which could be used by salespeople or insurers
Demiurge•3mo ago
That's a good example, yes. I think this one can actually be interpreted by multiple AI agents to do search on the algorithms, or could even train a model, and then run the model. How amazing would it be, if this could actually all happen based on a few prompts :)