Hacker News

New stories

Live mirror
30 storiesupdated just nowView source snapshot
  1. You can run Git on object storage if you re-make packfiles(tigrisdata.com ↗)
    discuss
  2. Fourteen AI models against a customer edge. Divert blocked first(divert.cloud ↗)
    1comments
  3. Fault tolerance in low-bandwidth model parallelism(tplr.ai ↗)
    discuss
  4. Driscoll's Gave China Its Blueberries–Then China Swiped the Secret(wsj.com ↗)
    discuss
  5. Breakout List(breakoutlist.com ↗)
    2comments
  6. Show HN: Pixel Agents – A pixel-art mission control for your Claude Code agents(mateovalle.github.io ↗)
    discuss
  7. A Trump-backed crypto bill just suffered a bruising defeat in the Senate(npr.org ↗)
    discuss
  8. Oil Prices Could Hit Highest Levels in Months After Saudi Pipeline Attacks(nytimes.com ↗)
    discuss
  9. The first (public) System One Model; Jev gives AI the properties of code(typesafe.ai ↗)
    discuss
  10. Iran strikes on Amazon data centers caused permanent loss of customer data(arstechnica.com ↗)
    2comments
  11. Amazon bumps minimum starting pay to $20/hour, adds new discount for employees(thehill.com ↗)
    discuss
  12. Google confirms Pixel phones exploited in 'targeted' modem based attack(9to5google.com ↗)
    discuss
  13. AI Compilers Are Not Just Compilers for AI(aicompilers.github.io ↗)
    discuss
  14. History of the BBC TV Idents(bbc.com ↗)
    discuss
  15. A mouse whose brain cortex is made up of human cells(technologyreview.com ↗)
    discuss
  16. Ask HN: AI Panic, you buying it?
    3comments
  17. The FBI Doubles Down on Easing 'Bestiality' Hiring Standards(wired.com ↗)
    1comments
  18. Show HN: Smarter Shell History for Zsh(github.com/overflowy ↗)
    discuss
  19. OSRS Wiki and RuneLite are under strain from low-effort AI development(runescape.wiki ↗)
    1comments
  20. CO3: Toward the Optimal FFI(mversic.github.io ↗)
    discuss
  21. Training Text-to-Image Models 3.6× Faster(linum.ai ↗)
    discuss
  22. Gnome 51 Released with Improved Frame Scheduling, Many App Improvements(phoronix.com ↗)
    1comments
  23. We killed our in-app AI chat and made the agent a first-class user(sensefold.app ↗)
    discuss
  24. Omarchy on Mac(github.com/omacom ↗)
    discuss
  25. Whiteboard Defense(twitter.com/mitchellh ↗)
    discuss
  26. Show HN: Ivx/AI Chat, AI client that doesn't track you (with a better GUI imo)(ivx.run ↗)
    discuss
  27. As Someone Who Has Written This Blog Post,(zachholman.com ↗)
    discuss
  28. Numerical Tours(numerical-tours.com ↗)
    discuss
  29. IPC Panic, a 4-call kernel panic in Apple XNU, up to macOS and iOS 26 included(seriot.ch ↗)
    discuss
  30. Inside the MIT Report on How AI Is Eroding Campus Culture(learningcurve.fm ↗)
    1comments

Show HN: SeasonMap – when to travel where? visualized with climate data

3 pointsby 1h agoseasonmap.app
1 comments
1h agoHN ↗

Author here. I'm trying to visit every country and I've been to 158 so far.

Before I decide where to travel, I'd ask a local friend which season to avoid, or open up dozens of browser tabs on climate data to figure out what the place is like in a given month.

Climate data still miss things. Cancun in September looks great on paper, with 31°C and 10 hours of sun, but it's hurricane season and the beaches can be covered in seaweed.

Typical info that locals would know, which can also be captured as static data.

So I built SeasonMap to answer "when should I go to <place>?"

What you can do:

- Pick a travel style (city walk, beach, hiking, skiing, max sun, low humidity, etc.) and see every place ranked on a map

- See what's in season and what to avoid, and why: monsoon, hurricanes, extreme heat, bad air, peak crowds

- Filter destinations by temperature, rainfall, sunshine, air quality and hazard seasons

- Open a place to see its whole year: month by month weather, events (festivals, whale watching, cherry blossom), crowd levels, practical notes like scams, and traveller anecdotes summarized by AI with links to the sources

Data Source & how I made it: - The climate data is ERA5 normals via Open-Meteo (2016–2025), corrected with NOAA station data where available.

- Events, hazards and traveller notes were researched and by AI agents, and every one links to its source. Gathering it was easy. Checking it was the hard part.

- Yes, I've used AI heavily on this project before anyone call it an AI slop. Making was easy, but it took billons of tokens of beating whack-a-mole ai to polish and tweak to make it usable and decent. Through that, I've created many skills and evals ranging from visual qa, evals for irregular data, automated i18n and others. It still feels much like AI as I was using Claude Design, which i want to improve on. I tried using local llm, but the throughput was so low.

Pricing: the first 5 minutes are fully open, no signup. After that, the top 3 destinations and 25 place breakdowns a month are free. A 30-day pass is $7, $39 a year or $69 lifetime.

iOS and Android apps are coming soon.

Any feedback welcome.