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Startup’s AI breaks global weather forecasting accuracy record

  • WindBorne Systems announces ability to precisely predict weather
  • System uses weather balloons, artificial intelligence 'deep learning'
  • Company made up of Stanford graduates in their 20s

GLENDALE, ARIZONA – JANUARY 01: A hot air balloon flys outside of State Farm Stadium before the Fiesta Bowl between the Liberty Flames and the Oregon Ducks on January 01, 2024 in Glendale, Arizona. (Photo by Christian Petersen/Getty Images)

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Imagine knowing, several days in advance of a hurricane, precisely where the storm will make landfall, exactly how strong the winds will be, and just how much rainfall will be dumped.

That day may be here, thanks to a team of Stanford graduates in their 20s who are taking the lead in the competitive field of artificial intelligence powered weather forecasting.

Startup WindBorne Systems announced Wednesday it beat Google’s DeepMind, the current leader in AI weather prediction, in key benchmarks set by U.S. and European government weather models.

In an exclusive interview with Semafor, the co-founders of the firm, backed by Khosla Ventures and Footwork, said they used an in-air fleet of around 100 inexpensive, hand-built weather balloons made from plastic purchased from a restaurant supply company to gather granular data, which they then analyzed using the same AI techniques that power ChatGPT.

According to the Semafor report, WindBorne’s WeatherMesh system takes advantage of two technology trends: the rapid evolution of AI algorithms and the precipitous decline in the cost and size of computer hardware and wireless equipment.

WindBorne’s weather balloons, which cost about as much to manufacture as an inexpensive mobile phone, can orbit around the earth for weeks, using AI to precisely control their paths. WindBorne says it already employs the world’s largest constellation of weather balloons, and will increase it 100-fold to 10,000 balloons, giving a tiny startup as much visibility into the earth’s weather systems as heavily funded government agencies.

Tech

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