Using Web3 and AI to Optimize Weather Forecasts ｜ Founders ｜ Manos Nikiforakis of WeatherXM

More than one-third of the worldwide economy is weather sensitive, affecting industries such as agriculture, renewable energy and shipping, among others. WeatherXM, a startup in the Protocol Labs Networks, seeks to improve weather forecasts by employing Web3 technology with artificial intelligence. In combining historical weather data from its proprietary weather stations with third party data from traditional weather forecasts, WeatherXM builds a machine learning model to improve localized forecasts around the world.
"We believe that there’s not enough weather data out there. And we believe that’s one of the major reasons why weather forecasts are wrong," says Manos Nikiforakis, who co-founded WeatherXM with Stratos Theodorou. Nikiforakis grew up among a farming community in Crete, Greece, and learned firsthand the impact of weather data on people's lives and work. In this episode of Founders, he explains how WeatherXM was created and how with large-scale deployment, the technology could lead to new, more effective and efficient business models, such as weather insurance on chain.
Chapters
00:00 - Intro to WeatherXM
00:25 - How weather correlates to energy production
01:27 - Using Web3 to increase weather data
01:50 - Closer look at the WeatherXM weather station
02:15 - Users can participate in the new data economy
03:06 - WeatherXM's machine learning model elevates weather prediction
03:37 - Growing up around agriculture showed the impact of weather on people's lives
04:25 - The Protocol Labs Network effect
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Website: weatherxm.com
Follow WeatherXM on Twitter: / weatherxm
Subscribe to Building Web3: bit.ly/BW3sub
Follow Protocol Labs on Twitter: / protocollabs
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