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Google’s latest AI weather model gives you no excuse to forget your umbrella
Confirmed
In Short: Google has launched WeatherNext 3, an advanced AI model that provides more accurate, high-resolution weather forecasts by using real-time satellite data instead of traditional physics simulations, according to a blog post by Google.
Google has launched WeatherNext 3, an advanced AI model that provides more accurate, high-resolution weather forecasts by using real-time satellite data instead of traditional physics simulations, according to a blog post by Google.
The model, introduced by Google DeepMind and Google Research, is the most advanced and accurate global weather model to date, as reported by independent live evaluations by Brightband.
Despite its advancements, WeatherNext 3 still relies on national weather datasets for forecasts, indicating that more work is needed for true direct data assimilation.
Samier Merchant, a Google senior staff engineer, and Ferran Alet, a staff research scientist manager at DeepMind, emphasized the model's ability to learn patterns from vast amounts of data, addressing the chaotic nature of weather.
Bill Gates has highlighted the importance of AI-powered weather forecasting, noting that better forecasts can significantly improve crop yields in developing countries, underscoring the broader impact of such technology.
What's confirmed
- Today, Google DeepMind and Google Research are introducing WeatherNext 3, the most advanced and accurate global weather model to date, according to independent live evaluations by Brightband.
What's still developing
- Google has launched WeatherNext 3, an advanced AI model that provides more accurate, high-resolution weather forecasts by using real-time satellite data instead of traditional physics simulations.
- Most of us have probably looked out the window at falling rain while our weather app confidently suggests we won’t get wet if we head out.
- “This is going to be the first time that some of the core variables feed and power a lot of the Google products,” Samier Merchant, a Google senior staff engineer, told TechCrunch.
- “Weather is chaotic, and so small differences really start to perturb massively…Machine learning targets the problem we are really solving, which is approximate noisy physics from incomplete information and finite…
- Regardless, both models still rely on national weather datasets to perform forecasts, so more work will be required for true direct data assimilation.
- Bill Gates recently cited AI-powered weather forecasting as a crucial benefit of the technology, with better forecasts improving crop yields in developing countries.
- “At the end of the day, I think Google is about providing useful information to the user, and a lot of what users are looking for has to do with the weather in some way or another,” Alet said.