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🌎 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐞𝐯𝐞𝐫 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐦𝐨𝐝𝐞𝐥: 𝐏𝐫𝐢𝐭𝐡𝐯𝐢 𝐖𝐱𝐂 𝐞𝐧𝐚𝐛𝐥𝐞𝐬 𝐥𝐢𝐟𝐞-𝐬𝐚𝐯𝐢𝐧𝐠 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬
🌎 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐞𝐯𝐞𝐫 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐦𝐨𝐝𝐞𝐥: 𝐏𝐫𝐢𝐭𝐡𝐯𝐢 𝐖𝐱𝐂 𝐞𝐧𝐚𝐛𝐥𝐞𝐬 𝐥𝐢𝐟𝐞-𝐬𝐚𝐯𝐢𝐧𝐠 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬
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Hurricane Katrina killed hundreds of people as it made landfall on New Orleans in 2005 - many of these deaths could have been avoided if alerts had been given one day earlier. Accurate weather forecasts are really life-saving.
Hurricane Katrina killed hundreds of people as it made landfall on New Orleans in 2005 - many of these deaths could have been avoided if alerts had been given one day earlier. Accurate weather forecasts are really life-saving.
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🔥 Now, NASA and IBM just dropped a game-changing new model: the first ever foundation model for weather! This means, it's the first time we have a generalist model not restricted to one task, but able to predict 160 weather variables!
🔥 Now, NASA and IBM just dropped a game-changing new model: the first ever foundation model for weather! This means, it's the first time we have a generalist model not restricted to one task, but able to predict 160 weather variables!
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Prithvi WxC (Prithvi, “पृथ्वी”, is the Sanskrit name for Earth) - is a 2.3 billion parameter model, with an architecture close to previous vision transformers like Hiera. 
Prithvi WxC (Prithvi, “पृथ्वी”, is the Sanskrit name for Earth) - is a 2.3 billion parameter model, with an architecture close to previous vision transformers like Hiera. 
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💡 But it comes with some important tweaks: under the hood, Prithvi WxC uses a clever transformer-based architecture with 25 encoder and 5 decoder blocks. It alternates between "local" and "global" attention to capture both regional and global weather patterns.
💡 But it comes with some important tweaks: under the hood, Prithvi WxC uses a clever transformer-based architecture with 25 encoder and 5 decoder blocks. It alternates between "local" and "global" attention to capture both regional and global weather patterns.
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𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
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🔮 Nails short-term forecasts - Prithvi WxC crushed it on 6-12 hour predictions, even outperforming some traditional numerical weather models
🔮 Nails short-term forecasts - Prithvi WxC crushed it on 6-12 hour predictions, even outperforming some traditional numerical weather models
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🌀 Tracks hurricanes like a champ - For Hurricane Ida, it predicted the landfall location within 5 km (vs 20+ km errors from other AI models), which is a huge progress!
🌀 Tracks hurricanes like a champ - For Hurricane Ida, it predicted the landfall location within 5 km (vs 20+ km errors from other AI models), which is a huge progress!
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🔍 6x downscaling power - Can zoom in on weather data to 6x higher resolution with 4x lower error than basic methods
🔍 6x downscaling power - Can zoom in on weather data to 6x higher resolution with 4x lower error than basic methods
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🌊 Models elusive gravity waves - Accurately simulates these crucial but hard-to-capture atmospheric oscillations
🌊 Models elusive gravity waves - Accurately simulates these crucial but hard-to-capture atmospheric oscillations
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As climate change intensifies, tools like Prithvi WxC will become more and more crucial to avoid disasters!
As climate change intensifies, tools like Prithvi WxC will become more and more crucial to avoid disasters!
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Announcement post 👉 
Announcement post 👉 
link
https://newsroom.ibm.com/2024-09-23-ibm-and-nasa-release-open-source-ai-model-on-hugging-face-for-weather-and-climate-applications
https://newsroom.ibm.com/2024-09-23-ibm-and-nasa-release-open-source-ai-model-on-hugging-face-for-weather-and-climate-applications
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Model on the Hub 👉 
Model on the Hub 👉 
link
https://huggingface.co/Prithvi-WxC
https://huggingface.co/Prithvi-WxC
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Thank you 
Thank you 
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@clem
clem
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 for highlighting it!
 for highlighting it!
🌎 𝐓𝐡𝐞 𝐟𝐢𝐫𝐬𝐭 𝐞𝐯𝐞𝐫 𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐦𝐨𝐝𝐞𝐥: 𝐏𝐫𝐢𝐭𝐡𝐯𝐢 𝐖𝐱𝐂 𝐞𝐧𝐚𝐛𝐥𝐞𝐬 𝐥𝐢𝐟𝐞-𝐬𝐚𝐯𝐢𝐧𝐠 𝐰𝐞𝐚𝐭𝐡𝐞𝐫 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐨𝐧𝐬

Hurricane Katrina killed hundreds of people as it made landfall on New Orleans in 2005 - many of these deaths could have been avoided if alerts had been given one day earlier. Accurate weather forecasts are really life-saving.

🔥 Now, NASA and IBM just dropped a game-changing new model: the first ever foundation model for weather! This means, it's the first time we have a generalist model not restricted to one task, but able to predict 160 weather variables!

Prithvi WxC (Prithvi, “पृथ्वी”, is the Sanskrit name for Earth) - is a 2.3 billion parameter model, with an architecture close to previous vision transformers like Hiera. 

💡 But it comes with some important tweaks: under the hood, Prithvi WxC uses a clever transformer-based architecture with 25 encoder and 5 decoder blocks. It alternates between "local" and "global" attention to capture both regional and global weather patterns.

𝗞𝗲𝘆 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀:
🔮 Nails short-term forecasts - Prithvi WxC crushed it on 6-12 hour predictions, even outperforming some traditional numerical weather models
🌀 Tracks hurricanes like a champ - For Hurricane Ida, it predicted the landfall location within 5 km (vs 20+ km errors from other AI models), which is a huge progress!
🔍 6x downscaling power - Can zoom in on weather data to 6x higher resolution with 4x lower error than basic methods
🌊 Models elusive gravity waves - Accurately simulates these crucial but hard-to-capture atmospheric oscillations

As climate change intensifies, tools like Prithvi WxC will become more and more crucial to avoid disasters!

Announcement post 👉 https://newsroom.ibm.com/2024-09-23-ibm-and-nasa-release-open-source-ai-model-on-hugging-face-for-weather-and-climate-applications

Model on the Hub 👉 https://huggingface.co/Prithvi-WxC

Thank you @clem for highlighting it!
🔥
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