In a bid to democratise access to AI technology for climate science, IBM and Hugging Face have announced the release of the watsonx.ai geospatial foundation model.
The geospatial model, built from NASA’s satellite data, will be the largest of its kind on Hugging Face and marks the first-ever open-source AI foundation model developed in collaboration with NASA.
Jeff Boudier, head of product and growth at Hugging Face, highlighted the importance of information sharing and collaboration in driving progress in AI. Open-source AI and the release of models and datasets are fundamental in ensuring AI benefits as many people as possible.
Climate science faces constant challenges due to rapidly changing environmental conditions, requiring access to the latest data. Despite the abundance of data, scientists and researchers struggle to analyse the vast datasets effectively. NASA estimates that by 2024, there will be 250,000 terabytes of data from new missions.
To address this issue, IBM embarked on a Space Act Agreement with NASA earlier this year—aiming to build an AI foundation model for geospatial data.
By making this geospatial foundation model openly available on Hugging Face, both companies aim to promote collaboration and accelerate progress in climate and Earth science.
Sriram Raghavan, VP at IBM Research AI, commented:
“The essential role of open-source technologies to accelerate critical areas of discovery such as climate change has never been clearer.
By combining IBM’s foundation model efforts aimed at creating flexible, reusable AI systems with NASA’s repository of Earth-satellite data, and making it available on the leading open-source AI platform, Hugging Face, we can leverage the power of collaboration to implement faster and more impactful solutions that will improve our planet.”
The geospatial model, jointly trained by IBM and NASA on Harmonized Landsat Sentinel-2 satellite data (HLS) over one year across the continental United States, has shown promising results. It demonstrated a 15 percent improvement over state-of-the-art techniques using only half the labelled data.
With further fine-tuning, the model can be adapted for various tasks such as deforestation tracking, crop yield prediction, and greenhouse gas detection.
IBM’s collaboration with NASA in building the AI model aligns with NASA’s decade-long Open-Source Science Initiative, promoting a more accessible and inclusive scientific community. NASA, along with other federal agencies, has designated 2023 as the Year of Open Science, celebrating the benefits of sharing data, information, and knowledge openly.
Kevin Murphy, Chief Science Data Officer at NASA, said:
“We believe that foundation models have the potential to change the way observational data is analysed and help us to better understand our planet.
By open-sourcing such models and making them available to the world, we hope to multiply their impact.”
The geospatial model leverages IBM’s foundation model technology and is part of IBM’s broader initiative to create and train AI models with transferable capabilities across different tasks.
In June, IBM introduced watsonx, an AI and data platform designed to scale and accelerate the impact of advanced AI with trusted data. A commercial version of the geospatial model, integrated into IBM watsonx, will be available through the IBM Environmental Intelligence Suite (EIS) later this year.
By leveraging the power of open-source technologies, this latest collaboration aims to address climate challenges effectively and contribute to a more sustainable future for our planet.
(Photo by Markus Spiske on Unsplash)
See also: Jay Migliaccio, IBM Watson: On leveraging AI to improve productivity
Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The event is co-located with Digital Transformation Week.
Explore other upcoming enterprise technology events and webinars powered by TechForge here.
The post IBM and Hugging Face release AI foundation model for climate science appeared first on AI News.