IBM, NASA join hands to research impact of climate change with AI
Tech major IBM and NASA’s Marshall Space Flight Center have announced a collaboration to use IBM’s artificial intelligence (AI) technology to discover new insights in NASA’s massive trove of Earth and geospatial science data.
The goal of this joint work is to advance the scientific understanding and response to Earth and climate-related issues like natural disasters and warming temperatures, also the joint work will apply the new IBM AI foundation model technology to NASA’s Earth-observing satellite data for the first time.
Foundation models are types of AI models that are trained on a broad set of unlabeled data, can be used for different tasks, and can apply information about one situation to another.
“Applying foundation models to geospatial, event-sequence, time-series, and other non-language factors within Earth science data could make enormously valuable insights and information suddenly available to a much wider group of researchers, businesses, and citizens. Ultimately, it could facilitate a larger number of people working on some of our most pressing climate issues,” Raghu Ganti, principal researcher at IBM, said in a statement.
Over the last five years, these models have rapidly advanced the field of natural language processing (NLP) technology, and IBM is pioneering applications of foundation models beyond language, said the company.
“Building these foundation models cannot be tackled by small teams,” Rahul Ramachandran, senior research scientist at NASA’s Marshall Space Flight Center in Huntsville, Alabama, said in a statement.
“You need teams across different organisations to bring their different perspectives, resources, and skill sets,” he added.
Moreover, IBM and NASA plan to develop several new technologies to extract insights from Earth observations.
The first model will be trained on over 3,00,000 earth science publications in order to thematically organise the literature and make it easier to search for and discover new knowledge.
The second model will be trained using the popular Harmonized Landsat Sentinel-2 (HLS2) satellite dataset from the USGS and NASA, with applications ranging from detecting natural hazards to tracking changes in vegetation and wildlife habitats, the company mentioned.
Further, other potential IBM-NASA collaborative projects in this agreement include developing a foundation model for weather and climate prediction using MERRA-2, an atmospheric observation dataset.