{"id":14665,"date":"2024-03-26T13:46:17","date_gmt":"2024-03-26T13:46:17","guid":{"rendered":"http:\/\/TheNextWeb=1405099"},"modified":"2024-03-26T13:46:17","modified_gmt":"2024-03-26T13:46:17","slug":"esa-to-build-chatgpt-style-earth-observation-digital-assistant","status":"publish","type":"post","link":"https:\/\/www.londonchiropracter.com\/?p=14665","title":{"rendered":"ESA to build ChatGPT-style Earth observation digital assistant"},"content":{"rendered":"\n

The European Space Agency (ESA) has announced it will build a ChatGPT-style digital assistant to help humans better decode complex Earth observation data<\/a>.<\/span><\/p>\n

Led by \u03a6-lab (Phi-Lab) \u2014 the agency\u2019s Earth observation innovation and investment arm \u2014 the <\/span>chatbot will be trained to understand human queries about the Earth and respond with human-like answers. The lab is due to kick off the project next month.<\/span><\/p>\n

Earth observation tools like satellites and weather stations gather <\/span>vast volumes of data on our home planet every day. Most of this information is unlabelled, which makes it hard for traditional <\/span>machine learning<\/a> algorithms to make sense of what they are seeing. <\/span><\/p>\n

That is why ESA <\/span>\u03a6-lab is working on<\/span> developing a foundational AI model to underpin the digital assistant. Foundational <\/span>models, like those used to power ChatGPT, are AI<\/a> neural networks trained on unlabelled datasets and designed to handle a wide variety of tasks. <\/span><\/p>\n

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This means ESA\u2019s chatbot will be able to take unlabelled Earth observation data straight from satellites and quickly translate it into meaningful insights. <\/span><\/p>\n

\u201cThe concept of an Earth observation digital assistant that can provide a broad range of insight from varied sources is a tantalising prospect,\u201d said Giuseppe Borghi, head of ESA \u03a6-lab.<\/span><\/p>\n

The lab h<\/span>as several ongoing initiatives for creating foundation models dedicated to Earth observation. These models provide critical information on topics such as how to minimise damage from extreme weather events or the amount of methane pollution in the atmosphere. <\/span><\/p>\n

\"Richat_structure_ESA\"
<\/i><\/a>The 40 km-diameter circular Richat structure in the Sahara desert is one of the many geological features the ESA is using to test its AI models. Credit: ESA<\/figcaption>