MOUNTAIN VIEW, Calif. – The pace of innovation in the space sector is picking up thanks in part to artificial intelligence and machine learning.
Amazon Web Services customers, for example, are designing spacecraft parts with generative AI. The parts are then 3D-printed and run through a battery of tests.
The process leads to rapid iteration of designs that are “very intuitive and very innovative at the same time,” Alistair McLean, AWS Satellite Solutions principal architect, said Feb. 7 at the SmallSat Symposium here.
Generative AI relies on deep-learning models to answer questions or create content based on patterns detected in enormous datasets. Much of the benefit for space companies comes from pairing generative AI with more traditional machine-learning algorithms and computer-vision models.
“It’s a wonderful menagerie that seems to be a growing in terms of data and ways that customers are applying it,” McLean said.
Cognitive Space, a startup specializing in automating satellite operations, uses Open AI’s ChatGPT and similar tools to search imagery archives and answer questions related to satellite tasking.
In the past, someone looking for satellite imagery would have pulled up a map and drawn a box around the area they wanted to search.
Now, a customer can find imagery by simply asking to see “synthetic aperture radar, hyperspectral and multispectral sensors over the city of Denver from the last two weeks,” said Hanna Steplewska, Cognitive Space president and chief operating officer.
Geospatial analytics company HawkEye 360 also benefitting from AI in its work identifying radio frequency emitters around the world. The Herndon, Virginia-company known for geolocating emissions sources rapidly developed a new product that goes beyond labeling an emitter as an X-band radar.
For instance, it can specify an…
Read the full article here