Spiral Blue offers to run Your Code in Space

Science

SAN FRANCISCO — Australian startup Spiral Blue is inviting developers and researchers to run custom code on its SE-1 space-based computer.

After deploying its own machine-learning algorithms on SE-1, Spiral Blue issued a call Aug. 31 to people interested in sending code to space. Applications for the initiative, called Your Code in Space, can be as advanced as applying artificial intelligence to satellite imagery or as simple as creating a meme, Mei He, Spiral Blue business development officer, told SpaceNews.

Spiral Blue will respond to proposals submitted through the company’s website with information on how, when and at what cost various codes could run on the SE-1 computer.

“We are trying to make sure that it’s as accessible as possible to everyone including students and hobbyists,” He said.

Cropping Clouds

Spiral Blue’s SE-1 payload integrated with the Satellogic spacecraft launched in January on a SpaceX Falcon 9 rocket. Sydney-based Spiral Blue announced SE-1’s successful commissioning in April.

Since then, Spiral Blue has tested its own machine-learning algorithms to crop clouds out of satellite imagery on SE-1. Vessel detection algorithms and customer code has also been tested.

“It took us about five years to get our hardware working in orbit,” He said. “Now, we’re able to help others. We’ve done the hard work.”

Spiral Blue suggests Your Code in Space applications like environmental monitoring, disaster response, agricultural insights, urban planning and wildlife conservation.

Your Code in Space is “enabling companies to gain space heritage in a fraction of the traditional time by proving to be extremely effective at removing the barriers to running custom analytics in space,” Spiral Blue chief technology officer James Buttenshaw said in a statement.

Henry Zhong, Spiral Blue head of AI, said in a statement, the company has “achieved our dual goal of making our satellite programmable, allowing third parties to run their own code on-board and drastically reducing data requirements by bringing down just useful insights.”

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