NASA and AWS are working together to use artificial intelligence to protect Earth from solar superstorms, according to an Amazon blog post.
As the world becomes ever more wired, solar coronal mass ejections (CME) represent a significant threat to countries around the globe. One such event occurred in March 1989, affecting the U.S. and Canada.
According to Amazon, “the Hydro-Quebec electric grid collapsed within 90 seconds. A strong electric current surged through the surface bedrock making all intervention impossible. Over 6 million people were left without power for nine hours. At the same time, over in the United States, 200 instances of power grid malfunctions were reported. More worryingly, the step-up transformer at the New Jersey Salem Nuclear Power Plant failed and was put out of commission.”
Given how much more digital the world is now, a CME like the ‘89 one could wreak havoc on power grids, satellites, wireless communication and much more. As a result, NASA is continually looking for ways to detect and warn of CMEs as early as possible, to give grid and satellite operators time to take protective measures. This is where AWS and Amazon’s experience with machine learning come into play.
“NASA is working with AWS Professional Services and the Amazon Machine Learning (ML) Solutions Lab to use unsupervised learning and anomaly detection to explore the extreme conditions associated with superstorms,” writes Arun Krishnan, editor of the Amazon Science website. “The Amazon ML Solutions Lab is a program that enables AWS customers to connect with machine learning experts within Amazon.
“With the power and speed of AWS, analyses to predict superstorms can be carried out by sifting through as many as 1,000 data sets at a time. NASA’s approach relies on classifying superstorms based on anomalies, rather than relying on an arbitrary range of magnetic indices. More specifically, NASA’s anomaly detection relies on simultaneous observations of solar wind drivers and responses in the magnetic fields around earth.”
By analyzing anomalies, it gives NASA the ability to better understand what causes a solar superstorm and predict when one will occur.
“To improve forecasting models, scientists can examine the anomalies and create simulations of what it would take to reproduce the superstorms we see today,” the blog continues. “They can amplify these simulations to replicate the most extreme cases in historical records, enabling model development to highlight subtle precursors to major space weather events.”
NASA and Amazon are providing another excellent example of the transformative effect artificial intelligence and machine learning will continue to have on day-to-day life.