LEO EO/IR/SAR Data Processing & ATR Astronaut Robotic Assistant & Health Management Constellation Management & Collision Avoidance Communication Network Reconfiguration/Optimization Planet/Comet/Asteroid Identification & Tracking Internet of Space Things Weather Monitoring & Prediction Natural Disaster Monitoring, Warning, & Impact Analysis Autonomous Emergency First Response
Enabling COTS in Space Electronics Systems
On Earth Data Processing Planet/Comet/Asteroid Identification & Tracking Constellation Management & Collision Avoidance Weather Monitoring & Prediction Natural Disaster Monitoring, Warning, & Impact Analysis Autonomous Emergency First Response
Moon Mineral/Mining Mapping & Site Identification Swarm Drone Management & Optimization Early Warning Threat Detection (Gateway) Lunar Station/Base Power Optimization & Management
Stratosphere EO/IR/SAR Data Processing Communication Network Gap Enablement Weather Monitoring & Prediction Natural Disaster Monitoring, Warning, & Impact Analysis
Title Why space By John McHale, Editorial Director needs artificial intelligence
MEO Methane Super Emitter Tracking Internet of Space Things Collision Avoidance Autonomous Emergency First Response
Route to Mars Solar/Cosmic Radiation Detection Autonomous Navigation/Course Correction Communication Network Reconfiguration/Optimization
GEO Smart Adaptive Comms Solar Flare & GRB Monitoring & Notification Weather Monitoring & Prediction Natural Disaster Monitoring, Warning, & Impact Analysis Autonomous Emergency First Response Early Warning Threat Detection
The GSI Technology project to work with other companies to bring novel computing architectures to mission-critical space systems is called FRACTALS [Fault tolerant and Resilient Associative Computing for Artificial inteLligence in Space]. GSI Technology illustration.
By Paul Armijo and George Williams
The modern-day revolution in artificial intelligence (AI) is fueled by neural networks, a concept that dates back to the 1950s; this concept has surged in the last decade under its new, much improved, guise called deep learning. Deep learning is empowering systems with unrivaled abilities to perceive their environments The visually and to make sense of human language through voice or text. But what do face recognition in family photos or customer-service chatbots have to do with advanced space tech and military intelligence-gathering? Quite a bit, it turns out, and the common denominator is data.
30 June 2020
Deep learning can consume massive amounts of data and distill all of it into compact machine learning models. When deployed, these trained models can be used for a myriad of tasks here on Earth: object recognition, language understanding, predictive analytics, even complex decision-making. In space, these models can perform similar roles as they process massive amounts of sensor data to gather and interpret intelligence, predict mission-critical events, facilitate human-computer interaction, and empower local-vehicle autonomy. From Earth to Mars â&#x20AC;Ś and beyond As artificial intelligence (AI) is added to missions, more and more Earth observational (EO) data will be processed on board instead of sent down to Earth. This evolution toward increased AI will take many years. In the meantime, thousands of satellites will continue beaming data back to the surface until end of life. This reality means that we still need to build advanced high-performance computing (HPC) systems here on the ground that use smarter, power-efficient algorithms to crunch all that data. We will need AI to process multispectral imagery not just over space, but over time. This kind of analysis is critical for improved weather forecasting and real-time disaster awareness, as well as justin-time first response. We can leverage AI not only to protect people against natural disasters, but also against human-made ones. A tremendous amount of space junk is hovering right above us, and we can use AI to predict when and where the most dangerous ones will make landfall.
MILITARY EMBEDDED SYSTEMS