Finding purposely-hidden nuclear sites is hard. But new tools and datasets allow analysts to interactively explore huge geotemporal datasets. OmniSci has recently partnered with the Center for Nonproliferation Studies (CNS) and Planet to demonstrate how daily satellite imagery, machine learning for feature extraction, and interactive analytics can help make the world safer. CNS continually assesses potential nuclear missile production sites. It has found that in North Korea these are often hidden at the ends of new mountain roads. How can we turn this insight into actionable data?
Finding Purposefully Hidden Sites with GPUs and ML
Amazon Web Services (AWS)
AWS is the world’s most comprehensive and broadly adopted cloud platform, offering over 175 fully featured services from datacenters globally. Millions of customers are using AWS to lower costs, become more agile, and innovate faster.
CloudFactory is a global leader in combining people and technology to provide a workforce in the cloud for machine learning and core business data processing.
Cognilytica is an AI focused research, advisory, and education firm.
Databricks is the data and AI company. Thousands of organizations worldwide rely on Databricks’ open and unified platform for data engineering, machine learning and analytics. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to solve the world’s toughest problems.
Maverick Quantum Inc (mavQ)
Maverick Quantum Inc (mavQ) is a low code & artificial intelligence platform that enables organizations with digital transformation while creating valuable insights and outcomes.