With the advent of high-speed 5G mobile networks, enterprises are more easily positioned than ever with the opportunity to harness the convergence of telecommunications networks and the cloud. As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers to reduce latency and increase responsiveness of their applications. As an example, smart venue solutions can use near-real-time computer vision for crowd analytics over 5G networks, all while minimizing investment in on-premises hardware networking equipment. Retailers can deliver more frictionless experiences on the go with natural language processing (NLP), real-time recommendation systems, and fraud detection. Even ground and aerial robotics can use ML to unlock safer, more autonomous operations.

Amazon Web Services brought its compute and storage capabilities to the mobile edge this week for developers in Boston and the San Francisco Bay area with its new AWS Wavelength on Verizon's 5G network. AWS' first Wavelength Zones use Verizon's 5G Edge mobile compute platform to allow developers and enterprises to deploy ultra-low latency-dependent applications to mobile and connected wireless devices at the edge of Verizon's 5G Ultra Wideband network. Use cases for 5G mobile edge compute using AWS Wavelength include machine learning (ML) inference at the edge, autonomous industrial equipment, connected cars, smart cities and factories, the Internet of Things, live and interactive video and game streaming, and virtual reality. Developers can build applications that provide near-real-time analytics for instant decision-making and automated robotic systems for manufacturing facilities. AWS Wavelength's debut comes eight months after AWS CEO Andy Jassy and Verizon CEO Hans Vestberg (pictured) unveiled the new service at the AWS re:Invent conference in Las Vegas in December.