Intel and National Science Foundation Invest in Wireless-Specific Machine Learning Edge Research

What’s New: Today, Intel and the National Science Foundation (NSF) announced award recipients of joint funding for research into the development of future wireless systems. The Machine Learning for Wireless Networking Systems (MLWiNS) program is the latest in a series of joint efforts between the two partners to support research that accelerates innovation with the focus of enabling ultra-dense wireless systems and architectures that meet the throughput, latency and reliability requirements of future applications. In parallel, the program will target research on distributed machine learning computations over wireless edge networks, to enable a broad range of new applications.

“Since 2015, Intel and NSF have collectively contributed more than $30 million to support science and engineering research in emerging areas of technology. MLWiNS is the next step in this collaboration and has the promise to enable future wireless systems that serve the world’s rising demand for pervasive, intelligent devices.”
– Gabriela Cruz Thompson, director of university research and collaborations at Intel Labs

Why It’s Important: As demand for advanced connected services and devices grows, future wireless networks will need to meet the challenging density, latency, throughput and security requirements these applications will require. Machine learning shows great potential to manage the size and complexity of such networks – addressing the demand for capacity and coverage while maintaining the stringent and diverse quality of service expected from network users. At the same time, sophisticated networks and devices create an opportunity for machine learning services and computation to be deployed closer to where the data is generated, which alleviates bandwidth, privacy, latency and scalability concerns to move data to the cloud.

“5G and Beyond networks need to support throughput, density and latency requirements that are orders of magnitudes higher than what current wireless networks can support, and they also need to be secure and energy-efficient,” said Margaret Martonosi, assistant director for computer and information science and engineering at NSF. “The MLWiNS program was designed to stimulate novel machine learning research that can help meet these requirements – the awards announced today seek to apply innovative machine learning techniques to future wireless network designs to enable such advances and capabilities.”