EDA Finds a Common Framework for AI

By David White, Cadence
EETimes (April 29, 2019)

There's a model emerging for designing commercial decision systems such as EDA tools with embedded machine learning, writes an AI expert at Cadence in the first installment of a two-part article.

Last year, I was asked to serve on a panel at the NATO Science and Technology Board meeting. The group included folks from the various NATO countries working on AI and machine learning, mostly for applications associated with military-related operations, logistics, piloting, and surveillance-related decision-making. Over the past six months, our discussions have continued as we see more commonality with the military and aerospace communities in the area of AI-based applications for complex decision systems.

My talk was focused on the use of AI and other technologies to improve electronic design automation given that the cost, performance, and reliability of electronics is critical to the mission success of many systems and vehicles. There are also growing concerns about the cost of electronics development and processes related to the verification and support of next-generation AI chips, whether they use conventional or neuromorphic architectures.

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