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Design007-Sept2018

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18 DESIGN007 MAGAZINE I SEPTEMBER 2018 Feature Interview by Andy Shaughnessy I-CONNECT007 David White has been involved with artifi- cial intelligence research for almost 30 years. Now, David is the senior group director of R&D for Cadence Design Systems, and I knew we'd have to speak with him for this month's issue on AI. In a recent interview, we discussed his decades of work in AI, Cadence's research into AI and machine learning, and what he believes AI could mean for the EDA tools of the future. Andy Shaughnessy: Tell us a little about your background, your work with AI, and your thoughts on AI overall. David White: I started working in AI in 1989 as a college student after discovering a copy of Par- allel Distributed Processing, by David Rumel- hart. I was so enthralled that I completed my undergraduate thesis on using neural network- based controls for a robotic arm. That work led me to McDonnell Douglas, now Boeing, where I worked in the New Aircraft Products Division on machine learning research for manu- facturing and flight con- trols. As a result of this work, NSF asked me to chair the first NSF Workshop on Aerospace Appli- cations of Neural Networks, which included machine learning research- ers from across the country as well as a presidential science advisor and govern- ment officials. Cadence: Bullish on AI I joined the MIT AI Laboratory where I con- tinued my research and edited and co-authored a book on intelligent decision and control systems in 1992 with leaders in the machine learning world such as Michael Jordon, Paul Werbos and Andy Barto. I completed my grad- uate work at MIT where my research applied machine learning and chemometrics to semi- conductor processing. I later co-founded and served as CTO of Praesagus, a company that was acquired by Cadence in 2006, and I have been working on electronic design automation with Virtuoso technology since 2009. In terms of my thoughts on AI, I am really excited about the prospects of building intel- ligent decision systems that can learn from users and their environment. We believe we are bringing a unique perspective to how we build these systems. We are combining innova- tions in machine and deep learning with large scale optimization and distributed processing in unique ways. Much of what we are working on has applications beyond EDA and extends to how we can build design and analysis soft- ware that tailors itself to the user and their mission. Shaughnessy: How did Cadence first get involved with AI? White: I joined Cadence in 2006 when our company was acquired, so my frame of refer- ence begins then. Cadence's research in machine learning (ML) for physical design and electrical analysis started in the

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