-
- News
- Books
Featured Books
- design007 Magazine
Latest Issues
Current IssueShowing Some Constraint
A strong design constraint strategy carefully balances a wide range of electrical and manufacturing trade-offs. This month, we explore the key requirements, common challenges, and best practices behind building an effective constraint strategy.
All About That Route
Most designers favor manual routing, but today's interactive autorouters may be changing designers' minds by allowing users more direct control. In this issue, our expert contributors discuss a variety of manual and autorouting strategies.
Creating the Ideal Data Package
Why is it so difficult to create the ideal data package? Many of these simple errors can be alleviated by paying attention to detail—and knowing what issues to look out for. So, this month, our experts weigh in on the best practices for creating the ideal design data package for your design.
- Articles
- Columns
- Links
- Media kit
||| MENU - design007 Magazine
Cadence: Bullish on AI
October 15, 2018 | Andy Shaughnessy, Design007 MagazineEstimated reading time: 2 minutes

David White has been involved with artificial 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 Parallel Distributed Processing, by David Rumelhart. 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 manufacturing and flight controls. As a result of this work, NSF asked me to chair the first NSF Workshop on Aerospace Applications of Neural Networks, which included machine learning researchers from across the country as well as a presidential science advisor and government officials.
I joined the MIT AI Laboratory where I continued 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 graduate work at MIT where my research applied machine learning and chemometrics to semiconductor 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 intelligent 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 innovations 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 software 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 reference begins then. Cadence’s research in machine learning (ML) for physical design and electrical analysis started in the 2009-2010 timeframe, with two persons and myself. Our motivation came from observing the scale and complexity that grew with the increase in data such as larger designs, larger simulations, etc.
To address these problems, we began to look at data-driven solutions such as analytics and machine learning. When we began the work, there was not the same buzz around machine or deep learning, and we just found it to be a useful tool to create fast models of complex non-linear problems that required long compute times using more traditional methods.
To read this entire interview, which appeared in the September 2018 issue of Design007 Magazine, click here.
Suggested Items
TT Electronics Secures Multi-Million-Pound Defense Contract with Ultra PCS
07/18/2025 | TT ElectronicsTT Electronics, a leading provider of global manufacturing solutions and engineered technologies, announced that it has been awarded a significant new contract with long-standing customer Ultra PCS Ltd (Ultra Precision Control Systems).
NEOTech’s Agave 1 Facility Earns AS9100 Certification for Commercial Aerospace Manufacturing Excellence
07/17/2025 | NEOTechNEOTech, a premier provider of electronic manufacturing services (EMS), integrated design engineering, and advanced supply chain solutions for the aerospace and defense, medical device, and high-tech industrial markets, proudly announces that its Agave 1 manufacturing facility in Juarez, Mexico has officially received AS9100 certification.
Federal Electronics Invests in HydroJet Inline Cleaning Technology at Hermosillo Facility
07/15/2025 | Federal ElectronicsFederal Electronics, a leader in providing advanced electronic manufacturing services, has strengthened the advanced cleaning capabilities of its Hermosillo, Mexico facility with the recent installation of a HydroJet Inline Cleaner from Austin American Technology (AAT).
FTG Announces Q2 2025 Financial Results
07/09/2025 | Globe NewswireFiran Technology Group Corporation announced financial results for the second quarter 2025. Revenue: Recorded at $48.7 million, a 25.6% increase over Q2 2024.
Moog Announces Acquisition of COTSWORKS
07/07/2025 | BUSINESS WIREMoog Inc., a worldwide designer, manufacturer and systems integrator of high-performance precision motion and fluid controls and control systems, announced the acquisition of COTSWORKS Inc., an aerospace and defense fiber optics transceiver component manufacturer, for a purchase price of $63 million.