Predictive Engineering and Artificial Intelligence
Humans make decisions and solve problems using heuristics (“thinking fast”) or abstract approaches such as modeling (“thinking slow”). Artificial intelligence approaches can similarly use either heuristics that are related to correlation and categorization, or use models that are related to causation. Predictive Engineering, which melds engineering modeling with probabilistic thinking, aligns closely with causation and an aspect of artificial intelligence called Causal Learning. Issues with some artificial intelligence approaches will be explored, with real (and sometimes controversial and provocative) examples, and promising approaches encompassing causation /predictive engineering will be discussed.
Date and Time
Location
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Registration
- Date: 31 Jan 2025
- Time: 09:00 AM to 09:41 AM
- All times are (UTC-10:00) Hawaii
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- Starts 12 November 2024 12:00 AM
- Ends 31 January 2025 12:00 AM
- All times are (UTC-10:00) Hawaii
- No Admission Charge
Speakers
Eric Maass
Biography:
Eric Maass, PhD
Senior Director, DRM, Medtronic Restorative Therapies Group
Technical Fellow and DRM Master Black Belt (Retired)
Eric retired as Senior Director and Technical Fellow at Medtronic, leading and Coaching successful new product and technology development projects. Eric joined Medtronic in October 2009, after 30 years with Motorola in roles ranging from Research and Development through Manufacturing, to Director of Operations for a $160 Million business and Director of Design and Systems Engineering for the Wireless group of Motorola SPS.
Eric was a co-founder of Six Sigma, and had been the Lead Master Black Belt for DFSS at Motorola. His book, Applying DFSS to Software and Hardware Systems, provides clear step-by-step guidance on applying DFSS for developing innovative and compelling new products and technologies, while managing the business, schedule and technical risks. His newest book, “Flawless Launches – Profitable Products” shares methods that have led to very successful product launches.
Eric received his Bachelor’s degree in Biological Sciences from the University of Maryland Baltimore County, his Master’s degree in Biomedical and Chemical Engineering from Arizona State University and his PhD in Industrial Engineering from Arizona State University. Dr Maass also currently serves as an Adjunct Professor at Arizona State University, and served as chairman of the Industrial Advisory Board for the NSF-Sponsored B.R.A.I.N Industry/University collaborative research consortium. In his active retirement, he has been invited to provide training and consulting for 17 corporations.