This webinar is Part 1 of the Artificial Intelligence in Industrial Automation and Machinery series.
AI is everywhere. It's not just powering applications like smart assistants, machine translation, and automated driving, it's also giving engineers and scientists a set of techniques for tackling common tasks in new ways. And yet, according to recent estimates, while many organizations recognize the value and potential of AI, few are using it—Gartner's recent survey of 3,000 companies indicated that, of the 50% that are beginning to plan for AI, only 4% have actually implemented it.
Many organizations are deterred by what they see as the overwhelming challenges of implementing AI:
This talk will show how engineers can tackle challenges of using AI within manufacturing and examples where they have been applied from research and industry.
David Willingham is a Principal Product Manager responsible for MATLAB’s Deep Learning Toolbox. David joined MathWorks in 2006, and during this time amassed over 14 years of applied engineering experience supporting a variety of application areas in Artificial Intelligence including Deep Learning, Machine Learning, Reinforcement Learning, Predictive Maintenance, Statistics, Big Data & Cloud Computing. David has worked with clients in Finance, Mining, Medical, Aerospace, Automotive, Industrial Automation & Energy Industries and has published papers on Predictive Maintenance at AUSIMM Industry conferences for Mining, Mill Operators in 2016, and Iron Ore 2017.
Rareș Curatu is responsible for driving the business development of the Industrial Automation & Machinery industry for MathWorks in EMEA. Working with companies in energy generation and transmission, machine building, and automation equipment manufacturing, Rareș helps them to adopt Industry 4.0 and Industrial IoT workflows based on MATLAB and Simulink.
Recorded: 22 Sep 2021
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