A series talk with Augmented Ops Podcast
How can we train 10,000 ML/AI engineers in the next 10 years?
Principle-, practice-, project-, and professional-based learning are key to mastering the required skills, explains Dr. Jay Lee, Director of the Industrial AI Center at the University of Maryland.
Tune into the full discussion at this link.
How can machine learning be applied to solve real operational problems?
Dr. Jay Lee, Director of the Industrial AI Center at the University of Maryland, explains how he developed an ML solution to solve seemingly random equipment failures at a Toyota plant and how much the tools to develop them have progressed in the years since.
Watch here: https://lnkd.in/eTNSpj3k
Do we need to rethink how we’re approaching the use of AI/ML in industry?
Dr. Jay Lee, Director of the Industrial AI Center at the University of Maryland joins us to discuss:
1️⃣ How to build a talent base of AI/ML engineers
2️⃣ Why we need to focus on augmenting human intelligence, rather than replacing it
3️⃣ How to develop AI/ML applications to solve real operational problems
4️⃣ And more!
Listen now: https://lnkd.in/dyaS8PMZ
“The biggest challenge is not about technology in AI, it's about talent”
says Dr. Jay Lee, Director of the Industrial AI Center at the University of Maryland. Check out the blog post on our recent discussion about his vision for developing a new educational paradigm to train 10,000 ML/AI engineers in 10 years.
Read it here: https://lnkd.in/eXP76KUf
How can we train enough ML/AI engineers to meet the needs of industry?
Dr. Jay Lee, Director of the Industrial AI Center at the University of Maryland explains his Three S approach for training engineers: systematically, at scale, and with speed.