Adoption: Individual Enthusiasm vs Organizational Caution

From neural networks in the ‘90s to the rise of AI copilots—how MathWorks is shaping the future of engineering innovation.

In this episode, I sit down with Richard Rovner, Vice President of Marketing at MathWorks, to explore the fascinating evolution of AI in engineering. We trace the technology’s journey from its early days in the 1980s, through transformative milestones like deep learning and code generation, all the way to today's AI-driven design tools and copilots.

Richard shares insider perspectives on how AI is changing the engineer’s workflow, what generative AI means for the future, and why the human touch remains essential in a world of accelerating automation. If you’re curious about where engineering and AI are headed—or how to stay ahead in this rapidly shifting landscape—this conversation is packed with insights you won’t want to miss.

Siemens

https://new.siemens.com/global/en/company/topic-areas/artificial-intelligence.html

MathWorks

https://www.mathworks.com/

MATLAB

https://www.mathworks.com/products/matlab.html

Simulink

https://www.mathworks.com/products/simulink.html

Neural Network Toolbox

https://www.mathworks.com/products/neural-network.html

Deep Learning Toolbox

https://www.mathworks.com/products/deep-learning.html

Statistics and Machine Learning Toolbox

https://www.mathworks.com/products/statistics.html

Text Analytics Toolbox

https://www.mathworks.com/products/text-analytics.html

MATLAB Copilot

https://www.mathworks.com/products/matlab-copilot.html

SAS

https://www.sas.com/

FAW Ulm (Forschungsinstitut für anwendungsorientierte Wissensverarbeitung)

https://www.faw-ulm.de/

Coca-Cola Freestyle

https://www.coca-colafreestyle.com/

ARM Cortex-M

https://www.arm.com/products/silicon-ip-cpu/cortex-m

Max Planck Society

https://www.mpg.de/en

Reinforcement Learning

https://en.wikipedia.org/wiki/Reinforcement_learning

Model-Based Design

https://www.mathworks.com/solutions/model-based-design.html