#117 - Dr Richard Ahlfeld - CEO, Monolith AI

“If we look at automotive over the last 10 years, it is estimated that there is about 400bn euro worth of R&D data. If an OEM tries and learns from that data, it can develop a USP with regards to standard manufacturing processes, spend less time on it, and allocate resources to harder things like software development.”

Automotive product development is not just incredibly expensive, but also an extraordinarily complex process. Everything you see on a production vehicle is, at the end of the day, the result of hundreds of tug-of-war contests. Design and cost, manufacturability and serviceability, power and weight. The list goes on. Dozens of teams with hundreds of engineers pursuing conflicting design objectives, but eventually finding an optimum through a series of very difficult trade-offs.

Any benefit an automaker can take in the design and development process that accelerates take-to-market and improves margins is an absolute no-brainer. So what role can machine learning play?

In this episode of the AI in Automotive Podcast, I am joined by Dr Richard Ahlfeld, CEO of Monolith. We discuss how machine learning can be a potential game-changer in automotive R&D, and deliver some serious acceleration and cost benefits in the design and development process. 

Complex mathematical equations, ketchup bottles and a million dollar prize. This episode of the show has it all!