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Sisällön tarjoaa Jayesh Jagasia. Jayesh Jagasia tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.
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#117 - Dr Richard Ahlfeld - CEO, Monolith AI

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Manage episode 329062784 series 2793161
Sisällön tarjoaa Jayesh Jagasia. Jayesh Jagasia tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

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!

AI in Automotive Podcast

  continue reading

40 jaksoa

Artwork
iconJaa
 
Manage episode 329062784 series 2793161
Sisällön tarjoaa Jayesh Jagasia. Jayesh Jagasia tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

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!

AI in Automotive Podcast

  continue reading

40 jaksoa

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