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#212 Structuring Volvo For Operational Success with Leonard Aukea, Head of Machine Learning, Engineering & Operations at Volvo

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Manage episode 345281213 series 2310475
A tartalmat a Felipe Flores biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Felipe Flores vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

The motor industry has always been right at the forefront of innovation, and this is also true when it comes to embracing machine learning and AI. This week’s guest on the Data Futurology podcast is Leonard Aukea, the Head of Machine Learning, Engineering & Operations at Volvo, who shares with us insights into what the global vehicle giant is doing to bring value to the operations chain across the company.

For Aukea, it has been a story of establishing best processes across the organisation. He said that one of his first priorities was to bring the various data science teams together to minimise the impact of siloing, and encourage the machine learning practitioners to adopt software engineering principles. This might not be immediately comfortable to them, but as Aukea said, ML experts are smart people working on complex problems, and facilitating an open-minded approach across the organisation is key to driving long-term success.

“You need to start simple,” he said. “Think about processes, ways of working, and the cultural aspects, and try to fit tooling and infrastructure along that kind of endeavour. You don’t need to choose the most extreme state-of-the-art tools.”

At one point, Aukea noted, things being pushed into production were becoming unmanageable, so he and his teams took a step back and reset. “We went back and decided to focus on first principles,” he said. “We evangelised these first principles to develop good ways of working, and then adopted the infrastructure and tooling towards building AI on top of that.”

Ultimately, Aukea said, quality comes from the processes, rather than the technology. There are, of course, technical challenges, but for anyone aiming to get true value out of machine learning, the focus needs to be on the processes.

Aukea then explains how, with those processes in place, he and his team have been able to start delivering deep and valuable insights. For more on how Aukea was able to structure Volvo for success with machine learning in operations, tune in to the podcast!

Enjoy the show!

Thank you to our sponsor, Talent Insights Group!

Join us in Sydney for Ops World: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

Read the full podcast summary here.

  continue reading

268 epizódok

Artwork
iconMegosztás
 
Manage episode 345281213 series 2310475
A tartalmat a Felipe Flores biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Felipe Flores vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

The motor industry has always been right at the forefront of innovation, and this is also true when it comes to embracing machine learning and AI. This week’s guest on the Data Futurology podcast is Leonard Aukea, the Head of Machine Learning, Engineering & Operations at Volvo, who shares with us insights into what the global vehicle giant is doing to bring value to the operations chain across the company.

For Aukea, it has been a story of establishing best processes across the organisation. He said that one of his first priorities was to bring the various data science teams together to minimise the impact of siloing, and encourage the machine learning practitioners to adopt software engineering principles. This might not be immediately comfortable to them, but as Aukea said, ML experts are smart people working on complex problems, and facilitating an open-minded approach across the organisation is key to driving long-term success.

“You need to start simple,” he said. “Think about processes, ways of working, and the cultural aspects, and try to fit tooling and infrastructure along that kind of endeavour. You don’t need to choose the most extreme state-of-the-art tools.”

At one point, Aukea noted, things being pushed into production were becoming unmanageable, so he and his teams took a step back and reset. “We went back and decided to focus on first principles,” he said. “We evangelised these first principles to develop good ways of working, and then adopted the infrastructure and tooling towards building AI on top of that.”

Ultimately, Aukea said, quality comes from the processes, rather than the technology. There are, of course, technical challenges, but for anyone aiming to get true value out of machine learning, the focus needs to be on the processes.

Aukea then explains how, with those processes in place, he and his team have been able to start delivering deep and valuable insights. For more on how Aukea was able to structure Volvo for success with machine learning in operations, tune in to the podcast!

Enjoy the show!

Thank you to our sponsor, Talent Insights Group!

Join us in Sydney for Ops World: https://www.datafuturology.com/opsworld

Join our Slack Community: https://join.slack.com/t/datafuturologycircle/shared_invite/zt-z19cq4eq-ET6O49o2uySgvQWjM6a5ng

Read the full podcast summary here.

  continue reading

268 epizódok

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