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Felipe Flores에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Felipe Flores 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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#212 Structuring Volvo For Operational Success with Leonard Aukea, Head of Machine Learning, Engineering & Operations at Volvo

45:41
 
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Manage episode 345281213 series 2310475
Felipe Flores에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Felipe Flores 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.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 에피소드

Artwork
icon공유
 
Manage episode 345281213 series 2310475
Felipe Flores에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Felipe Flores 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.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 에피소드

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