![]() Ultimately, Aukea said, quality comes from the processes, rather than the technology. “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.” “We went back and decided to focus on first principles,” he said. You don’t need to choose the most extreme state-of-the-art tools.”Īt one point, Aukea noted, things being pushed into production were becoming unmanageable, so he and his teams took a step back and reset. “Think about processes, ways of working, and the cultural aspects, and try to fit tooling and infrastructure along that kind of endeavour. 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. 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 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.įor Aukea, it has been a story of establishing best processes across the organisation. 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.
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