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Geoffrey Cann에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Geoffrey Cann 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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Making Legacy Engineering Data Sweat

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Manage episode 384121188 series 3488265
Geoffrey Cann에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Geoffrey Cann 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.

A pioneering application of artificial intelligence at Woodside Energy is finally ready for wider deployment in oil and gas.

I learned about this use case back in 2016, at APPEA’s annual conference in Perth, where Woodside’s data science team presented their work. Surprisingly, few companies bothered to replicate this innovation, even though it was both proven and easy to execute.

Many oil and gas facilities have been in production for decades, and want to be in production for decades more.

Not only do these assets handily outlast their designers, but they’re now outlasting their maintenance engineering staff, operations, logistics managers, and key suppliers. In short, the complete original workforce.

But the oil and gas industry has long relied on the memory of its people to recall critical information about its assets, information beyond the kinds of data easily found in modern systems. Answers to questions like “why did we design it this way”, and “have we encountered this problem before” depend on the memories of workers.

Oil and gas companies cannot reliably use ChatGPT, as it was trained on the whole of the internet, and is a mix of fact and fiction, science and religion, truth and lies, and faulty logic. However, training a private version of ChatGPT unlocks a huge use case that was proven many years ago.

  continue reading

104 에피소드

Artwork
icon공유
 
Manage episode 384121188 series 3488265
Geoffrey Cann에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Geoffrey Cann 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.

A pioneering application of artificial intelligence at Woodside Energy is finally ready for wider deployment in oil and gas.

I learned about this use case back in 2016, at APPEA’s annual conference in Perth, where Woodside’s data science team presented their work. Surprisingly, few companies bothered to replicate this innovation, even though it was both proven and easy to execute.

Many oil and gas facilities have been in production for decades, and want to be in production for decades more.

Not only do these assets handily outlast their designers, but they’re now outlasting their maintenance engineering staff, operations, logistics managers, and key suppliers. In short, the complete original workforce.

But the oil and gas industry has long relied on the memory of its people to recall critical information about its assets, information beyond the kinds of data easily found in modern systems. Answers to questions like “why did we design it this way”, and “have we encountered this problem before” depend on the memories of workers.

Oil and gas companies cannot reliably use ChatGPT, as it was trained on the whole of the internet, and is a mix of fact and fiction, science and religion, truth and lies, and faulty logic. However, training a private version of ChatGPT unlocks a huge use case that was proven many years ago.

  continue reading

104 에피소드

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