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محتوای ارائه شده توسط EETech Media and All About Circuits. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط EETech Media and All About Circuits یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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Getting Out of the Weeds with John Deere’s Revolutionary AI Technology

55:43
 
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Manage episode 365917925 series 2661101
محتوای ارائه شده توسط EETech Media and All About Circuits. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط EETech Media and All About Circuits یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Imagine 1500 laptops strapped to a 120 foot (36 m) wide sprayer being pulled behind a tractor. That gives you a rough understanding of the compute power inside the John Deere See & SprayTM that targets herbicide to the weeds, not the crops. These might be “the smartest agricultural machines in the world,” says Chris Padwick, Director of Computer Vision and Machine Learning at Blue River Technology, a wholly owned subsidiary of John Deere.

Padwick was not looking to return to his agricultural roots, but in a “shields down” moment” he was approached by a startup, Blue River Technology. He recalls being “completely blown away” by what they were doing in computer vision.

After initially developing a product for lettuce thinning, Blue River pivoted to the problem of row crop weeding. In the US alone, the agricultural industry uses over 20 million gallons of herbicide annually, almost all of it through broadcast spreading across the entire field. Blue River set to work on changing the paradigm to only spray the weeds. According to Padwick, this “dot matrix printer for weeds” has the potential to “save 15 million gallons of herbicide” and “about a billion dollars.”

In this episode of the Moore’s Lobby podcast, Padwick takes us behind the scenes to discuss the challenges of data collection in the fields, image classification, the compute technology that drives these real-time systems, and much more. On this business side, he reflects on the 2017 acquisition by John Deere and how important that was in their development of products at scale that can operate in rugged environments for two decades.

“I feel like we're going to look back on farming in five or ten years and we're just going to be amazed…Precision spot spraying is going to be the way that people treat their crops going forward because it's going to allow them to save so much more chemical. And the sustainability in the environment is kind of unparalleled. So I really feel we're kind of at that inflection point for agriculture.”

So, listen in on this fun interview as Padwick describes:

- His graduate research into Big Bang cosmology and background radiation

- Why he left engineering as an undergrad—seriously, universities we have to fix this outdated solution to engineering education!

- Blue River’s global operations to collect crop and weed images to drive continuous improvement

  continue reading

95 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 365917925 series 2661101
محتوای ارائه شده توسط EETech Media and All About Circuits. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط EETech Media and All About Circuits یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Imagine 1500 laptops strapped to a 120 foot (36 m) wide sprayer being pulled behind a tractor. That gives you a rough understanding of the compute power inside the John Deere See & SprayTM that targets herbicide to the weeds, not the crops. These might be “the smartest agricultural machines in the world,” says Chris Padwick, Director of Computer Vision and Machine Learning at Blue River Technology, a wholly owned subsidiary of John Deere.

Padwick was not looking to return to his agricultural roots, but in a “shields down” moment” he was approached by a startup, Blue River Technology. He recalls being “completely blown away” by what they were doing in computer vision.

After initially developing a product for lettuce thinning, Blue River pivoted to the problem of row crop weeding. In the US alone, the agricultural industry uses over 20 million gallons of herbicide annually, almost all of it through broadcast spreading across the entire field. Blue River set to work on changing the paradigm to only spray the weeds. According to Padwick, this “dot matrix printer for weeds” has the potential to “save 15 million gallons of herbicide” and “about a billion dollars.”

In this episode of the Moore’s Lobby podcast, Padwick takes us behind the scenes to discuss the challenges of data collection in the fields, image classification, the compute technology that drives these real-time systems, and much more. On this business side, he reflects on the 2017 acquisition by John Deere and how important that was in their development of products at scale that can operate in rugged environments for two decades.

“I feel like we're going to look back on farming in five or ten years and we're just going to be amazed…Precision spot spraying is going to be the way that people treat their crops going forward because it's going to allow them to save so much more chemical. And the sustainability in the environment is kind of unparalleled. So I really feel we're kind of at that inflection point for agriculture.”

So, listen in on this fun interview as Padwick describes:

- His graduate research into Big Bang cosmology and background radiation

- Why he left engineering as an undergrad—seriously, universities we have to fix this outdated solution to engineering education!

- Blue River’s global operations to collect crop and weed images to drive continuous improvement

  continue reading

95 قسمت

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