John Deere’s Doug Sauder | Machine Meets World

“Historically, the most important sensor has been the farmer’s eyes themselves as they observe the physical environment,” says Doug Sauder, Director, Digital Product Management & Analytics at John Deere.

“And what we’re doing with camera technology is really augmenting those human eyes with cameras. We’re augmenting and supporting the human brain with computers, and then we’re augmenting the human hand with robotics. And so those things really come together to give farmers additional tools.”

Speaking on Infinia ML’s Machine Meets World, Sauder says “this is no different than the type of innovation that we’ve been doing for 180 years. It’s just different than the steel plow. Now we’re talking about cutting edge technologies like AI, but it’s all about helping farmers be more productive, more profitable, more sustainable.”

More interview highlights:

The Demand for Agricultural Automation

“Sometimes the conversation about automation gets into, oh, are jobs going to be replaced by robots, those type of conversations. In farming . . . there’s a real labor shortage globally, a shortage in skilled labor. Farmers, our customers, are asking us for more automation. They want the ability for a lower skilled operator to be able to operate a piece of equipment that used to require someone with many years of training.”

“And in addition to that, we’re really talking about automation doing for a farmer what they just can’t do without the technology. And so maybe to, I like to say that we’re helping farmers be better micromanagers. Micromanaging is also a bad word in business, but in farming, it’s a great word. . . . “

“Picture that your job as a farmer is to care for millions of [personal] gardens in a given season. You just can’t do that without technology that can automate and give the precise application of nutrients, the precise placement of seeds.”

Doing the Data Dirty Work

“Your AI strategy has to run on data. It’s easy to get focused on the exciting algorithm that’s going to be developed, the predictive model that’s going to be developed, but it’s the unglamorous work of collecting data, of assessing data quality, of building data pipelines and robust structures that allow for data scientists to get at that data.”

“Often you’ll find that data scientists will spend 70% of their time just wrangling the data to get it into a useful form. And so those investments in that foundational data acquisition and transformation pipelines, that’s really where the initial focus of a company should start. Because if you don’t have that data, you’re going to really struggle to create value on top of it.”

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Machine Meets World is Infinia ML’s weekly interview show with AI leaders.

You can watch on this page, listen as a podcast (AppleGoogleSpotifyStitcher), and email the show at mmw@infiniaml.com.

Full Interview and Transcript

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Cognizant’s Bret Greenstein on Machine Meets World

Bret Greenstein, SVP and Global Head of AI & Analytics at Cognizant, talks artificial intelligence with Infinia ML’s James Kotecki.

Machine Meets World streams live on YouTube weekly. It’s also available in audio form on Apple PodcastsGoogle PodcastsSpotify, and Stitcher.

Recorded August 11th, 2020.

Killer Quote

“Companies that delegate absolute authority for data science and AI . . . to a technologist [are] really missing the point of the responsibility of a business leader to ensure that systems behave without bias and that they reflect the values and the goals of your company.” (14:29)

More Highlights

“Most AI projects are actually data projects.” (5:14)

The value of AI that can quickly adapt as the rules change. (23:16)

AGI is an interesting thought experiment – and a confusing distraction. (25:21)

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Full Transcript

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Deepgram CEO Scott Stephenson on Machine Meets World

Scott Stephenson, CEO of the speech recognition company Deepgram, talks artificial intelligence with Infinia ML’s James Kotecki.

Machine Meets World streams live on YouTube weekly. It’s also available in audio form on Apple PodcastsGoogle PodcastsSpotify, and Stitcher.

Recorded July 28th, 2020.

Killer Quote

“You can have a human listen to a conversation, you can have them infer what was happening, all of that… In the future, you’ll be able to have the equivalent of a much cheaper human do it, which would be the machine. And the cost of that will drastically reduce, and that will mean that we’ll have to come up with new laws and rules and ways of operating in society to deal with that.” [16:01]

More Highlights

How working in a “James Bond lair” led to the development of Deepgram. [4:14]

How doing particle physics is like doing deep learning for speech. [6:10]

How always-on recording can change human behavior. [19:58]

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Full Transcript

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Pryon CEO Igor Jablokov on Machine Meets World

Pryon CEO Igor Jablokov joins Infinia ML’s James Kotecki on Machine Meets World, the interview show about artificial intelligence.

The show streams live on YouTube weekly. It’s also available in audio form on Apple PodcastsGoogle PodcastsSpotify, and Stitcher.

Recorded July 13th, 2020.

“Everybody’s going to have access to an AI that can help them do their jobs better, and we hope that that’s going to reduce the delta between the haves and the have nots.” [23:32]

More Highlights

Humans can’t grasp AI’s full potential [6:34]

Sci-fi predictions vs. business forecasting [9:54]

Accessible augmented intelligence through natural language [25:59]

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Full Transcript

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Forrester’s J. P. Gownder on Machine Meets World

J.P. Gownder, VP, Principal Analyst at Forrester, talks artificial intelligence with James Kotecki, Director of Marketing at Infinia ML.

Machine Meets World streams live on YouTube weekly. It’s also available in audio form on Apple PodcastsGoogle PodcastsSpotify, and Stitcher.

Key Quote

“. . . for AI, we need to have more comprehensive governance that includes everything from ethics to explainability to accountability to bringing together all of the operational side of a model. Is it working properly? Is it being retrained continuously? Is it getting better? Does it need to be retired? But also, wedding that to some of these broader customer-relevant and employee-relevant issues.” [15:17]

“ . . . what AI is trying to do using probability is creating new conundrums that the business isn’t used to dealing with. And people aren’t very good at probabilistic thinking in the first place. So I think unfortunately, it’s one of these cases where you’ve got to bring everyone together to do this internally. My colleague Michele Goetz and I did a whole bunch of interviews around this. And we found that even some really large, sophisticated technology companies haven’t mastered every dimension of AI governance.” [16:09]

Other Highlights

A human-centered view of artificial intelligence [9:21]

The coming decade of job loss, job gains, and job transformation [24:49]

Gownder’s science fiction recommendations, which tackle inequality, climate change, and AI [27:24]

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Cognizant’s Ben Pring on Machine Meets World

Ben Pring, the Director of Cognizant’s Center for the Future of Work, recently joined Infinia ML’s James Kotecki on Machine Meets World, the interview show about artificial intelligence.

The video show streams live on YouTube weekly. It’s also available in audio form on Apple PodcastsGoogle PodcastsSpotify, and Stitcher.

Recorded June 9, 2020.

Key Quote

“If we don’t want to be seen as the cigarette executives of 2040 or 2050, I think it behooves us, as people who love technology, who are in positions of some responsibility or a lot of responsibility, to use technology in a way that we won’t be the villains in the movies that are made about what went on now in another generation or two.”

“. . . the people in the plastics industry are not particularly held in high esteem now, because we can see the damage that has been done. The waste in the oceans, that those people weren’t particularly interested in the sort of damage that they unleashed, if you like. And that’s clearly the discussion we’re beginning to have around some aspects of technology at the moment.” [22:42]

Other Episode Highlights

The Machine Learning Demo that Scared Him [11:51]

The Modern Relevance of Orwell’s 1984 [18:32] — Ben says the book was published on June 9th, but it was actually published June 8th. We’re inclined to let this slide.

Regulation: Adding Traffic Signs to the Information Superhighway [27:35]

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Full Transcript

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