Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!): ISRR 2019 – October 6-10, 2019 – Hanoi, Vietnam Ro-Man 2019 – October 14-18, 2019 – New Delhi, India Humanoids 2019 – October 15-17, 2019 – Toronto, Canada ARSO 2019 – October 31-1, 2019 – Beijing, China ROSCon 2019 – October 31-1, 2019 – Macau IROS 2019 – November 4-8, 2019 – Macau Let us know if you have suggestions for next week, and enjoy today’s videos.
What’s the world’s hardest machine learning problem? Autonomous vehicles? Robots that can walk? Cancer detection? Nope, says Julian Sanchez. It’s agriculture. Sanchez might be a little biased. He is the director of precision agriculture for John Deere, and is in charge of adding intelligence to traditional farm vehicles. But he does have a little perspective, having spent time working on software for both medical devices and air traffic control systems. I met with Sanchez and Alexey Rostapshov, head of digital innovation at John Deere Labs, at the organization’s San Francisco offices last month. Labs launched in 2017 to take advantage of the area’s tech expertise, both to apply machine learning to in-house agricultural problems and to work with partners to build technologies that play nicely with Deere’s big green machines. Deere’s neighbors in San Francisco’s tech-heavy South of Market are LinkedIn, Salesforce, and Planet Labs, which puts it in a Continue reading Want a Really Hard Machine Learning Problem? Try Agriculture, Says John Deere Labs