Monday, March 12, 2018

Machine Learning for Plant Disease Diagnosis and Prediction

AI is being applied to everything these days -- including various fields of endeavor generally thought of as low-tech and backwards, such as agriculture.

In this vein, I gave a talk last week in Leshan, in Szechuan province (mainland China), on the application of AI to diagnosing crop diseases (from images of leaves) and predicting disease course, disease response to treatment, etc. In the talk, I reviewed a bit of existing literature and suggested some new twists based on discussions with farmers, crop doctors and agricultural researchers in Leshan. This was part of a collaboration between Chinese knowledge management firm KComber (and in particular their Yoonop service, ) and my bio-AI project Mozi AI Health and decentralized AI project SingularityNET. The talk I gave in Leshan wasn’t video-recorded, so after I got back home to Hong Kong I recorded a post-talk video going through the same concepts from the talk, using the same slides, with a few additions… Here it is!

(I was kind of half-asleep when recording the video as it was well past midnight but, that's when I found a free 30 min for this ... so it goes ... ) The slides from the talk, saved to PDF, are at: .... (This PDF version lacks the robot videos I showed in the talk in Leshan, but those videos are somewhat peripheral to the main topic anyway....)

In more futurist-evangelist talks I give, I often stress the importance of using AI for broad global benefit -- because if early-stage AGIs are actively engaged in helping people of all sorts in various practical ways, the odds are likely higher that as these AGIs get smarter and smarter, they will be richly imbued with positive human values and interested in keeping on helping people. Down-to-earth practical work on stuff like machine learning for diagnosing and predicting crop disease, is how this high level concept of "AI for broad global benefit" gets realized....