705: ML-Powered Precision Agriculture — with Feroz Sheikh, Jeremy Groeteke, and Thomas Jung

#PrecisionAgriculture #MLInAgriculture #DataScienceInAgriculture @JonKrohnLearns engages in a riveting conversation with Feroz Sheikh (Chief Information Officer and Chief Digital Officer at Syngenta Group, and former Global Head of Engineering and Data Science), Jeremy Groeteke (Head of Computational Agronomy, leading Syngenta Group's digital agronomy and data science initiatives), and Thomas Jung (Syngenta’s Head of R&D for IT, spearheading the digitization of science for plant and planetary protection). Together, they unravel the transformative role of data science in agriculture. Delve into computational agronomy's potential to reinvent age-old farming methodologies and address worldwide issues like food adequacy and climate variation. With keen insights on precision farming, satellite imagery, and the promising horizon of automated farming, this episode illuminates the dynamic synergy between tech and Mother Nature. This episode is brought to you by AWS Inferentia (https://go.aws/3zWS0au) and by Modelbit (https://modelbit.com), for deploying models in seconds. Interested in sponsoring a SuperDataScience Podcast episode? Visit https://jonkrohn.com/podcast for sponsorship information. In this episode you will learn: • [00:00:00] Introduction • [00:07:13] What is precision agriculture? • [00:09:58] What is computational agronomy? • [00:19:06] How Syngenta helps growers optimize yields • [00:31:26] How to bridge the gap between R&D and out in the real world • [00:35:20] What is generative chemistry? • [00:39:23] How generative chemistry accelerates the discovery of new compounds • [00:53:51] How you could make a big social impact in agriculture with data science • [00:57:55] How to go about designing ML models for agriculture Additional materials: https://www.superdatascience.com/705