#170 computer vision x agtech, precision spraying, herbicide

Each year, about 1 billion pounds of chemicals are sprayed on crops in the US alone – globally, that number is around 5.6 billion.

Our guest today is AgTechLogic, and they are solving this problem.

They do this by helping Farmers retrofit their existing machinery with precision sprayers that use computer vision to identify weeds and spray only on the weeds in a concentrated way that kills the weeds and won't overlap with the crops.

Today, nearly all farmers use broadcast spraying, or spraying everything. By implementing this tech, farmers can save a lot of money and produce healthier produce.

Let's get into it. 🌱🌎


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Topics:
**1:13 Introduction and Overview
**1:43 Reducing Chemical Overuse in Agriculture
**7:36 Validation and Early Discoveries
**11:11 Market Research and Initial Trials
**15:37 Concerns about Herbicide Usage
**20:34Case Studies and Cost Savings
**24:04 Objections and Early Adoption
**24:57 Reducing Water Usage and Regrowth
**26:09 Building Trust and Landing the First Pilot
**28:54 Entrepreneurship Later in Career
**32:07 Collecting New Data
**35:40 IP and Moat
**37:38 Funding Journey
**41:03 Responsible Growth
**42:55 Future Plans and Getting the Message Out
**45:48 Reaching Out and Educating Farmers
**47:54 Takeaways

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Links:
**Tom Gauthier | AgTechLogic
**Follow CleanTechies on LinkedIn
**@Silas & @Somil_Agg on X 

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a user’s guide to out-of-the-box computer vision models – wi

Today’s guest is Adam Burns, Vice President of Network and Edge and director of EdgeAI Development Tools at Intel. Adam returns to the podcast this week to talk about out-of-the-box solutions for computer vision in manufacturing, retail, healthcare, and beyond. Throughout the episode, Adam discusses relevant use cases related to Intel’s Geti Platform, what industry leaders should know before deploying out-of-the-box AI products, and the essential lessons in model development he’s gained from developing these tools. If you’ve enjoyed or benefited from some of the insights of this episode, consider leaving us a five-star review on Apple Podcasts, and let us know what you learned, found helpful, or liked most about this show!