Is Agtech Entering A GenAI Era? Conversations From World Agri-Tech

Headstorm: https://headstorm.com/

AGPILOT: https://headstorm.com/agpilot/

Bayer Announcement: https://www.bayer.com/media/en-us/bayer-pilots-unique-generative-ai-tool-for-agriculture/

Bayer AgPowered Services: https://www.bayer.com/media/en-us/bayer-collaboration-with-microsoft-connects-farm-data-to-address-lack-of-data-interoperability-in-agriculture/

Microsoft World Agri-Tech Reflections: https://www.microsoft.com/en-us/industry/blog/sustainability/2024/04/02/world-agri-tech-2024-pioneering-agriculture-resilience-with-ai/

Claudia Roessler World Agri-Tech Reflections on LinkedIn: https://www.linkedin.com/posts/claudia-roessler-microsoft_world-agri-tech-2024-pioneering-agriculture-activity-7180973495110057984-Bay4?utm_source=share&utm_medium=member_desktop

FoA 111: Artificial Intelligence and Machine Learning with Jeremy Williams https://futureofagriculture.com/episode/future-of-agriculture-111-artificial-intelligence-and-machine-learning-with-jeremy-williams-of-monsanto 

FoA 361: Meet Norm, FBN's AI-Powered Ag Advisor with Kit Barron and Charles Baron https://futureofagriculture.com/episode/foa-361-meet-norm-fbns-ai-powered-ag-advisor-with-kit-barron-and-charles-baron

FoA 266:Microsoft Wants to Democratize Data-Driven Agriculture https://futureofagriculture.com/episode/foa-266-microsoft-wants-to-democratize-data-driven-agriculture 

FoA 345: Alphabet's Moonshot to Scale Sustainable Agriculture via Machine Learning with Dr. Elliott Grant of Mineral https://futureofagriculture.com/episode/foa-345-alphabets-moonshot-to-scale-sustainable-agriculture-via-machine-learning-with-elliott-grant-of-mineral 

“Yield Maps Killed Agtech Software, Can AI Fix It?” https://tenacious.ventures/insights/yield-maps-killed-agtech-software-can-ai-fix-it 

Bailey Stockdale LLM Benchmarking: https://www.linkedin.com/posts/gbstockdale_anthropic-claude-opus-is-the-new-leader-in-activity-7173365123196112896-SkEt?utm_source=share&utm_medium=member_desktop 

A couple weeks ago, I had the chance to attend World Agri-Tech in San Francisco. I spent the vast majority of my time there in one-on-one conversations, some recorded and some not, about the future of agriculture. It was really an embarrassment of riches to have so many interesting people in one place who work in agtech or agribusiness. ReThink Events was kind enough to provide me with a media pass for the event, and our quarterly presenting sponsor Headstorm helped to coordinate some key interviews that will be a part of today’s episode and a few other episodes that you’ll hear later this quarter. Take note that all of these recordings happened live at an event with thousands of other people, so there will be occasional background noise, but overall I was pleased with the quality of audio I was able to get considering the circumstances. 

There’s a temptation at this event in particular and others like it to ask what’s new and what’s next? That begs the question of “does there always need to be something new to talk about?” because we probably have a lot of “old” things to still be working on and working through. I actually encountered what I would consider a healthy mix of innovations that aren’t new but still requiring a lot of work to make an impact. This would include a lot of topics that won’t shock you if you’ve been listening to this show for any amount of time: data, automation, biologicals, regenerative, climate change, venture capital, etc. 

But if there was one topic that was new - or at least new-ish - it was the talk of the potential of generative AI to drive positive change in agtech. It’s clear several companies have been working on this or at least thinking a lot about it. And if you want a quick and oversimplified explanation of generative AI, think of it as a tool that can take raw data and create content in the way of text, like Chat-GPT, images like Midjourney, audio, like you heard last year in episode 361 when I used Descript to generate the intro to the episode in my voice from text generated from FBN’s Norm. 

All of those are examples of generative AI using more mainstream applications, but all they require is a prompt by me typing or speaking what I want the tool to make for me. This what makes it generative - the tool is making the content - not me.  But what does this really mean for for the future of agriculture? Are these just fun and interesting tools, or do they represent a massive step forward in technological capabilities? 

That was the tone of a lot of the GenAI conversations I was a part of. One of the more intriguing panels at World Agri-Tech, at least in my opinion, was titled “The GenAI Era: Navigating Opportunities and Challenges in Agtech”. It actually included three former guests of this podcast: Ranveer Chandra at Microsoft (266), Jeremy Williams at Bayer Crop Science (111), and Elliott Grant at Mineral (345). Also sitting on the panel was Elizabeth Fastiggi at AWS and Feroz Shiekh at Syngenta. 

If I had to summarize, every member of the panel was eager to say that generative AI represents a dramatic shift in the capabilities we have to actually make data valuable. Or to use the cliche term “to turn data to insights”. 

But what exactly is generative AI? And what is so dramatically different about it? Is this just filling the need to have another “big new thing” that will potentially not live up to the excitement like agtech has developed a reputation for? Those are the questions I wanted to ask at World Agri-Tech, and will seek to help answer for you in this episode.