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Opening Thoughts:
The one thing that is always interesting when I talk with Aaron is that he has a weird knack at getting into the sub-details of how technology affects Ag. He has a very analytical thought process through the bits and pieces to it all. It’s always good to hear those types of ideas and thought processes as many in this world of AgTech get caught too much on the big idea at times.
As we dove into a treasure trove of topics some of the most interesting parts to me was where AI actually can benefit us now and what that likely look likes. Beyond that, you also rarely hear many talk about small holder farms and how technology can push them way farther and faster that what we currently think of as needed in the modern agricultural world.
If we take a step back and really look at who can benefit from technology the most in Ag it’s probably people most don’t think of and unfortunately don’t care about. It’s a problem we all have and it’s one that Aaron and his team is trying to break through. I find that rather intriguing and with that said you should definitely take a listen to open your own mind to different ideas in Ag.
Here is the Summary:
In this conversation, I interview Aaron Hutchinson current Founder and CEO of Lighthouse.Ag and former Founder and CEO of CropTrak. We talk about precision agriculture and AgTech and the decades of history Aaron has experienced within it.
We discuss the challenges of implementing blockchain technology in agriculture, the need for data sharing and collaboration, and the importance of developing affordable and accessible technology for small-scale farmers. We also touch on the concentration of ag tech solutions on large-scale farms and the potential for innovation in serving the majority of farmers who operate on smaller scales.
The conversation explores the need for simpler and more affordable agricultural technology that is accessible to all farmers, including smallholders. The speakers discuss the challenges of adopting new technologies and the importance of backward compatibility. We also touch on the potential impact of AI and automation on jobs in agriculture and other industries.
The conversation highlights the need for consistent and high-frequency data to train AI models effectively. We conclude by discussing the potential of multimodal interfaces in agriculture, where farmers can have conversations with AI assistants to gather information and make decisions.
The conversation explores the potential of technology in agriculture, focusing on the integration of AI and the need for more integrated solutions. It discusses the importance of multi-threaded AI assistants and the future possibility of AIs communicating with each other.
The conversation also touches on the challenges of onboarding new software and the need for smaller, more modular changes. It highlights the slow adoption rate in agriculture due to financial and seasonal risks. The conversation concludes with a discussion on the importance of standards and the potential for a circular economy in agriculture.
Takeaways
Implementing blockchain technology in agriculture has challenges related to data storage, encryption, and the involvement of third parties.
There is a need for data sharing and collaboration in agriculture to improve decision-making and optimize farming practices.
Affordable and accessible technology is crucial for small-scale farmers to benefit from advanced agricultural practices.
The majority of farmers operate on smaller scales and may not have access to or be interested in cutting-edge ag tech solutions.
Investment in technology for small-scale farmers can have a significant impact on global food production and sustainability. There is a need for simpler and more affordable agricultural technology that is accessible to all farmers, including smallholders.
Backward compatibility is important when adopting new technologies to ensure a smooth transition and compatibility with existing systems.
AI and automation have the potential to impact jobs in agriculture and other industries, but they can also create new opportunities and improve efficiency.
Consistent and high-frequency data is crucial for training AI models effectively and obtaining accurate insights.
Multimodal interfaces, where farmers can have conversations with AI assistants, hold potential for improving communication and decision-making in agriculture. AI assistants have the potential to become higher-order assistants that can provide real-time information and reminders.
The integration of AI and the ability for AIs to communicate with each other will revolutionize the agricultural industry.
Smaller, more modular changes in software and technology adoption are necessary for success.
Standards play a crucial role in the integration and compatibility of different technologies.
The concept of a circular economy in agriculture, where inputs and outputs are recycled and reused, has the potential to create more sustainable and efficient farming practices.
Sound Bites
"The next unicorn is probably not going to be the guy that sells it to the cutting edge farmers. Probably going to be the guy who figures out something to sell to the masses."
"How do you get something into these people's hands that allows them to have that benefit from all the knowledge of the rest of everything that's kind of going on in the world?"
"We live in a world where everybody's pushing their own direction for their own cutting edge. And we don't have any master and generators kind of pushing for these simpler products."
"AI wants millions of points. It wants the diversity of it."
"AI assistants become higher-order assistants for real-time information and reminders."
"AIs calling AIs to do thinking for them is not far off."
"Integrated solutions are necessary for successful adoption and acceleration."
Chapters
00:00 Introduction and Background
06:23 Challenges of Implementing Blockchain in Agriculture
25:12 Affordable and Accessible Technology for Small-Scale Farmers
30:52 The Concentration of Ag Tech Solutions on Large-Scale Farms
34:59 Investing in Technology for Small-Scale Farmers
38:42 The Importance of Backward Compatibility in Technology Adoption
43:39 The Impact of AI and Automation on Jobs in Agriculture
53:05 The Role of Data in Training AI Models
01:02:14 The Potential of Multimodal Interfaces in Agriculture
01:04:14 The Future of AI Assistants
01:05:38 The Integration of AI and AIs Communicating with Each Other
01:07:17 Challenges of Onboarding New Software and the Need for Modular Changes
01:08:54 The Importance of Standards in Technology Integration
01:14:21 Exploring the Potential of a Circular Economy in Agriculture
Watch and Listen:
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Closing Thoughts:
I’ll highlight again the need to rethink how tech affects Ag as we talked about in this episode. Many parts of the world are progressing faster in a shorter time frame than many in the modern world as they can leap frog the initial learning phases of tech itself and just take action with it as it has become normal.
While much of North America struggles with certain AgTech adoption, you are starting to see other parts of the world take it on with full steam as they just want to catch up and biases of the past do not affect them as much as either their isn’t a past to latch on to, or the past is a reflection of poor mistakes that do not want to be repeated.
We can talk all day long about the issues with money and politics regarding how tech is integrated in Ag and here in the states we do a great job of that. Maybe we need to get off our damn high horse and look out a little and see where tech can actually help those that need it the most.
Big tractors are not going to help everyone and while it’s all cool and fun to see that, it does little for the majority and especially for the minor players in Ag. We really need to find better ways to help those playing on the smaller fields, both figuratively and literally.
Some food for thoughts….
See you next time…
Thanks again everyone for watching, listening, and reading!