Speaker 1: 0:00

Welcome to Just Say hey.

Speaker 1: 0:01

The podcast podcast where we talk about the things that matter to small farms, and today is no different. You know, if you could have told your great-great-grandparents that there would come a time in life where you would have a box that you'd carry with you everywhere you went, that you'd carry with you everywhere you went, that not only allowed you to communicate with any place in the world, but also contained the entire database of human knowledge, they would have looked at you like you were insane. They would have thought this would have been more revolutionary than the fact that we fly on airplanes at faster than the speed of sound or that we have landed on the moon. And I think we're in a time of another technological revolution that, as small farmers, we really need to be paying attention to. And, whether we like it or not, ai is here to stay. It's not going anywhere, but it's not just for big tech companies anymore. We need, as small farmers, we need every advantage we can get to make our businesses profitable, to keep our farms running, to be able to make good decisions, and I think we are at the point, finally, that AI is giving us some tools that are actually beneficial for small farmers.

Speaker 1: 1:45

You hear a lot about AI for big farmers. I want to talk about what's real, what's hype, where the dangers are, what are the things that we need to pay attention to as we start into this new age of AI. And then also right after the intro here I've got a really special guest that'll be kind of cool to talk to and ask some questions. Right after the intro here I've got a really special guest that'll be kind of cool to talk to and ask some questions. But before we get there, if you like this podcast and you think I'm giving you some good information, let me know what I can help you out, with, what topics you'd like me to cover, and also share this with your friends and family. It really helps out. I appreciate it. Welcome to Just Say hey. The podcast where we talk about what matters to small farms, whether it's business, marketing, agronomy, equipment, livestock. If it matters to small farms, we'll probably talk about it here. So let's get into it. All right, hey, bot welcome to the show.

Speaker 2: 2:36

Thanks, john, it's great to be here. What's our topic for today?

Speaker 1: 2:47

So we're talking about AI and small farms and I was going to ask if you could tell us in your mind what is a good definition of AI?

Speaker 2: 2:50

Sure, AI, or artificial intelligence, is essentially technology that allows machines to mimic human intelligence. It can learn from data, recognize patterns and even make decisions. In small farms, AI can help with tasks like monitoring crops, predicting yields and optimizing resource use.

Speaker 1: 3:07

It sort of sounds futuristic, almost like a sci-fi movie, but what are some simple, real-world ways that AI is already helping small farms?

Speaker 2: 3:16

Absolutely, John. Ai is being used in small farms in some really practical ways. For example, AI-powered sensors can monitor soil health and moisture levels, which helps farmers water their crops more efficiently. Drones equipped with AI can survey fields to check on crop health and detect pests early. There are also AI-driven tools that can predict the best times for planting and harvesting based on weather patterns and soil conditions. It's all about making farming smarter and more sustainable.

Speaker 1: 3:49

I know a lot of farmers rely on their gut and instinct and experience to make decisions, but can AI really compete with that? That's a great point.

Speaker 2: 3:53

AI isn't about replacing a farmer's intuition and experience. It's more like a tool to complement and enhance them. Farmers still make the final decisions, but AI can provide data-driven insights that might not be immediately obvious. It's about blending technology with traditional knowledge to make farming even more effective.

Speaker 1: 4:12

So how does it help with things like predicting weather or knowing when to cut my hay?

Speaker 2: 4:16

AI can analyze vast amounts of weather data to predict trends more accurately than traditional methods. It can tell you the optimal time to cut your hay by considering factors like humidity, temperature and upcoming weather conditions. This helps ensure you get the best quality hay and avoid unexpected weather issues.

Speaker 1: 4:35

So what's one AI tool that a small farm could use right now with no learning curve?

Speaker 2: 4:41

A simple tool would be an AI-powered weather forecasting app. Many of these apps are user-friendly and offer precise, tailored weather predictions for your farm, helping you make informed decisions without a steep learning curve.

Speaker 1: 4:54

So what is the biggest myth or misunderstanding about AI in farming right now?

Speaker 2: 5:00

The biggest myth is that AI is too complicated or only for large-scale operations. In reality, many AI tools are designed to be accessible and beneficial even for small farms.

Speaker 1: 5:14

It's about enhancing existing practices, not replacing them. So farming's changed a lot over the last 50 years. If AI keeps advancing, what's one way you think small farms might look different in, say, 10 years from now?

Speaker 2: 5:23

In 10 years, small farms might be more tech-integrated. Using AI for precision agriculture, we could see widespread use of autonomous machinery, drones for crop monitoring and advanced data analytics to optimize every aspect of farming. This could mean more efficient resource use, higher yields and even greater sustainability.

Speaker 1: 5:43

Can you give me a limerick about a hay farmer in the rain?

Speaker 2: 5:47

Sure, here's a quick limerick. There once was a farmer named Ray whose hay fields were soaked every May. With AI's great aid, he knew when to cut hay, and now he makes bales come what may.

Speaker 1: 5:59

All right, thank you. Have a great day you too, john, take care.

Speaker 1: 6:03

Well, in case you didn't realize what was going on there, I had the questions that I wanted to ask, but there was nothing that had been pre-programmed. It was just a conversation and the AI was actually hearing what I said, figuring out what words I was using, what question I was asking, and then responding, thinking like a person. It just blows me away how good it is. I remember, oh, back in the mid 1990s, I was involved in a tech startup that was doing what we call concatenated speech, and it was the first beginnings of what became a very famous AI program and and it's amazing to me how far it has come in not only the sound of the voice and that's not one of the better voices that can be used it's just what was there. But it is amazing that it can understand now and figure out what you're saying in just simple English. To really kind of understand, there are basically three main types of AI, because there's not at this point, there's not one AI to rule them all. It's sort of there are. You use artificial intelligence to perform tasks or accomplish things. So what we call core AI is like what we just talked to. It was a large language model AI, but you also have generative AI, which is you may have seen on Canva or some of these other programs. You can have it make a picture for you. You write in a text prompt and it makes a picture. So you know, those are probably the most popular. But where I think for farming, where it really gets interesting is in functional AI, where AI is trained to do predictive analysis, have computer vision or autonomy, where it's learning and understanding its environment and performing a task based on feedback from the environment. You know, and predictive is things like weather, livestock, you know things like that. Where computer vision is.

Speaker 1: 8:23

I use computer vision right now and it's a simple app.

Speaker 1: 8:25

I think it's called picture this.

Speaker 1: 8:26

I'll be standing out in the field and I'll see a weed and I don't know, I may not know what that plant is, and I just walk over there, this thing, I open it up, I load it on my take a picture of it with my camera on my phone and this program goes in and identifies it for me so that when I call my spray guys I say, hey, I've got a field full of this. What can we do to kill mare's tail or lamb's tail or amaranth or spiny amaranth or you know any one of these weeds that we see. Being a first-generation farmer, I didn't grow up looking at these weeds, so I have to learn, and if there's not somebody there to ask, I literally take a picture of it and this program will tell me what plant is in my field, and so I know how to deal with it. Is this a harmful plant that I need to really get rid of this, or is this just a, you know, a late summer weed that will die out and has no health effects on the?

Speaker 2: 9:19

animals. I'm feeding.

Speaker 1: 9:21

So I think you know we're using this more and more and I'll just tell you. There's a last type of AI, just called learning-based, where it's reinforced learning. I think the Tesla cars use this. Where it drives, it drives until it makes a mistake. Where it, when it makes a mistake, it learns and doesn't do it again. So it's a reinforced learning model. There is so many things going on in AI and it's going to start moving even faster. Like computer programming, most programmers are using AI right now to generate the code instead of spending a thousand hours. I saw a guy the other day that created a complete iPhone app in 30 minutes.

Speaker 1: 10:03

In agriculture, you're seeing the bigger farms. This isn't quite the small farms yet. It's not out of the realm for small farms, but for the most part it's the bigger farms and that's crop and soil monitoring, where you have sensors or satellite data and AI is looking at this satellite data or these sensors and giving you recommendations or timings or things like that. Where I think we're using AI in small farms is weather. Now we use a service called BAM Weather and they're fantastic and I'm sure they're using this in some of their predictive models, but they still are human beings going in and looking at this and they are fantastic. You also see it in livestock health management. There's a company called Breeder. I think is, yeah, breeder, b-r-e-e-d-r, I think is the name of the company, and they do in beef herd management. You put a sensor on your cow and it does temperature, pulse, movement. So it understands, it learns. This program learns how that cow moves. It learns their temperatures. There you know the how their temperature fluctuate, fluctuates during the day, fluctuates during the day. And then you know when something comes out of the normal. That cow gets a temperature or it stops moving or any one of a number of factors. It says hey, sends a message to the farm, said hey, you need to go check number 387B, she's not moving, and so you know to go right out there and do. It works 24 hours a day.

Speaker 1: 11:35

I think the precision side we talked about it in, you know, kind of early on the precision side is really interesting. I mean the whole concept of the see-in spray is just amazing. I've seen a demo video of the sea and spray and the speed that that machine is moving over the field and making the decisions to use or not use chemical based on the identification of a plant. That's unbelievable to me. And then, finally, for small farms. I think there's a lot of applications out there that use artificial intelligence that can help me. I use it every day. But it can use artificial intelligence for things like in your business, whether it's financial, whether it's marketing, whether it's. You know, there are things that you can use, even if it's just to brainstorm ideas. But companies that you may use, like QuickBooks or, you know, facebook, they're using artificial intelligence to help drive better results for business, and so it's something we should keep an eye on.

Speaker 1: 12:45

And I'll say this because, you know, I know I've kind of gone through a lot of this pretty quick, but before we get into a couple other things here, I'm a big fan of history. I am, I love history. I love reading books from the early part of American history, whether it's the pre-revolutionary war or the settling of the Old West. I've always been a fan of that. And there's an author that I, I, everybody knows who he is louis lamore um. Have you ever seen john wayne's hondo? That's a louis lamore story he's written. I mean, I've read every one of his books, uh, but one of my. You know, some of my favorite books are books like um, the lonesome gods or the comstock Load or Last of the Breed is one of my favorites, every single one of his books.

Speaker 1: 13:42

The land is part of the challenge. It's almost like it's a character in the book because it determined a lot about the story. Determined a lot about the story. I mean, for example, if you were coming over in the you know the early 19th century, like 1820s, 1830s, and you were planning to go out west, you know, man, it's a six to nine month journey. When you got to Missouri, you better have a good wagon, you better have a team, you better have a cow for milk, you better have enough beans and bacon to last months.

Speaker 1: 14:22

When you got going over the plains, if you went the northern route, if you went over the plains, you had to leave at a certain time of year because you were going to run into winter weather. Going across the Rockies, the Rockies, you had to go across the desert. I mean, and this was such a challenge, and we are in this era of AI, we are in this, I think this paradigm change that there is so much data and so much information out there that we have to plan to conquer it. We have to conquer this information to be better at what we do, and that takes planning and it takes understanding. I mean guys would learn for a year, would study for a year and plan for a year before they made the crossing to get out to California. I mean it was a big deal and I think if you're farming now you need to be planning what you can do to mitigate risk, because if you farm you know it's a gamble every year and understanding how we can use these tools to mitigate our risk, to make the passage safer.

Speaker 1: 15:31

I mean the planning, the understanding, and I see these parallels in you know, technological changes.

Speaker 1: 15:39

I mean imagine going from you know where you had to cross the plains with a horse and a wagon to where you can drive in your air conditioner, your temperature controlled car at 80 miles an hour and cross from coast to coast in just a matter of days To where now you can. Instead of sending letters to people you haven't seen in years, you can now pick up the phone and talk to them almost instantly, anywhere they are To now understanding massive amounts of data Imagine weather is one of the most complex data sets that there is and we have tools now that allow us to analyze that for our specific location. And as we understand those things, what does that do for us? It allows us to make better decisions. It allows us to make better decisions. It allows us to make more informed choices. Farming is still up to us and I mean if we went in there and asked here, we'll do it right now, just to We'll ask this question. Hey, hay bot, I've got a question for you.

Speaker 2: 16:53

Sure thing, John. What's your question?

Speaker 1: 16:55

In the middle of winter. Would you get outside the tractor for me and take net wrap off of my hay? I hate that job.

Speaker 2: 17:02

I can imagine that's a tough job, especially in the cold, but I'm here to keep you company and offer any tips if you need them. I'm here to keep you company and offer any tips if you need them.

Speaker 1: 17:12

I think those kind of things that we have to do as farmers are they're always going to be the things we have to do but when we can make better decisions on livestock, when we can have somebody monitor our stock 24 hours a day and know when we have to be out there to check calving, for example, I mean, imagine being, you know, a cow-calf operator. You got 250, 350 mamas and you're going into calving season and you sleep perfectly sound. You're asleep at night until a sensor tells you that that mama's going into labor. Well, you better get up and get out there, because you know it doesn't take long for a cow. If that cow prolapses, or anything like that, you want to be out there, but you don't want to waste an entire night if you don't have to, because there's other things that you have to do. So I think there are times when we have to.

Speaker 1: 18:06

You know, look at the future as not this big, scary thing, but as how can it help us do the jobs we currently do better Now? Are there risks with AI? Are there things that we should be afraid of? Yes, and I think it's important for us to stay abreast of policies regarding AI, imagine this that you are using company A we won't name any companies, but imagine you're using a company's services to monitor your crops and it sees a soil deficiency because you have sensors. So this program, this AI, knows that you have a soil deficiency and it needs to recommend fertilizer. Well, because of who owns that AI and who's in control, and because it has your data who's in control and you know, because of it has your data it can now recommend fertilizer. That may or may not be the best application, but it's owned by the company, so that AI is giving you what you think may be the best information, but it has. It is programmed to have loyalty to the company, to recommend a company product or a prescription from that company, and I think that's really, really important for us to understand those relationships and I hope that's where regulation you know with companies, because we don't know. There's no way to stay on top of that. There has to be some way, and if you listen to this podcast, you know I hate government regulations. I hate them. I think there are a few things that the government needs to do, because it can do it better than anybody else, but there's only a few of them. That's it, just a few of them. But I think in AI there needs to be some sort of oversight, whether it's governmental, whether it's private, that tells us what loyalties that AI is generating that information for. Again, I mean, their fertilizer might be $400 a ton, whereas you can go down the road and buy the same, a similar fertilizer that may be better for your soil, for $50 a ton. Those are the sort of things that we have to worry about.

Speaker 1: 20:36

I think the other big thing is data ownership. I really believe that you me, everybody, we should own our own data. We should own our own data and if we don't, we should make sure that we, that it does not that that data ownership if it goes away, if that data goes away, it does not impact our business. So you know, I think there's some some issues with data ownership, with becoming dependent on big tech or big ag. I know we use John Deere Operations Center. I mean it's an okay program. I think they've. You know it's going through a growing phase again. Is it perfect? No, if you do everything in there now, you're tied to John Deere. Now do you own your data? I don't know. We got to go read the fine print on that. There's nothing I do in John Deere that I couldn't recreate in a couple hours somewhere else.

Speaker 1: 21:36

I think those are really the three main issues that I worry about Data ownership dependence, becoming dependent on one technology or one company, and then the bias and misinformation. You know that's a big one for me If you listen to several podcasts. I've talked about media bias and information bias, and I think AI if it's not, if we're using a data set from a company that we may not know the full ownership of this AI could be biased towards that as company's products and recommend those things to us even though they may not be, you know, the best solution you know. So, kind of to wrap up, I'd just like to say I don't think we need to be afraid of AI. I really don't. I mean, we've all seen the Terminator. I don't think that AI is going to rise up and try to take over humanity, and that's not what I worry about.

Speaker 1: 22:32

What I worry about is greed Companies using, you know, using the AI tech to make recommendations to us without giving, without us having access to all of our information. Again, soil fertilizer recommendations you know medical. Imagine that in medical. Again, soil fertilizer recommendations. You know medical. Imagine that in medical. You know AI in medicine is going to be huge. I mean there are going to be in the next 10 years. There are going to be huge revolutions in medicine. I would not be surprised in 20 years to see a cure to cancer. And you know you may think I'm joking, I'm not. I think that what would take a human being years, a doctor, a PhD in data science years to study could be done by an AI minutes or hours. I think these are the things where it really has the ability to be a great help to humanity.

Speaker 1: 23:37

What I'm concerned about is the nature of man and woman. I don't want to be discriminatory, man and woman but the nature of man to bias the outcome to their benefit. To bias the outcome to their benefit. So when a medical AI recommends medication for you, are they recommending a certain company's medication or are they recommending what's best for you? Where is the loyalty of that data? Is that data loyal to you and doing what's best for you, or loyal to the company and doing what's best for the company? So you know, those are things to think about.

Speaker 1: 24:15

I think this is a time to be excited about what's coming. I really do and I think you know you've heard me talk about it before. In chaos, there's opportunity and as small farms, I think there are places we can be using AI right now and using it effectively. It's not expensive. Get in there and start learning it. But we should be paying attention to policy, because any policy that's coming out about AI regulations, especially when it comes to health care, but in all forms of business that there has to be some oversight, because it can get really bad for us really quickly if we don't watch it. And with that, have a wonderful day, good luck and God bless.