Latest / What's Your Problem? / Building a Self-Driving Tractor to Change the Future of Food

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Building a Self-Driving Tractor to Change the Future of Food · What's Your Problem?

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Speaker 1: Pushkin. Just a quick note, today's episode is the last
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Speaker 1: the show notes. Thank you very much for listening to
1:02
Speaker 1: the show, and thank you in advance for helping us
1:04
Speaker 1: make the show better. Tim Booker grew up on his
1:08
Speaker 1: fan family's dairy farm in rural northern California.
1:13
Speaker 2: You know how when you're a kid, you always wait
1:15
Speaker 2: for summer vacation from school. My brother and I we
1:19
Speaker 2: actually we hated summer vacation because that meant, you know,
1:24
Speaker 2: eighty hours a week of work out in the open field.
1:26
Speaker 2: So you know, our friends would always say, oh, I
1:28
Speaker 2: can't wait until school's out. And we would go no,
1:31
Speaker 2: I want to stay in school.
1:34
Speaker 1: Tim went off to college, started out studying agriculture, but
1:37
Speaker 1: switched to computer science, and after he graduated he founded
1:41
Speaker 1: a string of companies. One of them he sold to Microsoft,
1:45
Speaker 1: now that he sold to Apple. But all along he
1:48
Speaker 1: kept farming on the side, and eventually his farming life
1:52
Speaker 1: and his tech life came together. As just kind of
1:55
Speaker 1: a weekend side project on the farm he and a
1:58
Speaker 1: few friends built on autonomous tractor. That weekend side project
2:03
Speaker 1: has now turned into a company powering autonomous tractors across
2:07
Speaker 1: the western US and part of Australia. I'm Jacob Goldstein
2:17
Speaker 1: and this is What's Your Problem, the show where I
2:19
Speaker 1: talk to people who are trying to make technological progress.
2:22
Speaker 1: My guest today is Tim Booker. He's a longtime farmer
2:26
Speaker 1: and the founder and CEO of Agtonomy. Tim's problem is this,
2:31
Speaker 1: how do you bring autonomous vehicles to specialty crops, crops
2:35
Speaker 1: like grapes and olives and almonds and apples. There's already
2:41
Speaker 1: lots of autonomous equipment for row crops like corn and
2:45
Speaker 1: wheat and soybeans, but as you'll hear, specialty crops present
2:49
Speaker 1: a particularly tricky set of challenges. Tim and I talked
2:53
Speaker 1: about the big picture about what autonomy will mean for
2:56
Speaker 1: farming and for food. But to start, I asked him
3:00
Speaker 1: about how he got from farming to computer science in
3:03
Speaker 1: the first place. So you go off to college study
3:08
Speaker 1: agricate culture Davis as a California farm kid does.
3:12
Speaker 2: Right.
3:13
Speaker 1: And did I hear you say in another interview that
3:15
Speaker 1: you lost a bet and as a result of losing
3:19
Speaker 1: the bet, had to take a computer science class.
3:23
Speaker 2: Yes, you heard right.
3:24
Speaker 1: What was the bet? Let's just say it was.
3:27
Speaker 2: At a fraternity party, so it might have involved you know,
3:30
Speaker 2: it might have involved beer. I don't know.
3:32
Speaker 1: I like that it's a drunken fraternity party that leads
3:35
Speaker 1: you into a career as a computer scientist. Like that
3:39
Speaker 1: is an interesting combination.
3:40
Speaker 2: Yeah, it was the It was the greatest bet I
3:43
Speaker 2: ever lost. But what was what was interesting? I all
3:47
Speaker 2: my friends growing up, their last names were Sagatio, of
3:50
Speaker 2: a Piano, Bach, Galupi, Gallo. These are incredible grape growing
3:53
Speaker 2: in why making families back in the seventies, even and
3:58
Speaker 2: I would always go over to their places to, you know,
4:01
Speaker 2: help them, because that's what playdates were back then. Is
4:04
Speaker 2: you basically went over to your friend's farm and worked
4:06
Speaker 2: with them, and I would learn how to prune grapes
4:09
Speaker 2: and even make wine. And I was fascinated by that industry,
4:13
Speaker 2: like incredibly fascinated by the growing of grapes. So, you know,
4:17
Speaker 2: I went to UC Davis for agriculture, and yes, I
4:21
Speaker 2: lost a bet and took a class in a five
4:24
Speaker 2: hundred person auditorium. Now keep in mind, I didn't grow
4:28
Speaker 2: up with any technology. I mean like tractors. That was
4:31
Speaker 2: about it. But the professor started talking and I'm in
4:36
Speaker 2: the last row, and the professor started talking, and everything
4:40
Speaker 2: he was saying I understood, and it just kind.
4:44
Speaker 1: Of hit me.
4:45
Speaker 2: And by the end of that quarter, you see Davis
4:47
Speaker 2: on the quarter system. I was upfront teaching the class,
4:51
Speaker 2: and so I knew something happened, like I found a passion,
4:57
Speaker 2: like the passion I had for agriculture. And so I
5:01
Speaker 2: had a decision to make, is do do I go
5:03
Speaker 2: the agriculture route or do I go this computer science
5:06
Speaker 2: route or this you know, high tech route. And I said,
5:09
Speaker 2: you know what, I'm going to do both. I then
5:12
Speaker 2: graduated from Davis and I went on to Stanford and
5:15
Speaker 2: grad school and then started bouncing between Silicon Valley and
5:20
Speaker 2: Sonoma County because when I was sixteen, I actually bought
5:24
Speaker 2: my first vineyard, a small, little two acres, and I
5:28
Speaker 2: loved farming that and that's kind of what got me to,
5:32
Speaker 2: you know, get my own larger place, as I did
5:36
Speaker 2: through the decades, which is now called Tratory Farms Tratory
5:40
Speaker 2: which means tractor and Italian because I wanted to name
5:44
Speaker 2: it after my childhood passion. And that's where that's where
5:49
Speaker 2: kind of that whole thing started. The duality or the
5:54
Speaker 2: dual path of agriculture and high tech.
5:57
Speaker 1: You have these sort of parallel lives going for a while, Right,
6:00
Speaker 1: you're working for Steve Jobs, you're starting companies. You've got
6:05
Speaker 1: a farm up in Sonoma. A little plane you're flying
6:09
Speaker 1: back and forth, right, And so tell me about the
6:15
Speaker 1: farm part of your life, Like that's you know, we're
6:17
Speaker 1: going to bring back the technology in a minute. But
6:20
Speaker 1: you're grown up. You have a real farm, Like what's
6:23
Speaker 1: your farm?
6:25
Speaker 2: Well, it started as a small little vineyard, only two acres,
6:30
Speaker 2: and then through the years I would do what's called
6:33
Speaker 2: a ten thirty one tax free exchange and get a
6:35
Speaker 2: bigger piece of land and then, you know, I don't know,
6:39
Speaker 2: about twenty five years ago, I got a much bigger
6:42
Speaker 2: piece of land.
6:43
Speaker 1: Yeah two acres, by the way, two acres isn't even
6:45
Speaker 1: a farm, right, two acres is like a yard.
6:47
Speaker 2: Yeah, pretty much a yard. Good good call. But it
6:52
Speaker 2: was French colmbard grapes and zinfandel grapes. So so, you know,
6:57
Speaker 2: fast forward two years later, as I would kind of
7:00
Speaker 2: get bigger and bigger places, I got this one place
7:03
Speaker 2: which was amazing beautiful hillsides. I had a vision for it,
7:07
Speaker 2: but it was just a forest, and I start clearing
7:09
Speaker 2: it for you know, the intention of growing more grapes,
7:14
Speaker 2: and I encountered these stumps, you know, equidistance throughout the land,
7:19
Speaker 2: and I was like, what is this? And then finally
7:21
Speaker 2: I uncovered some old olive trees from like the eighteen hundreds,
7:26
Speaker 2: and so did some research and realized, well, this was
7:28
Speaker 2: part of a big you know, Spanish land grant growing
7:31
Speaker 2: olives back in the eighteen hundreds. So I decided to
7:34
Speaker 2: bring that history back and that's what got me into olives.
7:38
Speaker 2: So I grow olives for olive oil and grapes for wine,
7:42
Speaker 2: and I have a winery operation public tasting room, so
7:46
Speaker 2: kind of bouncing between two worlds for decades.
7:50
Speaker 1: So before you started etonomy, tell me about the way
7:56
Speaker 1: you brought technology to your farm, Like, what did you automate?
8:00
Speaker 2: Yeah? I was unique in that I was a farmer,
8:05
Speaker 2: but I was also an engineer. I had both, you know,
8:09
Speaker 2: electrical engineering background as well as computer science background, so
8:13
Speaker 2: I could do things like create you know, automated water
8:17
Speaker 2: recycling plants that you know, had the flow meters everywhere
8:21
Speaker 2: it knew, you know, how to inject different microbes to
8:25
Speaker 2: process the waste water and then inject it back into
8:29
Speaker 2: the irrigation automatically. I had, you know, obviously all kinds
8:34
Speaker 2: of basic things like cameras and whatnot. But even in
8:38
Speaker 2: the fermentation of grapes, the tanks are all computer controlled.
8:44
Speaker 2: The computer controls whether to use you know, active refrigeration,
8:48
Speaker 2: which costs energy, or if the outside air is cooler
8:52
Speaker 2: than the inside, it automatically switches over and brings that
8:55
Speaker 2: kind of air in. So you know, everything from fermentation
8:58
Speaker 2: processes to water recycling to irrigation is radically automated. So
9:04
Speaker 2: I had automated darn near everything I could, and I
9:09
Speaker 2: didn't know I was actually doing ag tech. When I
9:12
Speaker 2: was doing this, ag tech wasn't a word that existed
9:15
Speaker 2: back then.
9:16
Speaker 1: You were just like puttering around on the weekends.
9:19
Speaker 2: I was puttering around on the weekends or night times whatever.
9:23
Speaker 2: I just knew my farm needed technology to automate things,
9:27
Speaker 2: because keep in mind, I was also bouncing between Sonoma
9:31
Speaker 2: County and Silicon Valley, and so I needed technology to
9:35
Speaker 2: also be able to monitor things. Right, But there was
9:39
Speaker 2: one area I hadn't automated, and that was the actual
9:41
Speaker 2: work in the orchards and the vineyards. And I was
9:44
Speaker 2: sitting there going, hell, you know, I automated this. I
9:47
Speaker 2: automated that, Hey, maybe I should try my hand at
9:50
Speaker 2: automating the field work. There's so much money being invested
9:54
Speaker 2: in autonomous passenger vehicles, and there's so much technology that's
9:57
Speaker 2: evolved there. I wonder if I could just apply that
10:01
Speaker 2: to this space and see if I can create an
10:03
Speaker 2: autonomous vehicle that can do these kinds of repetitive tasks
10:08
Speaker 2: like mowing, like spraying, you know, like underfining cultivation, like seating,
10:13
Speaker 2: like disking, things of that nature where you're just going
10:16
Speaker 2: back and forth up and down the rows.
10:18
Speaker 1: Right, Just to be clear, there had been a fair
10:22
Speaker 1: bit of automation, right, But on the sort of big
10:24
Speaker 1: egg row crop like corn and wheat side, as I
10:28
Speaker 1: understand it, but not so much on the permanent crop
10:31
Speaker 1: kind of fruit and nut side. Is that right? Was
10:33
Speaker 1: that the sort of state of.
10:34
Speaker 2: Play exactly, Jacob So, in row crops or in broad
10:38
Speaker 2: acre farming, you know, the big million dollar tractors or
10:41
Speaker 2: half million dollar tractors, there has been automation there for decades,
10:46
Speaker 2: things called auto steer. You know, you're on these flat areas,
10:50
Speaker 2: very big fields. You can see the sky. GPS had
10:54
Speaker 2: evolved so it would be somewhat accurate, you know, a
10:58
Speaker 2: meter or whatever it might be, and so you could
11:01
Speaker 2: just control the vehicles based on that. When you think
11:04
Speaker 2: about permanent crops, which is a huge percentage value wise
11:08
Speaker 2: of our foods supply, the permanent crops, you're talking about
11:13
Speaker 2: trees and vines that are very very expensive. They take
11:17
Speaker 2: many years to develop, and so if you hit them,
11:21
Speaker 2: it's kind of a big deal. It's kind of expensive
11:24
Speaker 2: and you have to get really close to them. So
11:26
Speaker 2: you're not talking about being an open field where you
11:29
Speaker 2: can be you know, plus or minus half a meter.
11:31
Speaker 2: You're talking about being like one inch away from you know,
11:34
Speaker 2: the trunks of these trees, and if you accidentally move
11:38
Speaker 2: you know, abruptly, or you know, don't steer correctly, you're
11:41
Speaker 2: going to hit it. So you can't rely on kind
11:44
Speaker 2: of the things that you can rely on in broad
11:47
Speaker 2: acre farming and the rowe crop farming. So there needed
11:51
Speaker 2: to be more advanced technology. And thankfully, due to all
11:55
Speaker 2: the attention and investments that were being made in you know,
11:58
Speaker 2: the autonomous passenger vehicle world, that technology started to become available.
12:05
Speaker 2: You know, call it maybe less than a decade ago,
12:08
Speaker 2: but when I said, you know, kind of seven years ago,
12:12
Speaker 2: like hey, you know, my expenses are continuing to go
12:14
Speaker 2: up at tratory. I've automated DAR near everything, but I
12:18
Speaker 2: haven't automated the field work. Could we take some of
12:21
Speaker 2: that technology and could we create a solution, an autonomous
12:25
Speaker 2: solution that could do these repetitive tasks that you need
12:29
Speaker 2: to do in permanent crops. And so with some friends
12:33
Speaker 2: built a prototype five years ago and the prototype worked
12:38
Speaker 2: really well. We literally built an all electric autonomous tractor.
12:44
Speaker 1: What did it look like and what did it do?
12:46
Speaker 2: Didn't look like a traditional tractor. We took out the
12:49
Speaker 2: diesel engine. We put in electric motors and batteries, and
12:54
Speaker 2: we put on cameras and we had you know, an
12:58
Speaker 2: Nvidia compute system in it, and we started to create
13:02
Speaker 2: this sensor based vehicle. It had eight wheels, it articulated,
13:07
Speaker 2: and it could do really steep st and one of
13:10
Speaker 2: the reason why we did that is because that tratory
13:12
Speaker 2: the slopes are very very steep. By the way, one
13:15
Speaker 2: of the main inspirations for doing this autonomous vehicle came
13:18
Speaker 2: from a documentary I watched. I think it was a
13:22
Speaker 2: National geographic. It was called Mission to Mars, The Story
13:25
Speaker 2: of Spirit and Opportunity. And these were Mars rovers in
13:28
Speaker 2: the nineties that NASA shot up and we're hoping would
13:33
Speaker 2: operate for you know, fifteen days or you know, a
13:37
Speaker 2: couple of months, and they ended up lasting almost fifteen years.
13:40
Speaker 2: And I was watching this documentary before I actually built
13:43
Speaker 2: this prototype, and it reminded me that, hey, there are
13:47
Speaker 2: environments where you can take your time in making decisions.
13:53
Speaker 2: So they had animations of how the rover would approach
13:56
Speaker 2: a rock and it would just stop and then it
13:58
Speaker 2: would radio JPL, you know, take some time to radio JPL.
14:02
Speaker 2: They would take a week and write some new code.
14:04
Speaker 2: They would then download it, and then the vehicle, the
14:07
Speaker 2: rover would move to the left that whenever it encountered
14:10
Speaker 2: a rock, it would move to the laughter to the right.
14:12
Speaker 2: And I said to myself, my god, you know, they
14:15
Speaker 2: had autonomous vehicles operating on Mars in the nineties and
14:19
Speaker 2: they could do it because there wasn't a lot of
14:21
Speaker 2: traffic on Mars, just like agriculture. And that's when my
14:25
Speaker 2: head really exploded and I said, wait, there are these
14:28
Speaker 2: industrial markets that need automation, and you don't necessarily have
14:33
Speaker 2: to immediately, you know, be responsive to the vehicle if
14:39
Speaker 2: it encounters something it can't figure out, like oh, there's
14:42
Speaker 2: a tree in front of.
14:43
Speaker 1: Me, unlike on a road in traffic. Correct. Correct, So
14:48
Speaker 1: when you build this prototype that you don't even know
14:52
Speaker 1: is a prototype as you're telling it, right, this thing
14:54
Speaker 1: that you're doing with your friends, I mean it sounds
14:57
Speaker 1: like a lot of the sort of tex stack is
15:00
Speaker 1: basically commodified by that point. I mean, is it a
15:02
Speaker 1: sort of you're at this moment where you can be like, oh, well,
15:05
Speaker 1: buy these sensors and we'll start with this piece of software,
15:08
Speaker 1: and like you can almost build an autonomous vehicle from
15:12
Speaker 1: off the shelf parts. Is that sort of the starting point.
15:14
Speaker 2: From a hardware perspective. Absolutely, from a software perspective, no,
15:20
Speaker 2: at that time, so no, we were actually building a
15:22
Speaker 2: perception stack, you know that could you know do all
15:26
Speaker 2: the Well, first you had to localize, so you have
15:27
Speaker 2: to figure out where in the world do you are,
15:30
Speaker 2: And so we did need to see GPS at least once,
15:33
Speaker 2: but then the computer vision technologies and the perception stack
15:37
Speaker 2: could then align to the crop itself. One of the
15:40
Speaker 2: big differences that in approach that we took that obviously
15:44
Speaker 2: the row crops, the broad acre farms don't need to
15:46
Speaker 2: do is we actually said, hey, what if we exploit
15:51
Speaker 2: the structure the crop itself and utilize that structure to
15:55
Speaker 2: navigate safely through it and farm precisely around it.
15:59
Speaker 1: Meaning like know what a tree is and know what
16:02
Speaker 1: your relationship should be to a tree. Is that what
16:04
Speaker 1: that means? Correct?
16:06
Speaker 2: And in the early days we said, hey, there's one
16:09
Speaker 2: common characteristic and permanent crops. They all have a trunk,
16:14
Speaker 2: So what if we could be the best detectors of
16:18
Speaker 2: trunks in the world and utilize that for alignment? And
16:22
Speaker 2: as I said, also you know, working around that plant.
16:25
Speaker 1: So that's the key sort of training piece, Like you
16:28
Speaker 1: train really hard on trunks.
16:30
Speaker 2: That's right, that's right. We initially labeled trunks. We would
16:34
Speaker 2: drive through, we would get you know, tons of photos
16:37
Speaker 2: and we would manually label around the trunk area. And
16:41
Speaker 2: then we would take those images and we would tweak
16:44
Speaker 2: them and create synthetic data and we would label those
16:48
Speaker 2: and once you get enough of a data set, you
16:51
Speaker 2: can start to do some additional machine learning with that, right.
16:55
Speaker 2: And what was interesting was, you know, we got so
16:58
Speaker 2: good at detecting trunks. We even called it trunk vision.
17:00
Speaker 2: We trademark trunk vision. Not that you know, we do
17:04
Speaker 2: a lot more than trunk vision today, but that's how
17:07
Speaker 2: that's how we got it to, you know, run through
17:10
Speaker 2: the orchards and run through the vineyards. And what was
17:12
Speaker 2: really interesting is we initially trained on grapes, on grapevines
17:17
Speaker 2: and the rootstock right the trunk. And one day my CTOs,
17:22
Speaker 2: you know, he said, hey, let's run it in the olives.
17:25
Speaker 2: And I'm like, oh, but you know, you're sure it's
17:27
Speaker 2: going to work. He's like, I don't know if it's
17:29
Speaker 2: going to work. I don't know how well the training
17:31
Speaker 2: will translate. And so we set it off in the
17:34
Speaker 2: Olives and it just worked. Now, it wasn't perfect, but
17:40
Speaker 2: it made us realize, Wow, there's a lot of leverage
17:42
Speaker 2: between crops here in these permanent crop areas. Generalizes, it
17:46
Speaker 2: generalizes really well. And of course he's continued to evolve that,
17:51
Speaker 2: and you know, we now do all kinds of additional
17:53
Speaker 2: training to make sure in a new crop type we
17:56
Speaker 2: are very very accurate in exploiting the structure of the crop.
18:01
Speaker 1: Besides driving through trees without hitting them, which I recognize
18:05
Speaker 1: as non trivial, what else did the tractor do? Did
18:08
Speaker 1: it do work?
18:09
Speaker 2: Yes, it did work. It mowed initially. The very very
18:14
Speaker 2: very first job we did was mowing because we have
18:16
Speaker 2: cover crop. Sometimes the cover crop gets like six feet
18:18
Speaker 2: tall and you chop it up with a flail mower
18:22
Speaker 2: and then it composts in between the trees or the
18:26
Speaker 2: vines and and even that, like you think mowing, Oh yeah,
18:30
Speaker 2: you just set it at four miles an hour and
18:31
Speaker 2: you let it go. You cannot do that, right, because
18:34
Speaker 2: think about what a human does. The human's on a vehicle.
18:37
Speaker 2: It's really funny. I asked my engineers you know, well,
18:40
Speaker 2: did you ever use a push mower when you were
18:42
Speaker 2: a kid, And they're like, what's a push mower? Anyway?
18:45
Speaker 1: Separate topic, but pushmore is really hard. It's harder than
18:49
Speaker 1: you think that was th pushover means the more without
18:53
Speaker 1: an engine. It doesn't just mean a gas mower that
18:56
Speaker 1: you put.
18:56
Speaker 2: Right right right and then and then you know, we
18:59
Speaker 2: got motorized mowers for lawns, right that you that you
19:04
Speaker 2: know actually had wheels and had an engine on them.
19:07
Speaker 2: But even with those, if you would go through the
19:10
Speaker 2: and if it would bog down, as the person operating
19:14
Speaker 2: that lawn mower, you would slow it down in order
19:18
Speaker 2: for the blades to catch up, right. And so if
19:21
Speaker 2: you think about it, you can't just set a tractor
19:24
Speaker 2: going to mow. You need to get that feedback to
19:28
Speaker 2: understand if it's bogging down, and therefore you need to
19:32
Speaker 2: slow down or increase the RPM in order to do
19:36
Speaker 2: the job properly.
19:37
Speaker 1: Right.
19:38
Speaker 2: So that's something we learned immediately, But we already thought
19:42
Speaker 2: about that because we were all farmers. We had farmer
19:45
Speaker 2: DNA in us, and we knew that's how a human operated.
19:48
Speaker 2: So we just we started to think, Okay, how does
19:51
Speaker 2: a human do this? And what are the things we're
19:53
Speaker 2: gonna need feedback on like a human has in order
19:56
Speaker 2: to get the job done correctly. So we started with
19:59
Speaker 2: mowing and we became really really good at it.
20:02
Speaker 1: So you have your prototype and you decide to start
20:06
Speaker 1: a company. What do you have to do to turn
20:11
Speaker 1: your prototype into you know, something you can sell? Like, yeah,
20:15
Speaker 1: what's the what's the leap?
20:18
Speaker 2: Yeah, this was a big leap. You know. My mechanical
20:22
Speaker 2: engineering co founders was like, you know, whipping up all
20:25
Speaker 2: kinds of cool ideas. And then I thought about it
20:29
Speaker 2: as a farmer, and I said, wait a minute, as
20:32
Speaker 2: a grower, would I trust a startup company, you know,
20:36
Speaker 2: for a new tractor? Think about it, right, I'm a
20:41
Speaker 2: farm I rely upon equipment to get my job done,
20:47
Speaker 2: and that job is vital for the livelihood of the business,
20:52
Speaker 2: for the livelihood of the family if it's a family farm.
20:55
Speaker 2: So why would I trust a startup instead? What I
21:00
Speaker 2: need as a grower is I need trusted brands. I
21:04
Speaker 2: need their dealer networks. I need the parts, I need
21:06
Speaker 2: the service. This this equipment needs to be operating all
21:11
Speaker 2: the times that I need it for the sustainability of
21:14
Speaker 2: my business. And so I said to my colleagues, I said,
21:18
Speaker 2: you know what, I don't think we should build a tractor.
21:20
Speaker 2: I think that would be rather stupid. And I explained why,
21:23
Speaker 2: and they said, oh, that makes sense, and they said, well,
21:27
Speaker 2: how can we work with existing original equipment manufacturers? These
21:32
Speaker 2: incredible equipment manufacturers who've been at it for over one
21:34
Speaker 2: hundred years and they build incredible vehicles that really work
21:40
Speaker 2: well in these harsh environments. And so you know, at
21:44
Speaker 2: first investors that I was talking about, Hey, we're going
21:47
Speaker 2: to do an OEM model and you know, original equipment manufacturer,
21:50
Speaker 2: we're going to help accelerate their digital transformation because we
21:55
Speaker 2: know where the puck is going, right. We know that
21:57
Speaker 2: this industry too, just like other industries, needs to go
22:01
Speaker 2: through a digital transformation. Every day there's less and less
22:04
Speaker 2: skilled operators who go into agriculture. So the equipment manufacturer know,
22:09
Speaker 2: you know, they see the writing on the wall. They're
22:12
Speaker 2: not going to sell as much equipment because like there's
22:14
Speaker 2: less people to operate them. So they know automation is
22:17
Speaker 2: really important, and they know how to build incredible iron,
22:21
Speaker 2: but do they know how to build an AI factory?
22:24
Speaker 2: And that's what I said, you know we would focus
22:26
Speaker 2: on is that we would build software to make their
22:32
Speaker 2: incredible equipment incredibly smart and provide the solutions that make
22:38
Speaker 2: them autonomous and give growers ultimately new technologies that can
22:43
Speaker 2: help them save money and get an incredible ROI. It's
22:47
Speaker 2: almost like building equipment that comes with a skilled operator
22:49
Speaker 2: built in that you can turn on and off any
22:51
Speaker 2: time you want.
22:53
Speaker 1: As a bonus, you don't have to have the crazy
22:55
Speaker 1: capital outlay of building a tractor factory, right like, I mean,
23:00
Speaker 1: that's business. It seems way better.
23:03
Speaker 2: It does, but there's one catch, and investors early on
23:08
Speaker 2: would say, wow, I don't think you can get an OEM.
23:11
Speaker 1: And we did an OEM, an original equipment manufacturer attractor.
23:16
Speaker 2: Attractor company, and we did an incredible company called Bobcat.
23:21
Speaker 2: Douce on.
23:21
Speaker 1: Bobcat.
23:22
Speaker 2: They make excavators large and small, They make skid steers,
23:26
Speaker 2: they make trackloaders, they make tractors like normal looking tractors, right,
23:34
Speaker 2: and they they make forklifts. They make all kinds of things.
23:38
Speaker 2: So you know, really, what we're doing is exactly what
23:42
Speaker 2: I said earlier, which is to accelerate the digital transformation
23:46
Speaker 2: of these companies because they know they have to transform,
23:48
Speaker 2: they know they have to bring autonomy into their equipment
23:53
Speaker 2: and and and create you know, actonomy enabled vehicles. Right,
23:57
Speaker 2: So we're not like creating tractors. We're just helping them
24:02
Speaker 2: with the with the brains of the operation.
24:09
Speaker 1: We'll be back in just a minute. What's out there now?
24:22
Speaker 1: Is your software out in the world now? Dive in
24:25
Speaker 1: tractors around orchards and what are they doing and where
24:28
Speaker 1: are they and how many of them are there?
24:29
Speaker 2: Yeah, we have tractors throughout the Western United States, and
24:33
Speaker 2: I'm pleased to say that we also have vehicles in Australia.
24:37
Speaker 2: So we're super excited about the capabilities we've enabled. In
24:42
Speaker 2: the state of Washington, for example, where apples are number
24:45
Speaker 2: one in the world, we're doing a lot of spraying
24:49
Speaker 2: and a lot of mowing. And it's really it's very
24:52
Speaker 2: impactful because you're not just having one vehicle, but our
24:56
Speaker 2: customers have many vehicles. They have a fleet of vehicles,
25:00
Speaker 2: and they're able to operate those with one of their
25:03
Speaker 2: employees that they've upskilled to be able to supervise a fleet.
25:09
Speaker 2: And so it's kind of neat to see, you know,
25:11
Speaker 2: a whole fleet of vehicles leaving the main shop, driving
25:15
Speaker 2: on the dirt roads out to the different areas where
25:18
Speaker 2: they need to do work, do the work, and then
25:21
Speaker 2: all come back right, So it's a very seamless operation
25:26
Speaker 2: for them. Our software is also on mobile applications and
25:29
Speaker 2: that's how the main user experience exists. So think of
25:34
Speaker 2: you having the tablet or even just your smartphone, and
25:38
Speaker 2: the site is mapped out, usually with aerial imagery, and
25:42
Speaker 2: you can just point and say, I want to go
25:44
Speaker 2: and mow this, you know, this block of the orchard,
25:48
Speaker 2: and we basically can get close to where the crop is.
25:54
Speaker 2: And then once we're close to the crop, that perception
25:57
Speaker 2: stack I mentioned earlier about detecting you know this, or
26:00
Speaker 2: exploiting the structure of the crop itself. Take trunk trunk
26:03
Speaker 2: vision and it snaps the vehicle to grid, if you will. Right.
26:08
Speaker 2: But now, once you have trunk vision and you see
26:11
Speaker 2: in front of you, and you can see the terrain
26:14
Speaker 2: to a very high degree of accuracy, you can take
26:19
Speaker 2: mechanical weaters, for example, and manipulate underneath these trees, you know,
26:25
Speaker 2: these robotic weaters, and navigate while you're doing that very precisely,
26:32
Speaker 2: all under computer control. Whereas when a human does it,
26:35
Speaker 2: you're you know, driving a vehicle six miles an hour
26:38
Speaker 2: looking forward, you have your hand on six actuators on
26:41
Speaker 2: the you know, the weater and behind you, and you're
26:44
Speaker 2: trying to make it all work, and inevitably what happens
26:46
Speaker 2: is you don't get the weeds so the efficacy is
26:49
Speaker 2: not high, or you hit the tree and take it out,
26:53
Speaker 2: and you know that again costs a lot of money.
26:55
Speaker 2: So that's why herbicides have been used so much because
26:58
Speaker 2: it's really easy. It's called strip spray and you just
27:00
Speaker 2: spray it and you're done. But that's that's kind of
27:05
Speaker 2: a thing that we didn't realize. You know, this kind
27:07
Speaker 2: of autonomous technology would really open up is much more
27:12
Speaker 2: offerings for growers so that they don't have to use
27:16
Speaker 2: very expensive ag inputs or herbicides that they've been doing
27:20
Speaker 2: in the past.
27:21
Speaker 1: All this work that you're describing, is it happening in
27:24
Speaker 1: a like commercial way now, Like, are you out in
27:27
Speaker 1: the world getting paid for this? Yes? And what's that
27:29
Speaker 1: business model?
27:31
Speaker 2: On that note, Yeah, so we've been operating in paid
27:35
Speaker 2: pilots in twenty twenty three and twenty twenty four. We
27:39
Speaker 2: never intended to be paid for pilots. What happened was
27:44
Speaker 2: we'd have these demo days. We'd invite growers and they
27:47
Speaker 2: would say, I want to buy one. I said, well,
27:49
Speaker 2: they're not for sale. Well I want to rent one.
27:52
Speaker 2: I'm like, well maybe we can do that. Would you
27:54
Speaker 2: be interested in doing a pilot? Yes, and I'll pay you.
27:58
Speaker 2: And we're like okay. So in those original prototypes that
28:01
Speaker 2: we built, we actually rented them and it was kind
28:05
Speaker 2: of cool because it was a very small company. We
28:07
Speaker 2: didn't actually think we were going to recognize revenue until
28:10
Speaker 2: many years in. And I think our first year we did,
28:13
Speaker 2: you know, it was actually close to a million dollars.
28:16
Speaker 2: But then the second year we did several million dollars
28:18
Speaker 2: and that was in twenty twenty four. And this year
28:22
Speaker 2: we went big time and we have units operating from Washington, Oregon,
28:27
Speaker 2: California and now Australia. And so our business model right
28:32
Speaker 2: now is we work with the manufacturers. They manufacture everything,
28:36
Speaker 2: they procure all the parts, they bring it into their
28:38
Speaker 2: manufacturing facilities and they create these very high quality machines
28:43
Speaker 2: that are factory fit. Right, A lot of people think, oh,
28:46
Speaker 2: you do retrofit kits on tractors. We do not do that.
28:50
Speaker 2: We believe it's important to work with the engineers of
28:52
Speaker 2: these OEMs to make the equipment much more reliable, much safer,
28:57
Speaker 2: and lower cost, much lower cost when you integrate it in.
29:01
Speaker 1: And then when the farmer buys the machine with your
29:04
Speaker 1: software in it, with your autonomy package in it, like
29:08
Speaker 1: is it are they paying you a subscription? Is the
29:11
Speaker 1: price just embedded in the machine and you get some
29:13
Speaker 1: of the money.
29:14
Speaker 2: So the answer is yes to all of those because
29:18
Speaker 2: in some cases the software fees will be embedded in
29:22
Speaker 2: the machine. In some cases you will pay a monthly
29:25
Speaker 2: fee or an annual fee or a one time fee.
29:28
Speaker 1: Right.
29:29
Speaker 2: Think of serious XM. Serious XM creates technology, it gets
29:35
Speaker 2: embedded by the OEMs and their manufacturing facilities.
29:38
Speaker 1: Satellite radio just to satellite radio, yeah yeah.
29:42
Speaker 2: And goes to the dealers, and then the dealers basically
29:46
Speaker 2: sell to the end customer, and there's a free trial
29:49
Speaker 2: that comes and after the free trial, Serious XM retains
29:53
Speaker 2: those customers and charges a monthly fee.
29:57
Speaker 1: That's a good metaphor satellite radio, but for autonomous tractors,
30:02
Speaker 1: for high value.
30:02
Speaker 2: Crops exactly, there's another twist. I'll tell you that. By
30:06
Speaker 2: the way, the chairman of our company, the chairman of
30:09
Speaker 2: the board is Jim Meyer. He's the former CEO of
30:12
Speaker 2: Serious ExM.
30:12
Speaker 1: Ah okay, yeah.
30:14
Speaker 2: And by the way, he's brilliant at business and he
30:16
Speaker 2: really helps shape this kind of business model.
30:19
Speaker 1: What's the technical thing you haven't figured out yet.
30:23
Speaker 2: I'll give you a small example, but it's kind of important.
30:26
Speaker 2: So three point turns. If you think about permanent crops,
30:31
Speaker 2: you're going down these rows and there's you know, a
30:34
Speaker 2: person has a ranch it's called one thousand acres, and
30:37
Speaker 2: there might be a fence around the entire thousand acres
30:40
Speaker 2: right to keep deer out or whatever it might be.
30:42
Speaker 2: And they try to maximize the land they have, so
30:45
Speaker 2: they plant the crop pretty close to the edge of
30:47
Speaker 2: the fence, let's say. And so when you turn, you
30:50
Speaker 2: know in the headlands right, the headland turn, you might
30:54
Speaker 2: not have a lot.
30:54
Speaker 1: Of space, so you can't just like make a kind
30:57
Speaker 1: of U turn at the end of the row and
30:58
Speaker 1: go down the next.
30:59
Speaker 2: Correct correct correct. So you know, right now we can
31:03
Speaker 2: do about eighty percent of farmlands and permanent crops. But
31:07
Speaker 2: imagine if we could do point turns, we can achieve
31:11
Speaker 2: one hundred percent. But but there's a twist, right because
31:14
Speaker 2: sometimes you not you don't have an implement, that's the
31:17
Speaker 2: device you attached to the tractor that does the work.
31:20
Speaker 2: So you have implements you can attach for mowing, for spraying,
31:23
Speaker 2: for weeding, for disking, for all kinds of things. Some
31:26
Speaker 2: of those implements are actually trailers.
31:30
Speaker 1: H huh.
31:30
Speaker 2: Okay, So imagine you know, being on a site slope
31:34
Speaker 2: with rocky soil and everything, and you have a trailer
31:37
Speaker 2: and you have to do a three point turn to
31:40
Speaker 2: get into the next row.
31:41
Speaker 1: That's a high skill that's a high skill moment, right,
31:44
Speaker 1: that's hi know what they're doing exactly exactly.
31:47
Speaker 2: And you know, ectonomy enabled vehicles have lots of cameras.
31:50
Speaker 2: They have you know, minimum of eight cameras including rear
31:53
Speaker 2: facing cameras and side facing cameras, and so you have
31:56
Speaker 2: to really now start to you know, do very sophisticated
32:00
Speaker 2: modeling of the you know, physics of that tractor as
32:04
Speaker 2: well as that implement or trailer, which we which we
32:08
Speaker 2: do today as we go forward, but now we have
32:10
Speaker 2: to do it going backwards. So we haven't mastered that
32:13
Speaker 2: yet but we're getting close, and I'm super excited about that,
32:17
Speaker 2: both from a technological achievement perspective as well as a
32:21
Speaker 2: business need.
32:25
Speaker 1: It's a nice when they go together. Yeah, so let's
32:29
Speaker 1: so madch for a minute, like I'm you know, there
32:32
Speaker 1: are other people working on other agricultural technology projects, other
32:39
Speaker 1: ag tech projects, even other autonomous projects. Like when you
32:42
Speaker 1: zoom out and think about farming and technology more generally
32:45
Speaker 1: in the medium term, you know whatever that means, five years,
32:50
Speaker 1: ten years, like, how's the world going to change?
32:55
Speaker 2: Well, so, first of all, there are a lot of
32:58
Speaker 2: others working on similar problems. We all have a slight twist,
33:03
Speaker 2: either in business model or in technology approach. I think
33:08
Speaker 2: that in the future is all going to be autonomous capable,
33:13
Speaker 2: and we see the writing on the wall right when
33:16
Speaker 2: it comes to labor challenges that we're having, we have
33:20
Speaker 2: a severe labor gap. If I were to ask you
33:24
Speaker 2: how many people do you know who you know whose
33:26
Speaker 2: kids go into agriculture, the answer is probably going to
33:29
Speaker 2: be not that many. I have three children, Jacob, and
33:33
Speaker 2: none of them are taking over the farm. And then
33:36
Speaker 2: you know, of course we have things like you know,
33:38
Speaker 2: some immigration policy changes that have occurred that are only
33:40
Speaker 2: exacerbating the problem.
33:42
Speaker 1: Even in the absence of a labor shortage, that some margin,
33:45
Speaker 1: automation wins, right, Like that's what happened with the tractor
33:48
Speaker 1: and like, whatever's right. So yes, I'm fully prepared to believe.
33:52
Speaker 1: And yes, I can see how the current politics might
33:55
Speaker 1: be accelerating the shift to automation. But yes, so okay,
33:58
Speaker 1: automation is going to win. I stipulated, like what's that
34:02
Speaker 1: going to mean? What's it going to look like? You know,
34:04
Speaker 1: tell me something about the future based on that fact.
34:07
Speaker 2: Think about ro crops, right, I believe row crops are
34:11
Speaker 2: going to radically change. So here is one big inflection
34:13
Speaker 2: point that I think is going to happen. Right now,
34:16
Speaker 2: we have these large, large tractors in row crops. It
34:20
Speaker 2: cost a million dollars. Fully autonomous ones cost well over that.
34:24
Speaker 2: And why are there big tractors. It's because these these farms,
34:29
Speaker 2: you know, want as many acres done per hour by
34:32
Speaker 2: one person. But now if automation comes in, you don't
34:36
Speaker 2: necessarily need these large vehicles that have huge ground compassion.
34:40
Speaker 1: This is your trillion dollar play. Now you're going to
34:43
Speaker 1: disrupt John Deere. Is that where this is.
34:45
Speaker 2: Going yes, So I mean, but think about it, right, if.
34:50
Speaker 1: You're the only reason you need to make the vehicle
34:52
Speaker 1: as big as possible is if you have to have
34:54
Speaker 1: a dude on every one of them. That's what you're saying.
34:56
Speaker 1: It's not necessarily it could be like like the way
34:58
Speaker 1: it's like a drone swarm, you could do a drone swarm,
35:00
Speaker 1: but for tractors.
35:02
Speaker 2: Broad acre swarming exactly right, Yeah, And that's there's some
35:07
Speaker 2: additional benefits, right, So instead of spending and a million dollars,
35:10
Speaker 2: you can do more work with five tractors that cost
35:13
Speaker 2: less than that with their implements as well, and now
35:16
Speaker 2: you have some additional benefits, so you actually get more
35:21
Speaker 2: work done faster, and if one of the tractors breaks down,
35:24
Speaker 2: you have redundancy. Right, If your big million dollar tractor
35:28
Speaker 2: breaks down, you got issues. It's like thousands of dollars
35:32
Speaker 2: a minute that you know that it's not running. So
35:35
Speaker 2: I think there's a lot of opportunity in agriculture that
35:39
Speaker 2: we hadn't thought about once automation is achieved. I mean,
35:42
Speaker 2: I describe the herbicide challenge in permanent crops. I believe
35:46
Speaker 2: that is completely can be completely eliminated with automation, and
35:52
Speaker 2: you know computer controls, computer vision, like you.
35:55
Speaker 1: Just pick the weeds instead. If you have essentially very
35:58
Speaker 1: cheap robots that are very dexterous, you just pick the
36:01
Speaker 1: weeds instead of spraying them.
36:02
Speaker 2: Absolutely, it's already happening in row crops, you know. You
36:05
Speaker 2: look at carbon robotics, they're using lasers to kill weeds,
36:09
Speaker 2: you know, in lettuce fields and other kinds of crops
36:12
Speaker 2: that are called specialty crops. That's huge, right because before
36:16
Speaker 2: humans would would go in there, or you'd spray and
36:19
Speaker 2: use bag inputs or herbicides. So I think there's a
36:23
Speaker 2: huge there is a huge inflection point. But I just
36:26
Speaker 2: I want to make it clear to your listeners that
36:29
Speaker 2: just the core base of you know, being able to
36:31
Speaker 2: produce enough food for the population, we need automation. Four
36:35
Speaker 2: there are going to be these other benefits, some of
36:37
Speaker 2: which we don't even know yet. So I'm such a
36:41
Speaker 2: big believer in automation. It's why I brought my two
36:44
Speaker 2: worlds together, and it's why I've really dedicated my life
36:46
Speaker 2: to this mission. And I just I've never been as
36:50
Speaker 2: excited as I as I am now in terms of
36:52
Speaker 2: the impact that this company can have our share of impact,
36:58
Speaker 2: but all of us together, there's so much opportunity here.
37:01
Speaker 2: And you know, I think the incumbents are the ones
37:04
Speaker 2: that the incumbent equipment manufacturers are the ones that are
37:07
Speaker 2: really going to make it happen in terms of distribution
37:10
Speaker 2: and support and you know, getting it out there to
37:13
Speaker 2: the world. So couldn't be more excited.
37:20
Speaker 1: We'll be back in a minute with the lightning round.
37:32
Speaker 1: Let's finish with the lightning round. I heard you say
37:35
Speaker 1: on another interview that you are not a big fan
37:38
Speaker 1: of IPOs and that you generally prefer acquisitions. Why what
37:42
Speaker 1: do you got against IPOs.
37:45
Speaker 2: Well, that's from the old days. I've went through a
37:47
Speaker 2: couple of IPOs and just about killed me. So a
37:51
Speaker 2: lot of people think, you know, IPOs are glamorous and everything,
37:54
Speaker 2: but you know, the road shows are pretty intense and
37:57
Speaker 2: the pressures are really intense, and you know, I'm not
38:01
Speaker 2: just a fan of acquisitions. I mean, I think you're
38:03
Speaker 2: seeing a lot of differences in the private market than
38:06
Speaker 2: you have in the past. Companies like open Ai who
38:09
Speaker 2: are raising billions of dollars in the private market and
38:13
Speaker 2: not having to go public.
38:15
Speaker 1: You could just stay private forever. You could just be
38:17
Speaker 1: a company that makes more money than it's spends. You
38:19
Speaker 1: could do that for as long as.
38:21
Speaker 2: You want, exactly exactly. So I think the IPO, you know,
38:27
Speaker 2: I mean, just look at the last few years of IPOs.
38:30
Speaker 2: There just haven't been that many. And so there are
38:32
Speaker 2: other ways to build incredibly valuable companies. I get asked
38:36
Speaker 2: all the time, what's your exit strategy? And I always
38:39
Speaker 2: have the same answer. I only focus on building value
38:43
Speaker 2: opportunities come, and I think entrepreneurs who build companies for
38:48
Speaker 2: an exit aren't building the company for the right reasons
38:52
Speaker 2: and aren't building really valuable companies either.
38:56
Speaker 1: What's one thing that Steve Jobs told you that stuck
38:58
Speaker 1: with you.
39:02
Speaker 2: I had the pleasure of working for some incredible entrepreneurs,
39:05
Speaker 2: Steve Jobs being one of them. And what I did
39:08
Speaker 2: learn is that these incredible entrepreneurs, they each had like
39:12
Speaker 2: a singular mantra. And for Steve, it was all about design.
39:16
Speaker 2: It's all about design, and there were things he would
39:19
Speaker 2: push for that we'd sit there and scratch our heads
39:22
Speaker 2: and go, wait, that's going to add like one hundred
39:24
Speaker 2: dollars cost to this, and and we would do it
39:29
Speaker 2: and the product would be successful, and we're like, Okay,
39:32
Speaker 2: he was right. You know. I learned from from Bill
39:37
Speaker 2: Gates that it's all about software, and you know what,
39:41
Speaker 2: he was right. I learned from Michael Dell that it's
39:43
Speaker 2: all about costs, and guess what, he was right. So
39:46
Speaker 2: I think, you know, the every entrepreneur that makes serious impact,
39:51
Speaker 2: you know, has these kind of core mantras. So what's
39:55
Speaker 2: yours I viewed as a combination. But there is one
39:58
Speaker 2: thing that I will tell you very very clearly in
40:02
Speaker 2: your listeners, and I tell my teammates probably every day,
40:07
Speaker 2: if not every week. You know, it's all about show me,
40:12
Speaker 2: don't tell me. And that particularly applies to these industrial markets.
40:20
Speaker 2: The best way to sell industrial equipment, and this is
40:24
Speaker 2: what dealers do is, you know, hear Susie farmer take
40:28
Speaker 2: this piece of equipment and use it for a day,
40:31
Speaker 2: and she'll take that piece of equipment, use it on
40:33
Speaker 2: her ranch, on her farm, whatever, and inevitably she will
40:37
Speaker 2: buy it because she gets to try, you know before.
40:40
Speaker 2: So I think I think the show me mentality is
40:43
Speaker 2: really really important in this era, and in ag tech
40:46
Speaker 2: in particular, because there've been some companies that have been
40:49
Speaker 2: developed by pure tech people and pure tech people. You know,
40:54
Speaker 2: telling farmers that you know, we can farm better than
40:57
Speaker 2: you is not a good recipe for success, right, And
41:01
Speaker 2: so by focusing on show me, it's really what resonates
41:06
Speaker 2: with our customers, it's really what our customers need, and
41:11
Speaker 2: it's just how business is done in these industrial worlds.
41:14
Speaker 2: So that's my mantra, show me, don't tell me.
41:21
Speaker 1: What's one ridiculous word somebody once used to describe the
41:25
Speaker 1: wine that you grow? Hm hmm.
41:33
Speaker 2: I didn't even know what this. I still don't know
41:35
Speaker 2: what this word means. But ethereal, I'm like, like, what
41:41
Speaker 2: does what does that mean?
41:42
Speaker 1: It doesn't stuck around, It's like I don't even know
41:45
Speaker 1: I drank.
41:45
Speaker 2: Yet, Like yeah, I don't know, right, So you get
41:48
Speaker 2: all kinds of feedback.
41:50
Speaker 1: Is that a fancy way of saying easy drinking sounds
41:52
Speaker 1: like easy drinking? Probably?
41:54
Speaker 2: Yeah? Yeah, yeah, But you get all kinds of great feedback.
41:58
Speaker 2: And I mean that's the cool thing about sort of
42:00
Speaker 2: the show me mentality is when you develop products that
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Speaker 2: end users you know, consume or use, and you see
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Speaker 2: their reaction and you know, there you you please them,
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Speaker 2: You give them something of value That's that's what gets
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Speaker 2: me motivated all the time. And that's why you know,
42:20
Speaker 2: this space is so exciting for me, because that that
42:22
Speaker 2: impact has felt like really really quickly. When when you
42:26
Speaker 2: do have a solutions at work, or when you do
42:28
Speaker 2: make great wine, or when you do make great olive oil.
42:32
Speaker 1: Yeah, I don't think autonomous tractors as ethereal, I please don't.
42:44
Speaker 1: Tim Booker is a farmer and the founder and CEO
42:47
Speaker 1: of Actonomy. Please email us at problem at pushkin dot fm.
42:52
Speaker 1: We are always looking for new guests for the show.
42:56
Speaker 1: Today's show was produced by Trinamanino and Gabriel Hunter Chang,
43:00
Speaker 1: who was edited by Alexander Garrettson and engineered by Sarah Brugueret.
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Speaker 1: I'm Jacob Goldstein. We'll be off for the next few
43:07
Speaker 1: weeks for the holidays. I want to thank you very
43:10
Speaker 1: much for listening to the show this year. It really
43:13
Speaker 1: means a tremendous amount to all of us. I hope
43:15
Speaker 1: you have a great holiday, happy New Year, and we
43:18
Speaker 1: will be back with more episodes of What's Your Problem
43:21
Speaker 1: in twenty twenty six.