Human history shows that agriculture was one of the earliest innovations. It allowed populations to shift from a hunting and gathering to feeding the masses through organized efforts to grow crops. For decades, technology may have appeared to accelerate much faster in other industries, but advancements in equipment, seeds and planting tactics have continued to increase farm production. Now, 5G connectivity is about to unleash the next wave of innovation in farming, with smart equipment and backend data allowing farmers to do more with less, a critical need in an industry with finite resources.
In this episode of The Restless Ones, we sit with Igino Cafiero, CEO of Bear Flag Robotics—a subsidiary of industry-leader John Deere, and pioneer in bringing autonomy and intelligence to the world of tractors. From engineer to founder, Igino’s passion for solving problems—especially ones with such meaning as feeding the world—is palpable. Igino believes autonomy is just one part of a connectivity-enabled path to helping farmers increase yields through the use of smart sensors, data and machine learning. As we learned, the farm of the future may already be here.
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:03):
The real insight here, and really why I think autonomy
is the biggest thing in HAGG is not actually for
the automation itself. It's because we're using all these sensors,
radars and cameras and light ars for safety making sure
the tractor doesn't do something dangerous. The insights that we're
gleaning from these sensors we're using for safety to do
(00:24):
the automation can then be used to feedback value to
farmers as we get this larger data set on a
performed basis that will allow them to be many orders
of magnitude more productive than previous generations. Welcome to the
restless Ones. I'm Jonathan Strickland. As you may know, I've
spent the last fifteen years covering technology and learning how
(00:46):
it works, demystifying everything from massive parallel processing to advanced
robotics and everything in between. Yet it's the conversations with
some of the most forward thinking leaders, those at the
inner side action of technology and business that fascinated me
the most. Gino Cafilero really fits the description of a
(01:09):
restless one. He graduated from Carnegie Mellon University with a
bachelor's degree in Electrical and computer engineering. He then earned
his first master's degree at Stanford University, again in electrical engineering.
He became a software engineer and later attended the Wharton
School where he earned his second master's degree, this time
(01:30):
in business administration. And in between working and learning and
asking questions, he came up with the idea for Bare
Flag Robotics. The company is in the business of providing
automation solutions for the agricultural industry. We'll hear more about
a Geno's path to bear Flag Robotics in a moment.
I just want to take a second to acknowledge that
(01:52):
a Geno's enthusiasm and attitude towards taking on challenging problems
and finding innovative solutions is absolutely content pages. I guess
what I'm saying is that during this conversation I geeked
out more than just a little bit. As you'll hear,
the Geno's work focuses on a sector that's a blind
spot for a lot of people. There's a misguided concept
(02:14):
that farming hasn't significantly changed for decades, when in fact,
the agricultural industry represents a field where bleeding edge technology
and the benefits of high speed, low latency, connectivity are
fueling monumental changes. But before we get too deep into that,
I first wanted to learn more about a Gino himself. Well, Gino,
(02:38):
First of all, let me welcome you to the Restless Ones.
It is a pleasure to have you on the show, Jonathan,
Thank you so much. It's a thrill to be here.
I first like to get to know my guests before
we start diving into all the nitty gritty. So the
question I have for you then, is how did you
first get interested in technology? What was it that sparked
(02:59):
your desire to pursue that, Johnathan, that's such a broad
prompt um. I mean, the five year old boy and
me always love taking things apart and understanding how they worked. Right,
All my toys were always in pieces. I was always
asking my dad to help me put it back together,
just because I wanted to understand how it worked. And
(03:19):
then the adult went to engineering school, became a software
developer by trade, formerly an electrical engineer. But in the background,
I've always worked on projects in the garage, working on
old Beater trucks and trying to build anything that I
thought was cool, which you know, fast forwarding to bear
flag was actually, you know, the skill needed. How can
we marry cutting a bleeding edge robotics and software with
(03:43):
the physical world. And that's the quick version of how
we got to where we are. I love that because
it starts off with taking things apart and then learning
how to put them back together again in order to
have them work again. It's it's like the perfect genesis
story of an engineer. Well, I think the old adages,
you know, if it's not broken, it doesn't have enough
(04:03):
features yet. And certainly, certainly something we've fallen in the
trap of. Before you talked about becoming a software engineer,
you were working a lot with companies that were really
focused on developing and supporting infrastructure. What sort of lessons
did you learn along the way as you were working
through these jobs. I'd love to say that, you know,
(04:26):
my career was just deliberate sort of, Hey, I'm gonna
go from step A to step B because I know
I want to get to step X, you know, someday.
But maybe some folks are like that. My foresight was
not that strong, you know, very very tactically. I did
try to set myself up on teams to understand how
problems are solved at scale. I'm always fascinated with this,
(04:47):
how do we take something from a whiteboard to having
world impact? And I'm very lucky that in previous jobs
is able to do that. I was super fortunate to
be in the room when my previous company they were
just white boarding out how they wanted to do this solution,
and you know, listen, every single thing on that whiteboard
changed over the course the next five years. Don't get
(05:09):
me wrong, but it was cool to be in that
room and have mentors and people that I highly respected,
having these lively debates about how we want architect solutions
and thinking not only about how we're going to do
step one through two, but also step like through a
hundred as well. And that paradox was thrilling and then
something we lived through completely at Bear Flag as well.
(05:31):
The ideas that we had when he founded the company
were based in sound reason about what we knew to
be true in the world, but they have all very
quickly as we learned new things and had more experiences.
I would say that while I was extremely fortunate to
work on these incredible teams with folks who have shaped
(05:53):
industry in the first half of my career, I found
a true passion here in agriculture. I remember having this
distinct thought early in my career that hey, listen, I'm
okay at this and I can do this, but it's
not what lights me up. I don't leave work and
think about this. I'm not thinking about this that stop
signs and in the shower and on the weekends and
when I'm doing other things. For some reason, the dots
(06:15):
connected so clearly that I won't have the impact that
I really want to have in my life if I'm
not passionate about what I'm doing. And that's why Baar
Flag has been such an incredible journey. It's been thrilling
and awful and exciting and terrifying. But the glue there
is the passion for what we're doing, and I think
that's why a lot of folks on the team are
working hard. Here. Can you talk a bit about the
(06:35):
genesis for bear Flag Robotics. I was at a really
fortunate juncture in my career. I just finished business school
and I was spending time with my in laws in
rural Oregon. By father in law is a commercial fisherman.
The other one's a professional water well driller, and as
you know his company, but my wife's uncle actually owns
(06:56):
a construction aggregate rock quarry in Williamtte Valley, and I
was exceedingly interested in that. So I went out with
Tom and his son Eric and spent some days with
them and learned about that operation. Honestly, just because I
was curious. I want to know more. This is really cool.
This is an industry I knew nothing about. When I
talked to Tom and Eric quite a bit and started
to understand about how they think about their operation. And
(07:17):
they own their land, they have their equipment paid off
there on top of their finances. They just can't find
labor at wages that makes sense for their operation. This
is right. You know, when cruise was making big news
and Weymo was becoming sort of an idea in engineering
circles right, and folks were starting to pay more attention
to a V and the dots started to connect for
(07:38):
me that hey, we can really help quite a bit here.
And so I started noodling on these ideas and started
looking at other industries to you know, obviously mining within construction,
marine trucking applications are coming online. So there was a
lot of movement and I called up one of my
very close friends from undergrad, Aubrey, and she's an engineer too,
but a gun into consulting and I was like, hey, Obbs,
(07:58):
listen like this idea, like can you read team this
with me? Can you shoot some holes in it? And
we started talking and you know, you know, half an
hour talk started turning into three or four hour talks
just about the space, and sort of our excitement kept
feeding off one another, and albody's like, hey, do you know,
I think this is actually pretty pretty solid, Like there's
something here, there's a they're there. And so we spent
(08:20):
you know, four or six weeks really looking at mining
and then the story fast forward and I was trying
to meet with mining customers just to understand more, and
I had the privilege of visiting a farm in Wheatland, California,
And like I said, it sounds corny, Jonathan, but like
that day really did change our lives. They said, listen,
like the rock quarries here, this this isn't really our problem.
Our pain point is in the orchard. We just can't
(08:40):
find labor to run these tractors and do these operations
we need for our business. Can you help here? And
very shortly after we became an agriculture company. Clearly, the
labor issue is a huge part of why automation is
so important already and going to become even more important
in agriculture over the years. Are there other elements of
(09:01):
agriculture where automation is just going to be transformative in
that industry? Here's the big idea. So the labor problem
in AGG is the existential threat. You cannot talk to
a farmer without them talking about some sort of labor issue.
The folks that they have on their farm, the high performers,
(09:21):
the folks who come in on time, understand the operation,
or easy on the equipment, are dependable. Those are the
m v p s of the operation. They're the most
valuable folks, and farmers will do anything to protect those folks.
But it's just increasingly difficult to find more really good folks,
and so they're looking for automation anyway they can, and
we can add a tremendous amount of value doing that.
(09:43):
The real insight here, and really why I think autonomy
is the biggest thing in AGG is not actually for
the automation itself. It's because we're using all these sensors
bare flag use radars and cameras and light rs and
there's other sensors to the we've experimented with. But we're
using these sensors first for safety, right making sure the
(10:04):
tractor doesn't do something dangerous harm equipment, you know, God forbid,
harm a person. But those same sensors that we're using
for safety are being used constantly as we go through
these fields. The insights that we're gleaning from these same
sensors we're using for safety to do the automation can
then be used to feedback value to farmers. And as
(10:25):
we learn more and as we get this larger data
set on a performed basis, we can provide these insights
to farmers that will allow them to be many orders
of magnitude more productive than previous generations. That's that's the
really big idea, that's the exciting part. Yes, we're gonna
help farmers today, Yes we're gonna allow them to farm
more with less, but this is really just the tip
(10:47):
of the iceberg. And if you look forward a decade,
two kid decades, god forbid, over the next century, the
kind of positive impact we will be able to have
on the global food supply is really exciting. That's why
we're here. That's the big idea. To me. It's so
exciting because we're looking at sort of the genesis of
the transformation of agriculture, right We're seeing that moment where
(11:08):
it's going to explode, and we aren't entirely sure what
the landscape is going to look like afterward. But the
potential benefit of having more efficient farms that are growing
what needs to be grown, when it needs to be grown,
getting to where it needs to go, addressing shortages where
they are. It's the sort of text story that I
(11:31):
personally find thrilling and inspiring. I couldn't agree more. One
of the things maybe for the listeners to know, you
Bare Flags a start up. In the fall of twenty one,
we are acquired by John Deere, and so now we're
a start up operating inside of John Deere. And the
CEO of John Deer recently was giving a talk and
I was happy to be in the audience and the
insight he had his listen Like John Deere historically has
(11:53):
been very good at doing more with more. We could
always produce bigger equipment, higher uptime, bigger engines. And now
the challenge of our generation today is to do more
with less. And when we look at the kind of
technology that Johndear is investing in like see and spray,
this is technology that allows you to spray exclusively weeds
rather than drenching your whole field in applicants and you
(12:14):
can just select specifically through computer vision the weeds to spray.
And then obviously autonomy and push through electrification now too,
how can we grow more with less? And that's an
idea that is extremely attractive to us as we think
about a sustainable future. As I understand it, your company,
what you do is you take these pieces of equipment
(12:35):
that have been manufactured and then you retrofit them with
the various sensors and systems. Is that correct, That's exactly right.
So the you know, the one liner for Bare Flag,
you know, as a startup, was we build autonomous technology
for farm tractors. We had no interest in building the tractors.
We didn't anticipate we could create a lot of new
value there as far as the farmer is concerned. But
(12:58):
we would procure the machines attractors themselves from rental fleets, dealerships,
customers themselves, put the sensors, compute necessary to make them
autonomous on them and the deploy them as a service,
and it was working really well. We were really making
waves and picking up the clip on operations. That being said,
we have had a long standing relationship with John Deer,
and when they propose that we partnered together, we sort
(13:20):
of looked at each other and like looked at our
mission realized that hey, listen, we're on a march here.
We can do this the hard way, or we can
do this the fast way, which is to work with
John Deer, which has the largest install base in the world.
Talking to their leadership, we were very quickly understood their
priority to get autonomous to the world, which aligned with
our priority to and it's been a really good fit. Well.
(13:43):
One thing that we on the Restless Ones love to
talk about is connectivity. And when you're talking about automation
and you're talking about sensors and you're talking about gathering
data and you're talking about these massive pieces of equipment,
my first ideas that connectivity apps slutely has to be
kind of the underlying foundation that makes all that possible.
(14:04):
Can you speak to that a little yeah, I mean
we we recognize that too. You know, there's really two
types of data transfer. One is you know, the back
haull of all the data you get, and these can
you know, inform our machine learning models and help train
our tractors to operate better. But then also just the
pure insights that are getting from those fields that we
can then use and turn around and deliver value back
(14:26):
to that farmer on top of the operation itself. But
then there's also the real time command and control. The
bare flag machines had these real time videos web based interfaces.
You could basically have the incab experience from your tablet
as you monitor your fleet while you're driving your truck
around the ranch. And so connectivity was especially cord of that.
You know, we borrowed a lot of technology ideas from
(14:49):
other folks in the industry who working in parallel industries
around how can we degrade the resolution of the video
when we have lower connectivity and things like that. But truly,
one of the biggest enabling technologies of autonomy and all
this goodness we're talking about really is that connectivity. Well,
and and you were mentioning that sort of in cab
(15:10):
experience of being able to view the situation as if
you were actually sitting in the tractor as it's going
I imagine for that to be useful, to be really useful,
you need to have connectivity that has very low latency
so that you see what's going on as it's going on,
as opposed to, yeah, this is what your tractor was
doing five ten thirty seconds ago. That's exactly right, Hey listen, Like,
(15:35):
there's also other really cool ideas. You know, in the future,
you know, autonomous tractors will be a RoboCop. They'll do everything,
they'll do it better than the human all the things.
We're not there yet, and we're frankly like not that
close to that, so there's still has to be human interactions.
So while that machine can autonomously till or cultivate or
harvester plant that field, you still need to move it
(15:56):
to the next field. And so things like remote piloting
come into play where hey, listen, I don't want to
drive out twin dang minutes to drive this tractor thirty
across a private dirt road. Can I just remote control
it from my iPad? And the answer is absolutely yes,
you can, but you need connectivity to do that. Oh yeah, yeah.
Anytime you're talking about actually controlling the vehicle, particularly one
(16:18):
as enormous as the ones we see in the agricultural industry.
Then obviously having that ability to have a low latency
connection is absolutely critical. We would want to make sure
that whatever is enabling the decision making has the lowest
latency possible, because you can't react to a hazard that
(16:39):
actually happened five seconds ago, then it's too late. Conventional
thinking says you have to pay more to get more.
I want the world, But Team Obile for Business uses
unconventional thinking to deliver premium benefits for better r o
I from customized five G solutions to three sixty we
(17:00):
help you reach your business goals right now. I wanted
now innovating to improve business today and tomorrow. That's unconventional
thinking from t Mobile for Business. Capable device required covers
not available in some areas. Some require certain planter features
mobile dot com do your farmer's interface with this technology
(17:25):
in a direct way or is this truly attractress as
a service where you have your own team working on things. Yeah,
So talking specifically to bear Flag, one of the things
that we really emphasize is getting the market as soon
as possible. Startups in general usually wait too long to
go to market, and we knew that was a trap,
and so we tried to get in the field as
(17:46):
quickly sposible. What that meant is that in the very
early days, listen, the solution was not fully baked. It
would break in new and novel ways we've never seen before,
you know, quite frequently, and we needed folks in the
cab to finish that job up by hand the farm.
The farm is not paying for an experiment of science
project in this field. He's paying to have that field tilled.
And while early doctors did have a ton of patients
(18:06):
and curiosity, at the end of the day, they had
a job to do and we need to do that
for them. And so a service model really makes sense.
And you see this a lot in robotics in general.
Robotics companies that are early often do adopt service models
because they can develop their technology and parallel to developing
their business. But as we matured more, there was more
and more that we're handing over to the grower. Fundamentally,
(18:27):
it'll be the farmer operating their equipment. That's the direction
we're going. I remember reading a research study in robotics
where the goal was to teach a robot how to
open a door, and the robot stared at a door
for two full days before even attempting, because these are
non trivial engineering and robotics problems. So having that approach
(18:50):
where you are cognizant that ultimately the farmer has a
job that needs doing, so you cannot just leave it
to chance that everything works perfectly. This whole system is learning.
Every single time you have a different field, your system
is learning. It is adding to the base of knowledge
that all the different systems draw from, and that it
(19:12):
improves over time. I could not agree more. Would you
say it's fair to say that now big agricultural machines
like tractors have joined the Internet of Things? Is that
an accurate description? Oh? Yes, without hesitancy, and quite frankly too,
even before fair flag and autonomy came along. These tractors
are extremely sophisticated devices. The number of computers on this
(19:37):
machine parallels a car. Right. These farming operations are massively impressive,
huge oftentimes public companies farming at scale. You know, they
run their operations like any sort of manufacturing company would
they have. They understand everything that's going on all the time.
Their devices are connected they have predictive maintenance on their machines,
(19:57):
they have GPS technology for guidance to make sure they
don't have overlap, and you know, allows their drivers to
go longer without fatigue. All sorts of technology enables these customers.
Can you talk a little bit about the conclusions that
farmers will be able to make based upon the data
that's being gathered by these devices just as they're going
(20:17):
about their job of tilling or harvesting or what have you. Yeah,
and this is one of the coolest parts. Right. The
future is an exciting place, and I'll touch like very
quickly on what's possible. Farming is a problem with some
of the most variables that I know of in the world.
Right there's weather concerns and crop concerns, and disease concerns
and soil concerns, and market prices, labor markets and biology
(20:40):
and all sorts of things. And so it's actually really
hard just to run simple experiments about hey, you know,
a B test this field in this field because it's
so hard to control all your variables. And so as
we are able to collect all kinds of information about
farmers field over then nextent amount of time, we can
actually start to pull out those experiments and hide site
post hoc and that's the real value. That's where we'll
(21:03):
be able to glean the insights, and that's what we're
working towards. That being said, it's not all slidewear, it's
not all tomorrow. Very specifically, what we were working on,
we you know, bare flag at the privilege of working
with one of the largest cotton growers in the United States,
and they would rotate with another crop called staff flower
to make sure the nutrients are put back in the
soil properly. And so what we would do is we
(21:24):
do the spring tillage pass which is on a fallow field,
a field that doesn't have crops, and we'd be able
to understand how compact that soil was, and you could
actually see in the data where someone had driven a
tractor across that field. Dagon really to cut across the
field because it so will be more compacted there, and
that would show up in our data. And then we
could link that to the spring passes we made while
(21:45):
the sap flowers growing and use our lighters two sense
the canopy volume and then start to correlate. Hey, listen,
like it wasn't obvious to the human eye, and it
wasn't obvious because we didn't have these insights. But we
can actually see now where that saff flyer or has
more canopy volume, and we can go back and fix
those spots and anticipate where that is to increase yields.
(22:07):
These are really exciting things once again that weren't obvious
to the naked eye before, but we can start to
do through robotics to actually increased heield once again, you know,
doing more with less. This is beautiful, this idea of
patterns and and meaning emerging from the collection of data.
This is obviously the sort of the promise of big
data at large, right, you know that you've got all
(22:29):
this information and now comes the task of finding how
to stiff through that, find the signal versus the noise,
find the meaning. There the idea that this is something
that is applicable across the entire industry, but it's also
going to be customized, tailor made for each individual region,
each individual field, because as you say, the real world
(22:51):
is a terrible test environment. There's just you have no
control over so much that can impact the whole process.
That's exactly right, Well, I have to also ask you
what are some of the constraints on modern farms from
a technological standpoint. You know, we were just talking about
all the variables that you can't control for technologically. What
(23:13):
are some of the constraints you have to work within.
One of the broader challenges, Jonathan, is, like you said,
every farm is different, and so a challenge for a
company like bear Flag is picking what are our beachheads
where we gonna get a foothold, what sort of collection
of farms are similar enough that we can start to
build a business around as we extend into other types
(23:36):
of crops, And then even then it's like, okay, great,
these farms that have some similarities, well they do sometimes
you know, on the low end, four different types of operations,
all the way up to you know, ten or twelve
different types of operations with their attractor in that same field.
And so as the startup, once again, how are we
picking the operations we're gonna do If we can only
do two of those twelve, how much of how you
are we actually giving to that farmer? And so when
(23:57):
I think about the barriers to adoption, you know, why
do in every farm in the world have autonomy. Today
I reflect on just how broad agriculture is, not only
crop to crop, but season to season and region to region.
There is just so much value to unlock and then
to deliver. This will be the work of a lifetime.
I also have to ask you you were talking earlier
(24:19):
about being acquired by John Deere, that partnership that's been formed,
that you were operating as a kind of an independent
startup underneath the auspices of John Deere. For those looking
to understand the integration of a startup into an established enterprise,
what was that process like, what sort of challenges did
it present and what sort of opportunities has it opened up?
(24:41):
To start with? The reason it was obvious was a
culture fit. We'd had the privilege of knowing the folks
that John Deere we're in their startup collaborator in nineteen
got to know the business development folks, but then also
the engineers in the leadership, and started to have time
to really understand who these folks were and what made
them tick and what inspired and motivated them. And it
was very clear was a lot of the same things
(25:02):
folks at John Deer really care about the higher purpose.
They really care about the mission. They care about taking
care of farmers, they care about the quality of the
products that they deliver, and they have immense pride in
the brand. And that's something that we felt the same too.
Write like, nothing about agriculture is easy, nothing about startup
is easy. But there's this intense desire and passion and
(25:24):
drive to have that impact, to deliver that value. And
we made the same personal connections with our customers and
our farmers as Deer has with theirs, and so finding
this commonality between this higher purpose is what makes it work. Now. Listen, Yeah,
like Bare Flag is a small, scrappy startup, so there's
gonna be differences. They're the main thing to call out.
This isn't like old school thinking, our new school thinking
(25:45):
that you know, the folks a John dere are some
of the sharpest that I know in agriculture. It's just
how you steer a massive cargo tanker compared to how
you know, steer a ski boat. Like, they just take
different skills and they have different strengths, and so figure
out how we complement each other has been really exciting.
There's a strong model here to Johndie required Blue River
(26:06):
Technologies about five years ago now, and that was a
really good model for success. It was, hey, listen, we're
going to support you and every way you want, but fundamentally,
we're gonna leave you alone here and allow you to
keep doing what you do, keep that lightning in a bottle,
keep you being creative and motivated, an ability to move
quickly without getting in your way, and Johnie has done
a remarkable job at that. Before I could let a
(26:29):
gino go, I had to ask him one more thing. Okay,
here's the one that I gotta know. What does the
farm of the future look like? Yeah, oh man, I
think it's an evolution. Right listen, I'm gonna give you
an answer, and you'renna think it's a cop out, But
(26:50):
then we're gonna get to the goodness. The cool thing
about farmers is two things I've learned. They'll always shoot
you straight, which might not always be comfortable, but it's
always useful. And what you have delivers value. They will
be quick adopters. These guys don't chase trends. They are
especially as stute. It's sniffing out bologny and cutting to
(27:10):
like what can actually deliver value to their farm. And
so as we iterate. The most important thing as we
go will be to demonstrate that we are delivering value
every increment. This is sort of like you know evolution, right.
Evolution is such that the mutations always need to benefit
the species in order for them to be adopted as
you go right, and we end up with these incredibly
complex sort of like eyeballs and hearts, you know, and organs,
(27:33):
but they're always iterative steps. And I see the same
thing happening on the farm, you know, the visionless and
like you sit back and like, how can a corn
and soy grower really just become like a futures trader
on their commodity that's in their field and they don't
need to get into attractive That's that's sort of the
vision that you have in the back of your mind.
I think we're candidly a long way away from that.
Where I really see automation and autonomy helping the short
(27:54):
run is to make folks more effective, more productive, allow
them to grow more on fewer acres. When we look
at things like the economic headroom that autonomy itself unlocks,
there's a ceiling there. It's really limited by the size
of the tractor in the number of hours in the day,
but when we look at the date and the insights
that's gleaning to help it grower, have more yield, creaker
(28:15):
to lower cost. From our seat in the ballpark right now,
that headroom is limitless. There's no known barrier, no practical
limitations on growing more with less, and I think that's
the direction we go. The idea of a farmer sort
of like resting in better this iPad while the whole
farms running, I think is comical, but also to just
knowing enough farmers to know they would never be satisfied
(28:37):
doing that. They want to get out there and work
their land and run their equipment. There's an element of
that too well. Gino, I have to say, this has
been an inspiring, informative, educational conversation. I've really enjoyed it.
Thank you so much for coming on our show, Jonathan,
Thank you so much. It's been a thrill, really a
pleasure to chat. It was impossible for me to suppress
(29:01):
my enthusiasm for a Gino's work. I think back to
the challenges my grandparents faced on the farm and how
they could have benefited from the incredible technology now being deployed,
and it's really exciting to think about how data will
ultimately fuel a revolution in food production. It's the sort
of impact that everyone will experience down the chain. Increased yields,
(29:23):
healthier crops, lower costs of production. Those will benefit everyone
from the farmers down to the consumers. Will learn how
to be better stewards of the land, decreasing the environmental
impact of agriculture in the process. It's the sort of
big picture problem that can be tackled with the right approach,
and it's not about throwing technology at an issue, but
(29:46):
rather the careful application of a thoughtful approach followed by
meticulous analysis of the data we gather. That's what's going
to change the world. None of that would be possible
without the connectivity part of the picture. To realize this future,
we need those wireless connections with high throughput and low
latency in place. Five G technology is literally enabling the
(30:09):
technologies that will transform how we do business. More than that,
it's transforming the world and it's phenomenal that we live
in a time where this kind of connectivity isn't just possible,
it's here and it's growing. Please be sure to join
(30:30):
us for future episodes of The Restless ones. As I
speak with more leaders and disruptors who are building our
path to the future, I'll see you then. T Mobile
for Business knows companies want more than a one size
fits all approach to support. I want the world, so
(30:51):
we provide three sixty support customized to your business. From
discovery through post deployment. You'll get a dedicated account team
and expertise from so Lucian's engineers and industry advisors already
right now, I want it now. Three six support that's
customized for your success. That's unconventional thinking from T Mobile
(31:13):
for Business
The real insight here, and really why I think autonomy
is the biggest thing in HAGG is not actually for
the automation itself. It's because we're using all these sensors,
radars and cameras and light ars for safety making sure
the tractor doesn't do something dangerous. The insights that we're
gleaning from these sensors we're using for safety to do
(00:24):
the automation can then be used to feedback value to
farmers as we get this larger data set on a
performed basis that will allow them to be many orders
of magnitude more productive than previous generations. Welcome to the
restless Ones. I'm Jonathan Strickland. As you may know, I've
spent the last fifteen years covering technology and learning how
(00:46):
it works, demystifying everything from massive parallel processing to advanced
robotics and everything in between. Yet it's the conversations with
some of the most forward thinking leaders, those at the
inner side action of technology and business that fascinated me
the most. Gino Cafilero really fits the description of a
(01:09):
restless one. He graduated from Carnegie Mellon University with a
bachelor's degree in Electrical and computer engineering. He then earned
his first master's degree at Stanford University, again in electrical engineering.
He became a software engineer and later attended the Wharton
School where he earned his second master's degree, this time
(01:30):
in business administration. And in between working and learning and
asking questions, he came up with the idea for Bare
Flag Robotics. The company is in the business of providing
automation solutions for the agricultural industry. We'll hear more about
a Geno's path to bear Flag Robotics in a moment.
I just want to take a second to acknowledge that
(01:52):
a Geno's enthusiasm and attitude towards taking on challenging problems
and finding innovative solutions is absolutely content pages. I guess
what I'm saying is that during this conversation I geeked
out more than just a little bit. As you'll hear,
the Geno's work focuses on a sector that's a blind
spot for a lot of people. There's a misguided concept
(02:14):
that farming hasn't significantly changed for decades, when in fact,
the agricultural industry represents a field where bleeding edge technology
and the benefits of high speed, low latency, connectivity are
fueling monumental changes. But before we get too deep into that,
I first wanted to learn more about a Gino himself. Well, Gino,
(02:38):
First of all, let me welcome you to the Restless Ones.
It is a pleasure to have you on the show, Jonathan,
Thank you so much. It's a thrill to be here.
I first like to get to know my guests before
we start diving into all the nitty gritty. So the
question I have for you then, is how did you
first get interested in technology? What was it that sparked
(02:59):
your desire to pursue that, Johnathan, that's such a broad
prompt um. I mean, the five year old boy and
me always love taking things apart and understanding how they worked. Right,
All my toys were always in pieces. I was always
asking my dad to help me put it back together,
just because I wanted to understand how it worked. And
(03:19):
then the adult went to engineering school, became a software
developer by trade, formerly an electrical engineer. But in the background,
I've always worked on projects in the garage, working on
old Beater trucks and trying to build anything that I
thought was cool, which you know, fast forwarding to bear
flag was actually, you know, the skill needed. How can
we marry cutting a bleeding edge robotics and software with
(03:43):
the physical world. And that's the quick version of how
we got to where we are. I love that because
it starts off with taking things apart and then learning
how to put them back together again in order to
have them work again. It's it's like the perfect genesis
story of an engineer. Well, I think the old adages,
you know, if it's not broken, it doesn't have enough
(04:03):
features yet. And certainly, certainly something we've fallen in the
trap of. Before you talked about becoming a software engineer,
you were working a lot with companies that were really
focused on developing and supporting infrastructure. What sort of lessons
did you learn along the way as you were working
through these jobs. I'd love to say that, you know,
(04:26):
my career was just deliberate sort of, Hey, I'm gonna
go from step A to step B because I know
I want to get to step X, you know, someday.
But maybe some folks are like that. My foresight was
not that strong, you know, very very tactically. I did
try to set myself up on teams to understand how
problems are solved at scale. I'm always fascinated with this,
(04:47):
how do we take something from a whiteboard to having
world impact? And I'm very lucky that in previous jobs
is able to do that. I was super fortunate to
be in the room when my previous company they were
just white boarding out how they wanted to do this solution,
and you know, listen, every single thing on that whiteboard
changed over the course the next five years. Don't get
(05:09):
me wrong, but it was cool to be in that
room and have mentors and people that I highly respected,
having these lively debates about how we want architect solutions
and thinking not only about how we're going to do
step one through two, but also step like through a
hundred as well. And that paradox was thrilling and then
something we lived through completely at Bear Flag as well.
(05:31):
The ideas that we had when he founded the company
were based in sound reason about what we knew to
be true in the world, but they have all very
quickly as we learned new things and had more experiences.
I would say that while I was extremely fortunate to
work on these incredible teams with folks who have shaped
(05:53):
industry in the first half of my career, I found
a true passion here in agriculture. I remember having this
distinct thought early in my career that hey, listen, I'm
okay at this and I can do this, but it's
not what lights me up. I don't leave work and
think about this. I'm not thinking about this that stop
signs and in the shower and on the weekends and
when I'm doing other things. For some reason, the dots
(06:15):
connected so clearly that I won't have the impact that
I really want to have in my life if I'm
not passionate about what I'm doing. And that's why Baar
Flag has been such an incredible journey. It's been thrilling
and awful and exciting and terrifying. But the glue there
is the passion for what we're doing, and I think
that's why a lot of folks on the team are
working hard. Here. Can you talk a bit about the
(06:35):
genesis for bear Flag Robotics. I was at a really
fortunate juncture in my career. I just finished business school
and I was spending time with my in laws in
rural Oregon. By father in law is a commercial fisherman.
The other one's a professional water well driller, and as
you know his company, but my wife's uncle actually owns
(06:56):
a construction aggregate rock quarry in Williamtte Valley, and I
was exceedingly interested in that. So I went out with
Tom and his son Eric and spent some days with
them and learned about that operation. Honestly, just because I
was curious. I want to know more. This is really cool.
This is an industry I knew nothing about. When I
talked to Tom and Eric quite a bit and started
to understand about how they think about their operation. And
(07:17):
they own their land, they have their equipment paid off
there on top of their finances. They just can't find
labor at wages that makes sense for their operation. This
is right. You know, when cruise was making big news
and Weymo was becoming sort of an idea in engineering
circles right, and folks were starting to pay more attention
to a V and the dots started to connect for
(07:38):
me that hey, we can really help quite a bit here.
And so I started noodling on these ideas and started
looking at other industries to you know, obviously mining within construction,
marine trucking applications are coming online. So there was a
lot of movement and I called up one of my
very close friends from undergrad, Aubrey, and she's an engineer too,
but a gun into consulting and I was like, hey, Obbs,
(07:58):
listen like this idea, like can you read team this
with me? Can you shoot some holes in it? And
we started talking and you know, you know, half an
hour talk started turning into three or four hour talks
just about the space, and sort of our excitement kept
feeding off one another, and albody's like, hey, do you know,
I think this is actually pretty pretty solid, Like there's
something here, there's a they're there. And so we spent
(08:20):
you know, four or six weeks really looking at mining
and then the story fast forward and I was trying
to meet with mining customers just to understand more, and
I had the privilege of visiting a farm in Wheatland, California,
And like I said, it sounds corny, Jonathan, but like
that day really did change our lives. They said, listen,
like the rock quarries here, this this isn't really our problem.
Our pain point is in the orchard. We just can't
(08:40):
find labor to run these tractors and do these operations
we need for our business. Can you help here? And
very shortly after we became an agriculture company. Clearly, the
labor issue is a huge part of why automation is
so important already and going to become even more important
in agriculture over the years. Are there other elements of
(09:01):
agriculture where automation is just going to be transformative in
that industry? Here's the big idea. So the labor problem
in AGG is the existential threat. You cannot talk to
a farmer without them talking about some sort of labor issue.
The folks that they have on their farm, the high performers,
(09:21):
the folks who come in on time, understand the operation,
or easy on the equipment, are dependable. Those are the
m v p s of the operation. They're the most
valuable folks, and farmers will do anything to protect those folks.
But it's just increasingly difficult to find more really good folks,
and so they're looking for automation anyway they can, and
we can add a tremendous amount of value doing that.
(09:43):
The real insight here, and really why I think autonomy
is the biggest thing in AGG is not actually for
the automation itself. It's because we're using all these sensors
bare flag use radars and cameras and light rs and
there's other sensors to the we've experimented with. But we're
using these sensors first for safety, right making sure the
(10:04):
tractor doesn't do something dangerous harm equipment, you know, God forbid,
harm a person. But those same sensors that we're using
for safety are being used constantly as we go through
these fields. The insights that we're gleaning from these same
sensors we're using for safety to do the automation can
then be used to feedback value to farmers. And as
(10:25):
we learn more and as we get this larger data
set on a performed basis, we can provide these insights
to farmers that will allow them to be many orders
of magnitude more productive than previous generations. That's that's the
really big idea, that's the exciting part. Yes, we're gonna
help farmers today, Yes we're gonna allow them to farm
more with less, but this is really just the tip
(10:47):
of the iceberg. And if you look forward a decade,
two kid decades, god forbid, over the next century, the
kind of positive impact we will be able to have
on the global food supply is really exciting. That's why
we're here. That's the big idea. To me. It's so
exciting because we're looking at sort of the genesis of
the transformation of agriculture, right We're seeing that moment where
(11:08):
it's going to explode, and we aren't entirely sure what
the landscape is going to look like afterward. But the
potential benefit of having more efficient farms that are growing
what needs to be grown, when it needs to be grown,
getting to where it needs to go, addressing shortages where
they are. It's the sort of text story that I
(11:31):
personally find thrilling and inspiring. I couldn't agree more. One
of the things maybe for the listeners to know, you
Bare Flags a start up. In the fall of twenty one,
we are acquired by John Deere, and so now we're
a start up operating inside of John Deere. And the
CEO of John Deer recently was giving a talk and
I was happy to be in the audience and the
insight he had his listen Like John Deere historically has
(11:53):
been very good at doing more with more. We could
always produce bigger equipment, higher uptime, bigger engines. And now
the challenge of our generation today is to do more
with less. And when we look at the kind of
technology that Johndear is investing in like see and spray,
this is technology that allows you to spray exclusively weeds
rather than drenching your whole field in applicants and you
(12:14):
can just select specifically through computer vision the weeds to spray.
And then obviously autonomy and push through electrification now too,
how can we grow more with less? And that's an
idea that is extremely attractive to us as we think
about a sustainable future. As I understand it, your company,
what you do is you take these pieces of equipment
(12:35):
that have been manufactured and then you retrofit them with
the various sensors and systems. Is that correct, That's exactly right.
So the you know, the one liner for Bare Flag,
you know, as a startup, was we build autonomous technology
for farm tractors. We had no interest in building the tractors.
We didn't anticipate we could create a lot of new
value there as far as the farmer is concerned. But
(12:58):
we would procure the machines attractors themselves from rental fleets, dealerships,
customers themselves, put the sensors, compute necessary to make them
autonomous on them and the deploy them as a service,
and it was working really well. We were really making
waves and picking up the clip on operations. That being said,
we have had a long standing relationship with John Deer,
and when they propose that we partnered together, we sort
(13:20):
of looked at each other and like looked at our
mission realized that hey, listen, we're on a march here.
We can do this the hard way, or we can
do this the fast way, which is to work with
John Deer, which has the largest install base in the world.
Talking to their leadership, we were very quickly understood their
priority to get autonomous to the world, which aligned with
our priority to and it's been a really good fit. Well.
(13:43):
One thing that we on the Restless Ones love to
talk about is connectivity. And when you're talking about automation
and you're talking about sensors and you're talking about gathering
data and you're talking about these massive pieces of equipment,
my first ideas that connectivity apps slutely has to be
kind of the underlying foundation that makes all that possible.
(14:04):
Can you speak to that a little yeah, I mean
we we recognize that too. You know, there's really two
types of data transfer. One is you know, the back
haull of all the data you get, and these can
you know, inform our machine learning models and help train
our tractors to operate better. But then also just the
pure insights that are getting from those fields that we
can then use and turn around and deliver value back
(14:26):
to that farmer on top of the operation itself. But
then there's also the real time command and control. The
bare flag machines had these real time videos web based interfaces.
You could basically have the incab experience from your tablet
as you monitor your fleet while you're driving your truck
around the ranch. And so connectivity was especially cord of that.
You know, we borrowed a lot of technology ideas from
(14:49):
other folks in the industry who working in parallel industries
around how can we degrade the resolution of the video
when we have lower connectivity and things like that. But truly,
one of the biggest enabling technologies of autonomy and all
this goodness we're talking about really is that connectivity. Well,
and and you were mentioning that sort of in cab
(15:10):
experience of being able to view the situation as if
you were actually sitting in the tractor as it's going
I imagine for that to be useful, to be really useful,
you need to have connectivity that has very low latency
so that you see what's going on as it's going on,
as opposed to, yeah, this is what your tractor was
doing five ten thirty seconds ago. That's exactly right, Hey listen, Like,
(15:35):
there's also other really cool ideas. You know, in the future,
you know, autonomous tractors will be a RoboCop. They'll do everything,
they'll do it better than the human all the things.
We're not there yet, and we're frankly like not that
close to that, so there's still has to be human interactions.
So while that machine can autonomously till or cultivate or
harvester plant that field, you still need to move it
(15:56):
to the next field. And so things like remote piloting
come into play where hey, listen, I don't want to
drive out twin dang minutes to drive this tractor thirty
across a private dirt road. Can I just remote control
it from my iPad? And the answer is absolutely yes,
you can, but you need connectivity to do that. Oh yeah, yeah.
Anytime you're talking about actually controlling the vehicle, particularly one
(16:18):
as enormous as the ones we see in the agricultural industry.
Then obviously having that ability to have a low latency
connection is absolutely critical. We would want to make sure
that whatever is enabling the decision making has the lowest
latency possible, because you can't react to a hazard that
(16:39):
actually happened five seconds ago, then it's too late. Conventional
thinking says you have to pay more to get more.
I want the world, But Team Obile for Business uses
unconventional thinking to deliver premium benefits for better r o
I from customized five G solutions to three sixty we
(17:00):
help you reach your business goals right now. I wanted
now innovating to improve business today and tomorrow. That's unconventional
thinking from t Mobile for Business. Capable device required covers
not available in some areas. Some require certain planter features
mobile dot com do your farmer's interface with this technology
(17:25):
in a direct way or is this truly attractress as
a service where you have your own team working on things. Yeah,
So talking specifically to bear Flag, one of the things
that we really emphasize is getting the market as soon
as possible. Startups in general usually wait too long to
go to market, and we knew that was a trap,
and so we tried to get in the field as
(17:46):
quickly sposible. What that meant is that in the very
early days, listen, the solution was not fully baked. It
would break in new and novel ways we've never seen before,
you know, quite frequently, and we needed folks in the
cab to finish that job up by hand the farm.
The farm is not paying for an experiment of science
project in this field. He's paying to have that field tilled.
And while early doctors did have a ton of patients
(18:06):
and curiosity, at the end of the day, they had
a job to do and we need to do that
for them. And so a service model really makes sense.
And you see this a lot in robotics in general.
Robotics companies that are early often do adopt service models
because they can develop their technology and parallel to developing
their business. But as we matured more, there was more
and more that we're handing over to the grower. Fundamentally,
(18:27):
it'll be the farmer operating their equipment. That's the direction
we're going. I remember reading a research study in robotics
where the goal was to teach a robot how to
open a door, and the robot stared at a door
for two full days before even attempting, because these are
non trivial engineering and robotics problems. So having that approach
(18:50):
where you are cognizant that ultimately the farmer has a
job that needs doing, so you cannot just leave it
to chance that everything works perfectly. This whole system is learning.
Every single time you have a different field, your system
is learning. It is adding to the base of knowledge
that all the different systems draw from, and that it
(19:12):
improves over time. I could not agree more. Would you
say it's fair to say that now big agricultural machines
like tractors have joined the Internet of Things? Is that
an accurate description? Oh? Yes, without hesitancy, and quite frankly too,
even before fair flag and autonomy came along. These tractors
are extremely sophisticated devices. The number of computers on this
(19:37):
machine parallels a car. Right. These farming operations are massively impressive,
huge oftentimes public companies farming at scale. You know, they
run their operations like any sort of manufacturing company would
they have. They understand everything that's going on all the time.
Their devices are connected they have predictive maintenance on their machines,
(19:57):
they have GPS technology for guidance to make sure they
don't have overlap, and you know, allows their drivers to
go longer without fatigue. All sorts of technology enables these customers.
Can you talk a little bit about the conclusions that
farmers will be able to make based upon the data
that's being gathered by these devices just as they're going
(20:17):
about their job of tilling or harvesting or what have you. Yeah,
and this is one of the coolest parts. Right. The
future is an exciting place, and I'll touch like very
quickly on what's possible. Farming is a problem with some
of the most variables that I know of in the world.
Right there's weather concerns and crop concerns, and disease concerns
and soil concerns, and market prices, labor markets and biology
(20:40):
and all sorts of things. And so it's actually really
hard just to run simple experiments about hey, you know,
a B test this field in this field because it's
so hard to control all your variables. And so as
we are able to collect all kinds of information about
farmers field over then nextent amount of time, we can
actually start to pull out those experiments and hide site
post hoc and that's the real value. That's where we'll
(21:03):
be able to glean the insights, and that's what we're
working towards. That being said, it's not all slidewear, it's
not all tomorrow. Very specifically, what we were working on,
we you know, bare flag at the privilege of working
with one of the largest cotton growers in the United States,
and they would rotate with another crop called staff flower
to make sure the nutrients are put back in the
soil properly. And so what we would do is we
(21:24):
do the spring tillage pass which is on a fallow field,
a field that doesn't have crops, and we'd be able
to understand how compact that soil was, and you could
actually see in the data where someone had driven a
tractor across that field. Dagon really to cut across the
field because it so will be more compacted there, and
that would show up in our data. And then we
could link that to the spring passes we made while
(21:45):
the sap flowers growing and use our lighters two sense
the canopy volume and then start to correlate. Hey, listen,
like it wasn't obvious to the human eye, and it
wasn't obvious because we didn't have these insights. But we
can actually see now where that saff flyer or has
more canopy volume, and we can go back and fix
those spots and anticipate where that is to increase yields.
(22:07):
These are really exciting things once again that weren't obvious
to the naked eye before, but we can start to
do through robotics to actually increased heield once again, you know,
doing more with less. This is beautiful, this idea of
patterns and and meaning emerging from the collection of data.
This is obviously the sort of the promise of big
data at large, right, you know that you've got all
(22:29):
this information and now comes the task of finding how
to stiff through that, find the signal versus the noise,
find the meaning. There the idea that this is something
that is applicable across the entire industry, but it's also
going to be customized, tailor made for each individual region,
each individual field, because as you say, the real world
(22:51):
is a terrible test environment. There's just you have no
control over so much that can impact the whole process.
That's exactly right, Well, I have to also ask you
what are some of the constraints on modern farms from
a technological standpoint. You know, we were just talking about
all the variables that you can't control for technologically. What
(23:13):
are some of the constraints you have to work within.
One of the broader challenges, Jonathan, is, like you said,
every farm is different, and so a challenge for a
company like bear Flag is picking what are our beachheads
where we gonna get a foothold, what sort of collection
of farms are similar enough that we can start to
build a business around as we extend into other types
(23:36):
of crops, And then even then it's like, okay, great,
these farms that have some similarities, well they do sometimes
you know, on the low end, four different types of operations,
all the way up to you know, ten or twelve
different types of operations with their attractor in that same field.
And so as the startup, once again, how are we
picking the operations we're gonna do If we can only
do two of those twelve, how much of how you
are we actually giving to that farmer? And so when
(23:57):
I think about the barriers to adoption, you know, why
do in every farm in the world have autonomy. Today
I reflect on just how broad agriculture is, not only
crop to crop, but season to season and region to region.
There is just so much value to unlock and then
to deliver. This will be the work of a lifetime.
I also have to ask you you were talking earlier
(24:19):
about being acquired by John Deere, that partnership that's been formed,
that you were operating as a kind of an independent
startup underneath the auspices of John Deere. For those looking
to understand the integration of a startup into an established enterprise,
what was that process like, what sort of challenges did
it present and what sort of opportunities has it opened up?
(24:41):
To start with? The reason it was obvious was a
culture fit. We'd had the privilege of knowing the folks
that John Deere we're in their startup collaborator in nineteen
got to know the business development folks, but then also
the engineers in the leadership, and started to have time
to really understand who these folks were and what made
them tick and what inspired and motivated them. And it
was very clear was a lot of the same things
(25:02):
folks at John Deer really care about the higher purpose.
They really care about the mission. They care about taking
care of farmers, they care about the quality of the
products that they deliver, and they have immense pride in
the brand. And that's something that we felt the same too.
Write like, nothing about agriculture is easy, nothing about startup
is easy. But there's this intense desire and passion and
(25:24):
drive to have that impact, to deliver that value. And
we made the same personal connections with our customers and
our farmers as Deer has with theirs, and so finding
this commonality between this higher purpose is what makes it work. Now. Listen, Yeah,
like Bare Flag is a small, scrappy startup, so there's
gonna be differences. They're the main thing to call out.
This isn't like old school thinking, our new school thinking
(25:45):
that you know, the folks a John dere are some
of the sharpest that I know in agriculture. It's just
how you steer a massive cargo tanker compared to how
you know, steer a ski boat. Like, they just take
different skills and they have different strengths, and so figure
out how we complement each other has been really exciting.
There's a strong model here to Johndie required Blue River
(26:06):
Technologies about five years ago now, and that was a
really good model for success. It was, hey, listen, we're
going to support you and every way you want, but fundamentally,
we're gonna leave you alone here and allow you to
keep doing what you do, keep that lightning in a bottle,
keep you being creative and motivated, an ability to move
quickly without getting in your way, and Johnie has done
a remarkable job at that. Before I could let a
(26:29):
gino go, I had to ask him one more thing. Okay,
here's the one that I gotta know. What does the
farm of the future look like? Yeah, oh man, I
think it's an evolution. Right listen, I'm gonna give you
an answer, and you'renna think it's a cop out, But
(26:50):
then we're gonna get to the goodness. The cool thing
about farmers is two things I've learned. They'll always shoot
you straight, which might not always be comfortable, but it's
always useful. And what you have delivers value. They will
be quick adopters. These guys don't chase trends. They are
especially as stute. It's sniffing out bologny and cutting to
(27:10):
like what can actually deliver value to their farm. And
so as we iterate. The most important thing as we
go will be to demonstrate that we are delivering value
every increment. This is sort of like you know evolution, right.
Evolution is such that the mutations always need to benefit
the species in order for them to be adopted as
you go right, and we end up with these incredibly
complex sort of like eyeballs and hearts, you know, and organs,
(27:33):
but they're always iterative steps. And I see the same
thing happening on the farm, you know, the visionless and
like you sit back and like, how can a corn
and soy grower really just become like a futures trader
on their commodity that's in their field and they don't
need to get into attractive That's that's sort of the
vision that you have in the back of your mind.
I think we're candidly a long way away from that.
Where I really see automation and autonomy helping the short
(27:54):
run is to make folks more effective, more productive, allow
them to grow more on fewer acres. When we look
at things like the economic headroom that autonomy itself unlocks,
there's a ceiling there. It's really limited by the size
of the tractor in the number of hours in the day,
but when we look at the date and the insights
that's gleaning to help it grower, have more yield, creaker
(28:15):
to lower cost. From our seat in the ballpark right now,
that headroom is limitless. There's no known barrier, no practical
limitations on growing more with less, and I think that's
the direction we go. The idea of a farmer sort
of like resting in better this iPad while the whole
farms running, I think is comical, but also to just
knowing enough farmers to know they would never be satisfied
(28:37):
doing that. They want to get out there and work
their land and run their equipment. There's an element of
that too well. Gino, I have to say, this has
been an inspiring, informative, educational conversation. I've really enjoyed it.
Thank you so much for coming on our show, Jonathan,
Thank you so much. It's been a thrill, really a
pleasure to chat. It was impossible for me to suppress
(29:01):
my enthusiasm for a Gino's work. I think back to
the challenges my grandparents faced on the farm and how
they could have benefited from the incredible technology now being deployed,
and it's really exciting to think about how data will
ultimately fuel a revolution in food production. It's the sort
of impact that everyone will experience down the chain. Increased yields,
(29:23):
healthier crops, lower costs of production. Those will benefit everyone
from the farmers down to the consumers. Will learn how
to be better stewards of the land, decreasing the environmental
impact of agriculture in the process. It's the sort of
big picture problem that can be tackled with the right approach,
and it's not about throwing technology at an issue, but
(29:46):
rather the careful application of a thoughtful approach followed by
meticulous analysis of the data we gather. That's what's going
to change the world. None of that would be possible
without the connectivity part of the picture. To realize this future,
we need those wireless connections with high throughput and low
latency in place. Five G technology is literally enabling the
(30:09):
technologies that will transform how we do business. More than that,
it's transforming the world and it's phenomenal that we live
in a time where this kind of connectivity isn't just possible,
it's here and it's growing. Please be sure to join
(30:30):
us for future episodes of The Restless ones. As I
speak with more leaders and disruptors who are building our
path to the future, I'll see you then. T Mobile
for Business knows companies want more than a one size
fits all approach to support. I want the world, so
(30:51):
we provide three sixty support customized to your business. From
discovery through post deployment. You'll get a dedicated account team
and expertise from so Lucian's engineers and industry advisors already
right now, I want it now. Three six support that's
customized for your success. That's unconventional thinking from T Mobile
(31:13):
for Business
Popular Podcasts
24/7 News: The Latest
The latest news in 4 minutes updated every hour, every day.
Therapy Gecko
An unlicensed lizard psychologist travels the universe talking to strangers about absolutely nothing. TO CALL THE GECKO: follow me on https://www.twitch.tv/lyleforever to get a notification for when I am taking calls. I am usually live Mondays, Wednesdays, and Fridays but lately a lot of other times too. I am a gecko.
The Joe Rogan Experience
The official podcast of comedian Joe Rogan.