Feeding the world by AI, machine learning, and the cloud
With increasing global population and climate change, regenerative agriculture looks to grow more food with less environmental impact.
In partnership withInfosys Cobalt
Although the world population has continued to steadily increase, farming practices have largely remained the same. Amid this growth, climate change poses great challenges to the agricultural industry and its capacity to feed the world sustainably. According to the World Bank, 70% of the world’s fresh water is used in agriculture and droughts and heat waves continue to threaten crops. And that is where the challenge arises to feed the world while mitigating the environmental effects of agricultural practices.
The answer to this challenge, according to Thomas Jung, head of IT Research and Development at Syngenta, is regenerative agriculture. Just as important as clean water and clean air, soil is the critical foundation of agriculture. The crux of regenerative agriculture is to grow more food with less environmental impact by enhancing the health of soil.
“So not much has changed, but we need to feed more and more people,” he continues “How do we address this challenge of feeding the world in a sustainable fashion without exploiting our soils more?”
Regenerative agriculture efforts look to find solutions to help plants stay healthy, find solutions to make crops more resistant to climate change-induced droughts and heatwaves, and use less water in farming.
Therefore, what’s necessary is, “moving beyond the traditional agriculture and the way we've been doing this for probably 100 years or more. I mean, this is a leap,” says Jung. “This is an agricultural revolution that is ongoing, and artificial intelligence will play the decisive role in it.”
Although farmers have invaluable knowledge of their own crops and fields, says Jung, AI and machine learning tools can be instrumental in cataloging greater detail, refining algorithms, and creating recommendations for solutions. As more data is collected and algorithms continue to improve to create new innovations, we’ll be even closer to understanding our planetary ecosystem, says Jung. Breakthroughs like soil regeneration, really living with sustainable agriculture across disciplines are achievable within the next three years.
“There's a lot of advocacy for open source, for democratized data, for fair data, and we need to bring that to the industry,” says Jung. “This can't just be an NGO or a volunteering thing, that this is how I believe our industry needs to work. So we really want to share, we want to lead by example, we want to nurture the community, and through that, win altogether.”
This episode of Business Lab is produced in partnership with Infosys Cobalt.
Laurel Ruma: From MIT Technology Review, I'm Laurel Ruma, and this is Business Lab, the show that helps business leaders make sense of new technologies coming out of the lab and into the marketplace. Our topic today is innovation in agriculture. Feeding the world's population is no small feat, and farmers in the industry are faced with a number of challenges, from drought, to supply chain. However, technology can help improve crop health, diversity and yields, as well as encourage sustainability. Two words for you, scientific collaboration. My guest is Thomas Jung. Thomas is the Head of IT Research and Development at Syngenta. This episode of Business Lab is sponsored by Infosys Cobalt. Welcome, Thomas.
Thomas Jung: Thank you, Laurel. Thank you for having me.
Laurel Ruma: Could you define and tell us about regenerative agriculture? Why is it important to Syngenta?
Thomas Jung: It's important to Syngenta much as it is important for the world really, because the principle is that we want to grow more food with less environmental impact. Soil is the foundation of agriculture, and really an essential resource for all we do and all the ways we provision our food, just as much as water or clean air, but probably most forgotten about. So, regenerative agriculture really is a set of practices that we want to apply to enhance the health of our soils. For that, there's a number of principles, and most important probably is to minimize the disturbance of the soil. Agriculture still uses a lot of tilling practices, for example, where we heavily disturb the soil to keep our plants healthy. Actually, we can do with much less, to essentially leave the soil in peace and do their magic.
We can also look at diversifying crops, making sure we don't extract all the same nutrients from the soil all the time. So, working much more through crop rotations, planting different things across time and space. And probably last not least, also optimizing the application of our inputs, biological inputs, chemical inputs, all the means we have to help our plants grow. We can also do that in smarter ways so the soil stays healthy, and essentially the fields are regenerated and are not being exploited, as happens throughout the world at the moment.
Laurel Ruma: What kind of challenges is the agricultural industry facing right now? Climate change is certainly one of them.
Thomas Jung: Sure. It's possibly one of the biggest really, right? I mean, drought you mentioned in the intro, water, actually 70% of the world's water is used in agriculture, and that's an enormous figure. So how can we use less water? How do we can actually make plants resistant to drought, where there is no water or not enough water? Heat, with the heatwaves coming across all our continents actually, so how can we prepare plants for this, but also how can we help plants while they suffer from that? Not least, also in context of climate change, carbon. About a quarter of the world's emissions are from agriculture, so how can we help agriculture to be much more carbon efficient and ideally even to recapture carbon in the soils that we're using? And so there's a big playing field around climate change and how we can help.
It's not the only challenge, unfortunately. The other big one is simply world population. Looking back some just a hundred years, world population grew factor five, but we're still using the same old farming practices. Tractors, fertilizers going across the fields. Not much has changed, but we need to feed more and more people, and how do we address this challenge of feeding the world in a sustainable fashion without exploiting our soils more? How can we be respectful with soils, respectful with the environment, conserve and restore? And this needs our science, so this is a space where we can play a lot as Syngenta and as a farming community, as an ag industry.
Laurel Ruma: Right, and one of those things is that focus on people, focus on the population of the world, focus on feeding people. Your research and development team at Syngenta certainly has a certain mission, so what does that team do, and then how do you incorporate that philosophy of doing less harm?
Thomas Jung: Right. Our mission is focused at the farmer and the plant. Our mission is to help the farmer to grow healthy food for the world, and many ways to do this. I mean, the most immediate impact that we can have as Syngenta and who we are in the whole ecosystem is finding ever-better solutions to help the plants stay healthy. There's a number of options actually that are in our hands. First of all, this is a hugely-growing area. It's biological products, how can we trigger the capacity of plants to help themselves essentially by using products that the plants themselves produce? And we actually help them, multiplying this, applying principles from nature to really help plants rebuild their own strength. This is one of the probably big growth areas where we can do so much more and we're excited to drive our science in that space.
But we can also innovate a lot in conventional crop protection, synthetic, biological, so that we can find better solutions that are more targeted, more specialized, that can fight off very specific pests, that we don't need to go across any potential harm that could happen, that we can really target based on better science, based on better knowing what happens in a field, based on knowing exactly what a plant suffers from. And all of this will need our technology and our research and development to understand more and more. There's a lot of knowledge already of course in the hands as well of our growers. Agronomy is super advanced compared to a hundred years ago, but a lot of this is still being done manually and with a lot of personal thinking. And the space of digital science in there is vast, and we can do lots more, and we're on our way actually to contribute a lot here.
Laurel Ruma: So, it's kind of a leap here. We're talking about manual processes and systems, how does, though, artificial intelligence and machine learning factor into your work that your team does, so you may be at the cutting edge of some of these technologies, but then you're translating the outputs and outcomes to the farmers in the fields?
Thomas Jung: Very right. I think we are looking at a leap here, for sure. I mean, that's certainly my ambition, that's also Syngenta's ambition. As I said, moving beyond the traditional agriculture and the way we've been doing this for probably a hundred years or more. I mean, this is a leap. This is an agricultural revolution that is ongoing, and artificial intelligence will play the decisive role in this. Typically, it takes the industry more than 10 years to find new crop protection products. So there's really deep research, a lot of testing, making sure whatever we come up with is effective and safe, so we need to find ways to do this faster, to do this smarter.
Looking at chemistry, the chemical space is enormous. There are estimations that are probably 10 to the power of 60 active molecules that could make a difference one way or the other. How do we find that chemical needle in the haystack here? So, generations of smart PhDs found so many great things, but what have they overlooked, or what have they never been able to look at at all? It's impossible to search that space for any human, for any lab, even for an automated lab. And so that's another huge playing field for artificial intelligence, for machine learning, and for putting our data in action actually.
Laurel Ruma: And you mentioned the cloud, so your division made the shift to the cloud with the help from Infosys and other partners, and now you're 100% cloud. The entire company's also on track to do so as well. So, what has the shift to the cloud allowed you and your division to do in terms of innovation, and as an entire company, what are the goals now that that is the plan? What's in the future for the cloud?
Thomas Jung: Yeah, it's great timing actually that you're asking, because Syngenta as an overall company, we just shut down our last and very final data center service last week. So now even as Syngenta, we're now fully cloud-based. R&D has been for a couple of years already. The only compute that we still have locally is very limited high-performance computing capabilities for selected use cases. We do a lot of high-performance compute also in the cloud. For us, cloud is a commodity almost already. So, the whole move to cloud business, basically we've been dealing with for years ago, and now we're just reaping the benefits.
We don't think about cloud as what will it enable, but we really use it in a way that's almost business as usual for us already. So first of all, there's agility that we never had in the old world. The agility to explore, to try new things, to spin up a server, to spin up a service, to just try new algorithms or to just put gigabytes of images somewhere instantaneously. That scientific agility, it's hard to mirror in a fixed data center the world. That's just freeing up our scientists to do the best of what they can do.
The other bit is simply scalability. With the enormous data volumes that we collect, also that we process, we can't forecast, frankly. We have an idea of where we're going, but we can't do a two-year forecast of what volumes we want to be processing in December '24. So, cloud really gives us the flexibility to do exactly what our science needs, and we can respond to our needs within a day or within hours, essentially. We're not stuck within our old school forecast business. We can focus on our science, which is fantastic for our researchers. So, we deal much less with classical IT issues and focus on the digital magic that our people are doing.
Probably thirdly, just to mention, and that's to me one of the huge benefits, is collaborations. We really can't solve all that we're discussing here alone, so how can we most effectively share not only our data, but also our algorithms and the way we work? And likewise, how can we best use what other companies, universities, others are creating, coming up with, and how can we be in this together best? And of course, connecting corporate networks is a challenge, each one we need to do, so I think being cloud-based is a foundation for very effective collaboration as well.
Laurel Ruma: So, lots of efficiencies by shifting to the cloud for the internal team. How does this translate to value to customers?
Thomas Jung: Three types of customers maybe to differentiate here, and I mean my team is an IT team. My team's direct customers will be our scientists, and first of all, digital scientists. Those data scientists that look into our data and come up with so much smarter conclusions than they would've been doing before. For this type of customer, they've always been smart themselves. They've always had their computer underneath their desk and trying to render algorithms. Now they have access to much more power than they ever dreamt of. So really, being central in the cloud with the whole team brings together what they're doing, they get access to much more innovative tools, and of course to much a bigger scale, and they're connected with their colleagues, which they haven't been before.
But also, practical scientists who are in the field testing products, looking after plants, or who are in a lab, for example, working on biology, chemistry. And we'll always need those, so this isn't going to be a digital-only science at any point I think. Those colleagues, they can actually learn from the real world through data we collect in the cloud. We're bringing this back into the labs, into our scientific realities, and our colleagues can plan much better what they do, they can learn from what they see outside, and we're really closing the loop here with real-life data versus lab data.
Lastly, and most importantly, the growers, our real customers are making the big difference for the plants that we all grow together, they have access to real specific recommendations. Syngenta, we offer a tool called Cropwise which farmers can use to plan their operations in the field, but also to understand much better what practices will be appropriate at a given point in time, to select the right seeds, for example, for their particular situation, or to understand simply what's going on in the field. And also here, being cloud-based, we're making this available to farmers across the world, but we're also again closing the loop with our scientists, so our scientists can feed what they learn into the recommendations that we can give to our growers. So, we really have a two-way learning here and we can bring the learnings directly into the world, rather than waiting for years before we can do that.
Laurel Ruma: And you mentioned earlier how important collaboration is. What kind of value does Syngenta get by embracing open science and experimentation and really offering those opportunities to collaborate, whether it's scientist to scientist, or with algorithms, et cetera?
Thomas Jung: Yeah, I mean, we're taking big data literally here, and I think we can only create a real breakthrough if we work together. Syngenta alone, yes, we're a huge company, super smart people, but our datasets are still limited to what we can do. Solving the challenges we discussed earlier will need all of us to stack hands, so I believe that real breakthrough will only happen when the industry does collaborate, and we want to be the leading team and being collaborative and working across boundaries, that's across industries even, and certainly across companies, universities.
In the public sector, for example, just to call out a couple maybe. We've been working with the Open Data Institute to publish some of our data in a reusable format, raw data essentially, that scientists across the world can use, because we want to engage in that joint R&D practice. So there is data that we just share with the community, but we also care about data standards. So we're a board member of AgGateway, that is a consortium of I think what 200 or more food sector companies working on how do we actually drive digital agriculture? So we're making sure that the standards work for all and we don't end up with proprietary ideas by each member of the food chain, but we can connect our data across.
The private sector, again, it's just as important. We're lucky enough to be headquartered in Basel, which is a cluster of science really, and of chemical sciences in particular. A lot of pharma companies are around here. So, we can also exchange a lot of what we learn between pharma and agriculture, we can learn about chemistry, we can learn about practices, how we work, how we work through our labs. We're intensely in touch with our colleagues around the region here, but of course also elsewhere, and it's quite a natural cluster.
Maybe last, not least, one of the real exciting perspectives for me that I realized, I don't know, just couple of years ago, not many really, is how much there is if you look across industries. So, recently I hired somebody, a digital expert from Formula 1, and why that? I mean, if you look at this technically, steering or controlling, understanding a Formula 1 race car remotely isn't much different from steering a tractor. I mean, the vehicles will be super different, but the technology in a way has a lot of similarities. So, understanding IoT in that case and understanding data transfer from the field to control centers, it doesn't matter what industry we're working on, we can learn all across.
We're also working with a super experienced partner in the image recognition space to understand better what happens on the field, where as Syngenta, we can bring agronomic knowledge and that partner can bring technical knowledge on how to make most of the images. From a very different field, nothing to do with agriculture, but still the skills are super transferable. So, I'm really looking for talent across industries, and literally anybody who's up for our cause, and not limited to people with life science experience.
Laurel Ruma: That's really interesting thinking about how much data F1 processes on a single race day or just in general, the amount of inputs from so many different places. I can see how that would be very similar. You're dealing with databases of data and just trying to build better algorithms to get to better conclusions. As you look around the larger community, you're certainly seeing Syngenta is definitely part of an ecosystem, so how do outside factors like regulation and societal pressures help Syngenta build those better products to be part of and not outside of that unavoidable agricultural revolution?
Thomas Jung: It's a great point, because regulatory in general, of course, is a practical burden to some, or may be perceived as one actually. But for us in digital science, it's a very welcome driver of innovation. One of the key examples that we have at the moment is our work with the Environmental Protection Agency in the US, the EPA, which has stepped forward actually to stop supporting chemical studies on mammals by the year 2035. So, what does that mean? It sounds like a big threat, but really what it is, it's a catalyst for digital science. So we very much welcome this request. We're now working on ways to use data-based science to prove the safety of products that we invent. There's couple of major universities across the US that have received funding from the EPA to help with finding those ways to do our science, so we are also engaging to make sure that we do this in the best possible way together and we can really land at a data-driven science here and we can stop doing all these real-life tests.
So, it's a fantastic opportunity, but of course, a long way to go. I think 2035 is somewhat realistic. We're not close yet. What we can do today is, for example, we can model a cell. There's organ-on-a-chip as a big trend, so we can model up to a whole organ, but there's no way we can model a system or even an ecosystem at this point. So, a lot of space for us to explore, and I'm really happy that regulators are a partner in this, and actually even a driver. That's superbly helpful. The other dimension that you mentioned, societal pressure is also there. I think it is important that society keeps pushing for causes like regenerative agriculture, because this is what, first of all, creates the grounds for us to help with that. If there is no demand, it's hard for Syngenta to push it forward alone.
So, I think the demand is important, and the awareness that we need to treat our planet the best possible way, and we're also working with, for example, The Nature Conservancy, where we're using their scientific, their conservation expertise to bring up sustainable agricultural practices in South America, for example, where we're having some projects to restore rainforests, restore biodiversity, and see what we can do together there. So again, a bit like what we discussed before, we can only be better by collaborating across industries, and that includes NGOs as much as regulators and society as a whole.
Laurel Ruma: So, although 2035 is sort of that distant goal, thinking about the next three to five years, what technologies and capabilities are you most excited about?
Thomas Jung: The next three years, to me, I'm excited about finally using what we have to the best of its capabilities. I mean, we got all the tools already in a way. There are mega-trends like quantum compute, but to me that's years out in terms of real input. So talking 2035 again, for the next three years, I think end-to-end digital, and truly end-to-end, that is including what happens across the planet. Understanding the planetary ecosystem, bringing all that data together to find better solutions to regenerate our soils and to really live sustainable agriculture, connecting across all disciplines. That to me is the real achievable breakthrough over the next three years. And that, again, needs us to connect, first of all through the cloud, of course anyway, but then across industries, as we discussed before.
So, how can we bring all this together and smartly work together on these challenges? And we have all the technology we need. I don't think we need to invent much new here. It's how we use this. So, capability-wise, mostly looking for culture change. There's a lot of advocacy for open source, for democratized data, for fair data, and we need to bring that to the industry. This can't just be an NGO or a volunteering thing, but this is how I believe our industry needs to work. We really want to share, we want to lead by example, we want to nurture the community, and through that, win altogether.
Laurel Ruma: Excellent. Thank you so much, Thomas, for joining us on Business Lab.
Thomas Jung: Thank you very much for the conversation.
Laurel Ruma: That was Thomas Jung, the Head of IT Research and Development at Syngenta, whom I spoke with from Cambridge, Massachusetts, the home of MIT and MIT Technology Review, overlooking the Charles River. That's it for this episode of Business Lab. I'm your host, Laurel Ruma. I'm the Global Director of Insights, the custom publishing division of MIT Technology Review. We were founded in 1899 at the Massachusetts Institute of Technology, and you can find us in print, on the web, and at events each year around the world. For more information about us and the show, please check out our website at technologyreview.com.
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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.
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