Investing in Regenerative Agriculture and Food
Investing in Regenerative Agriculture and Food podcast features the pioneers in the regenerative food and agriculture space to learn more on how to put our money to work to regenerate soil, people, local communities and ecosystems while making an appropriate and fair return. Hosted by Koen van Seijen.
Investing in Regenerative Agriculture and Food
377 Rob de Laet - Water is key to cool the planet within 20 years
A conversation with Rob de Laet, project lead of Cooling the Climate and co-author of the book Cooling the Climate: How to Revive the Biosphere and Cool the Earth Within 20 Years. The science is pretty clear and getting clearer by the day: water cools the planet. The more living, healthy vegetation we have on this planet, predominately perennials and thus trees, agroforestry systems and healthy forests, the cooler the climate is and the less extreme weather events occur. Living plants literally make the Earth sweat and remove heat from the biosphere.
Humans have systematically devegetated the planet as Judith D. Schwartz likes to say, and the ongoing climate weirding suggests we may have gone too far. Now we're seeing real calculations: how many square kilometres do we need to regenerate to lower the global temperature by just one degree?
If this is all becoming increasingly evident, why isn’t it common knowledge yet, especially in the headquarters of banks, insurance companies, sovereign wealth funds, and governments?
This is the story of a successful entrepreneur getting drawn into water cycle restoration, planetary cooling and all the good stuff that comes with it. We share notes on why this movement, maybe the defining story of our time, hasn’t broken through yet and what we can do about it.
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In Investing in Regenerative Agriculture and Food podcast show we talk to the pioneers in the regenerative food and agriculture space to learn more on how to put our money to work to regenerate soil, people, local communities and ecosystems while making an appropriate and fair return. Hosted by Koen van Seijen.
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Welcome to another episode today with technologist innovator, inventor and a leader in the. I have to do it again. Technologist innovator, inventor and a leader Welcome, paul. Hi, good to be here and first of all shout out to Henry Dimbleby, who put us in touch and who already mentioned you in our two hour long deep dive Don't go and listen to that now, people, I'll put a link below if you haven't and who already mentioned you in our two-hour-long deep dive Don't go and listen to that now, people, I'll put a link below if you haven't listened to that yet but mentioned digital twins and said you really, really have to talk to Paul. And here we are, and I agree.
Speaker 1:We had a pre-call and I had the pleasure of doing a bit of background research into your fascinating journey into technology and, of course, the world of food and agriculture.
Speaker 1:You're definitely not deep in the world of regenerative food and agriculture, but you've played a large role in moving a lot of food like more food than most people will ever touch in their lives, and so I would love to unpack that what you see, what you have noticed, what are the opportunities of digital twins and other deep technologies that we need, that are already there that we might not even know how to use yet, so I'm really looking forward to that. This will be a wide-ranging interview and conversation, but first of all starting with a personal question in this case, how did you roll into the world of technology case? How did you roll into the world of of technology? I can see background behind you a lot of different boxes and things, probably full of cables and all kinds of um things to build. But what were you always like that? Or how did you roll into into the world of tech?
Speaker 2:well, I suppose as a child, um, you know when, when many of my contemporaries were reading kind of I don't know, innie b Blyton or books like that, you know, I was normally reading instruction manuals for cars and things like that and taking stuff apart and putting it together again and maybe making new things out of those parts.
Speaker 2:So I was always fascinated by how things work and how things are built and by machines of all sorts, and so that love of how the world works kind of drove me to studying physics at university. But even then I was fascinated by the kind of the early days of personal computers. But even then I was fascinated by the early days of personal computers and I nearly dropped out of my physics degree to do a first startup. But I always kind of knew that I wanted to work with computers and technology, and probably within startups, and so that led me into the computer industry and sure enough, about two years in the opportunity came to do a first startup and and I grabbed it. So it's, it's really it's been that way from the start and, and I suppose over that journey the technologies may have changed and evolved, but many of the sort of many of the themes have continued, particularly the the excitement of working at the interface of software and hardware systems. You know things, things that move under software control are much more exciting than just on a screen.
Speaker 1:And was it always the case for you like that interface or that connection between the hardware, physical world and the software world, or has that been gradually over time, like your first startup or the first companies you worked at and with? Was that predominantly the software side or also the stuff you could touch the hardware side?
Speaker 2:No, I think earlier on the startups that I worked in were more software focused, but I suppose then the physical world started to come in in terms of sort of the more real-time applications. So so software that interacts with the real world in terms of control, and then that led on to the whole area of what I would now call smart machines. Others might call them robots, but I think increasingly that term robots is too narrow to around is in the area of smart machines and related technologies to that, including what the modeling technologies you know, like digital twins that are hugely important in the gestation cycle, if you like, of those smart machines and I don't know if you are, if you were or are a foodie at all.
Speaker 1:But let's say, when did the food world um enter your, your professional life, not just your kitchen um in in your journey and, uh, there was quite a profound uh one, I think, in terms of scale, in terms of technology, in terms of moving parts, in terms of especially, let's say, moving things that can can go bad quite quickly if they are in the wrong temperature or are put on top of each other in the wrong order. It's, it's very different from moving. I mean, probably also, clothes are tricky and a lot of other materials are tricky, but food, specifically fresh produce, even more makes it a very interesting challenge. How did did that happen? How did you roll into the world of food? Or maybe it was always a dream to be working on food and agriculture?
Speaker 2:So I suppose the place at which I or the point at which I got involved in moving food was when I joined Cardo and that kind of happened by accident. Somebody gave my name to a recruitment consultant and they persuaded me to have a chat with somebody and they then in turn persuaded me to go and have a look at their first generation warehouse in Hatfield, and when I stepped into that kind of Aladdin's cave of technology I was completely blown away. It was their first generation warehouse in Hatfield, so it was conveyor-based and a long way from where the technology got to during my time there.
Speaker 1:What was impressive when you stepped in, Just for people to understand was it the noise, was it the smell, was it the size? Just for you coming from what you were doing before.
Speaker 2:So I'd had some involvement, certainly with robots before that, but nothing like this. This was like a roller coaster or a theme park of food. It was, you know, boxes of groceries flying around over many kilometers of conveyor and being, if you like, controlled like you trains on a track, taking the right kind of turning left and right at junctions and eventually ending up in the back of vans. And so it was all about machines for orchestrating, if you like, that picking and packing of grocery, controlled by some very sophisticated software. And I was just blown away, you know, I just thought this is like the ultimate kind of train set that I've stepped into and it was mesmerizing, you know.
Speaker 2:And I think a few months later I joined to do a one-year consultancy project. Uh, I ended up then joining permanently and I ended up staying 15 years, which, uh, given the journey I had been on with startups, I was very, you know, surprised by, in a sense, I it was never my game plan to do that, but it was a kind of a, you know it was a love affair with the technology, but also with the culture.
Speaker 2:You know of the company, which was incredibly inventive and creative, and you know, very like you know, what you experience in startups and I had experienced in other startups, even though by then, by 2006, when I joined, it was a, you know, still quite a big company. And so I think you know it was this blend of technology and invention that attracted me. And you know, during that period I became CTO, I grew a huge technology division and then handed that over in the UK Aria you know it's the sort of the sharp end of the innovation spike or the innovation factory at Ocado and we were looking at all sorts of future potential technologies in that division that might be relevant and applications that might be relevant to the future of the company. And then, in 2020, I left and the end of 2020 and decided that what I wanted to do was Right in COVID when.
Speaker 2:Well, yes, it was in the midst of COVID, which was an easy Interesting times for online retail.
Speaker 1:Yeah, well, yes.
Speaker 2:I mean, it was an accelerant, certainly. You know, arguably, online grocery delivery became sort of the fifth emergency service. You know it was something that a lot of people relied on, but also all sorts of kind of automated processes became important because of trying to keep people out of areas that were dangerous, of areas that were dangerous. And indeed, you know, there was a desire for all sorts of other smart machines to help deal with the pandemic. But, you know, one of the challenges with smart machines is that they have a different gestation cycle. To what does that mean?
Speaker 2:Well as in you know, if you think about how a new piece of technology is ideated and then designed and created and tested and prototyped and eventually put into production, you know that's what I would refer to, its kind of gestation cycle, as in. You know, like you know, a gestation cycle of an animal or a human. You know a gestation cycle of an animal or a human, but you know software and hardware has a gestation or a life cycle and a gestation cycle. So it's, you know, and digital technologies. You know software and AI and so forth. It's very different and the digital and the physical worlds are different and the really exciting things happen when the two come together.
Speaker 1:It's such an interesting point, because I think many people underestimate and I will put a video below of what you also did at Ocado Because retail online is incredibly difficult, incredibly small margins, which is you don't have the margins that a lot of other technology companies have. If you're mostly in the software side, it's a different world, which means you need to be super efficient and cutting edge and, at scale, you need to move a lot of things very, very, very smartly, and that led to an incredible cycle of innovation from you and others as well. How do you push the boundaries? How do you do this smarter, faster, which 10 years ago, when we thought, or 20 years maybe, when Okado started online supermarket or online groceries or retail in general, was more almost like picking from the supermarket itself, like the same layout, the same, like it was basically just moving it online, which, of course, is not ideal, just as we're still stuck with the same typewriter letters on our laptop, which is not ideal. So, just to the immense innovation that has happened there by merging or by using both the hardware, the robotics which has changed dramatically, I think, over the last years and the incredible sort of director software, we now have to do the dances, and COVID has pushed that and pushed it to the limits, probably in certain extents.
Speaker 1:But now, what do you see now, with the possibilities we have on all the suite of technologies it's not one, it's not just digital twins, it's not just living labs, it's not just the sw, it's not just living labs, it's not just the swarms robotics you've built. If we, I don't know, lay of the land is maybe the wrong intro into we're now talking in November 2024, it seems like everything is accelerating, but what do you see? Where those physical and non-physical will touch, what are exciting pieces for you? Of course, we're interested in food and ag, but I'm also just having you here to to see, okay, what should we know in food and agriculture? What is what is exciting to you? What is interesting, what is meaningful, what is not interesting, what should we ignore in your world? Because you, you look so much deeper and further than I think many of us do in the food and ag space when it comes to technology gosh.
Speaker 2:Gosh, that's a good question or big question.
Speaker 2:I think the first thing to say is you know there is an incredible frenzy and focus, you know, on AI at the moment, and arguably not AI in its inclusive, its wider sense, but in large language models and generative AI, and you know they're incredibly important and powerful technologies. I was on the AI Council in the UK and helping to, you know, be part of a group advising government, and so you know I'm a fan of, of ai in all of its flavors and it is a. It's a much bigger toolkit, if you like, than just large language models and generative ai. But those are what is in a sentence at the moment and that's what's kind of captivated, if you like, uh, people's attention, including, you know, uh, just, you know, normal people for whom ai wasn't a big part of their world, and for some it still isn't, but for many, uh, many more now it is because it's become much more accessible. Um, so ai has had its kind of chat gpt moment. Some other technologies haven't yet. But the point is, one of the other flavours of AI is embodied AI, which is when you put that kind of intelligence, if we want to call it that, inside a machine, inside a smart machine, and that's the smarts, if you like, like in the smart machine. But but it's a symbiotic relationship because the smart machine also can be the arms and legs of ai. It can allow ai to escape, if you like, from inside uh, you know, uh, your desktop or whatever, and uh, or a server, and get out into the physical world and and and do that with scalability, scalability and agency. So smart machines, uh, as they go around, you know, often they're controlled or orchestrated by sort of centralized kind of ai systems, but, and sometimes they're autonomous. So sometimes you know, like autonomous vehicles or drones, you know they, they're able to perform without, you know, minute to minute control. They probably still need some degree of orchestration because they need to know what you want them to do. But it's a blend of the two. And so now we've got AI, and now we've got smart machines, and now we've got smart machines. And then the third member of the Holy Trinity, if you like, is what I would call synthetic environments. So synthetic environments is a family, another family like AI and, in fact, another family like smart machines, because there are many different kinds of smart machines.
Speaker 2:It's probably worth going on synthetic environments just to point out that you know, you often say that you know, you often say to people, you know. So what robots do you have in your home? Well, I've done that. And they go I don't have a robot at home. I said, well, I think you do. And they say what I said well, do you have a washing machine? They say, oh, yes, I've got a washing machine, but that's as robots anymore, you know.
Speaker 2:So you know, a drone is a robot. A 3D printer is a robot or a smart machine, an autonomous vehicle. In fact, a normal connected car is a very sophisticated smart machine with hundreds of CPUs in it. You know controlling, you know everything that's happening. So it's, you know.
Speaker 2:There are lots of things out out there, lots of smart machines out there, hiding in plain sight, if you like. You just don't necessarily think of them as that, you know. But so there is a whole family of smart machines. There's a whole family of AI technologies, and then there's a family of modeling technologies called synthetic environments, and in that family it's got five members. It's simulations, emulations, visualizations, digital shadows and digital twins, and once again they are very different, they're complementary, but they form a family and once again there is an evolutionary cycle in there in the sense that you know everyone a lot of people are talking about digital twins now and it's in the zeitgeist and you know it's got people's attention and that's great.
Speaker 2:I'm a huge fan of digital twins, but unfortunately the term has now been so hijacked Poor Henry has had to listen to me bend his ear about this because you, I said you know, unfortunately. Well, a lot of people talk about digital twins. You know they don't mean digital twins. Sometimes what they're talking about is just a static sort of 3d diagram or render of a physical thing in the real world. That's a. That's a powerful you know thing. It may be very useful. It's not a digital you know thing. It may be very useful.
Speaker 2:It's not a digital twin, you know, and you know the key thing is a digital twin has to have that modeling element, you know. It has to be able to predict the future. It's not just a data store, it's not just a sort of, you know, a collection of data about some physical asset, the physical twin, collection of data about some physical asset, the physical twin. But then the other key thing is it needs to be connected to its physical twin in both directions. So if we think of an example of a weather forecasting system, that's a digital shadow. It takes a lot of data in from weather stations around the world, it models it, it, it predicts the weather in the future, and then you know, we, we get it on the, you know on the news, so to speak. The. That's a digital shadow because the connection is in one direction. What makes a true digital twin, in my terms, and most of the terms, is that then, when you take those insights and you use it to control the real world, you know, then you've created a digital twin.
Speaker 2:So so, anyway it the point is there is a family there of technologies. What they do is they allow you to under to understand how complex systems work they. They allow you to optimize those systems. They allow you to sort of delve back into the past. They let you predict the future. They let you understand what the implications are of the interventions you want to make on the physical world, whether they're the intended or the unintended consequences, so incredibly important in many areas, including when you want to innovate and model new technologies before they exist. So if you're inventing a new kind of robot or a new kind of smart machine, you know if you can do the modeling in silico, as it's called, ie in a digital model, it's much cheaper and faster and less risky than building prototypes in the physical world. But eventually, once you've sort of hammered out the design and you're confident that it's going to work in this digital model, then you start building the physical prototypes and putting them through their paces, and that's when you start moving on to things like living labs as being environments in which you can do that testing. So there is a whole ecosystem, if you like, that supports this blend of technologies.
Speaker 2:But the really exciting alchemy happens when you start cooking with all of them together. Where you start cooking with all of them together. And, in fact, coming on to the subject of food, my view on transformative innovation and invention is that it's very much like great cooking. You have to think about the utensils, so the technologies, the building blocks, the talent and so forth. You have to think about the utensils, so the tools, the frameworks that allow you to assemble and manipulate those raw ingredients. But the recipes are incredibly important, so the culture, the ways of working, the creativity, the ways of solving problems, so that it's that blend of the ingredients, the utensils and the recipes, just as it is in cooking, that makes it transformative. And you need, if you really want to get the most out of it, you need to work on all three of those together.
Speaker 1:So it's a sort of a, it's an amalgam, and yeah, and when you sit with somebody like Henry Dimbleby or with maybe looking at a farm or at a food operator, of course coming from the extreme high tech side of the food, like moving the food as most efficiently as possible to to our plates in the end consumer Like what do you see when you look at the, when you imagine I don't know how much time you spend on farms, but is it I'm not saying laughable or you would imagine what we could do here, or does it get very interesting for you? Or are you thinking, oh my God, this is also. This really seems like we're in 1950 in some cases. Or what do you feel or sense when you're interacting with the food and agriculture system, if that happens a lot, or if you imagine an average farm in the UK or an average farm in your area.
Speaker 2:So my first journey into agriculture and farming was long before any of what I've just talked about happened.
Speaker 2:My father, who had been a corporate lawyer all his life, retired and suddenly announced because he'd been very much involved in the kind of the birth of the Green Party in the UK and was hugely interested in the concept of organic food and self-sufficiency, which was a kind of a concept that had come out then, and a famous book called Of the Same Name by John Seymour, you know, which he and my mother read, and they were captivated by that.
Speaker 2:And they, they. I was just about to go off to university and they said, oh, we've decided we're going to go and buy, you know, a farm in Wales and that's what they did. So, just when most people, you know, retiring at the age of 70, you know, might have put their feet up and maybe done a bit of gardening, you know, on the allotment, my father and my mother and indeed all of us in different ways, headed off, you know, to this hill farm in Wales and it was an extraordinary eye-opener about just how, how challenging, you know, farming is, especially with animals, and you know it's a 24 by 7, you know job, and in all weathers and with all the unpredictability that weather and conditions bring, and I think we get, we have been getting better at that, but still we've been getting better.
Speaker 2:But you know I can tell you, on a on a hill farm in Wales, it's pretty rugged.
Speaker 2:On a hill farm in Wales it's pretty rugged, you know you do get some sunshine but it's, you know, snow, wind and hail is all too common at that altitude and you end up, you know, you, you, you. So it's, it's very challenging, but it was also an amazing sandpit for creativity. So you know, I used to spend my time building machines, you know, with my eldest brother, you know, welding stuff together, making crop sprayers and making new machines for doing things in the farmer. But we were also doing things like building a biogas generator to turn, you know, the pig shit into gas, and anyway. So it was a sandpit, you know, for, for, for starting to explore different ways to, you know, in a, in a kind of a very kind of simplistic way, automate aspects of that but also and unoptimize it, although we weren't building, you know, digital twins of it, but the so that was my first taste, if you like, was my first taste, if you like, and I came away from that and it's still.
Speaker 2:I look back on that as some of the sort of the four or five most precious years of my life, you know, in terms of what I was able to experience there, but also with a huge degree of admiration, if you like, for people who do that, you know, day in, day out, you know for the whole of their lives. So then obviously, you know, got into food in a different way. But then when Henry, during COVID, asked me to join the advisory board of the National Food Strategy, you know, particularly in terms of offering kind of technology advice, you know, I jumped at it because I just thought this is, it's such an important. It's important at the best of times, but it was incredibly important, you know, during the pandemic. So, but also not just the food system as it is, but the fact that we need to be, you know, finding ways, you know, for it to be more sustainable, both for us as humans in terms of healthy eating, but also in terms of the impact on the planet. And obviously, if anybody listening hasn't read the National Food Strategy, I would commend it to them. It's amazing, but one of the things in there, which I think was chapter two, was about systems thinking and was about and one of the recommendations was around, if you like the need to create a data ecosystem for the for the food system, and perhaps come back to the second one. But but the first one is important because systems thinking was incredibly important. You know, in terms of Ocado, what we did there, because you need to optimize it in an end-to-end system, but it's also incredibly important in all sorts of systems.
Speaker 2:The food system is a very complex system of systems, but it sits within a wider set of systems, whether that's energy and transport and logistics and healthcare and so on, and international trade. So our everyday lives are an amalgam of many different kinds of systems and if we want to understand them better, you know we model data and modeling are absolutely key. You know how we collect the data, that that we need to build the models, but then you know building the models and then using those to answer questions, but also to do things like you know, optimizing the behavior of those smart machines we talked about earlier, using those to answer questions but also to do things like you know, optimising the behaviour of those smart machines we talked about earlier. And then, coming back to your question, so if we when I look at now, at agriculture, or indeed many other systems, from, you know, transport to energy, to defence, to healthcare, you know there are extraordinary opportunities, you know, not just for AI, but for smart machines and for modelling and for, you know, remote sensing and the internet of things, and for living labs, labs, you know, and so it. That's part one of the reasons why one of the first things, uh, one of the organizations that I, I'm a government organizations, I'm I'm still involved in, it's called the robotics growth partnership, which advises government on smart machine, um, uh, and robotic uh technologies, and uh, back in 2022, we authored something called the cyber physical infrastructure vision, which is really about how we can use that blend of technologies that we've been talking about, but at a national scale, or, as I like to put it, how do we build a better lego set for the UK or, ultimately, for the planet? You know, because we need.
Speaker 2:We need to change the way in which we build things, whether that be infrastructure or public services, or products, all kinds of products and services, because we need to do it in ways that are, you know, more sustainable, more efficient and more affordable. So that's one of the things that's really excited me in recent years is that idea of how we use all of these different kind of technologies, but at a national scale and ultimately a planetary scale. And that includes, if we want to zoom back to agriculture, you know the opportunity, you know to use automation and optimization to improve yields, to improve sustainability and, if you like, find new ways in which to turn photons from the sun into calories, which is the game that we're really playing when we grow food but to find new ways of doing that that are not only healthier in terms of the products but also kinder to the environment. And one of the challenges we face with that is when you want to compare conventional agriculture with alternative forms of agriculture, like vertical farming and algae and lots of other things like that.
Speaker 2:You know the problem is that it's not a like for like, and conventional agriculture, as many of your listeners will know, you know has a lot of hidden externalities.
Speaker 2:So you know whether it's, you know, pollution or soil erosion or effects on flooding, or chemicals, pesticides you know all of those things have an impact, if you like, on the environment. But when you are working out, if you like, the net cost, if you like, not just to the consumer but to society, they often don't get taken into account and therefore we need to find ways to understand those externalities and once again, the National Food Strategy talked about that in detail. And one of the ways we can do that is through modeling. You know, we can produce, you know, potentially digital models of a theoretical, if you like, farm or field or whatever it is part of the outcome, and model those externalities and understand, or start making a step towards understanding, what their true cost is, if you like, in a whole of life sense, so that when you, you know, you, you buy an apple, you know, yes, you're buying an apple, for you know whatever it costs, but what does it cost, uh, if you like, uh, the planet to to grow that apple, and what would that be like if it was grown in a different way?
Speaker 2:Um, and obviously the whole push towards sustainable agriculture is trying to get to somewhere in between whereby we can have, you know, the benefits of conventional agriculture, but without some of the current negative, unintended consequences and because it feels like there's such a powerful tool set like these three families and within them, um, like an immensely powerful tool set, um readily available or coming available or, in many cases, um.
Speaker 1:But it also feels it's mostly ignored by food and ag. I mean, we see a lot of investments going into ag tech or we saw and it's cooling down a bit, um, robotics have a name but it always feels very superficial in general, like it doesn't feel part of a much bigger vision and it sort of seems I don't know why. That is why food and agriculture hasn't embraced or hasn't at least interacted with like the simplest forms of just modeling one or two farms and seeing what are the externalities, what are the net negative, what are the the net negative and the net positives that it's producing, etc. Like how do we, if we would change this in management, what would happen without changing it? One of the many um issues with farming is is you have a harvest every year, or even less if you do perennial, and and you just the iteration cycle is so long and so slow that it's very, very difficult to imagine or to have a culture of innovation. A lot of this suite of technologies could fix part of that, because you could iterate very quickly or you could model and understand what potentially will happen.
Speaker 1:And yet I don't see people talking about, okay, what would an agriculture system in the UK? I mean, you've done some of that, I think, with the food system, but what could it look like? Or what somebody on the podcast just a few hours ago said. We lack the imagination. We cannot even imagine what a food system looks like and we're just stuck in. Okay, this just gets worse over time. Let's just put a few Band-Aids left and right. What do you feel? What's the blockage there? Is it a mindset? Is it age of farmers? Is it we just don't care too much about?
Speaker 2:the countryside, like what's the? Because the tools are there. It seemed to be there and only getting better every minute. So it it's. It's a lot of different things. So the first thing I would say is look, the, the technology does uh, you know is there but in many cases needs to mature further. You know, smart machines are getting smarter, they're getting more capable, you know, particularly on the back of ai, not just in terms of the intelligence within them, but the, the power of ai in the design process, if you like, of the of the smart machine.
Speaker 1:So I really even before they're built, even before they're built.
Speaker 2:So in the kind of stage of what you would call computational design, the ability for AIs to come up with new, new solutions, if you like, for making smart machines smarter and better, often by connecting AIs to simulation models, because when you put those two together, all sorts of things happen, because the simulation allows the AI to explore the real world. You know the physical, it understands things like the laws of physics and how things move, and gravity and the constraints that come with that. So it's really important that you do that.
Speaker 1:Yeah, gravity is good. You know it's kind of difficult, it wastes a lot of energy when you fight it.
Speaker 2:so you know, as poor old you do, that, yeah, gravity is good. You know it's kind of difficult, it wastes a lot of energy when you fight it. So you know, as poor old drones know. But you know the point is you need that blend of not just AI going off, you know, generative AI coming up with all sorts of weird and wonderful solutions which actually wouldn't work in physical. But when you put it connected and this is what has been happening in, for instance, in architecture for some time I mean, you've seen extraordinary buildings that have been built where you know the design often has come from an AI but connected to an engineering model that actually puts constraints, if you like, on the creative juices of the AI to make sure that it has structural integrity and could be built and could be maintained and all the other things. So it's that combination.
Speaker 2:Well, so there is work to be done in making smart machines smarter and more capable, and that's something that you know I and others are very much involved in and we're about to publish the latest version of a strategy for smart machines that sort of takes us out to 2035. So it's it's kind of work in progress, but, but that's part of it is the evolution of smart machines, but the other part is, as your other podcast was saying, it is the sense of the possible. It is our ability to imagine futures, if you like, where these technologies have been deployed and and how. What would it look like, what would we want from it, what problems could it solve, what problems might it create? You know, and that, um, for those of us who live and breathe these technologies, it's easier to do some of that, but none of us can do it perfectly.
Speaker 2:but the um, uh, uh, but for you know, for people who don't use these technologies it's uh, it's very uh, it's much more, it's much more difficult, and that's why we need to find ways to share um, uh, use cases, to share videos, to share models of it, so that people can immerse themselves in those kind of futures and get an idea of, oh, look, what they did, you know, over here on this farm or in this you know industry, or whatever, and how might my business be different or similar to that? How might my business be different or similar to that? And once again, so modelling has a role to play in helping explore, helping people understand and have that sense of the possible. I'm going to have to stop and throw a cat out of the room because it's got in here and it's being incredibly noisy, so I'm just going to throw this cat out the side. Sorry about that. The joys of animals you know, there we go. We've had many different onesvening in different episodes.
Speaker 2:My cats like being involved in online recordings, so where were we?
Speaker 1:Yes, the imagination piece, the imagination.
Speaker 2:The sense of the possible is very important and it could help with that.
Speaker 1:That's what you're saying.
Speaker 1:We can absolutely help with that Show and even immerse ourselves, which is the word you use like what, and I I often feel we miss that, like if we look at a landscape, we look at a most landscapes are very degraded and and are not full of life, definitely, but somehow, because maybe we've lived there for a long time or we we're used to the landscape without a lot of trees or without a lot of insects, or somehow over time, it slowly went down and, like our baseline, just have been, has been slipping away and we're like this is normal and and somehow I that it's it's not normal, or at least not how it could be in 10 years or 15 years or whatever cycles we we're going through.
Speaker 1:And so I think there's, apart from managing what we currently have or managing it a way smarter, there's a huge potential of OK, what could it look like? What are the different scenarios, what are different options? With climate modeling, with what species actually could live here in 10 years, 15 years? What management we need to manage complex systems because a farm, we've made them simpler over time, but we probably need to complexify them over time, which brings a lot of challenges and we have a smaller workforce and we need more machinery and smart machinery to do that like I don't think many people can even imagine what a farm looks like in 15 years. We sort of think, okay, maybe a smarter tractor and that's sort of hit, but of course it's not going to look like that well, things like autonomous tractors and and you know, drones for microdosing well, yes, but it's.
Speaker 2:I was going to say that, yes, it's about you know the machinery to work on conventional uh farms and fields and so forth, you know.
Speaker 2:But the sad reality is that, you know, climate change means that areas that used to be farmed in that way, you know, many of them, are becoming, you know, infertile. And it's not about you know, putting an autonomous tractor on there. Actually, just the soil quality and the amount of water that you can, you can uh bring, you know, and, and, and, and, the, the, the kind, the kind of um crops, if you like, you'd need that would withstand, you know, the, perhaps the increased heat, all of that um means that we're going to have to find new ways also to grow things in areas that would be called extreme environments, if you like, or else they're just going to become deserts. So I think there's a whole area of exploration for this kind of technology. That is about how do you create ways of growing food in controlled conditions but in a landscape that is perhaps now no longer amenable to conventional agriculture, and people have been starting to do that, you know, using solar power and, and you know, effectively, huge greenhouses in, you know, deserts and places like that and it's, you know, and how do you recycle the water, and and so you know that is a whole branch of exploration but that's going to be very important. So it's it's not just about, you know, bringing technology to bear, you know on, you know on farming as we knew it, you know it's also going to be about, uh, about that.
Speaker 2:But then there's there's another strand which is back to the whole thing about how do we turn photons into calories in in other ways, um, which, um, somebody called I Boyd, who was also mentioned by Henry, I think, on that podcast that he did. A good friend of ours, you know, has done a huge amount of thinking and in this area and talks very eloquently about it, and we are going to have to find alternative ways to do that. You know which, obviously some people have been exploring with lab based meat and other people have been exploring with. You know, can we turn things like algae, you know, into palatable food? You know there are many different ways and other people are trying to grow stuff in bioreactors, you know, particularly because some of those technologies are going to be important if we want to to grow food, you know, on other planets, whether that's the moon or mars or whatever. So so it isn't just about the earth.
Speaker 2:Now, you know, people are thinking very much ahead to ways to do that kind of food creation, if you like, in very hostile conditions. So it's a multi. What I'm trying to say is it's a multi-pronged or multi-strategy approach to how we might solve this very complex problem of sustainable, healthy food production. And to do that, you know, for the whole world, you know. So we've got to make sure that the ways in which we would do it don't, if you like, are sustainable and don't just increase the problems that we have that have led to climate change.
Speaker 1:And to ask a few questions. We always like to ask what would be your main message to the investment world, the financial world either people investing their own money or other people's money about these technologies or this family of different technologies, but also the work you've been doing. What would be be? Of course, they let's say we do this on stage and they listen to this, but they also forget and people don't remember a lot of things. If there's one seed, one thing you want them to remember and to really to guide their work through, let's say what would be the one thing you want them to take away?
Speaker 2:well, I'm not sure I'm going to stick to one, but I'll stick to a few. But I think the first thing I would say is that, in my experience, everybody focuses well, not everybody, but many people focus on what I would call the outcomes, the verticals, you know, whether it's technologies or solutions or sectors or whatever, and of course, those are incredibly important because that's where the results come. But I'm much more interested in what I would call the horizontals, the enabling technologies, the enabling solutions, the, the things that let you scale, that let you be more efficient, that let you optimize, and we've been talking about some of those. So the modeling, you know, the AI, smart machines they are all about things like scalability and efficiency and reproducibility and resilience, you know, and that blend of horizontal technologies that cuts across and supports the verticals often doesn't get enough investment and it doesn't get enough, if you like, interest, I would say, you know, from governments. And there's an S at the end of that, you know, because it's a recurrent problem. Because it's a recurrent problem Because it takes it's like slow cooking, it takes longer often to build those horizontals and everybody wants the fast food, the kind of the outcomes you know, and I think we've.
Speaker 2:That's got to change, because we do need to build things better. You know in it, wherever you look, you look, you know whether it's services, whether it's products. We need to build better. We need to build for maintainability, we need to build for recycling and reuse. We need to change the materials that we use so that they are more sustainable, and so, again, it's back to that systems approach. We need to look at it from a systems approach, but we need to change the Lego. We need to change the recipes that we employ. You know, in how we go about building what we call the built environment, which is basically everything that is man-made person-made, if you like. So it's everything that isn't the natural environment.
Speaker 1:So you know we've built a lot of it now, and even a big chunk of that is man-made or managed.
Speaker 2:Oh well, exactly, or man-affected, you know, as in you know. So the natural environment and the built environment have, you know, crossed over, often in not such positive ways. So the first thing I would say is focus on the horizontals. But also one of the things about the horizontals is they lead to intersectionality. They often cut across. They're the things that connect one industry maybe with another. So solutions in one industry or one sector that you can then steal and adapt to solve problems in another and I'm an intersectionality nut. I think it's incredibly important.
Speaker 2:I think, if we stay, if we, if we stay, you know, I used to say to people when I was at Ocado you know, working for me, you know, don't go out and hang out with people and build networks with people who work in online grocery. Go off and talk to people who build lawnmowers or nuclear reactors or whatever, because you know what you may learn in those other areas. You know you may then be those other areas you know you may then be able to bring back and it may be incredibly powerful. But it's also likely to be a source of of novel thought and creation, because you know, if you're in an echo chamber of people doing the same things as you. It's probably just, you know, the same old things will go round and round. So intersectionality is very important and it's very important in innovation and invention. So it's very important to help tackle some of this growing list of exponential challenges that we've made for ourselves as a species. So it's you know, we need to get as many novel ideas into the solutions as possible, and those horizontal technologies are part of the kind of the web, if you like, that connects all those different verticals in the different areas. So that's the next thing I would say is invest in the kind of the tools that let us do things faster and more scalable, but also let us join up the solutions, uh, from different, so that we're not building everything from scratch, because obviously, the more that we can build shared solutions across different systems, you know that's good for everybody. It's it takes cost out. Uh, it means we don't have all sorts of different spares. It means we don't. It means we have greater interoperability. You know this.
Speaker 2:This happened in the pandemic when, you know, governments were asking, you know, people in the smart machine world, oh, we want smart machines to look after and clean hospital red zones. You know what have you got. And the answer is well, the answer is twofold, one or threefold. First one, the gestation cycle, means that I talked about earlier, means that you know we're not going to just be able to create them overnight. Secondly, the supply chain to build them, you know, is kind of shut down, as it was, you know, during the pandemic.
Speaker 2:And then the third thing is that you know most of these machines are not built with interoperability or reuse in other areas in mind. But there was a classic example of where you might want to take things from one place where you had them and move them over here. But the answer is you know, you need to design for that, you need to think about that beforehand and therefore the more in which there are standards and the kinds of standards that actually we take for granted in the software world. So open source and cloud has transformed how we do software. Well, we need the equivalent for hardware.
Speaker 1:We need that same sort of, those same kind of shared solutions for hardware and what would you do if you would be on the other side of the table, as as an investor? Let's say, you wake up tomorrow morning and you are in charge of a significant amount of money. We usually say, let's say, a billion, in this case pound sterling, and I'm not looking for dollar amounts or exact amounts, looking for what, our big buckets, what are things you would focus on for a very long-term potential investment strategy. But if you had to put that kind of money to work which is a bit of a weird question, I understand, but it's just. I like to ask it because I'm when resources are almost unconstrained, like what would, what do people prioritize and what do they focus on?
Speaker 2:Well, I would definitely focus on exactly what I've just been saying, which is those enabling technologies and solutions to accelerate many different kinds of outcomes. I like to think of them as wormholes. They allow you to perhaps out-compete other players who are doing things in a traditional way. If you can find a wormhole that acts as a shortcut to that and the most powerful one I've ever come across is modeling, but, you know, and, and in conjunction with AI now, as we've been talking about, so I think, um, that would definitely affect my investment. I'm I think the the um things that make you go faster and accelerate are, you know, are incredibly powerful. Secondly, um and this is very much affected, if you like, the portfolio of startups I work with.
Speaker 2:Yes, climate technology in all its shapes and forms is important. One of the challenges is that a lot of typical investment sources don't really like to build or invest in hardware, don't really like to build or invest in hardware. They prefer digital because it's cheap to build and to distribute and it's quicker to build and less risky. But, unfortunately, most of the things that we need to deal with the challenges in the physical world that we created, which is not just climate change, it's, you know, how do we have affordable and sustainable health care around the world? How do we, how do we feed everybody around the world? You know there are, and how do we have, you know, better resilience to future pandemics, because we're definitely going to have them. So, therefore, you know that that that's all going to involve physical interventions in our physical world, and so we're going to need hardware, and so we've got to get better at building it, like we've been talking about, but we've also got to encourage new forms of investment in it, because if we want these technologies and there are some very exciting climate technologies emerging we're going to have to find a way to fund not only their initial research but their scale up and their adoption. You know, and that that is often where they hit trouble, because and that is where nation states, I think, need to step in, you know, and that is where nation states, I think, need to step in, you know, and sovereign wealth funds and so forth, because we it's no longer a challenge, I would argue for traditional investment. This is the future of our species and this planet that we're playing with here, and therefore, you know there is really nothing more important. You know that we could invest in, you know, than the solutions to these kinds of exponential challenges, and we need to get really serious about that.
Speaker 2:If it's now 15 seconds to midnight or whatever it is, and you only have to listen, you know.
Speaker 2:You listen to the speeches at conferences like COP, and I think I stopped listening probably a couple of them ago, because one of my takeaways from that was there's barely any talk about better ways of collecting data, you know, more efficiently, but there's no talk about better tools.
Speaker 2:There's no talk about, you know, how do we create the sort of, you know, the tools, both to understand the problems but also to solve it. You know there's lots of talk about how technology will do it, but we've got to start innovating, if you like, on behalf of our planet rather than just, if you like, the vested interests of individual companies and shareholders and even nation states. So how we do that in a joined up way, you know, is something that we haven't got a solution to at the moment. You know we struggle to do that, you know, with healthcare, in terms of the WHO, but we're not really driving planetary scale innovation and problem solving, you know, in a joined up way, and we're going to have to because it doesn't, as we know, respect borders, you know, and so, and I'm not sure, yeah, if a billion would be enough to unlock it.
Speaker 2:A billion is definitely not enough there, but maybe what one can start doing with that is trying to nurture some of those really key emergent climate technologies, but also maybe do more of the modeling that allows you to demonstrate, if you like, what those different solutions be. At me, what you know, and that's that's kind of what you know an area that's always interested me is the whole idea of building earth twins. How do we build digital twins at a planetary scale of both our man-made systems and our natural environment? How do we collect the data scalably from, you know, on land, in and under the sea, in the air? You know how do we use space observation and satellites to do that? But building, we need all that to feed the earth twins. But you know we need all that to feed the earth twins.
Speaker 2:But you know that's something that a growing number of people are starting to talk about and there are some interesting projects there, but it's critically important because we've left it so late to intervene. We can't afford to get it wrong, and one of the things we've been talking about is models allow you to explore those futures. As long as they're accurate and you can run them at many times faster than real time, so that you can you know you can accelerate that exploration into the future. It's not like you have to wait ten years for a model to model ten years, you know you can run it many times faster than real time, and and so it's a. So I would definitely be putting some money into that, not just because I think it's important, but because it's going to be needed, so it's it's also commercially, you know, important and it's something where it could have, you know, all manner of different impacts, both commercial and environmental, and also the National Food Strategy has got a jolly good list of things to invest in.
Speaker 2:You know, in my experience, most innovation, as it's called and I don't really like the word innovation, because I'm much more interested in invention, which is more radical, but because innovation tends to be incremental, most innovation is focused on playing what I would call the current games a little bit better, and an example of that might be the fascination at the moment with humanoid robots, which are incredibly complex, costly machines, basically to try and mimic what humans do using human tools and human processes, with all the limitations that come with those, and you know.
Speaker 2:That's about finding a better way to play the current game you know of of human created products and services. I think the future lies in in finding new, completely new. We need to change the game. You know. We need to to as I've been talking about in this podcast radically change the way that we build solutions um, uh and uh, if you know, because we need to do it faster, but also because we need to do it more sustainably, but to do it with a systems approach. So don't't just find ways to automate, if you like, what we've done before, but think about it, you know, from scratch and think about it at a systems level.
Speaker 1:And so, once again, I would want to bring that to everything in that innovation portfolio thinking, you know, in terms of systems rather than just a set of individual investments and it's a great point to wrap up, and I want to be conscious of your time, but still ask one, one final question on the magic wand which we always ask. It might be actually the, the earth, uh, the earth twin or earth twins, but it might be something completely different. If you so, we take away your, your investment portfolio, but you do have the power to change one thing, one thing, overnight. We've had countless different examples, from extremely practical changing the common agriculture policy in europe to the global mindset shift and everything in between. So definitely feel free to go wild if you want to, but if you can change one thing overnight, what would that be?
Speaker 2:Okay, well, the. I love that film. I mean, mean, we've been talking. We touched for a brief moment on the idea.
