Every year, there are a few scientific advances >> [music] >> that reach the moment where they're ready to change the world. And this report is how we find and share them. >> Welcome to Radio Davos, the podcast from the World Economic Forum that looks at the biggest challenges and how we might solve them. This week, we're looking at 10 emerging technologies that might be [music] set to change the world in the next 5 years. >> It is interesting every year to zoom [music] out and look at the cohort of 10 and see, you know, do we see any signals around where the frontier might be heading? [music] >> In that report, we learn about revolutionary healthcare treatments, how we can rethink how we generate and store energy, about AI, quantum, and biotechnologies. >> Some of these technologies are becoming much more personal, [music] personalized cancer vaccines, and and things like that, where we're really starting to think instead of like a population average, [music] we're moving towards technologies that are addressing an individual, a really specific need. [music] >> Follow Radio Davos wherever you get podcasts, or visit wef.ch/podcasts, [music] where you'll also find our sister programs, Meet the Leader, one-on-one interviews with some of the most interesting people in the world, and Agenda Dialogues, the full [music] audio from the best discussions at World Economic Forum events, including the annual meeting in Davos. I'm Robin Pomeroy at the World Economic Forum, and with this look at the top 10 emerging technologies of 2026. [music] >> It really shifts the way science is happening. >> This is Radio Davos. Welcome to Radio Davos, and yes, this week we're talking about technologies that could change all our lives in the next 5 years. And to talk about that, I'm joined by my colleague, Kimmie Bettinger. Hi Kimmie, how are you? >> Hi Robin, I'm great, great to be here with you today. >> It's great to see you, and I'm so glad we've got someone who knows about these technologies, because I have in front of me the top 10 emerging technologies of 2026 report, which you helped put together. Tell us what you do at the forum, and then tell us about the report. >> I lead our work on emerging technologies for the forum. I'm based in our San Francisco office, so helping to connect our global partners and communities with what's really on the forefront of innovation in the Bay Area and beyond. >> Right. And this report is kind of the flagship maybe of of your work through the year. Tell us kind of the history or something about the top 10 tech report. >> Yeah, so every year there are a few scientific advances that reach the moment where they're ready to change the world. And this report is how we find and share them. We've been publishing the report for 14 years. Uh so we have a really exciting corpus of technologies that we can look back on and understand what scaled, what solved, and what might still be to come. >> You have a great corpus of work. We have a great corpus of podcasts as well, and viewers can go back, I think for the last six of these reports we've done really interesting podcasts. It's one of my favorite episodes of Radio Davos of the year, because what you've got here are 10 technologies that a jury of experts has decided cuz there must be hundreds, thousands of technologies that are being worked on, but you've stripped it down to 10. Just tell us how that comes about, this list of 10. >> You're right. We start with a really broad list of technologies. We're scanning across many academic fields, many industry sectors. Um and we get the chance to then talk to the world-leading experts in different fields to understand how might we think about this set of technologies, which ones really have momentum. And then we go back and talk and look at some of the quantitative signals, too. We're looking at things like how is this moving in academia? What sort of funding are we seeing? How many patents are we seeing in this space right now? And and how's that starting to accelerate? From there, we take the list to our advisory council. This is a group of world-leading experts that sit across a wide range of kind of innovation spaces and they help us select that final 10. And really that advisory council is helping us think about impact. Not only which technologies are most likely to scale, but which ones will be most consequential for the world should they get to mainstream adoption. >> That's why this list is so interesting. It's not just 10 cool ideas. These are 10 technologies which according to your expert council could be scaling up in the next 5 years and could have a big impact. That's so it's actually it's not just cool tech, it is cool tech, but it could have big impacts on real lives. Should we I'm going to talk to you a bit more about this idea of scaling of technologies a bit later, but why don't we just crack on and we're going to go through the top 10. I think we'll talk about scaling halfway through the list. >> Okay. >> Remind me that's our plan. As we set off at the bottom of this mountain of 10 things, small mountain, here we go one by one through the report. I'm going to read out what the technology is and you're going to tell me all about it. >> Okay. >> Number one on the list and they're not in any particular order, right? This is just the way you put them together in the report. It's about energy. It's everything to grid energy. What is that? >> Yeah, so everything to grid energy takes the nodes that are connected to our grid and turns them into a smarter system. So you can think about things like an electric vehicle, a commercial building, a rooftop of solar panels, even maybe a battery at a storage warehouse. And it really takes these nodes and says, "Okay, not only can you draw down power from the grid, but you can now store power, you can send it back to the grid." And that means that we can manage demand in real time. Have you ever spent a summer in, let's say, New York City or I I guess Geneva summers can get quite hot. >> We don't have much air conditioning. Yeah, if you got to talk about air conditioning. I'm sure it's coming, but not yet. >> Yeah, we I spent a few really hot summers in New York City. The kind where you step outside and you can feel the heat coming off the sidewalk or you know, you can really hear the hum of the air conditioners as you walk down the street and that moment is really that heat really puts a ton of strain on the grid. You are at a moment where any spike in demand can send things out of balance and and it happens everywhere in the world that at any place where there's that type of heat. And so what everything to grid energy does is it provides us with stability, agility, and resilience. And I will say I think that when we look at kind of the the pull factors in the moment of time that we're in, we're starting to hear conversations about the energy demands of AI. And so when we're already at a point where grids can be really stressed by increasing temperatures and we have this new force coming in, it's really important that we start to think about how might we reimagine that grid. >> So you talk about nodes. This is Let me just read a um a sentence from the report. Buildings, vehicles, and devices are no longer just electricity consumers. They are now active resources that can help reimagine the grid. >> Yeah. >> So basically your electric vehicle has a battery in it. It can go both ways. It can store electricity. It can put electricity back in the grid because at times if the wind's blowing hard, the sun's shining, renewable energies are producing lots of energy which sometimes can't be consumed. >> Exactly. >> It can be stored, not necessarily in a massive battery somewhere, but in lots of individual ones. >> Yep. >> Anywhere where this small-scale technology is available. >> Yeah. Yeah, exactly. And some of the things that are really making that possible actually are new battery chemistries that allow for that type of grid scale storage, which is quite cool. And we're also starting to see some innovations in kind of the way that we can move energy back and forth, that bidirectional flow. So, this is really starting to become possible in exciting way. >> Right. That's mentioned in the report here. Newer chemistries um for batteries such as lithium and sodium batteries. Some can charge faster, some can last longer. So, this is also hardware. So, you've got those chemistry, but also hardware is mentioned here. New semiconductors that work better and new control systems. And I'll cite it again verbatim. New control systems letting distributed storage activity stabilize the grid rather than passively feeding it. So, it's it's not just we're generating electricity, we're using it. There's a it's much more subtle than that. And this will stabilize the grid to use that term. >> Yeah. Yeah. I had the chance to speak with Doug Grant who's had held a few positions at the National Lab of the Rockies in the United States and exactly he calls this the technology that's really the foundation for a completely reimagined grid. >> A reimagined grid. And we often hear about one of the major challenges to the energy transition and to the AI demand data center demand is grid infrastructure. And this is another way of looking at that. That's called everything to grid energy. That was number one, Kim, you on our list. We turn the page to number two. Talk of lithium. Direct lithium extraction. What is that? >> Yeah. So, you mentioned the energy transition and we talked a little bit about batteries and and the role that they play in that. Lithium is a key component of the energy transition because it's part of most of our batteries. Direct lithium extraction is a way that we can pull lithium out of a brine in a matter of hours instead of years. We can take the water that the lithium is in and actually put it back underground. So, we're able to use less water in the way that we do that. And I think most importantly, it can happen in a smaller and more modular way. Uh so, what that means is we don't require really specific geological conditions to access lithium and extract it anymore. Do Actually, I should ask, do you know how we get the lithium in our batteries today? >> I was just going to get into that. I know something about the desert in Chile. >> Yeah, yeah. So, right now, the way that we get to lithium is primarily through lithium ponds, and they require a high-altitude desert. So, place that this happens is the Atacama Desert in Chile. And if you look at the satellite photos of this, you know, you kind of look down and it looks like a piece of art. I mean, you wouldn't know you you would have no idea that this is how we're actually getting one of the key components for for the future of our energy transition. They're these huge turquoise ponds that are perfectly geometric in shape, and they stretch for kilometers. And the way that it works right now is we kind of pour the lithium brine into these ponds, and we wait, sometimes for up to 2 years, for the sun to evaporate the water so we can get to that lithium. So, really direct lithium extraction is a step change in the way that it speeds up the process, it makes it more modular, and actually, it unlocks some of the kind of geography of where we can do this. We no longer necessarily need a high-altitude desert to get to to get to lithium. And when we think about the increasing demands for lithium for batteries, this is really important. >> Yeah, the current concentration in supply of lithium in the world, I think, or refining capacity, here we are, China, 62%. Chile, 13%. Argentina, 11%. Especially right at the moment, that's where the lithium comes from. >> Well, I should say lithium is a bigger supply chain. So, typically you have to extract and then you have to refine and then you turn the lithium into battery grade material. And so, right now what that supply chain looks like is we're moving kind of this lithium across many, many continents, right? It's starting in maybe the Atacama Desert in Chile. It's going probably to China for that refinement step and then it's maybe going back to, let's say, Detroit in the United States to power to be part of a battery for an electric vehicle. With the kind of lithium extraction becoming smaller and more modular, actually one of the things that people are start starting to think about is can we start to collocate the extraction and the refinement? It's now a bit more of a possibility there. So, that's really exciting when we think about the kind of the entirety of that lithium supply chain as well. >> They're also in this report, it looks at the promise of some of these technologies, but also it looks at the challenges or knock-on unintended consequences in some of them. And we we we don't have time to mention all of those, but if you listeners or viewers to this want to read that report, one of them, a challenge to the investment in that is when um a commodity gets cheaper, people don't want to invest in it so much. So, this says that uh lithium has lost over 80% of its value since 2022 and that makes so why would I then invest in a new plant making this? So, and that that's a challenge to scale, which we're going to talk about a little bit more, is what's my return on investment? >> Yeah. Yeah, that's totally true. Lithium is a commodity in that regard, but that's why I think some of these new kind of concepts that people are exploring around colocation the extraction and refinement actually help us to think how we might evolve around what that investment might look like. >> Let's move on. Number three is passive radiative cooling materials. You mentioned earlier uh summer in New York. This might be somewhat related to that. Tell us about passive radiative cooling material. >> Yeah. Um well, actually, uh I was this week uh passed our colleague Espen in the hallway. He leads energy uh the energy work for the forum. And he was talking to me about the cooling paradox. Have you Have you heard about that? >> No, I was going to say no. >> Okay. Cuz I didn't want to say yes. >> So, basically, cooling a building takes a lot of um electricity. And that electricity creates heat. That heat then turns the surrounding environment hotter, which means we need even more cooling. It's the type of positive feedback loop that you you really don't want. Now, with passive radiative cooling, imagine a paint that cools itself. We can use it as a coating. And what it can do is it actually sends heat up directly to deep space. We bypass our atmosphere. And so, it allows us to cool things without using electricity. You can imagine putting it on a roof, and it can actually drop the temperature of a building below the temperature of an air of the air around it. And this is exciting when you think about some of the hottest places on Earth, and the applications there they might be become more livable with less need for air conditioning. >> This is some extent climate change adaptation, isn't it? Which all over the world will need to face. And one of the things we'll need to face is more frequent heat waves and just generally higher temperatures. But in cities, so urban heat islands are now on average 0.5 to 4° C warmer than surrounding rural areas. >> Yeah. >> I mean, parks, trees, [snorts] those things we know can help providing shade, green areas that can reduce the heat island if cities are well designed. What you're talking about here is materials, things like paint, roof tiles, window films, and heavy-duty fabrics applied and and any of those things could be applied to new construction or retrofitted into existing ones. Oh, and even here's another uh like thing I underlined here. A a company in the United Kingdom has developed a coating for power cables that can keep them cool enough to carry more electricity >> Yeah. >> So, there's lots of reasons we need to cool and these are ways that are fairly low-cost, as you were saying. >> Exactly. And I actually think the kind of the the big opportunity here, of course, is is for people for for for our communities, but there other applications that are really really interesting that we're starting to explore. You know, when we think about um supply chains, this is maybe a way that we can start to keep supply chains more stable. And we can think about keeping factories open or in locations that previously weren't viable because of heat and things like that. And you know, we can keep schools open at different times of year. So, I really think that this is one of those technologies that has a really wide range of of opportunity space. >> Some of it's kind of old technology as well. I mean, you talk about Geneva compared to New York. Geneva has almost no air conditioning. >> Yeah. >> Uh some shops have it, but um some offices have it, but houses don't and schools don't, would you believe? They're getting to a point now where either they're going to have to close schools or they're going to have to really rethink. And I think a lot of this could be achieved without air conditioning with things like um what do they call it? Window films, certain paints, building materials, a lot of which can be retrofitted. That was cool. Oh, let's say one other thing. You mentioned how this could because it's a low-cost thing, how you could really also help in lower-income countries. Think of very hot countries um that aren't the richest countries, some of these technologies could be very effective there. Energy savings, using passive radiative cooling materials, according to this report, could reach up to 40%. You could save 40% of your energy if you adopted some of these technologies. >> Yeah, we're starting to see some smaller pilots and studies that are showing that you know, that scale of energy saving, which is really exciting. >> Passive radiative cooling materials. On to number four, which starts with an acronym. Let me see if you know what the acronym stands for. I've got it written down here. >> Yeah. >> It is PFAS destruction. >> Yeah. Yeah, so PFAS is is the you know, the set of chemicals that make pans nonstick or they make things like firefighting film work. And we call them forever chemicals. >> Come on, what's the acronym? >> It's per and poly Robin, I can't pronounce this one. >> Great, I'll I'll tell you something. >> and poly fluoroalkyl uh substances, yeah. I probably butchered that. Um but essentially, these are what we call forever chemicals. I I actually had the chance As you can tell, organic chemistry wasn't my area of expertise when I was in school. I did have the chance to speak with one of the world leading experts from China recently and he was explaining the reason why we call PFAS forever chemicals is because they're actually based on the carbon-fluorine bond, which is one of the strongest in organic chemistry. >> And and they're designed to be forever chemicals. These are the things for What did you say? There is this heat, water, and chemical breakdown. The delivery is designed using that bond, the carbon-fluorine bond. So, they don't break. >> Yeah. >> The trouble is, when you've stopped using them, or they're polluting the environment, they don't biodegrade. >> Exactly. So, we've found PFAS in places like the Arctic. It's in rainwater on every continent in the world and even actually in the bloodstream of almost everyone we've tested for it. Historically, we've been able to contain PFAS, but we've never been able to break that bond, that carbon-fluorine bond. The exciting thing is we now have figured out how to do that. We're able to There are a few different approaches that we found that can break the carbon-fluorine bond, and that's really exciting because what it means is that for, you know, communities maybe that live by contaminated land or water, we no longer just have to contain the problem. We can actually start to solve it. >> One of the techniques is running contaminated water across specialized electrodes. >> Yeah. >> Um so, you use the electrical current to strip out PFAS molecules, which can then be dealt with. Interesting. I mean, where where where would Who would be doing this? Who would be pulling out these forever chemicals and breaking them down? >> So, right now we're early days with this technology, and we're still kind of in this like moment where we're moving from research to development, and a lot of this is actually government-funded. Governments have a big incentive to start to clean up uh kind of these contaminated sites for a few reasons. One, for the health of their citizens. It's really important that we're able to kind of provide like clean drinking water and clean land and things like that. The The reason this is also interesting is because of the kind of maybe commercial avenues this might open up. Land that was previously considered untouchable is now something that we can maybe start to repurpose and and and invest in and use in different ways. So, starting to to see that happen there. >> And this report also, for each of these things, as I say, looks at the advantages, potential challenges, potential unintended disadvantages, and also what might be required to to get them moving at scale. And policy is something that comes in to all of these things to a greater or lesser extent. And this is one where if there are government requirements to clean up that land or whatever, this is where this technology would have a real use. >> And I should say we have made amazing strides when it comes to PFAS containment in recent years. And there are new policies that are being put in put in place right now around containing these forever chemicals. That, you know, these are big recent milestones. What PFAS destruction does is actually say, "Okay, can we take that one step further?" Instead of just creating a policy or regulation around containment, can we start to think about getting rid of them in totality? >> That was PFAS destruction. We're almost at the halfway point of our top 10 tech. The next one is precision fermentation. >> Yep. So, precision fermentation is a process where we can give microbes, like let's say a simple microbe like a yeast, a new set of instructions so that it can produce something that we might want, like a protein or a fat molecule or something along those lines. What they're What these microbes are able to produce is identical to what we might get from the other kind of more traditional ways of doing that. So, for example, we can get a whey protein that would be identical to what we would get from a cow. Which is really interesting, in particular when we think about one of the challenges we're facing. I recently heard this stat that by 2050 we'll have a world population of 9 billion people, and we're going to have to feed them all. The way we do that right now, um the math doesn't work to scale that. We've already hit quite a few of our planetary limits on land use, on water use, and emissions. And so precision fermentation presents us with an alternative way that we might get to some of those needs around food and things like that. The other thing I love about precision fermentation actually is because it's a process, it's not just, you know, the outputs aren't just food-related. We are also starting to see really exciting things happen in developing kind of cosmetic ingredients or even chemicals that we used to have to get from fossil fuels. >> And it's already being used this technology, right? If If you're a bodybuilder >> Yeah. >> like me and you're buying whey protein, those things in the big tubs. >> Yeah. >> Some of that has very often produced, it could have been produced from milk, I guess. That's what whey would have been. But now it can be created as a non-dairy product through this So it works these are big fermentation tanks >> Yep. >> that are in which this stuff is grown. >> Yep. And we are starting to see some of this come to market. There are a few companies that are doing this. For example, the Every Company has kind of a precision fermentation product that um creates something that's eggs. Um and they actually have a partnership with Walmart right now. So it we're definitely starting to see some of the food application spaces scale um and interesting to think about what are the other opportunities and and and how might this serve kind of a broader population and our broader needs. >> Joel, expert panel has decided this could really have an uptick in the next 5 years. >> Yeah, exactly. >> Okay. We are at halfway point. That one was called, let me repeat it, precision fermentation. Scaling then, um you can have a great idea. You can you can work in a laboratory. But it's not going to change the world if you can't get it out at scale. >> Yeah. >> What What have you learned in your work at the World Economic Forum and putting together this report about how things can be moved up to a greater scale. >> Yeah, so we talked about how we've been doing this report for 14 years. I actually get asked this question a lot. Where are the technologies now that you've highlighted in previous editions? And I can say that some of them have scaled. Some took a lot longer to scale than we thought they would. >> years is the timeline of it. >> And some of them, you know, haven't have stalled out. And when we look back to understand why might that be, for the most part the reason isn't the technology. The research is there and really strong and we're seeing, you know, the development is there and and and it tends to come down to three things. The first is whether the pieces around it are ready. So, for example, we first identified mRNA in 2014. The science was solid, but there was no good way to get the mRNA into human cells. The missing piece was the delivery system and that didn't come around until 2018. >> So, mRNA vaccines we're familiar with that from the COVID vaccine. And you're saying that technology had been identified by one of these reports on these annual reports on the top 10 tech, but it required a missing piece to move that technology forward and that can be a stumbling block or slowing down the development of things. But you said there are a couple of other things. >> Yeah. Yeah. So, the second factor that we've identified from looking back at the 14 years is whether there's someone who's ready to take that first back to really go for it with an early version because usually the early version is is rougher and definitely more expensive. So, someone needs to be willing to work with that. Sometimes that happens because the need is so severe. So, for example, we've identified liquid biopsy in a in a previous edition. I Oncologists were willing to work with it when it was expensive and unproven because the rate of recurrence around cancer was really high and they had nothing else available to them. And their patients yeah, their patients needed something to solve that problem. Other times we see government creating that push. So, for example, South Australia back to that first big grid battery um after their power crisis. And then of course, there's sometimes a company that just has resources and I guess the nerve uh to go first on that. >> Great. Well, let's get back into it. You're listening to Radio Davos from the World Economic Forum and we're looking at the top 10 emerging technologies of 2026. We've talked about five of them. Let's do the other five. Timmy Bettinger is here with me talking you through these. Number six on the list is huh Let me see if I pronounce this right. Exosome drug delivery. >> Yeah. Yes. So, we have uh we've highlighted in previous years and we'll get to talk about in a little bit, incredible advancements in medicine. We now have medicines that can find a single disease cell and target it specifically. We have medicines that can turn off a mutation or even edit a gene. But, a medicines is only useful if it can get to the place that it needs to go. It turns out we actually have a delivery mechanism in our bodies already that can help us do this. It's the exosome. The exosome >> that we're all familiar with. Uh let me It's the old the old exosome. W- when was the exosome going to come into its own? Finally, it will. What is an exosome? >> Okay. So, your cells make a tiny packet that kind of a membrane wrapped packet that they use to send messages back and forth from each other. And with exosome drug delivery, >> So, this is every cell >> Yep. >> We know what a cell is, has an exosome, is a part of the cell, and it is a it's functional. One of its functions is to deliver information. >> Yep. Yep, exactly. And so, what we're able to do now is actually load those those kind of couriers with a package, with a drug, and we can tell them exactly where to go. What's the What's the delivery address? And we can use the exosomes to take the drug to where it needs to go. And this is exciting because there are certain places in the body that have been really hard for drugs to reach because we have kind of barriers around them for for protection reasons. One of those is the blood-brain barrier. And because the exosome is a courier that the body recognizes, it can actually cross the blood-brain barrier. This is really exciting because that means diseases like Alzheimer's or Parkinson's that have been really hard to treat for decades are now on the table. >> Right. So, in a nutshell, previous ways of delivering drugs into the body have often been rejected by the body because the body fights kind of foreign bodies coming to it. This isn't a foreign body. The exosome is part of your own body. >> Exactly. >> But if you can find a way to deliver that medicine via that, I like the way it's written in the report, you load you load the packet with therapeutic cargo, and then the body accepts the delivery because it recognizes the courier. It's not a foreign body delivering this drug to wherever it's needed. It is part of your own body already there, but which this medicine has been put into. >> Yep, exactly. >> It's very and interesting you mentioned the brain diseases like Parkinson's and Alzheimer's. It also, according to your report, there have been trials on this, clinical trials, in cancer as well as those neurological diseases and on the long-term effects of COVID-19. And there's an example here where it seemed to be quite effective treating pancreatic cancer. >> Mhm. Yep. >> I think a lot of people are going to be really interested in finding out more about Can we get it right? A lot of people will be interested in finding out more about exosome drug delivery. Should we move on to the next one? >> Let's do it. >> Let's do it. Number seven on the list of 10, in no particular order, is Oh, here we are. Heard about this already. Personalized mRNA cancer vaccines. >> Yeah. So, personalized mRNA cancer vaccines, you know, the way that they work is a doctor can actually take a biopsy of a specific tumor, and it can read the mutations that are unique to that tumor, and develop a back a vaccine built for that exact cancer, for that exact patient, in weeks. That is incredible. Um I watched a friend go through chemotherapy 2 years ago, and one of the things that was hardest for me was just knowing that uh typically treatments tend to be kind of a a controlled damage. Chemotherapy is not necessarily kind of, you know, right-size for an individual cancer, or let alone an individual patient. And so, this really changes the way that we can start to treat and and manage these types of diseases that can be really, really hard. And I know most people have have known someone who's who's um gone through chemotherapy or or experienced something like that. So, this one for me in particular feels really, really important and helpful. >> Yeah. Everyone listening to this will know someone who's been through cancer and cancer treatment. And it it always seems like cracking a of all nut with a sledgehammer. >> Yeah. It's a good analogy. >> You know, it's going to create a lot of damage. You might open the the nut, but it does create a lot of damage. Here, with the personalized, these are custom-built medicines. This is so interesting, because we talk about cancer, but there are dozens of types of cancer, and then each patient within that it will look different what that actual mutation is is totally different. So, what you've just told us is that a sample of that actual mutation can be taken and very quickly there can be a treatment developed for that particular mutation in that particular patient. >> Yeah. >> So, that sounds amazing. It It almost sounds too good to be true. One thing that worries me about it is it must be horribly expensive. >> Yeah. Right now, it is quite expensive. Um and one of the things that we think about as this should scale is making sure that we have kind of the health systems in place that we can deliver this type of treatment to everyone who needs it. So, this will be a big consideration as we look to the pathway to scale as something that we need to make sure we get right. >> Yeah, in in the report here it says, "Early treatments exceeding $100,000 per patient put personalized vaccines well within reach of patients." Yeah, if you are living in a wealthy country and it's going to save your life, $100,000 might seem quite a reasonable price. >> Yeah. >> But, a lot of people billions of people aren't in that situation. And so, there are people read this report that uh there are ways of looking at how these technologies might be adapted with a hybrid models that combine personalized off-the-shelf vaccines that might also give some of the benefits at a lower cost at some stage in the development of this. I wanted to say another thing from this report. We've already looked at how some of these emerging technologies, if they scale up over the next 5 years, could have quite a transformative effect on the industries. So, power grids will operate slightly differently because there'll be these localized ones. That was one of the first technologies we looked at in the report. Here, imagine this, pharmaceutical companies now make those drugs that are used in chemotherapy on a mass scale and ship them out to people. This would totally change the kind of the industry model, wouldn't it? >> Yeah, yeah, this is really interesting. I think, you know, in in health in particular, it's you know, primarily built around this kind of blockbuster scale model and because of the way that research and development happens, that's kind of important for the economics of it. What personalized mRNA cancer vaccines does, alongside other kind of breakthroughs happening in medicine right now, is actually invert that logic and say, we can, instead of creating a kind of a a big kind of one-size-fits-all approach, why don't we start to think about how we can create something specific for a specific patient? One of the kind of elements that might make this kind of more cost-effective and and and help us think through that is the role that AI might play in some of these processes and and kind of the the discovery process there. Should we figure that out? I think, you know, yes, we have more personalized. It also starts to change kind of where and how this happens. So, you can also think more localized in the sense that maybe you have kind of the the lab just down the hall from where the patient's treatment is happening. You know, you can, you know, walk down the hall to do that biopsy and and spin up that treatment in the same building in which you are actually engaging in treating a patient. >> Absolute you know, paradigm shift. Potentially, that technology is personalized mRNA cancer vaccines. Let's move to number eight, which is quantum simulation. Oh, I love quantum. >> Why? Why? >> Why? Cuz I don't understand it, Kimmy. You're going to help me out on this one. I mean, it's not that I understand most of what we talk about here, but quantum, you know, let you you'll get a test on this one. Go whenever it comes up on Radio Davos, um I always hope for an expert in front of me. Quantum simulation for drug discovery. >> Yeah. Okay, so uh the way that this works is quantum computers can actually model a molecule using the laws of physics. Um so we can watch kind of a drug candidate, a molecule, fold and lock into its target atom by atom before we even have to make a single molecule in the lab. Um and that's a level of specificity that we currently are able to do. A lot of the ways that we kind of think about drug candidates is using a lot of approximation. So this kind of changes the kind of the nature in which we're able to understand yeah, likelihood of success. >> So the way that drugs are discovered and developed, early stages of a drug discovery, scientists don't just make some >> No. >> drug and inject it into a living organism. >> Yeah. >> Before that, it's done on computers and it has been for quite some time. Modeling But what you're saying is the the classic kind of modeling is not that exact. It It assumes that Let me just read this from the report. The conventional computers approximate molecular behavior by reducing its complexity. And the same sentence continues, quantum simulation models it directly. So it really is the real world. This is the real molecule rather than just we've assumed it's something a bit like this, which is kind of what computers are currently doing. These quantum calculations, because they're much more complex, they're much faster, they can really give you a genuine assessment of what that molecule does. >> Yeah, and this is exciting. I was speaking to the chief scientist at a big pharmaceutical company a few months ago and he shared this stat with me. Nine in 10 drug candidates around the world fail trials. And again, we talked a little bit about the >> Failed clinical trials. So they have they have started. >> Right. Exactly. They've kind of modeled them out, think that they might be successful and move them into clinical trials and they failed there. >> Nine out of 10 of them fail because the previous the computer modeling had said it might work, but it didn't in nine out of 10. >> Yeah, for a variety of reasons, but that that that definitely contributes here. So, you know, quantum simulation can really help us shift that that stat a little bit. And again, that changes the economics because right now we're really beholden to what we can move forward into into clinical trials and if we're not succeeding there, you know, it's slower, it's resource intensive, it's expensive, and patients' lives are on the line at the end of the day. And so this really changes that calculus. >> There was a recent episode of Radio Davos about rare diseases. >> Yeah. >> I urge people who are interested in health care and rare diseases to go out and listen to that. There are hundreds of millions of people around the world with so-called rare diseases. >> Yeah. >> Not all that rare because there are hundreds of millions of people. But each individual disease is very often there's not, if you like to put it in, you know, economic terms, there's just not the market there for pharmaceutical companies to develop treatments. Maybe this would help solve that. >> Yeah, exactly. If we're able to kind of bolster that kind of discovery process of how we might identify a molecule before it moves into a lab and we can do that much more successfully, what that means is as economics change and and maybe that changes the way we think about what's treatable or addressable or not. It kind of opens up the possibilities or the universe of diseases that we can start to explore. So, that's super exciting. >> That technology was called quantum simulation for drug discovery. Number nine on the list of 10 emerging technologies. Now, this is some of them you can tell what they mean just by the title. And then these titles are a bit more enigmatic. So, I'll just say number nine is world models. >> Yeah. We were chatting earlier about our kids. You know, I have a 9-month-old son named >> And who now? >> Yeah. 9-month-old son named Hayes. And watching him learn has been amazing. I can give you an example. He has never he doesn't know what the word gravity means. But, I can watch him, you know, sitting in his high chair, looking over the edge and and dropping his spoon on the floor. >> Oh, they love that. That's spoons going down there 20 times during the night. >> Luckily, we have a dog, so So, that helps us. Um but yeah, he, you know, he understands he feels the the the weight of the pull in his hand. He hears the thud when it hits the floor. He He can't speak. He could never tell you what gravity is, but he already has a little model in his head around how the world works, which is really cool. When we think about the way some of our most powerful AI learns right now, it's on descriptions of the world, text about the world, and things like that. What world models do differently is they actually learn like my son Hayes. They learn from experience. They learn from understanding how things bump into each other. And that opens up a lot of things we've been chasing for decades. We can think about robots that can respond to situations that are ambiguous on a factory floor. You know, we don't need to just say, "You do this one precise gesture 100 times a day." You know, you might not know the context and and the robot might not know the context that it's operating in and it's able to do so because it has these world models that it's built around. Similarly, we can look at climate models that can truly understand the way a storm moves, factories that can learn as they run, and so the gap between, you know, what AI can learn and what it can actually understand about the world is is starting to close. >> Yeah, it's quite a philosophical thing, isn't it? You know, did can something exist without language? Well, it certainly can in your son's case. He's He's discovered gravity. A baby's and toddlers are figuring out the world and they don't have words for it, but those things exist. So, my question would be, we just got used to large language models. Most people now understand more or less Well, no one really knows how they work, but more more or less the technology is they're fed vast amounts of words and sentences and all that data and all of human knowledge is contained in words, but lots of human knowledge or it is not words. It is that I'll suddenly react if you If I throw this pen at you, your hand's going to come up. Your brain isn't going through lots of words to do that. And so, bringing this real-world stuff, I'm just wondering where that data comes from and it says here these models ingest data from multiple sensory channels such as video, depth sensors, pressure readings, motion capture. >> So, there's lots of data and we think I guess we think about electric vehicles, how they You're in San Francisco, you see driverless cars all the time, right? Which, you know, is still is still witchcraft for most of us in Europe. But you're seeing them literally every day on the streets, right? That real They must already be doing some real-world sensory learning here, right? >> Yeah, so that's an interesting use case of yeah, that type of data could be really valuable as we start to think about how we build these world models. Yeah. >> Right. So, with applications for robots, but also as you mentioned for climate science. People can read more about that. It's number nine in the list. That's called world models. Kimmy, we're on number 10. It's the top 10. We're on number 10. >> We reached the finish line. >> there. Let's see if we can get through this one. Another one I wouldn't have no idea what it means from its title. Oh, maybe I would. Lattice-based cryptography. >> Yeah. Okay, you mentioned I'm from San Francisco, so I'll use a classic San Francisco analogy. I'll I'll use the analogy of fog. Lattice-based cryptography is a new approach to keeping your data safe that really hides your data inside of what we can think about as a mathematical fog. We have like a huge multi-dimensional grid where we mix random noise in, and from the outside, you really can't see the right answer that you're looking for. The fog obscures the right answer amid, you know, thousands of wrong answers, let's say. Even a quantum computer gets lost in this in this mathematical fog. >> To go back to quantum again, that's why this is important because we have cybersecurity now. We've got passwords. We've got all kinds of clever ways of stopping criminals breaking into our data, yeah, to our phones, to our computers, to our power grids, to our governments, to our military sites, whatever. Everything is at risk of cyberattack, which, if we're clever enough right now, we could control, but there's a future scenario where someone's got like a quantum computer, which has not yet been developed. And I I know it's in this report, uh there's a uh criminals can have a harvest now, decrypt later mentality, which means they can get all this decrypted data. They don't know what it means, but they'll know if they just hold it for a few years, they'll have a computer strong enough cuz it'll be a quantum computer. >> Yeah. >> They'll be able to decrypt it. And it might still be useful even in a few years time. So you're saying this technology could kind of future-proof that um protection of that data. >> Yeah, exactly. And we're already starting to see a move towards quantum safe encryption. And now it's just a question of whether we can move fast enough and make sure that we're doing it in a way that we can really keep sensitive data safe. >> So also in this uh report is this phrase homomorphic encryption, which if I understand it right, enables data to be shared without in some way revealing itself. >> Yeah. So when we think about data actually being truly quantum safe, it means we have kind of a new kind of trust in how we can use that data, which is really exciting. We can now compute on this data without needing to necessarily unlock or expose it. And so lattice-based cryptography not only is keeping us safe from this risk, but it's also moving us toward a future where we know our data is safe and we can do a lot more stuff with it. So an example that I can share from the report is, you know, there was a hospital that trained AI on 300,000 patient records from three different hospitals. That's really sensitive information. They were able to do it without actually revealing the underlying data. So we were able They were able to build an AI model that could do really robust analysis around health outcomes and things without ever having to expose the data of those individual patients. And it can help us move medicine forward. So yeah, that's kind of we talked a little bit about the risk, but there's also a huge positive opportunity here. >> That one is called lattice-based cryptography. You'll also see that to do the thing you were just referring to then again is a policy challenge because if one hospital is sharing patient data with another or one country to another using this technology where you're not just giving them lists of data but you're giving them encrypted data which will not be completely decrypted by the recipient but there'll be some way of using it. It requires standards to be put in place so that everyone's using the same standard that allows this method to work. It sounds like a big challenge but >> It is. I will say that we're starting to see some of the national standard setting bodies already start to establish this as a foundation. So for example, in the United States lattice-based cryptography is kind of the core to to the big quantum safe computing standards that have been put in place. So we are starting to see some kind of convergence around this as the way forward. >> Lattice-based cryptography is number 10 brings us to the end of the top 10 emerging technologies 2026. I mean doing this work Keri but was there any kind of takeaway for you on the way some of this technology is taking us? >> Yeah, it is interesting every year to zoom out and look at the cohort of 10 and see you do we see any signals around where the frontier might be heading. And we've started to tease out a few of the trends that I've noticed already. The first is that some of these technologies are becoming much more personal. We talked about the personalized cancer vaccines and and things like that where we're really starting to think instead of like a population average, we're moving towards technologies that are addressing an individual, a really specific need. The second that we also touched on a little bit is this idea of more local. Lithium that can be produced near where batteries are actually made but say or you know protein that can come from a bioreactor in a city that doesn't have a farm. >> Everything to grid energy. >> that can really be balanced at the neighborhood level. So, that relationship between kind of place and production is changing a little bit. And that that's maybe a really good thing for, you know, our supply chains and things. >> And that also is probably going to have potential impacts on the global economy as well. We talked about the pharmaceuticals industry and the energy industry. These are really hard to predict, but we'll see over the next 5 years what happens. Any other themes that hit you open during making this report? >> Yeah, yeah. The one other thing that stood out to me is there's this threat of of actually doing more with less. You know, cooling without electricity, for example. There's a few technologies that really start to cluster about kind of finding ways that we can get similar results without adding additional strain on on our planet. I think that's a really interesting through line here as well. >> And I mentioned earlier that you also kind of honestly address uh some of the drawbacks or challenges here. Are there some that stood out to you where you know, this could this could be great in some ways, but also >> Yeah, I will say the one that I has stayed with the me the most is actually precision fermentation. The challenge of feeding 9 billion is a massive one and it will require kind of all hands on deck. But the reason it stands out to me is because I actually my husband's a cattle rancher. Um and he comes from a family of generations of of cattle ranchers. And so, while precision fermentation can really offer a new way to meet our needs and produce foods and things, at the same time we run the risk of moving pulling that production away from kind of the families, the economies that have been doing that for for generations and longer. >> is and in less developed countries most most people still working in agriculture as well. And so, that has to be taken into consideration. >> Yeah, Yeah. >> Things like this are addressed in the report. I was going to ask you for your favorite. I have a feeling you're going to decline and just say that one is the one that resonates with you most. >> Yeah. Yeah. I I don't have a favorite. It's impossible to pick a favorite. The reason I love getting the chance to work with experts in in in in develop this report is because I get to learn across a huge breadth of topics and really see something that's could fundamentally change the world. It's impossible to have a favorite when that's the scope. >> They're not my children. I can't pick a favorite. >> Okay, what's yours? >> have one child, so that's that's your favorite for now. >> Yeah. Yeah. What's yours? >> Um it's a tight run thing. So, people encourage you that would be um link in the show notes. Go and get this report. Top 10 emerging technologies. And you can pick your favorite. I reckon it was I was thinking the everything to green energy. Love that because I just love the idea because that's so personal. If you you know, can manage your own electricity, feed it into the grid, take it off the grid. You know, it just seems so clever way of overcoming some of those problems of the energy transition of renewable energies. Also, incidentally, talking of drawbacks, the point is made quite clearly there. It's great if you own a house and you own a car, you might really this might in the next 5 years might be really great for you. What if you don't own a house or a car and you're renting? Maybe your landlord's burning money off this, but maybe not necessarily you. So, I do like this report really addresses a real world problems. So, that one which was number one, everything to green energy, actually is pipped to the post. I'm going to say my favorite of these has to be personalized mRNA cancer vaccines. The idea that um cuz we've all seen it. I know at least one person springs to mind who that was not available and it could be available in the next 5 years to someone ending up in that situation again. A personalized cure for cancer. I mean, come on. >> Yeah. >> So, I'll take that one. Before I let you go, Kim, you said this report's been going for 14 years. People can look back and find They can also find last 5 or 6 years on Radio Davos. It must have changed over the years the way innovation happens. >> Yeah. Yeah. Um really interesting. One of the the signals that was very clear to us this year is that the way scientific discovery happens is fundamentally changing with AI. You know, we've all talked about oh, it can compress timelines and things, but I actually think it's bigger than that. What we're seeing is, you know, science traditionally works on the kind of come up with an a hypothesis, run an experiment on it, learn from it, try another experiment. But actually with AI, what we're able to do is do a bit of experimentation pre-hypothesis. We're able to ask really, really broad, open questions and develop our hypothesis from that. So, that then typically the experiment phase a bit more of a of a of a validation stage. Um so, it really shifts the way science is happening. And as we think about okay, the next 14 years of this report, what does that mean? What might innovation look like? We're starting to consider where um where kind of we'll start we'll where we'll see resource going in science. And for us, maybe that's more, you know, maybe that's more around the models, the compute, the talent to to to do this type of work. And as we think about kind of where science happens and how science happens, who's able to deliver on that? Maybe maybe that is a bit more of the private sector or or kind of, you know, how can academia build into that? So, I think we'll start to see some big shifts in the landscape there as well. >> So, things are speeding up, but also there's fundamental changes >> Yeah. >> to how innovation is even dreamt up in the first place. >> Yeah. >> Kim Bettinger, thanks so much for joining us on Radio Davos. >> Thank you. [music] It's been a pleasure to to spend this hour with you, Robin. >> Please follow Radio Davos wherever you get podcasts or visit wef.ch/podcasts where you can also find our two other weekly podcasts, Meet the Leader and Agenda [music] Dialogues. Please follow us, subscribe, give us a rating if you like this episode about the top 10 emerging technologies. Give us a five-star rating and put it on your socials, invite your [music] friends to listen if you thought it was as interesting as I did. This episode of Radio Davos was presented by me, Robin Pomeroy. I'd like to say thank you [music] for listening, thank you for watching. This is a video podcast available on YouTube. Radio Davos will be back next week, but for me, goodbye.