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J-labs Company Profile, Stock Price, News, Rankings | Fortune

AI breakthroughs are moving out of academic labs and into companies that are training and  deploying the most advanced systems in history. That shift is reshaping who drives scientific  discovery and how quickly ideas make an impact in the real world. Three leaders at the forefront  of this transition explore how their work in health care, climate science, and autonomous  mobility could redefine the way we protect people and the planet. As the balance of power tilts  toward industry, who decides which innovations scale first, and whose needs they serve? 

The New AI Power Shift

Conferences

Beneath every visible city lies another one made of roots, rivers, soils, breezes, and microbial worlds — a restless ecology that shapes the urban realm as profoundly as any human plan. A former landscape artist, now working with AI research labs, invites us to look at this hidden metropolis with new eyes and explore how intelligent tools can help surface the needs and rhythms of non-human actors: trees that regulate microclimates, waterways that remember old paths, soils that hold the city together grain by grain. What new forms of governance and design become possible when we learn to listen to these quieter voices — and allow the invisible city to speak?

Invisible Cities

Beneath every visible city lies an invisible one made of roots, rivers, soils, a restless ecology that profoundly affects the urban realm. Yet our planning and policy frameworks remain very human centric. Former landscape architect Jan Bunge now works with AI. Research labs that invite us to look at this hidden metropolis with new eyes and explore how intelligent tools can help surface the needs and rhythms of nonhuman actors, giving them a voice in design and governance. He'll be in conversation with Brainstorm Design co-chair Tony Chambers. Thank you, Alan Welcome, Jan. Thank you. Good afternoon, everybody. What a great day it's been so far, and thank you again, Jan for joining us for the 2nd time at Brainstorm Design here in Macau. So today, We've heard a lot about the importance of human centered design. I'm quite right too. However, Jan thinks we should be thinking beyond this. We should be thinking more about multi-species centered design. So we'll dig into that in a moment. First, we're gonna have a quick career. Run through and life run through of Jan so far. So your beginnings which have informed you very well, very hippie commune upbringing in Berlin and in New York. This is young Yan with his pet pig, and a quick career run through, hippie commune. Worked as a landscape architect. Into urban design. Communication And then most significantly, and when we talked last time, a pioneer of virtual experienced twins with squint opera. And there's 2 projects we're going to look at here, which you, if you could explain to us, which are very significant, and many people will have heard of. So Scre Opera has the beautiful task of communicating super large projects in the built environment to non-technical people, and the way we do that is through immersive experiences where we try for you to have an experience of how things would look and feel like. This one was the Toyota for the launch of Toyota Wolver City, um. A couple of years back and uh from, from this kind of setup, we went into uh representing everything in game engines, very similar to what we saw before. So the next one is actually um simulated in unreal Game engine where you have the opportunity to dynamically go anywhere you want, but secondly, you can also switch between different options. Again, this is always about allowing non-technical people to get an idea of how things will look and feel like. And this one was a huge project in Neon, Saudi Arabia. Yeah, so basically opera simulates anyone who wants to build a new city, but Uh, you know, it's at a very early stages, um, and there's a lot of non-technical people involved who have to make important decisions. This is when, you know, you, you call them and they help you simulate those complex future realities. And then from that, how many many years working in this area and really being a pioneer, squint opera were doing the largest and most impactful work with virtual experienced twins, and your experience working with virtual experience twins and AI. So it led you to question the data that is input and then what actually ultimately drives AI and that's what's brought you back. To your first love and first work, landscape, architecture and design, and gardening. Yeah, to explain, I think in a funny way design data has become the frontier of design today, um, but As a landscape architect, I often think about gardens and if you go back in time and you look at early depictions of Persian gardens or the way we thought about the Garden of Eden or Chinese gardens, you'll see that they are always walled gardens, and this had a lot to do with our perception at the time, which was that the world around us, the nature Around us was actually dangerous, often life threatening, and so what we did was we cut out a little piece, built a wall around, and then within that little piece of man-made landscape, we forced trees to grow in squares and we we straightened our rivers and then we ended up with this. So we tried to tame nature and nature. We tried to control a complex system that we didn't fully understand. And Then we talk about natural catastrophes, but when we see floods like that, but what actually happens in reality is that the river is just remembering where it used to flow. Um, rivers have always meandered. This is a map of how the Mississippi River, which areas it used to occupy in the past. So you could say the river is just remembering where it used to go and it was our lack of understanding of this complex system. That led to those human catastrophes. So they're not natural disasters, they're human made. They're definitely manmade. So now at this moment in time when you know, we see all the advances in machine learning and AI, my hope is that for the very first time in human history, we can actually dare to look over the wall of our walled garden and try to Understand and at least see and perceive reality for what it is as a very complex, interdependent, interconnected, constantly changing dynamic reality. And if there are two things that I learned over the last couple of years as a designer, The reason why I got obsessed with data and what we put into those machines is that by definition, the way they work is based on the idea of a recursive learning loop. So any technology we ever invented before is static in the sense that a book will not change depending on how you read it. Here it's really whatever we put into it gets reinforced over and over again. So it's important to figure out what we put in and the second thing. It's something we have always known that the tools that we make and use actually shape us. Now we are dealing with a tool that is constantly reshaping itself as it shapes us. So again, I feel one of the most important frontiers as a designer is to really understand all the underlying infrastructure, all the underlying logic of how these machines work in order to use them in the best possible way for us. And you feel we are still living in anachronistically in a sense, yeah, still in the Gutenberg world. We all, uh, this is the only world we know actually. If you think about all our processes and systems, um, you know, there's hard borders, there are linear, it's all about being able to control and predict, but the reality is that even though we are still living in the Gutenberg world. The AI world is upon us and there is no way back and you know the simple way of looking at this is that. This AI world is the complete opposite of what we are today. So we're moving from linear to network systems, from static to dynamic, from specialized to integrated, from mechanical to organic, and in the end from control to emergence. And so this is not a little adjustment 10% different here or there. This is a fundamental by emergence you mean an unpredictable, unpredictable and constantly changing and evolving in time. So The other thing working a lot in stimulation, uh, I also came to believe that The intelligence or our power is really not about prediction, but it is very much about our capacity to perceive. I think the beautiful opportunity that we have is to use this technology to see more and that is really, you know, at this moment in time, too often people have a very complex problem and a very big question, and then they want to boil it down to one single answer. I think we should use the machine the other way around, you know, it should talk to us about the edges that we heard earlier about, you know, show me the things I didn't think about, show me the things I didn't know, yeah. Um, you know, both these elements are, you know, AI supported real-time design tools on the right. This is a tool where in real time the designer can stimulate environmental impact, whether it is heat gain or wind. This used to be. impossible to do in real time because those simulations, those calculations would take even 2 years ago, uh, a day to, to render. And so today, um, through the use of AI by training AI and understanding how those Complex systems actually work. We have the ability to simulate it in real time and give real-time feedback to the designer and the left is the simulation of wind, and by physicalizing the wind in the 3D model, you get a very different idea of what you're dealing with. So personally, I'm most obsessed with the question of, you know, how can we move from Building systems and tools and processes for human-centric design and how can we expand them to acknowledge that we are actually living in a multi-species reality. I feel like a lot of the problems that we have today is because we, we thought we understood enough. To take action and to manipulate, but by not knowing or not seeing the fringes or the site or the holistic picture, we ended up where we are today. So really how can we give agency to nonhuman entities that help us design and govern our cities better and in specific, specifically one of the non-humans that you are supporting and Highlighting its importance is trees. So this is a research project that started 6 years ago, uh, it's called Trees as Infrastructure, and it was actually started by a bunch of economists at Dark Matter Labs together with Lucid Minds, the AI research lab in Amsterdam, and they had the question of how can we validate the economic impact of trees to safeguard capital investment in in cities. So, so in order to, you know, make mission critical budget decisions at a large scale, they went very deep and they started looking at all the ways in which you could measure impact or value. the obvious ones pre sequester carbon and they have an impact on biodiversity which translates into carbon credits or biodiversity credits. But they also looked into aspects of human health, meaning reduction in temperature or improvement of air quality, as well as resilience related issues like how do the trees enhance the soil capacity to absorb water in a stormwater event, for example. Interestingly driven by economists. They're all driven by economists because cities have to decide. When they are planting trees, you know, which will give them the best uh impact. So, so everything today obviously needs to be validated and analyzed properly. So yeah, this is driven or started through an economic lens and uh it has been deployed in many cities, so uh in in Europe in the next slide you see a bunch of um uh examples, um, and, and uh if you want to validate something. That complex, then you really need to have scientific rigor and which means that all the underlying assumptions of this platform are actually peer reviewed and publicized so everyone can see if you agree with the core logic of the simulation and also the core algorithms that determine things like the species specific tree grows are accessible. I think it's a very important point. And if we talk about managing risk and liability, we need visibility. And so also I am also like you heard from Ben, very much of the opinion that you know the only way to do that is to open up this information and really open source as much as possible. And girls, tell us a little more about. So green unified systems started with trees, but the way the simulation is built is that it obviously has to take into account the whole ecosystem. So we talk to each other and they, so not only the trees talk to each other, so you need to represent all of those individually, but also they relate to the soil. So there's a module where you're simulating the soil, then there's the animals and then there's the climate and so green unified system is really designed to expand beyond the trees and that's what I'm currently working on is, is to explore how we can reach a point where we can actually start thinking about a tool that can go beyond those trees all encompassing looking at the whole ecosystem. So I don't have a great working on. I don't have a great name for it yet. So it's called Audoy. Uh, for the simple fact that this is a tool that helps you to analyze, understand, design, optimize, and implement nature-based solutions, um, and All these, uh, you know, are grounded in utilizing environmental intelligence in the design process, uh, in, in real time. So when you think about this challenge, you know, at the beginning you need something to assess assess your conditions and you want to set your goals, design different scenarios, test them virtually before you scale and then it all needs to feed back constantly into, into the model. Um, again, I feel. The real opportunity that we have today is that we can start to engage with complex systems that even 2 or 3 years ago were impossible for us to engage with um because of the just of the sheer dimension of the problem and In that sense, there is still a lot of research to do to figure out as a constant feedback loop is needed because we will never fully understand it and every model is always an abstract representation of reality. It is never the reality obviously in itself, but, but uh. I find it fascinating that today we have the technology that helps us to make sense of all this unstructured data and help us to see patterns. How we also heard earlier this morning. So designing with environmental intelligence. So it's another AI. We started with emotional intelligence this morning, but we're on to environmental intelligence. And we should be planetary gardeners because in the end, there is really no difference between the man-made world and the natural world. There is no outside of the system. Everything is connected and everything is happening in the same space. So we need to try to adopt a more holistic understanding of everything as a beautiful and very optimistic take. We're not going to neglect humans. But we are going to think more about the multi-species world we live in. This last slide is maybe the most complicated one because We do like the illusion of control. We do want to feel in control. And as we are engaging with those complex systems, we start to understand that it's impossible to control those systems in their, in their totality, and in the end, what I think we have to get used to is the idea that we are designing for emergence, designing for the unknown and therefore, you know, in a more dynamic. evolving way. It's urgent. Thank you. Thank you. Thank you for giving voice to the natural world and speaking up for the trees. Thank you. Thank you.

Microsoft recently unveiled an AI diagnostic system that scored four times higher than human doctors in identifying complex medical cases from the New England Journal of Medicine—a stunning benchmark, albeit in a highly-controlled setting. With speed, recall, and precision on its side, AI is quickly becoming a formidable force in clinical decision-making. But these tools aren’t infallible, and real-world medicine rarely mirrors textbook cases. As AI begins to shift from research labs to exam rooms, the stakes are growing: Who carries the liability when machines make mistakes? And what happens to trust, and the human touch, when your physician might be a program?

AI vs. MD

A new generation of defense tech startups is reshaping national security by bringing Silicon Valley’s speed and software to the front lines. Leaders from Anduril Industries, Vannevar Labs, and Allen Control Systems will discuss how they're deploying AI, autonomous systems, and counter-drone technologies to military users, including the Department of Defense. The conversation will explore scaling in a high-stakes environment, the connections—and tensions—between Silicon Valley and Washington, D.C., and the changing nature of warfare in the 21st century.

Erin Biggers
Vice President, Mission, Vannevar Labs 

Megan Milam
Senior Vice President, Government Relations, Anduril Industries 

Steve Simoni
Cofounder and President, Allen Control Systems 

Allie Garfinkle
Senior Reporter; Cochair, Fortune Brainstorm

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