Unpack actionable insights on converging technologies and industrial strategy hear leaders at Davos 2026 share what it takes to win the next era.
At Davos 2026’s “Converging Technologies to Win,” leaders argued that winning the next era depends less on breakthrough invention than on aligning ecosystems, energy, and adoption. Economist Laura D’Andrea Tyson contrasted Silicon Valley’s university–risk capital–basic science flywheel with China’s long-horizon industrial strategy, noting the US also practiced “industrial policy related to defense.” Saudi Arabia’s Minister Abdullah AlSwaha described a national blueprint centered on “talent, technology and build trust,” pushing both “great acceleration” and “great adoption,” from AI-enabled public services to healthcare deployments and positioning the Kingdom as a global testbed.
Honeywell CEO Vimal Kapur urged end-to-end thinking: if AI drives soaring power demand, leaders must ask, “what are you going to do with that?”—better videos or better healthcare. He argued the constraint is energy intensity (“kilojoules matter”), making gas and some nuclear near-term necessities, while AI can also unlock industrial efficiency.
Synopsys CEO Sassine Ghazi said Moore’s Law is “continuing, but it’s not affordable,” shifting innovation toward system-level design and advanced packaging. The panel warned of labor disruption—“I’m flattening it,” Ghazi said—yet emphasized augmentation over automation. Tyson flagged rising security risks, while others predicted “pervasive use of physical intelligence” and even that “we may cure cancer in our lifetime.”
Hello, everybody. Welcome to Davos, Switzerland. And welcome to the 2026 Annual Meeting of the World Economic Forum. We are happy that you're joining us live for this panel. And my name is Andy McAfee. I'm a scientist at MIT. I'll be the moderator today. And we're here at Thursday. We're close to the end of the annual meeting 2026. And I can assure you that the topic of this panel has been top of mind throughout the annual meeting this year. It's been probably one of the most actively discussed topics here, certainly because of this remarkable surge of progress we're seeing with AI, but for lots of other reasons as well. I think perhaps the dominant conversation this year at Davos has been exactly the subject of our panel today, which is converging with technology to win. Now, obviously, we need to define what win means. And that can mean different things to different people and different parts of the world. We probably need to talk a little bit about which technologies are top of mind, but this is the topic at Davos 2026, at least in anyone's top 2 or 3 list of topics. The good news is that we have people who are finally going to answer the question in 45 minutes, we're going to nail this. And the reason I say that with confidence is because of the panelists that I have the honor to share the stage with. I'm sitting next to His Excellency Abdulla Sawaya, who is the Minister of Communications and Technology for the Kingdom of Saudi Arabia. Next to him is a person who I personally have learned a lot from. Laura D'Andrea Tyson is an economist at the University of California, Berkeley. And you might have heard that there's a lot of technological innovation happening in and around the Berkeley area in Northern California. Luckily, Laura knows all the secrets, and she's going to share them with us. Next to her is Vimal Kapoor, who is the chairman and chief executive officer of Honeywell, a high tech company based in the United States. And last but not least is Sasan Ghazi, who is the president and CEO of Cynopsis, a technology company that you might not have heard of. Not as much of a household name, but critically important because they are a critical link in the semiconductor, manufacturing and innovation supply chain. I think without you all, we don't have the we don't have the chips that are powering the AI revolution. So first of all, thank you for that. And second of all, how the heck are you doing it? But I think, Laura, if we could start with you, please.
Okay. Happy to do it.
I because because economists like yourself have been studying this question for a long, long time. What is it that allows a region or a country to build a technology ecosystem that converges to a place that would make everybody happy? In other words, it innovates like crazy. It generates a lot of value for customers, a lot of wealth. It provides good jobs for a lot of people. Leaving modesty aside, you're part of the world. California is almost certainly the world leader in that. If you could give us your version of what happened in Northern California to make that work, and then more and then more broadly, because that's not enough. More broadly, what what's the secret sauce for getting the environment right to let this kind of magic happen? Industrial policy is a term that I know that you use. Some people do like it, some people don't. But there's no I think everyone here would agree. There's no way that we get these fantastic converging tech ecosystems without the government involved doing the right things. And I know you have beliefs about what those right things are. We'd love to start with those.
Good heavens, that was a long set of questions. In fact, I'm going to make a contrast. Let me make a contrast. The contrast between the kind of model that is behind the innovation. Technological revolutions in the United States, particularly around Silicon Valley. But I also want to talk about China, because if you I've been working for the past year on the battery and EV industries, and here is where a country, through an industrial strategy, it was a country that set the industrial strategy and then the country over many years. It wasn't like it didn't happen overnight, did a number of things to create the ecosystem with the private sector. Most of the producers of EVs in China are private companies, but it actually developed a whole ecosystem because it had a strategy to be a major player as a nation in EVs and batteries. Okay, so that's a quick summary of China. Of course, in the US, it really has been very much driven by basic science, by the relationships between companies and universities, I think. Synopsis. Right. It isn't synopsis connected. Yes to engineering faculty at Berkeley. We we know that, we have Google. And if we think about the history of Google, where does it come from? It's basically basic science support for students and faculty at a university, which leads to a breakthrough. The breakthrough becomes something which has a market value. It's taken out. It becomes a major what a major, a major company of the world. But it started that way, and it started that way with also people willing to take risks. So the issue of risk capital, I hear a lot about this in the situation that's going on in Europe, because there's a lot of discussion about how Europe has many technological strengths, but if it develops an innovation, frequently what it does is it looks for the risk capital, the private equity capital, the venture capital in the United States, because that market is so deep for financing it. So I want to emphasize, in, in the market model, the link with universities, the link with finance, the link with risk takers. Now, I'm going to say one other thing, because if you look back in history to the US, the US has not really had industrial policy, but it has had industrial policy related to defense. So a lot of the original breakthroughs, were coming out of DARPA or DARPA funded research that would occur at a university. So we did have the support of the Defense Department and the willingness to take risk in defense issues. And that that remains, by the way, that remains by the way, we used to have a lot, a lot of capital on the basic science side coming into, I would say just just medical research, cancer research, the development of new drugs, that drug pipeline that comes out of the United States. If you go back, you sort of see the support for basic science. So I would say those are the features of the US system in the in the Chinese system. I really want to say that it is the long term. A nation, not a company, has an industrial strategy. The nation decides that it wants to pursue competitiveness in this industry. It wants to pursue technological progress in this industry. It uses a variety of things, not access to venture capital, but essentially access to.
Sustained on hold on. In particular, us VC was incredibly important for the Chinese tech ecosystem.
Oh yeah.
No, no. Where where what I'm saying is that also in China, there is financing that is coming from the public sector. That's all. It's not to say that venture capital, at a certain point, if you think about, for example, AI, what China is pursuing at this point is really all of these amazing edge applications. And those edge applications are being financed by the private sector, by venture capitalists who are basically saying, we can, sell something to Tencent, and Tencent will actually transform what it does. So I really was thinking more, if you have a vision of a particular industry and the industry is nascent, it's not yet developed. Okay. Then having a public sector funding, which is essentially was part of China's strategy in EVs, but switching over time, switching over time to private sector.
Am I am I hearing right? You're doing a lovely job of saying that we have two very large, very successful tech ecosystems on the planet.
Yes.
Right now.
And they they.
Developed in different ways.
I'm hearing that you am I hearing correctly that you kind of prefer the Chinese one? No. Okay, great.
It's not that I prefer.
The Chinese one. I think if you I thought to a certain extent one of the words in the title of this was industrial strategy. To the extent that you're talking about industrial strategy, that is a national goal. And then you have to think about, are you equipped in your system to pursue the national goal? Okay. And so, for example, we have had now in the US, we had for a while, we decided we we needed for national security reasons to have a real ability to produce high end chips in the United States. It's a national security industrial strategy argument. We used a whole bunch of policy to get that done. We now have some production in the United States. Now, the problem, I would say is we have production, which is going to be pretty high cost. So keeping that competitive internationally is something we haven't solved.
Great. I want to make this concrete, Minister, you are responsible for formulating a national strategy for the kingdom. Indeed. My guess is that you and your colleagues have scanned the history and the current landscape of technology ecosystems. I'm sure as you've done that, there are two that stand out. There's the US, there's China. Is what you're doing more like one of those or the other. Are you a blend? Are you trying to find a third way? Like where where's your thinking on this?
And if we take a step back and we had the pleasure of collaborating during the digital age and that the guidance of His Royal Highness, how we can diversify our economy. And by the way, we've achieved 56% diversification of GDP.
Remarkably quickly.
Ahead of the 2030 mark. But really, it helped humanity overcome the over, you know, the great reset with the great resilience. And that's what the digital fabric gave us. And the investment thesis for the kingdom was very simple. If we double down on talent, technology and build trust with partners, we can achieve success and we're following the same, the same blueprint for the intelligence age, because the intelligence age would need two things the great acceleration, but the great adoption. And it's not only important that you focus on the supply side of the world, because that's going to trigger a couple of winters and bubbles. But it's the adoption. And that's why the kingdom we have energized the industrial age. It's only natural that we energize the intelligent age. Last year we clocked $0.11 per a million input output tokens. It's only natural for us to become the most AI enabled nation in the world. We're doubling down on generative AI in healthcare with UC Berkeley, and I'm going to share some success stories shortly. We're doubling down on AI, both in the public and private sector, where every private and public worker is going to have an agent to infuse that ten x productivity. And we have delivered the first physical AI deployment when it comes to a fully robotics heart transplant done within our national hospitals. Last but not least, is how we can become really the testbed for innovators and investors. Saudi last year and we had the largest investment ticket in AI and the largest success story in Nobel Prize winner, a Saudi American professor working with UC Berkeley and our national labs using AI to create new chemistry Metal-organic frameworks. Effectively a sponge with the right pore size to capture water from air and carbon. And when it comes to the largest ticket you can ask Jonathan Ross, who was introduced to the world two years ago on Leap, the largest tech event right now in the region, and by a mile from from a number of other other tech events. But on stage, how the kingdom is tackling the memory wall, how we're doubling down on memory, on the chip next to the chip and near to the chip. And we have demonstrated that $0.11 per a million input output token energizing Aramco, who wrote the first Po for Jonathan back then, how we could deliver bottom line efficiency with $1 billion last year and this year is creeping up to $2 billion of real AI adoption and how we can achieve the lowest uplift cost and carbon intensity. And this is a true testimony that in a call out to all our partners that in the intelligence age, you need a partner that can accelerate AI, but more critically adopt AI. And the Kingdom stands tall as your partner of choice.
Can Laura, let me ask one follow up question and then.
It's probably your follow up question.
Let's see how close we are on this one. Excuse me. Actually, I want to I want to calibrate the kingdom's ambitions here. At a minimum. I heard you say that the kingdom wants to ai enable the the organizations and institutions of of Saudi Arabia to take better care of the people of Saudi. You want you want to have amazing, not just digital but AI infrastructure for life in Saudi Arabia. That seems to me like the least ambitious thing that I heard you say, even though that's massively ambitious, are your ambitions to join the global stage of tech ecosystems that are transforming the world right before our eyes?
Trust me, the first time I met His Royal Highness, even when I was in the Silicon Valley, every year he would double or triple the target on us. So the ambitions is indeed global. And His Royal Highness has an investment thesis. The more prosperous the kingdom the Middle East is, the more prosperous the world is. And it's not a surprise that we fuel 50% of the digital economy in the kingdom. For the region, we fuel three x the tech force of our neighbors, and as a result, we fuel 50% of the VC funding and the number of unicorns. And as a byproduct of that, it's not a surprise that the World Economic Forum called out Saudi Arabia as the number one and number two digital riser consecutively. Going back to the intelligence age, we have energized the industrial world, and we helped the world achieve a more than $100 trillion of economic value. We want to help the world achieve the next $100 trillion by energizing the intelligence age. And we're laser focused. Since we're talking here about the technological walls, we're focused on addressing the energy wall 83GW the world needs we have already allocated. His Royal Highness has a committee that meets monthly on this, and he has designated one of the subcommittees His Royal Highness Prince Abdulaziz bin Salman. And we have allocated land energy that is available with more than ten gigawatts worth of capacity today in which we can deploy, and we've already have announced it. In the last visit of His Royal Highness to the Honorable President in DC, we had Jen-hsun Huang, we had Elon Musk, who are today in Davos, all have announced major investments and deployments with definitive agreements to go large in the kingdom. In terms of adoption, one true story alum, the most powerful Arabic LM we presented it to Adobe and Adobe right now have adopted it across all of their product suites. If you want to use an Arabic LM, it's powered by the Kingdom of Saudi Arabia, and we have partnered with Qualcomm to bring to the world the first hybrid AI laptop and endpoints. So these are true testimonies that the kingdom we're not going local here or regional, we're going global.
You are not playing small ball. If I use the American baseball analogy.
Israel has never.
Played small ball is not a thing we've associated recently. Trust me. Laura, before, before you ask your question, can I bring our other two panelists?
Oh, sure.
Sure. I'm sorry. No, no. Yeah. Vimal, let me go to you. You run Honeywell, which does business at the cutting edge of technology all over the world. As somebody leading an organization that interfaces with a lot of governments and a lot of ecosystems, could you talk about the things that you see that that give you optimism that that you're working in a, in a ecosystem that's heading in the right direction versus the things that you see that give you pause? You think this might not go so well? Is that is that a fair question?
Absolutely. And I you know, I think we as companies, Laura made a great point initially on ecosystems and ecosystems between, you know, the university system and the governments and how it creates innovation like Google. But companies like Honeywell and many others have very large investment in product development. And they're thinking ahead three, five, seven years, again with a strong linkage to the universities. Right. So one of the things we realized for the last 5 or 10 years is we need to be in the front end of interfacing with the governments to share with them what are we doing and have ability to shape a bigger picture. And, you know, governments like Saudi are very proactive. You know, we have access to people like His Royal Highness and others, very high access to share where things are going. And I'll give 1 or 2 examples. If you think about the world of AI, which is impacting every industry and therefore it has impact on energy consumption, one has to think about right way, all the way to the end, what will be AI used for and is the strategy to generate more energy is for the right cause. Because if you have a dialogue to say we need more power, we put more nuclear, we more more gas. The question I always pose is but what are you going to do with that? Have you been clear that are we going to make our best video and best pictures, or are we going to solve the healthcare problem?
Yeah.
What's your goal? And if you are going to solve the healthcare problem, we have solution for it. Then let us solve the energy problem in different ways. Is it gas? Is it nuclear? Is it energy storage. So I think ability to see this end to end picture, whether it's in the government, in United States or countries like Saudi or many other large economies, we see this as our responsibility. And what's in for a company like us. If we shape the policy right, it benefits us to be ahead of the game to understand our business model aligned with the policy. There's something in us for for that. But also it's our responsibility as a large company to give it back to the society in another form, to see these things are critical for the success of the society. And that's kind of where we think we have an important role to play in this whole ecosystem. And my concern, today is that, while there's a lot of dialogue on AI, it's bigger picture implications are not being discussed in depth on what it will be used for, because if it is being used for economic prosperity, please put more more power generation and do what? But it is being done for human curiosity and I'm going to do something more interesting. Probably it's not the best use of the resources of the planet at this point of time. So how do we have that dialogue and help people understand possibilities?
Are you telling me I shouldn't be creating funny images that amuse me on nano banana? Because that's ruining the planet? That that hurts.
Yeah. So it's.
Using energy that might be used in other ways. other ways, saying.
I get it, I just don't like it. Right? But on that point, there is a huge amount of concern right now about the environmental footprint, specifically of AI more broadly of of the digital ecosystems. And people are worried that, again, we might like making cool pictures with Llms, but the planet can't tolerate that. Is that an accurate belief?
I mean, look, the energy systems have been created over the last 100 years with hydrocarbons. Yeah, it started after World War one, so it's 105 years. So we have to be conscious that what I was created in 105 years can't be recreated in 20 years. Or maybe we can do in 30 years. Right. First you have to. So it's always going to be a slow move to a new state. So first we have to recognize that it's energy mix change. The energy transition probably is a little wrong representation. Now the choices we have made are limited. Because if you want to scale our power generation, the only source seems to be gas, because nuclear takes ten plus years to make. Other sources are not that interesting. But what what we have to think about in this is how do we drive energy efficiency? AI is a good source of energy efficiency in industrial sector. So while it's a source of consumption, it's also a source of efficiency. So therefore solving this problem holistically is a very interesting paradigm that you have to do it. But is there any black and white answer. No to this I wish I had it, I wish anybody else had it. I think the answer here lies on constant dialogue on technology evolution. Case in point is, companies like us never thought of energy storage at scale. On the demand side, today, we feel very confident that we can do energy storage at a source like consumption of, say, hospitals, stadiums, schools. And that can take a lot of peak power off. And therefore the energy demand is less. And that that is used now for AI generation, for healthcare problems. So solving this holistic issue is something we strongly believe in.
When you talked about the energy solutions available for these unbelievably energy hungry data centers, your list was short. Your list had one thing on it. If I listened correctly, you said gas. You didn't say gas and renewables. Can you educate us? Why not?
I mean, the what one has to appreciate is the intensity of energy. You know, I always like to. I'm an engineer by background. I always like to tell people the mix of energy. Doesn't matter. How much is wind, how much is solar? We like to advertise that kilojoules matter because energy intensity has to shift, not the mix. So solar power cannot produce cement. Solar power cannot produce steel.
It cannot.
They are very energy intensive, right? You still need a gas based heating, or.
Even after 3 or 5 more years of innovation in renewables. It's not there.
Physics, it's against physics. Physics won't allow it.
It's almost against.
So therefore, when you have to look at energy mix change in context of joules of energy, your challenge becomes different because the words still need to progress. Word needs to build more infrastructure. It still needs steel, it still needs cement. It's still need fuels. Now how do you do that in energy mix change, while you also want to build data centers and consume more energy. That's an interesting problem to solve. And today the problem is single threaded with the gas fired power plant. Maybe a little bit of nuclear. Nuclear renewables remain in the mix, but it cannot bring the the amount of joules we need to produce this infrastructure, which is required in the world.
Fantastic. So scene last but obviously not least to you. You run a you run a chip adjacent company. Is that a fair way to say it? Okay. So the question on everybody's mind about chips these days, because they are the it feels like they're the bottleneck for, the determining factor for how quickly things get amazing in the world. Everyone talks about the chip shortage and rationing chips and all that. So my question to you is, you know this better than probably almost anyone else. The chip industry has benefited from this almost miraculous phenomenon called Moore's Law since about the mid 1960s. And there are many ways to talk about that, right? One of them is that, either the amount of compute you can buy for the same dollar doubles every, let's say, 18 months, or the amount you have to pay for the same amount of power halves every 18 months. That phenomenon, unless I'm badly misinformed, has been pretty steady, pretty consistent in going on for something like 80 years. We've never seen anything like this. I hear a decent amount of conversation now that Moore's Law is running out of steam, and it strikes me that if that's true, then this flourishing of innovation that we have been seeing might actually slow down. Is that a thing that we should worry about?
First, let me, set the stage for our role in Moore's Law.
Good.
Where are you? Synopsis is the hundred billion dollar company that nobody has heard of. And the reason for it is we're part of an essential ecosystem. Moore's law does not exist in terms of continue that rhythm of 18 months of innovation. Without this stack of engineering innovation, it starts at the atomic level with material selection physics to build the transistor, to put it on a chip. The chip has billions of devices that somehow, magically, they work. And now, those devices, when you think of an AI chip, it's reaching a trillion devices and it's being being designed through number of vectors that you need to optimize. Moore's law is continuing, but it's not affordable. It's not at the same pace that what we were used to for the last 3 or 4 decades. Now, in any innovation, it has to be practical. Can you deliver it on time at an affordable cost? Therefore, the innovation is taking different, shape. So you start expanding at a system level to innovate. So when you think of AI. The reason it's possible today is because of the power of silicon. If silicon is not powerful, it can achieve the performance. You cannot run the models. The way, it's evolving is at an architectural level. You're able to stack multiple chips in a package. So the chips is becoming a system. So therefore it's not something to worry about because Moore's Law is hitting the limits of physics. There are other aspects to innovate, which is a system level innovation.
So this is great news. If I'm hearing you correctly, Moore's law is slowing down. That does not automatically mean that the party is over when it comes to this innovation digital bounty that we've been experiencing.
Yes, there is a terminology in the industry it's been referred to for the last five years or so, advanced packaging or multi-die, which is what essentially is your your only moving the part of the chip that you must advance process technology on Moore's Law. The rest of it is too expensive to move. So you disaggregate the chip, you break it into small chips, then you bring it back together in a system. That's what synopsis does. We provide our technology to every customer that is disaggregating that system, bringing it back together. And, just to give you a reference of the value and that supply chain, our company just six years ago was $10 billion in market value. We went up ten x to 100 billion. It just because of the essentialness in that supply chain to enable the everything you touch with silicon.
Okay. So a follow up question on that. You've calmed me down anyway that the semiconductor industry, which as you point out, is this astonishingly complex ecosystem and value chain, it might be one of the most complicated things we humans have ever built in the physical world. Right. You've calmed me down that it's going to keep the party going. And that's fantastic. There's another party going on, with innovation, with AI models of different kinds. There's absolutely a scaling law taking place. They keep on doing things that they could not do the week before. And I found myself in this weird position where I get up and I'm drinking my coffee. I look at the news from the tech sector, and I realized a little while back that I was no longer surprised at being astonished. I'm like, oh, wow, that's a miracle. Okay, great. You know, it's Tuesday. Is that party going to continue for a while?
Yes, that's that's the beauty of constraining a problem. Innovation. Come. Engineering comes to life when you constrain the problem. You look earlier, the discussion was China, us. If you look at China, for example, they got constrained from silicon access. They did not get access to the latest chips. Then deep sea came about. What happened? They they could not get access to the latest technology. You start going up the stack, which is the model. You create a far more efficient model for a specific workload. And it just beautifully works. Now, it does not mean China is further ahead than the US in models. Now in the US you have access to the latest silicon and you start what is silicon. It sits in a data center. Then that data center is used for the applications, the models. It can be for physical AI. It can be for a chatbot on your PC, for on your phone, whatever. So for each application there's an economic vector.
Yeah.
That's where power comes in, etc.. And then there is a differentiation. Are you able to deliver a product that's going to be first to market, and you just cannot do it without optimizing up that stack?
If I can just add one point to that, I mean, I think the Moore's Law in terms of more part of compute, is an interesting discussion and explained very succinctly on how this is not going to end. But the bigger power is how the ecosystem uses these tools to compound the power of it. So companies like us follow the tech word. All the innovation, Google is doing or Amazon is doing, and Microsoft and Nvidia and our engineers are able to connect the dots for the industrial sector. We serve to further compound the innovation. And I think innovation should not be looked in the blocks of individual components. It has to be look for the solution it provides. The solution. Compounding can happen with a human brain. To say, I thought this was possible, now it's almost possible. I'm going to give it a shot and make it happen. And I think that's what is propelling the innovation cycle. So things which we did 20 years back were not possible 20 years back, but now we are challenging ourselves for how our systems can co-create in a different manner. And it's opening up a new set of economic opportunity in industrial sector. And if I just make a quick point on example, so we make building management system in a building, we are sitting to make it more efficient so that it's more energy control. We are doing it for 40 years. We thought that was the best product we ever created. AI can make it even better than energy efficiency by another 10 to 15%. We never thought that 40 years back, but today we take that silicon, we take a compute power and put on top of it, and it's giving that extra 10 to 15% capability, which is ingenuity of human mind, that it can solve that extra set of problem. So Moore's Law continue. It continues to build more and more systems so that we are able to put it's all about economic value creation. How do you create more economic value, whether it's more revenue generation, more cost reduction. And that's what companies all all industrial companies are doing.
This is this is I promise. Let me say one more thing, and then I'm going to turn it over to you because I know you've got fantastic questions, but I have to react to this because this is the most encouraging and optimistic thing I have heard at Davos. Certainly this year, maybe, maybe in my time coming here, this is profoundly optimistic because what you two are educating us about is that there's this there's been this party going on with digital innovation. It doesn't solve all the world's problems, but it's a really good thing to have. And you two have just given us a very short masterclass. The, the conclusion of which is that that party is going to keep going, even if, as you say, if we run into ceilings or we start to approach a constraint, that's the wrong thing to concentrate on. The innovation ecosystem has the tools and the incentives to keep the party going, and we should expect a lot more digital innovation. All right. Laura, I'm sorry you had a question.
I really.
Want to go then to keep the party going. For what? I mean, you you actually first said, what should the goal be? I really do worry a lot about the fact that right now, the hyperscalers, all of all of them are on California. I think they're all they're in a race with one another. They're in a race with one another to get to AGI. They're not even sure why. They just think if they get there first, AGI would basically be able to to solve all human problems better than humans. Sounds absolutely fabulous. Why would you not want to do that? They are financed by a whole bunch of their financial structures who really are very much, return. The return is returned to investors. It's value creation. That's what it is. Okay. And it's not at all clear. There are lots of people who sort of do the numbers. Look at the the assumption about how much they're going to have to sell around the world to create the value, to support the financing they have raised there is not clear. There's a lot of risk here. So this is this is not an industrial strategy. This is a strategy of five firms competing against one another to achieve AGI. If you go to open seek which said, okay, we can't get these chips, but actually what we're going to do is we're going to provide open source. And basically then the rest of the Chinese economy can actually access this technology to apply it to their sector, to apply it to their consumers. And at the end of the day, that seems like a much more understandable approach. So I will then say, I have a question.
I keep on seeing you.
China leaning a little bit. Laura, I got to be honest.
I am not I'm, I'm I'm not China leaning. I am raising questions about the strategies being pursued by the hyperscalers, all of whom are here representing AI to the world. Okay, that's that's what.
I actually Saudi leaning because it's about acceleration and adoption coming together.
Got it.
Pardon.
It's about acceleration and adoption coming together. You're saying without the use cases.
Without the use cases without.
The use just focus on the supply side of the world.
We can't.
It has to be the supply and the demand.
The demand. Where is the demand.
To save lives.
To save lives, to actually improve energy efficiency over time because of the issue of the climate, which we can't mention here this year. But actually, I think we should we have real constraints on us from the climate. We have the issue of, youth and employment, youth and employment. So you said talent development has been very important in Saudi Arabia, but you have to find ways to keep those people moving in careers that generate living standards over time that are acceptable. That's a goal.
Laura, to your point.
That's an industrial strategy goal. It's not a goal of open AI. I like open AI's technology a lot, so I'm not. But it's not open AI's goal. It's value creation.
Before you jump in. Before you jump in, I just want to flag to our live participants here with us in the room. We're going to open this up for questions in just a little bit. But this is so spicy that I don't want to stop it right now. So over to.
You to build on Laura's point. I think where AI needs to emphasize is augmentation of skills, because if you look at the broader picture, human population is generally not growing in majority of the world today. There are exceptions, but there's a population shrinkage in most of the mature world, including China now, including China. So if I fast forward 15 years from now, if they're not going to be enough skilled people and people are not willing to do work where you have to work with hand to run an operation, run a building, run a plant, run a warehouse, how that work will get produced, and will it stop the economic progression? Or will the tools get created where one human can work of two humans, or a less experienced person can use a tool to do a work of more experienced person? We are focused to use and deploy AI. In that context. We are more around augmentation strategy of human to make them more productive. But that creates economic value.
And this is fascinating because I'm hearing two problems articulated that are basically the mirror image or the no, no, the the plane opposite of each other. Laura, I heard you talk about the fact that there might not be enough jobs to go around, that we're that we're creating some conditions for technological unemployment. I heard you just identify the exact opposite concern. There might not be enough people to do all the work that.
We have to do.
Which is it?
So but you have to differentiate between a work getting automated and augmentation. That's right. Because a human divides the work into three buckets. You define the problem, you execute the problem, and then you check if it was executed right. This is how humans have evolved over the last 1000 years in industrial world. Still, humans have to define what problem to solve. You can automate to execution. Software can come in, but the first and third step is augmentation. Let's take an example. Can AI read an x ray? Yes. But will you conclude a result of AI to say I read your x ray and here's a treatment you want a doctor? The last step to say right? Please tell me, is it the right one or wrong one? Right. And that's where the three step approach has to be done. So it's augmentation in the skills which are critical for for the planet. So I think if the focus is towards augmentation economic value creation will be higher and job losses will be lower. But if the focus is on the code automation and others that.
Couldn't agree more, it's all about acceleration adoption with the augmentation approach. Just to build on what has been said, there are few players that are just focused on the supply side of the world. That's like throwing good money after bad. And that's why it's not only takes capital, but a captive market and real use cases. So the x ray example, we have the largest virtual hospital today in in the world, part of the success story that we have under vision 2030. And what has happened as we deployed those AI agents, for those radiologists to be able to detect whether a tumor is benign or malignant, they were able to see more CT scans or MRIs, more x rays to be able to serve and help and protect more lives back. You know, taking a step back to that first robotics story of a heart transplant, he's able to get patients outside of the ICU room, in the CCU room, within for 4 hours or 48 hours, versus 4 to 8 weeks. This is a remarkable example of how, if you're talking about a responsible approach of leadership in the intelligence age, you need that acceleration adoption with the augmentation approach.
But we have. While I agree there hasn't been enough thinking of how to transform education and the talent that will be replaced with intelligence, yes, there is no question about it today. If you're graduating in computer science, you don't have a job. Very difficult. Five, six, seven years ago you could not get enough of them.
Enough jobs.
So there are tasks. If you're able to move it to automation, you don't need them anymore.
You don't need.
It as a company. I have 30,000 employees and about 25,000 of them are engineers. And those are the most sophisticated engineers in the world. Yes. Many part of my workforce. I'm flattening it. Why? Because I'm forcing and pushing to drive more augmentation, all the stuff that's been said. But what does that mean for the early in their career.
Coming in?
They don't have a job. And those are statistics there across the world that the unemployment for, areas that AI is able to automate is being impacted. Now the counter to it. Well that's great. You can do more innovation. But okay. That's not that's easy said. But innovate to build what is going to be a period of time where they're going to be stress in in the economy due to AI. But all of that being said, I'm a huge believer that you need to run and race with it because it's so significantly disruptive.
So so hold on. There will be bumps in the road, but we still have to accelerate.
You have no other choice.
You have no.
Choice because no, you.
Could you could try to mandate that. You got to slow down. Governments have tried to do that before.
But then you're missing a huge opportunity from solving significant problems. We may we may cure cancer in our lifetime because of the technology we have.
I think governments.
Definitely you have to raise.
Help us focus on the right areas.
I think help us focus.
On the right. I was thinking about all of those engineers, and basically I was thinking, okay, if the if computer science PhDs can't get jobs as fast, one of the things you could imagine is you could imagine more support for the universities. So those those computer science brilliant engineers could stay and continue to work on innovation in basic science. And sooner or later they would actually develop a product or a service which they could then go into the marketplace. I actually think your argument is to put in more basic science research, so you can support these people for longer periods of time as post-docs, because you can't say, oh, well, just go out into the world and become an entrepreneur. I mean, that's really you don't have any.
You need builders. Yes.
You have no, you don't have the ability to do that.
So we've got we've got time. If everybody is concise, we've got time for, I believe, one question from the audience, sir. The only rule, I'm sorry is threefold. It has to be concise. It has to be clear and it has to be a question.
Yeah.
Good question. Ten years from now on, the same panel, what is your prediction now that the world will be.
Oh yeah okay. Beautiful lightning round to end with. We're back where ten years in the future. What's the big story of the previous ten years? When you start.
History is a great predictor of the future.
We got to go quick. It's got to be a lightning round.
Lightning round? For every dollar made in infra, you'll see 20 bucks. In software. You'll see more use cases and more proliferation of these technologies to help the people, planet and prosperity.
Laura Short quick prediction ten years.
I think.
I'm very concerned about the national security breaches of all of this. I think we could have some serious issues that involve the geo economics that we're not talking about here. So I worry most about that. My positive side would be, yeah, I think it's quite possible we cure cancer. So so basically we I would say that is likely.
The ten year prediction.
I would say industrial ecosystem will work very differently in terms of the workforce it has. So we'll have to really evolve how the industrial machinery will evolve in the next one decade in terms of its processes and its workforce skills.
So I've seen ten years.
Pervasive use of physical intelligence that will dramatically change and improve human lives.
I can hardly think of a better note to end on than.
That's a good one.
I thank you all my panelists. Thank you for joining us.
Let's do that. So, so.