The New Geography of Innovation by Mehran Gul The Global Contest for Breakthrough Technologies
What's it about?
The New Geography of Innovation (2025) explores how cutting-edge technologies and high-growth startups are increasingly emerging outside traditional hubs such as Silicon Valley, reshaping the global innovation map. It investigates why certain regions suddenly become hotspots for breakthrough technologies, how government policy, talent, capital, and geopolitics interact in that process, and what this shift means for economic and technological power in the decades ahead.
For most of your life, “innovation” probably meant a few familiar places: a handful of big-name companies in Silicon Valley, maybe a research lab or two you’d seen in the news. For decades, that picture wasn’t far off, with a few companies setting the global pace in computing, the internet, and smartphone design. However, that world is changing fast. Breakthroughs in AI, clean energy, advanced manufacturing, and biotech are now emerging from cities you might struggle to place on a map.
Governments negotiate over chips and data with the same intensity they once reserved for oil and shipping lanes. Universities, investors, and startup founders are quietly rearranging themselves into new constellations – and the balance of economic power is shifting with them. In this lesson, you’ll learn how these new tech hubs are being built, how older ones are reinventing themselves, and how countries compete for the people and infrastructure that make it all possible. To see how far the center of gravity has already moved, it helps to start with a country that used to be dismissed as a copycat – but is now racing ahead, and turning new technologies into everyday reality.
Two decades ago, the idea that a Chinese internet startup could shape global tech would have sounded far-fetched. The story of Tencent shows how quickly that’s changed. It began with WeChat, a simple messaging service that caught on with a small but growing online population. Early on, most of its ambitions were domestic, and foreign investors saw it as a local curiosity rather than a future heavyweight.
Then came a pivotal decision: instead of just exporting its own products, it started importing the world’s best games and digital content into China, first as a distributor and then as an investor. It managed to keep promising studios alive with capital when they might otherwise have folded. That shift powered an extraordinary expansion. From a chat app company, Tencent grew into a giant whose services touch more than a billion users, and whose portfolio stretches from hit games like League of Legends, Fortnite, and Clash of Clans to major stakes in music, film, and social platforms across the globe. It’s now less a single company than a sprawling web of investments reaching into North America, Europe, and Asia. Tencent’s trajectory mirrors a wider change: Chinese firms that once imitated Western platforms now set global terms in sectors like gaming and digital entertainment.
Behind that rise is a particular pattern of innovation. China still lags the United States in foundational science and landmark prizes, and many leading AI architectures were first developed elsewhere. But the country has become extraordinarily good at the second phase of the technology cycle: rolling out new tools at speed and at scale. Nowhere else has adopted 5G networks, mobile payments, solar power, electric vehicles, industrial robots, and advanced batteries as quickly and as widely. The same is happening with autonomous vehicles, where Chinese cities host hundreds of robotaxis while similar services remain rare in Western streets. This dynamism sits alongside political limits.
As inequality has climbed and regulators moved against “disorderly expansion of capital,” large platforms have endured a sweeping crackdown and now operate under tighter state oversight, including government-held shares in some firms. Yet the leadership also expects these companies to help secure an international lead in strategic technologies. New ventures in areas like large language models, built by veterans of earlier waves of tech, show how strongly that expectation still pulls. China, in other words, is acting like an unusually ambitious student: still learning from the original pioneer, but determined to out-execute it in deployment. But what did that original pioneer actually build, and why does its template still matter to this race? Let’s find out in the next section.
If China looks like the hyperactive new star of tech deployment, Silicon Valley is the original template it learned from and now competes against. Silicon Valley, a relatively small stretch of Northern California, has produced an astonishing share of the world’s most valuable technology companies and billionaire founders. It draws in a huge slice of US venture capital and generates an economy that rivals whole countries. It’s the place other regions measure themselves against when they claim to be a serious tech hub, and that status did not come about by accident.
The story begins with Stanford University, in an era when the surrounding area was still largely agricultural. Lacking the prestige and funding of older East Coast universities, its leaders made a clear bet: instead of spreading resources thinly, they pushed hard into selected fields in science and engineering. At the same time, they moved aggressively to tap into the surge of postwar US defense spending, positioning the university as a key contractor for advanced research. That steady flow of federal money built up labs, attracted top scientists, and anchored a growing cluster of high-tech firms around the campus. A second move was to keep highly trained graduates in the region by encouraging them to start companies rather than leave for established industrial centers. Early firms such as Hewlett-Packard showed that small, engineering-led businesses near the university could grow into multinational players.
Stanford Industrial Park gave those firms a home close to campus, and helped entice figures like transistor co-inventor William Shockley and, later, the team that created Fairchild Semiconductor. Fairchild became a breeding ground for a whole generation of founders, who carried with them norms such as informal cultures, stock options, and a willingness to leave stable jobs to build something new. But what really made the region stand out over time was how those habits combined with a distinctive funding model. Venture capital embraced the idea that most risky bets would fail, but the occasional winner would be enormous. So, it directed unprecedented sums toward young, unproven entrepreneurs. This approach, together with dense networks of engineers who moved easily between firms, turned the Bay Area into an engine for repeated waves of innovation, from chips to personal computers, the internet, smartphones, and now artificial intelligence.
San Francisco’s current concentration of AI startups and the local dominance in advanced chips show how that reinvention continues, even as critics complain about costs, inequality, and politics. The obvious question is whether other regions can build their own versions of this success, or something meaningfully different. Let’s look at one prominent European attempt in the next section.
For years, Europe seemed like an observer in the global tech race, while the United States and China grabbed most of the attention. The rise of DeepMind, launched in London in 2010, shifted that picture. At the time, the UK had only a small number of billion-dollar tech firms and London was better known for finance than for frontier software, so early backing for the startup came mainly from overseas investors comfortable betting on long-shot AI research. Google’s acquisition of DeepMind in 2014 showed that cutting-edge AI could emerge from London, but it also exposed Europe’s weaknesses.
Many in the UK later felt that such an important lab had been sold too early and too cheaply, yet without access to deep capital and massive computing resources, it’s unclear whether the company could have grown at all. The same ecosystem that produced world-class research had not yet built the funding and infrastructure to sustain it independently. Since then, the environment has thickened. London now sits at the center of a UK tech scene that ranks just behind the US and China on measures like venture investment and the number of large startups, even as wider economic worries temper the national mood. A striking feature of this growth is geography used as a strategic tool. The redevelopment of King’s Cross has packed major tech offices into a compact district that also serves as London’s busiest transit hub, as well as the gateway to Europe’s high-speed rail network.
The local culture also feels different from the classic Bay Area story. AI founders describe an intense but slightly less cut-throat hiring market, fed by strong computer science departments at nearby universities – and not dominated by a few giant local platforms. The city’s concentration of government, finance, media, and design gives startups direct access to regulators, customers, and creative partners within a single urban space. Layered onto this is a strong concern with how power is used.
European investors and founders often emphasize privacy, fairness, and limits on corporate dominance. These concerns still fuel debates around DeepMind’s governance and defense-related work, showing how ethical arguments shape real decisions about ownership and research directions. Taken together, London and its orbit are an attempt to prove that an ambitious tech hub can be globally competitive while still reflecting European social values. To see a very different way of building a leading tech center, let’s turn next to a state that has tried to design innovation almost from scratch.
Faced with few natural resources and a tiny domestic market, Singapore chose to compete by making technology part of its basic infrastructure – on the same level as ports, housing, and defense. This mindset grew out of insecurity. After separation from Malaysia in the 1960s, the country had almost no natural resources and a very small population. So, its leaders set out to make it the most reliable place in Asia to do business.
Over time, clean administration, English law, and a welcoming stance to multinationals created a dense cluster of global firms and research institutes that gave it something to build on. On that foundation, Singapore launched an ambitious national program under the Smart Nation banner, coordinated directly from the top of government. Instead of outsourcing everything, it created an internal tech arm, GovTech, with hundreds of engineers working like a product company rather than a traditional ministry. That structure means the state can design and run its own platforms, adjust them quickly, and even share components across agencies instead of rebuilding the same tools over and over again. The impact shows up in everyday routines. Singpass, the national digital identity, is widely used to access thousands of services from both the public and private sectors, covering everything from healthcare records to housing and banking.
A nationwide layer of sensors feeds information on things like water leaks and air quality into central systems. They even have detailed digital models of the whole island which are used to test out buildings, roads, and sunlight patterns before construction starts. Large projects such as the Tuas megaport are conceived from the beginning as highly automated, data-driven operations, rather than upgraded versions of older facilities. People sit at the center of this model. Technical talent is treated as a strategic resource, with targeted paths to bring top engineers into public service, draw experienced Singaporeans back from global tech firms, and expose visiting experts to government projects. At the same time, the state has poured money and attention into building a startup and venture scene, using co-investment schemes and generous grants to attract funds and encourage local founders.
The result is a tightly run, highly digital city-state that many others study – but few can copy directly. Underneath its success lies a theme that matters everywhere: the belief that winning the race for talent is as important as buildings or capital. In the final section, we’ll zoom out to see how that global competition for brains is reshaping innovation as a whole.
If you want to understand who will lead the next wave of technology, follow the people, not the patents. Few places make that clearer than Canada, where a relatively small scientific community and a handful of standout founders have pulled the country into the heart of the artificial intelligence boom. Many of the key figures behind modern AI research in Toronto, Montreal, and Edmonton were born elsewhere, and a large share of headline founders in Canadian tech are also first-generation immigrants. That’s not an accident.
Canada has spent decades treating immigration policy as an economic development tool. It admits a high number of newcomers for its size, filters applications through a points system that rewards education and skills, and has designed work permits that make it relatively easy for tech workers to relocate. Programs have even targeted frustrated talent in the United States, while universities have become magnets for international students who often aim to stay and build their careers there. The social context helps this strategy land. Canadian identity is described as unusually flexible, making it easier for people from very different backgrounds to feel they can fit in. Research labs in AI-heavy cities routinely mix scientists from across the world, producing networks that cross both disciplines and borders.
At the same time, public concern over the pace of immigration has started to rise, and intake levels are being trimmed back. This offers a reminder to everyone that political support for openness cannot be taken for granted. Alongside immigration, Canada has built a distinct AI infrastructure. National institutes in Toronto, Montreal, and Edmonton are expected to do more than publish papers; they also help industries apply machine learning and supply skilled people to young companies. The aim is to compensate for smaller budgets than the US or China by moving faster in turning research into products, especially in fields like energy and industrial optimization. The broader tech ecosystem has deepened around this core.
The country now hosts many billion-dollar startups and attracts significant foreign investment, building on the success of firms like Shopify and on dense networks of accelerators, investors, and alumni. Taken together, Canada’s experience shows how immigration rules, research institutions, and social attitudes can upgrade a country’s role in frontier technology within a generation. In a world where advanced chips, capital, and office space are increasingly mobile, the places that manage to attract, keep, and empower rare talent are the ones quietly redrawing the map of innovation.
The main takeaway of this lesson to The New Geography of Innovation by Mehran Gul is that the map of innovation is being rewritten by places that can combine ideas, capital, and especially talent in new ways. Power is no longer locked into one valley or one country, but is emerging from ambitious cities, smart states, and open societies that move fast and learn from each other. The next big breakthroughs could come from almost anywhere – and that diversity of starting points makes the future of innovation more open and exciting.
The New Geography of Innovation (2025) explores how cutting-edge technologies and high-growth startups are increasingly emerging outside traditional hubs such as Silicon Valley, reshaping the global innovation map. It investigates why certain regions suddenly become hotspots for breakthrough technologies, how government policy, talent, capital, and geopolitics interact in that process, and what this shift means for economic and technological power in the decades ahead.
For most of your life, “innovation” probably meant a few familiar places: a handful of big-name companies in Silicon Valley, maybe a research lab or two you’d seen in the news. For decades, that picture wasn’t far off, with a few companies setting the global pace in computing, the internet, and smartphone design. However, that world is changing fast. Breakthroughs in AI, clean energy, advanced manufacturing, and biotech are now emerging from cities you might struggle to place on a map.
Governments negotiate over chips and data with the same intensity they once reserved for oil and shipping lanes. Universities, investors, and startup founders are quietly rearranging themselves into new constellations – and the balance of economic power is shifting with them. In this lesson, you’ll learn how these new tech hubs are being built, how older ones are reinventing themselves, and how countries compete for the people and infrastructure that make it all possible. To see how far the center of gravity has already moved, it helps to start with a country that used to be dismissed as a copycat – but is now racing ahead, and turning new technologies into everyday reality.
Two decades ago, the idea that a Chinese internet startup could shape global tech would have sounded far-fetched. The story of Tencent shows how quickly that’s changed. It began with WeChat, a simple messaging service that caught on with a small but growing online population. Early on, most of its ambitions were domestic, and foreign investors saw it as a local curiosity rather than a future heavyweight.
Then came a pivotal decision: instead of just exporting its own products, it started importing the world’s best games and digital content into China, first as a distributor and then as an investor. It managed to keep promising studios alive with capital when they might otherwise have folded. That shift powered an extraordinary expansion. From a chat app company, Tencent grew into a giant whose services touch more than a billion users, and whose portfolio stretches from hit games like League of Legends, Fortnite, and Clash of Clans to major stakes in music, film, and social platforms across the globe. It’s now less a single company than a sprawling web of investments reaching into North America, Europe, and Asia. Tencent’s trajectory mirrors a wider change: Chinese firms that once imitated Western platforms now set global terms in sectors like gaming and digital entertainment.
Behind that rise is a particular pattern of innovation. China still lags the United States in foundational science and landmark prizes, and many leading AI architectures were first developed elsewhere. But the country has become extraordinarily good at the second phase of the technology cycle: rolling out new tools at speed and at scale. Nowhere else has adopted 5G networks, mobile payments, solar power, electric vehicles, industrial robots, and advanced batteries as quickly and as widely. The same is happening with autonomous vehicles, where Chinese cities host hundreds of robotaxis while similar services remain rare in Western streets. This dynamism sits alongside political limits.
As inequality has climbed and regulators moved against “disorderly expansion of capital,” large platforms have endured a sweeping crackdown and now operate under tighter state oversight, including government-held shares in some firms. Yet the leadership also expects these companies to help secure an international lead in strategic technologies. New ventures in areas like large language models, built by veterans of earlier waves of tech, show how strongly that expectation still pulls. China, in other words, is acting like an unusually ambitious student: still learning from the original pioneer, but determined to out-execute it in deployment. But what did that original pioneer actually build, and why does its template still matter to this race? Let’s find out in the next section.
If China looks like the hyperactive new star of tech deployment, Silicon Valley is the original template it learned from and now competes against. Silicon Valley, a relatively small stretch of Northern California, has produced an astonishing share of the world’s most valuable technology companies and billionaire founders. It draws in a huge slice of US venture capital and generates an economy that rivals whole countries. It’s the place other regions measure themselves against when they claim to be a serious tech hub, and that status did not come about by accident.
The story begins with Stanford University, in an era when the surrounding area was still largely agricultural. Lacking the prestige and funding of older East Coast universities, its leaders made a clear bet: instead of spreading resources thinly, they pushed hard into selected fields in science and engineering. At the same time, they moved aggressively to tap into the surge of postwar US defense spending, positioning the university as a key contractor for advanced research. That steady flow of federal money built up labs, attracted top scientists, and anchored a growing cluster of high-tech firms around the campus. A second move was to keep highly trained graduates in the region by encouraging them to start companies rather than leave for established industrial centers. Early firms such as Hewlett-Packard showed that small, engineering-led businesses near the university could grow into multinational players.
Stanford Industrial Park gave those firms a home close to campus, and helped entice figures like transistor co-inventor William Shockley and, later, the team that created Fairchild Semiconductor. Fairchild became a breeding ground for a whole generation of founders, who carried with them norms such as informal cultures, stock options, and a willingness to leave stable jobs to build something new. But what really made the region stand out over time was how those habits combined with a distinctive funding model. Venture capital embraced the idea that most risky bets would fail, but the occasional winner would be enormous. So, it directed unprecedented sums toward young, unproven entrepreneurs. This approach, together with dense networks of engineers who moved easily between firms, turned the Bay Area into an engine for repeated waves of innovation, from chips to personal computers, the internet, smartphones, and now artificial intelligence.
San Francisco’s current concentration of AI startups and the local dominance in advanced chips show how that reinvention continues, even as critics complain about costs, inequality, and politics. The obvious question is whether other regions can build their own versions of this success, or something meaningfully different. Let’s look at one prominent European attempt in the next section.
For years, Europe seemed like an observer in the global tech race, while the United States and China grabbed most of the attention. The rise of DeepMind, launched in London in 2010, shifted that picture. At the time, the UK had only a small number of billion-dollar tech firms and London was better known for finance than for frontier software, so early backing for the startup came mainly from overseas investors comfortable betting on long-shot AI research. Google’s acquisition of DeepMind in 2014 showed that cutting-edge AI could emerge from London, but it also exposed Europe’s weaknesses.
Many in the UK later felt that such an important lab had been sold too early and too cheaply, yet without access to deep capital and massive computing resources, it’s unclear whether the company could have grown at all. The same ecosystem that produced world-class research had not yet built the funding and infrastructure to sustain it independently. Since then, the environment has thickened. London now sits at the center of a UK tech scene that ranks just behind the US and China on measures like venture investment and the number of large startups, even as wider economic worries temper the national mood. A striking feature of this growth is geography used as a strategic tool. The redevelopment of King’s Cross has packed major tech offices into a compact district that also serves as London’s busiest transit hub, as well as the gateway to Europe’s high-speed rail network.
The local culture also feels different from the classic Bay Area story. AI founders describe an intense but slightly less cut-throat hiring market, fed by strong computer science departments at nearby universities – and not dominated by a few giant local platforms. The city’s concentration of government, finance, media, and design gives startups direct access to regulators, customers, and creative partners within a single urban space. Layered onto this is a strong concern with how power is used.
European investors and founders often emphasize privacy, fairness, and limits on corporate dominance. These concerns still fuel debates around DeepMind’s governance and defense-related work, showing how ethical arguments shape real decisions about ownership and research directions. Taken together, London and its orbit are an attempt to prove that an ambitious tech hub can be globally competitive while still reflecting European social values. To see a very different way of building a leading tech center, let’s turn next to a state that has tried to design innovation almost from scratch.
Faced with few natural resources and a tiny domestic market, Singapore chose to compete by making technology part of its basic infrastructure – on the same level as ports, housing, and defense. This mindset grew out of insecurity. After separation from Malaysia in the 1960s, the country had almost no natural resources and a very small population. So, its leaders set out to make it the most reliable place in Asia to do business.
Over time, clean administration, English law, and a welcoming stance to multinationals created a dense cluster of global firms and research institutes that gave it something to build on. On that foundation, Singapore launched an ambitious national program under the Smart Nation banner, coordinated directly from the top of government. Instead of outsourcing everything, it created an internal tech arm, GovTech, with hundreds of engineers working like a product company rather than a traditional ministry. That structure means the state can design and run its own platforms, adjust them quickly, and even share components across agencies instead of rebuilding the same tools over and over again. The impact shows up in everyday routines. Singpass, the national digital identity, is widely used to access thousands of services from both the public and private sectors, covering everything from healthcare records to housing and banking.
A nationwide layer of sensors feeds information on things like water leaks and air quality into central systems. They even have detailed digital models of the whole island which are used to test out buildings, roads, and sunlight patterns before construction starts. Large projects such as the Tuas megaport are conceived from the beginning as highly automated, data-driven operations, rather than upgraded versions of older facilities. People sit at the center of this model. Technical talent is treated as a strategic resource, with targeted paths to bring top engineers into public service, draw experienced Singaporeans back from global tech firms, and expose visiting experts to government projects. At the same time, the state has poured money and attention into building a startup and venture scene, using co-investment schemes and generous grants to attract funds and encourage local founders.
The result is a tightly run, highly digital city-state that many others study – but few can copy directly. Underneath its success lies a theme that matters everywhere: the belief that winning the race for talent is as important as buildings or capital. In the final section, we’ll zoom out to see how that global competition for brains is reshaping innovation as a whole.
If you want to understand who will lead the next wave of technology, follow the people, not the patents. Few places make that clearer than Canada, where a relatively small scientific community and a handful of standout founders have pulled the country into the heart of the artificial intelligence boom. Many of the key figures behind modern AI research in Toronto, Montreal, and Edmonton were born elsewhere, and a large share of headline founders in Canadian tech are also first-generation immigrants. That’s not an accident.
Canada has spent decades treating immigration policy as an economic development tool. It admits a high number of newcomers for its size, filters applications through a points system that rewards education and skills, and has designed work permits that make it relatively easy for tech workers to relocate. Programs have even targeted frustrated talent in the United States, while universities have become magnets for international students who often aim to stay and build their careers there. The social context helps this strategy land. Canadian identity is described as unusually flexible, making it easier for people from very different backgrounds to feel they can fit in. Research labs in AI-heavy cities routinely mix scientists from across the world, producing networks that cross both disciplines and borders.
At the same time, public concern over the pace of immigration has started to rise, and intake levels are being trimmed back. This offers a reminder to everyone that political support for openness cannot be taken for granted. Alongside immigration, Canada has built a distinct AI infrastructure. National institutes in Toronto, Montreal, and Edmonton are expected to do more than publish papers; they also help industries apply machine learning and supply skilled people to young companies. The aim is to compensate for smaller budgets than the US or China by moving faster in turning research into products, especially in fields like energy and industrial optimization. The broader tech ecosystem has deepened around this core.
The country now hosts many billion-dollar startups and attracts significant foreign investment, building on the success of firms like Shopify and on dense networks of accelerators, investors, and alumni. Taken together, Canada’s experience shows how immigration rules, research institutions, and social attitudes can upgrade a country’s role in frontier technology within a generation. In a world where advanced chips, capital, and office space are increasingly mobile, the places that manage to attract, keep, and empower rare talent are the ones quietly redrawing the map of innovation.
The main takeaway of this lesson to The New Geography of Innovation by Mehran Gul is that the map of innovation is being rewritten by places that can combine ideas, capital, and especially talent in new ways. Power is no longer locked into one valley or one country, but is emerging from ambitious cities, smart states, and open societies that move fast and learn from each other. The next big breakthroughs could come from almost anywhere – and that diversity of starting points makes the future of innovation more open and exciting.
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