At the 2026 WAVES Conference, Wang Xiao from Jiuhe Capital, Liu Ying from SoftBank China, Gao Yuhui from Chuangdongfang, and Feng Dagang, CEO of 36Kr, discussed the evolving AI cycle. The three investors agreed that while the AI wave is more intense than previous ones, its fundamental nature remains unchanged—it is still a structural opportunity driven by technological advancement. Regarding changes in the venture capital industry, the panelists noted that state-owned capital now accounts for 80%-90% of fundraising, with increased demands for deeper research capabilities and forward-looking judgment on the investment side, and organizational structures are shifting toward a “partners + Agent” model. On entrepreneurship, societal enthusiasm for starting businesses has been fully mobilized, but valuation bubbles remain a concern. In terms of investment opportunities, the low-altitude economy is viewed as a ten-trillion-yuan sector, with AI-driven transformation of traditional industries and embodied robotics also identified as key focus areas.
Article author and source: 36Kr
Investment industry guests discuss AI cycle changes and share their investment insights and selections.
Feng Dagang | CEO of 36Kr (Roundtable Moderator)
Wang Xiao | Founder of Nine Union Ventures
Liu Ying | Partner, SoftBank China Capital
Gao Yuhui | Managing Partner, Chuangdongfang Investment
AI 70 Years: The Question of Cycles
Feng Dagang: To the three panelists on stage, I’d like to begin with a small story: In what year was the term “AI” first introduced? It was 1956. Today, the term “AI” is 70 years old. Compared to AI, we are all still young—we’re all about 20 years younger than AI. As the younger generation, today we’re here to discuss the changes happening in this industry. Right now, this industry is in summer. Summer means everything has already happened, but the outcomes are still uncertain. Throughout this process, I’ve sensed that many transformations are taking place within the industry. Today, we’ll mainly address a few key questions: Is the cycle the same as before? Is entrepreneurship the same as before? Is investment the same as before? And finally, how do our judgments and choices stand?
Let’s first discuss the cycle. Today is called VC 3.0; everyone here is a seasoned veteran who has lived through many cycles—is this cycle different from the ones before?
Some say this AI wave is particularly massive, so this cycle may be different from previous ones—we’ve broken out of an old cycle and entered a new one. Others argue they’ve seen many cycles before, and this one is essentially no different: each time, there’s an emergence, a boom, a period of prosperity, followed by decline—so is this time really any different?
Let’s proceed in order, starting with Wang Xiao. Wang Xiao was one of the earliest angel investors in 36Kr, back in 2011—fifteen years ago. Today, we especially thank him, as he was one of our very first angel investors.
Wang Xiao: Yes, 36Kr is 16 years old this year, and we’ve been making investments for about 15 years, so we’ve essentially grown alongside 36Kr from the ground up.
Feng Dagang: Then you go ahead and start.
Wang Xiao: My first cycle was the internet, the second was mobile internet, and now we’ve entered the era of technological exploration. I believe artificial intelligence is part of it—and could be considered the third cycle.
I believe the essence of this cycle is the same as previous ones: it’s a structural opportunity driven by technological and societal advancements, which may ultimately give rise to new major companies—this wave is no exception. Of course, there are differences: the driving force here stems from the continuous improvement in GPU computing power, leading to a significant leap in AI capabilities. We can already observe emergent intelligence, triggering structural changes across industries—including robotics, daily office work, and numerous other applications. Previously, the core was connecting people with information; now, artificial intelligence is directly generating vast amounts of content and service capabilities. Therefore, I believe this wave may be even more powerful than previous ones.
This time, there’s another difference: fundamentally, this cycle presents a major structural opportunity arising from the broader geopolitical competition between China and the U.S. Therefore, we’re not just looking at technology—we’re also paying attention to policy, the China-U.S. dynamic, and the opportunities created by various forms of containment. I believe this cycle operates on a much higher dimension, which is why many see it as different from previous cycles. However, I still believe the essence remains the same: ultimately, it’s about fulfilling human needs and seizing the large opportunities brought by shifts in technological structure.
Feng Dagang: I’d like to add two questions. In the past, the cycles we observed often appeared to be cycles of computers or the internet, but ultimately they became opportunities across countless industries. But now, there’s a voice suggesting that this wave might be solely an AI opportunity, and that in the future, there may be no countless industries—only the AI industry. That’s my first question: Is this round truly an opportunity across countless industries? Second, you just mentioned “replacement”—does this wave have little to do with “people,” because we’ve already been replaced? I’d also like to hear the other two panelists’ thoughts on these two questions.
Wang Xiao: I believe people will always find their way to survive. Each wave of industrial revolution has replaced workers in the past, but over time, we’ve still managed to find our place. Even as silicon-based life becomes increasingly intelligent, humans can still discover their value and continue to experience the beauty of the world.
So I believe artificial intelligence won’t truly replace humans, but it may disrupt certain jobs and professions—this is inevitable. Currently, programmers appear to be the most affected by this wave. While machines’ capabilities are significantly improving, what remains unchanged is humanity’s ability to adapt. Human learning capacity and adaptability to society still endure. Therefore, many years from now, you’ll find that AI continues to create a better world—just as the Industrial Revolution led to a massive leap in productivity and ultimately improved the quality of human life.
I believe artificial intelligence has great potential for further advancement. It represents a crucial milestone on the path to an intelligent society, following the Industrial Revolution and the Information Revolution. In the future, society’s productivity could be dramatically enhanced: factories will become fully automated, drastically reducing costs since no human labor will be required—only electricity will power them. Fusion energy will provide affordable power, and biotechnology will significantly improve our quality of life. In another ten to twenty years, I believe society will undergo a qualitative leap, bringing about a substantial increase in overall happiness.
Feng Dagang: Please welcome General Manager Liu.
Liu Ying: SoftBank China entered China in 2000 and has been investing for over two decades; I myself joined SoftBank China in 2009 to begin my investment career. Since SoftBank China primarily focuses on hard technology investments, I have experienced many ups and downs throughout the wave of technological advancement. However, I strongly agree with Mr. Wang’s perspective: no matter how this cycle changes, the essence remains unchanged—it is fundamentally the same, because all technological progress aims to improve people’s lives, reduce the cost of living, and enhance societal efficiency.
But what makes this cycle different? From the internet to mobile internet, SoftBank invested in countless projects, including Taobao. Regarding this AI cycle, I’m even more convinced it’s a technological transformation—specifically, the technological upgrading of traditional industries. So, the replacement of human labor has already been underway for a long time; it didn’t start only with the emergence of AI. Back then, we invested in Kuwa, which focused on autonomous driving and robotic vacuum cleaners, and they entered dark factories very early on.
So I agree with Manager Wang’s point: human adaptability is very strong. No matter how much things change or new industries emerge, people will always find a way to survive. As social efficiency improves and the cost of living decreases, I don’t think “whether people can survive” is even an issue—many individuals may be freed from jobs they dislike and move toward work they truly want to do. Therefore, before even discussing technological advancement, this is essentially a shift in social and labor structures. I believe this is ultimately more beneficial to human well-being.
This wave may bring some adjustments to the industry, but more importantly, it can significantly improve the efficiency of traditional sectors—this is crucial. When evaluating whether a project is worth considering, we should always ask whether it enhances efficiency in people’s daily lives—food, clothing, housing, transportation—or brings about fundamental change. I believe this criterion will never change.
Feng Dagang: What you said reminds me of a historian who wrote a book called *The End of History*. So I think both of your viewpoints are actually aligned—you would never agree to write a book on the end of technology or the end of history, because history has not ended; it repeats itself over and over again.
Mr. Gao, what do you think is the same and what is different this time?
Gao Yuhui: To give a brief introduction, Chuangdongfang is a well-established venture capital firm with a 19-year history. Originally, we focused on early-stage, small-scale investments in hard technology, primarily in manufacturing, and so far, we have backed over 40 listed companies.
From the perspective of our company’s characteristics, I’d like to share my thoughts on cycles and AI-driven displacement. I fully agree with what General Manager Wang and General Manager Liu mentioned earlier—that the essence of cycles remains unchanged: they always follow a pattern of initiation, expansion, overheating, bubble formation, collapse, and then the beginning of the next cycle. The overall structure remains constant. But what might change? Under this wave of AI, it’s become much harder to identify turning points in the cycle. Previously, the trajectory was linear, and we could roughly estimate turning points by analyzing various factors. But now, beyond AI, the implementation of China’s “9+6” industrial policies under the 15th Five-Year Plan is also reshaping the entire cycle. AI is truly permeating every industry and altering long-standing development trajectories. For example, in protein folding research—once a process requiring years of intensive effort—AI has dramatically accelerated progress. Similarly, in new materials development, a 2024 study explored using Martian soil samples to produce oxygen, addressing the oxygen shortage challenge posed by Musk’s Mars colonization vision. Without AI, this research might have taken 1,200 years. With AI’s assistance, it was completed in just one month—in fact, initial results from AI-for-Science approaches emerged in about two weeks. In short, AI’s impact on every industry is profound. When we make investments, we embed each project within the broader macroeconomic, industrial, and sector-specific curves—and these curves are still drawn the same way. So, while change is undeniable, some fundamentals remain constant.
When it comes to the impact on talent, the effect is enormous. Take India as an example: previously, graduates most aspired to join the major software companies, as getting hired by them meant a leap in social class. Each year, these major software firms hired at least tens of thousands, even hundreds of thousands, of software developers. But this year, that number has plummeted—so far this year, these companies have hired very few people, and it’s reportedly targeted to cut 30% of their workforce. Why? Because Western countries no longer need these entry-level programmers. For instance, Australia’s entire financial sector has begun phasing out Indian outsourcing. Tasks that once required hundreds of developers are now handled by small teams augmented with AI. The impact of this shift is profoundly far-reaching.
AI also presents a tremendous opportunity for China: “AI + robotics.” “AI + robotics” can fully offset the demographic dividend, potentially blocking the path to industrialization for Southeast Asian countries, including India—countries that have already missed out on industrialization over the past decade and are likely to miss it again over the coming decades. For China, however, “AI + robotics” is precisely a vital solution to addressing its aging society. The changes brought by AI may surpass our expectations, and overall, I believe this wave of development is highly advantageous for China.
The Evolution of Venture Capital
Feng Dagang: Let’s turn it around and start with General Manager Gao. We just discussed cycles, and all three of you agreed that a cycle is essentially a loop that hasn’t been broken. Next question: Has venture capital changed? I come from an investment background myself, and I can clearly sense that things are different now. In the past, as long as you found the right person or team and invested in them, you could just wait for an IPO. But today is different—we now need to learn AI ourselves, build all kinds of capabilities, help clients secure orders. They ask you, “Can you help me generate RMB 100 million in a year?”—and when they say “RMB 100 million,” they don’t mean fundraising; they mean, can you help me bring my product to market? We also face various regulatory challenges both internationally and domestically—all of which are fundamentally different from the past. So, how do you see the differences in venture capital today?
Gao Yuhui: The entire era has changed, and VCs must evolve. The most significant difference lies in fundraising, investment, management, and exit. First, there has been a massive shift in fundraising. More than a decade ago, when Chuang Dongfang was just starting, there was virtually no state-owned capital—funding came entirely from social sources. But according to the latest figures, using various metrics, state-owned capital has accounted for no less than 80–90% of total fundraising in China last year. What’s the key difference between state-owned and social fundraising? State capital comes with the local government’s objectives—such as reverse investment and industrial attraction—which represents a major change. This requires GPs to adapt by developing capabilities in industrial attraction and reverse investment. In other words, you can’t simply invest based on a single dimension—like thinking a project is good. You now need to “do it all”: not only evaluate the project’s potential but also balance the diverse demands of multiple stakeholders. This is the fundamental shift in fundraising.
The same is true on the investment side—it is increasingly moving toward greater professionalism and specialization. This demands that all VC firms enhance their research capabilities and forward-looking judgment beyond previous levels; the more intense the current trends, the higher the demand for robust research and anticipatory insight.
Third, the organizational structure will change. Today, a partner works with a few team members; in three to five years, a partner may work with several agents (AI agents). If simple analysis is delegated to AI, will the industry become highly homogenized? If everyone uses the same model, what role can venture capital firms play? What is our value? Our value lies in the tangible ability to surpass AI in judgment, and in developing unique investment strategies and analytical models. Whether we can keep pace with this wave and make new changes and innovations will determine our future position in the market—and whether we can transition from past success to new greatness.
Feng Dagang: So AI provides a standard answer, but if we want to do well, we must go beyond the standard answer.
Gao Yuhui: AI does not provide standard answers. The biggest issue with AI today is that it can only achieve a score of 70 to 80 on any given task. If you want a 90, human intervention is required—this will lead to extreme market polarization in the future. I have several perspectives: AI will not bring equality; it will not break down information or knowledge barriers. Instead, AI will create larger echo chambers, turning the 80/20 rule into a 90/10 rule. This means that the value of those who can elevate AI-generated work from 70–80 to 90–100 will become significantly more pronounced. Conversely, individuals whose work capacity only reaches 50–60 will be ruthlessly displaced, as AI agents can easily replace them. As previously mentioned, the current state of work involves a few leaders guiding middle and even support layers. The middle and support layers—such as entry-level programmers and other basic laborers—are likely to be gradually replaced by robots and AI. Meanwhile, those at the very top will face new, greater opportunities. This is a harsh stratification—even within the “1%,” further divisions will emerge between those who create the “shovels” and those who merely use them. This trend is unlikely to change in the future.
Feng Dagang: Please welcome General Manager Liu.
Liu Ying: I strongly agree with General Manager Gao—not only has the landscape changed, but LPs themselves have changed, and this raises the bar for GPs. In the past, we were skilled in specific types of sectors; we simply identified which sector to focus on and which companies within it were top-tier—we’d go all in on the top three and then focus on post-investment support. But that’s no longer the case. Today, there are many more conditions to consider. Ironically, I feel today’s entrepreneurs are far more mature than those we sought out in the past. Previously, many founders lacked comprehensive education or training, but now, young entrepreneurs emerging into the space are highly professional and well-rounded in their development. In fact, we don’t need to micromanage them—we need to focus on aligning LPs with the right companies. This remains critically important; if we fail at this, we won’t be able to invest in the right companies or meet LP expectations—and that represents a higher standard for GPs.
For entrepreneurs, the projects I’m currently invested in require less oversight—I no longer review and analyze every quarterly report as I used to, because they’re doing an excellent job on their own. However, as you mentioned, I do consider whether to help them enter a specific market, but only to the extent of my capacity. For example, one of my portfolio hospitals has a new drug that’s highly suitable for their needs; I might facilitate connections between them, but ultimately, their ability to collaborate remains key.
I remember investing last year in a company that builds satellites—I bought a few satellites, costing millions. But what’s the point? Are we going to keep the satellites at our home? That’s why, as GPs, we invest within our means and avoid interfering in the companies’ operations. If a company can’t even manage its own market, why invest in it? That’s the mindset of investors like us.
Feng Dagang: So it’s indeed harder and requires higher standards than before.
Wang Xiao: Now I feel that the entire investment industry has several characteristics. In the past, USD-denominated funds in China sought companies similar to U.S. business models, as China’s mobile internet largely followed this broad logic. In the past, the core logic of RMB-denominated funds was to invest in companies likely to meet listing requirements, as our RMB funds primarily extended from the PE stage toward the VC stage.
What is the new environment? The new environment is that the dollar is relatively less active than before. What does China now require? We must compete with the U.S. in technological competition; RMB-based state-owned and local guidance funds have become key investors, driven by policy objectives. This new paradigm essentially places Chinese entrepreneurs at the forefront of technology and U.S.-China competition—in areas such as hardware exports, model capabilities, and applications. Fundamentally, it puts our entire startup ecosystem on equal footing with the U.S. in competition. This represents a very different path: it’s now increasingly difficult to copy the U.S. model, because the U.S. hasn’t even figured it out yet—we need to be the first to do it.
What are the requirements for VCs? First, in the Chinese context, they must be able to raise funds across diverse environments while balancing the demands of various LPs. Second, in the absence of precedents to follow, how can they anticipate and enter early during phases where consensus forms rapidly? When consensus emerges quickly—in areas like brain-computer interfaces or nuclear fusion—funding rounds occur monthly, and valuations double each month; being just one month late means missing a 100% valuation gap, and two months late means a fourfold difference. This demands much higher capabilities from VCs. Third, AI provides a stronger foundation for VC organizational structure, team composition, internal information flow, and research mechanisms. For example, I’ve trained my AI assistant—Longxia—on my methodology and past judgments; its analytical capabilities are now quite strong. It can identify logical flaws in business plans and during founder meetings, flagging issues for me. With continuous training, its judgment has reached a high level and can even help fill blind spots. However, you cannot rely on it to make final decisions—it serves instead as a tool for reminders, assistance, summarization, and project organization.
So I believe AI has significantly enhanced the organizational structure of VC and serves as an excellent tool and methodology. The VC industry has undergone tremendous changes—today’s Chinese VC landscape looks completely different from just a few years ago. The people who are active have changed, because after such a dramatic shift in the environment, some have dared to take bold steps forward, while others have become discouraged. After this major industry transformation, 70%–80% of participants have become inactive; only a few can navigate through the cycles. The VC industry is also highly cyclical, and those who can truly transcend these cycles are inherently rare. Moreover, the underlying fundamentals and essence of each wave of change are fundamentally different. For VCs, identifying and adapting to these core elements remains a significant challenge.
Feng Dagang: Excellent! The three of you have highlighted three different perspectives on why the industry has changed—because our upstream and downstream have changed, and our roadmap and reference points have shifted. Just now, everyone mentioned: Has entrepreneurship changed too? As someone who started in investment, I can say entrepreneurship today is very different from the past. How could we have ever imagined a project that hadn’t even launched, hadn’t created any product yet, raising $100 million or $200 million, with hundreds of people and dozens or even hundreds of institutions rushing in? These were all unimaginable in the past. We also couldn’t have imagined a company generating hundreds of millions in revenue within just one year of founding—all of this is fundamentally different from before. So let’s turn back now—Xiao Ge, how do you see the evolution of entrepreneurship?
Wang Xiao: First, the country’s core driver is essentially rooted in technology and equity, leading to increased investment in technology.
Second, the entire society has been energized, because companies with market valuations in the hundreds of billions have emerged within just a few years. This has mobilized everyone—local governments, professors at research institutes, and people from all walks of life. In the past, entrepreneurship was confined to a very small circle—mainly internet, IT, and engineers. But now, the entrepreneurial circle spans the entire country, with countless people thinking about how to start a business. The entire society’s enthusiasm has been fully ignited, creating a massive wave of activity. Yet, after the bubble bursts, some strong companies will inevitably emerge and endure. So bubbles aren’t entirely bad—they may consume some social capital in the short term, but in the long run, they still give rise to many outstanding technology companies, which is exactly what our country needs today. I believe the current bubble is still significant; to be honest, what VCs are essentially buying is dreams. But there must still be logic and accumulated foundations. Once limited partners stop making money, the entire system will rapidly cool down. This is highly likely to happen in the future, because things are currently too hot—but it will eventually cycle back to a more normal state.
Feng Dagang: What’s your take on this blazing-hot era, Director Liu?
Liu Ying: It’s a bit impulsive. In fact, over our twenty-plus years of investment history at SoftBank, when we first entered China, it was common to encounter an idea—someone would come with a business plan and walk away with a large sum of money. That was normal, and I wasn’t particularly surprised. But I’d like to point out that since we have both USD and RMB funds, USD is long-term capital. When USD enters a hot sector, it primarily operates at a loss; once one investment succeeds, the entire fund becomes profitable and recovers all costs. Therefore, USD and RMB are different—when LPs differ, so do investment strategies and risk tolerance.
Looking back over the past twenty years, although the current environment resembles the earlier era of diverse innovation, our experience now means we won’t chase every trend or bubble as we once did—we still carefully analyze a project’s market team and its fundamental aspects. I believe there may be fluctuations, but the fundamental driver of any industry’s growth is substantial capital investment. Without significant funding to fuel artificial intelligence, AI, embodied robotics, and their underlying systems, these industries simply wouldn’t take off—so what we’re seeing now is entirely normal. Different funds have different preferences and strategies, and that’s perfectly fine, but it’s clear that the market is currently overheated.
Gao Yuhui: This is a phase where seawater and fire coexist—a rare and exceptional opportunity for entrepreneurs, especially with the “9+6” initiative in the 15th Five-Year Plan: nine strategic emerging industries plus six future industries. Why say that? It comes back to AI, which we’ve emphasized today.
AI and large models have already “ingested” all of human knowledge, meaning that the concept of a “one-person company”—once unimaginable—is now a reality. A single individual can now harness the entirety of human knowledge to pursue any goal they set their mind to. Think about how many entrepreneurial opportunities this creates. There’s a fundamentally new perspective on talent: in the past, calling someone “high-minded but low-handed” meant they had grand ideas but lacked practical ability—it was a criticism. But in the future, it may become a compliment. Because with AI as a force multiplier, high vision no longer guarantees low execution. This is truly cause for celebration. Just look at how brilliant the Chinese people are—someone like Zhang Xue, who recently emerged unexpectedly, could have enormous potential when empowered by AI. We could even reimagine every existing industry, which is incredibly compelling for investors.
However, on the other side, we do have some concerns—the LP structure has changed. Everyone can calculate the total amount of capital invested by state-owned funds. Under these circumstances, “concentration among large investors” emerges. It’s not uncommon to see funding rounds happening every month. Why is this happening? State-owned capital holds vast sums of money, but there is a strict constraint: they cannot afford losses. This aversion to loss drives them to invest exclusively in high-profile projects, leading to mutual endorsement—everyone sees the same projects as attractive. Ultimately, this results in collective pursuit of a few hot topics, creating valuation bubbles for these projects.
Feng Dagang: This is called banding together for mutual support or mutual exemption from liability.
Gao Yuhui: The concentration of funds has enabled these trending projects to develop at breakneck speed, but it remains uncertain whether their actual engineering and industrial implementation will stay on schedule.
In such circumstances, true long-term thinkers and traditional venture capital firms must remain steady—avoiding the temptation to blindly pile into large bets or chase trends. Instead, they should focus on the underlying logic: What is the likelihood of success for this development path in the future? Especially in today’s many hot areas, technology pathways have not yet converged. If you have massive capital, you might afford to pursue multiple trends and diversify your portfolio. But as an investment firm primarily guided by market-based capital, we must remain calm and analytically identify the most reliable and prudent approaches, selecting those with the highest probability of success.
Investment judgment
Feng Dagang: We’re now moving to the fourth question—a simple one that requires a brief answer. In today’s wave of change, is there one investment opportunity that you absolutely cannot afford to miss? What I mean is, although everyone says they’re investing in AI, some are investing in software, others in hardware, some in models, others in applications, some in the deeper layers of the industry, and others in overseas growth opportunities. Many of you may even be reluctant to share what you believe in—something others haven’t noticed yet, but you know exactly what it is and how critical it is. What is that judgment? Let’s start with General Manager Gao.
Gao Yuhui:
The low-altitude economy. After careful analysis, we will dedicate significant time, effort, and investment to the low-altitude economy, as it encompasses at least six to seven industries within the “9+6” framework, and represents a long-term, high-potential赛道 with a future market size in the trillions. For example, the low-altitude economy extends into new energy, AI, and advanced materials. In terms of AI, applications range from autonomous flight systems in cockpits to airspace management and route planning—all of which will rely heavily on AI. This is a sector we are determined not to miss, and we will prioritize its development. We have established a low-altitude economy industrial fund in Shenzhen, and we are committed to deeply exploring, thoroughly developing, and excelling in this industry.
Feng Dagang: Those interested in the low-altitude economy can contact General Gao.
Liu Ying: We may focus more on AI—we have a dedicated AI-focused fund that invests in the transformation of traditional industries, which is a key area of our interest. For example, we are closely following advancements in healthcare, warehouse systems, autonomous driving technologies, and software for embodied robots.
Feng Dagang: A practical approach to transforming countless industries.
Liu Ying: Yes.
Wang Xiao: AI, as a new form of productivity or a tremendous capability, requires an endpoint. If it interacts with humans, it needs a larger endpoint beyond smartphones; when combined with productivity, that endpoint is robotics. AI needs a tangible application that can enter the real world—an “endpoint.” For consumers, this is likely to be glasses or smart hardware; for businesses, it’s likely to be various types of robots. These are all areas we’re closely monitoring.
Feng Dagang: Today, one of our guests couldn’t be here in person, but he asked me to share his answer to this question: AI For Science. He said that while general AI companies, like Apple, might reach a $1 trillion valuation, AI companies could reach $5 to $10 trillion—but AI For Science could reach $20 trillion. This is everyone’s own assessment.
Future of VC
Feng Dagang: We’ll move to our final question: Will you still be investing in five years? I often talk with various investors, and recently there’s been a lot of divergence. Some investors are extremely excited, feeling that opportunities have arrived—they see the $2 trillion figure mentioned earlier and believe there were no such opportunities before to build companies of that scale. Others feel that LP structures have changed, they no longer want to deal with the hassle, so they’re creating sub-funds, licensing their brand, stepping back from frontline operations, and simply enjoying the returns. What are your thoughts on this?
Wang Xiao: We will definitely still be doing this in five years, and perhaps even in ten. Investing is about your understanding of it and what you truly want to achieve. The structure of LPs has changed, requiring some additional effort, but that doesn’t mean investing is no longer viable. The tide of societal progress moves forward relentlessly—there are always new things emerging, and every day you can engage with entrepreneurs about fresh projects and ideas. Talking with the smartest, most visionary people is inherently enjoyable, and I believe the outcomes will also be positive. We’re precisely in the era of technological exploration, where opportunities to invest in great projects are inevitable. In the past, trillion-dollar companies were all American; now, I firmly believe China has the potential to nurture companies that grow from zero to a trillion-dollar valuation—that’s the overarching trend.
Liu Ying: As long as the fund exists, you have to see it through. The funds we’re currently raising are mostly 12-year funds; since we’ve set up these funds ourselves, we’ll finish them no matter what. I believe we’ll still do it, but personally, and for my team—which includes younger members—I’ll increasingly focus on industry-specific areas. Over time, we’ve invested in many listed companies, and we can collaborate with them to deepen our efforts in these industries, allowing us to concentrate our energy and resources more effectively. This is my personal interest. Younger founders and team members may engage in communication, investment, research, and support, while those of us with more experience can provide them with industry resources. Within our company, we also categorize our funds accordingly—we’ll continue doing this work.
Gao Yuhui: I entered this industry because I saw that there’s no retirement limit—so long as you want to keep going, you can work well into your eighties or nineties. What an fascinating field this is! Every day, I engage with the brightest minds, the most interesting souls, and the most innovative ideas, watching a small spark grow into a roaring flame, even spreading like wildfire, making significant contributions to human progress. Being able to help drive that transformation is incredibly fulfilling. In short, as long as I’m able, I’ll keep going.
Minor setbacks really aren’t significant at all; when viewed within the broader context of history and market cycles, you’ll see this is just a small adjustment. And if you look beyond the surface of U.S.-China rivalry, how many opportunities emerge! Different people have different preferences—so long as you’re passionate about this industry, I don’t believe it’s a matter of timing.
Feng Dagang: Perfectly aligned with our theme—a blazing fire this summer!
The first forum of today’s conference has now concluded. We hope to have provided everyone with a broader perspective on how cycles, investing, and entrepreneurship have changed. Thank you very much to our three guests for offering such insightful answers to this question. Thank you all, and we’ll see you next year!
