Markets destroy the comfortable assumption that tomorrow behaves like yesterday. They reward those who can identify when the system’s structure changes and punish those who try to fit new realities into old frameworks.
That is why the conventional idea of “what something is worth” has become less relevant than how systems evolve. Investors who cling to formulas intended for stable conditions will always be surprised by nonlinear disruption.
Nowhere is this more obvious than in AI and energy, where the variables are not just changing; the equations themselves are being rewritten.
The selloff in technology stocks this week startled some investors. It shouldn’t have. The signals of an AI bubble have been flashing for some time: billion-dollar raises for companies with no product, multibillion-dollar valuations for companies with no revenue, and nine-figure offers made to individual researchers. The AI race is building products that are economic complements to one another—you need the turbines that power the grids, that power the chips, that run the models, that power the products. And you need firms to build their growth and hiring plans around the expectation that ever more of their work will be done by AI. AI is in a bubble, companies will fail, and capex is unsustainably high. The real question is whether the infrastructure being built now will unlock a technological era that outlasts the speculation that paid for it. History suggests yes. The pattern repeats because the pattern works. The bubble is not the danger. Missing the moment is.
The sustainability of advanced technologies, unique manufacturing capabilities, global access, and robust supply chains is currently dependent on ill-defined, reckless, and volatile political and economic strategies. Ignoring the reality of the situation and hoping things will eventually work out isn’t a good plan. For decades, the world has relied on Taiwan Semiconductor (TSMC) to produce the most advanced chips, powering everything from smartphones to artificial intelligence. This dependence has created an unprecedented vulnerability: a single geopolitical flashpoint controls the lifeblood of the global digital economy. The challenges of advanced semiconductor technologies and manufacturing are among the most pressing and significant issues of this generation. The U.S. must acknowledge that a world dominated by a single supplier is unsustainable. It must invest not only in fabs but also in intellectual capital, allied coordination, and long-term technological leaps. There is no guarantee of success. The rivalry with China will intensify, and Taiwan will remain a flashpoint. But inaction is the greater risk. Hope may provide comfort, but only strategy, investment, and execution will ensure resilience. Hope is not a plan.
A turbulent geopolitical and economic environment is here to stay. Allocating capital in today’s economic and geopolitical landscape requires a sharp focus on macro trends, a disciplined approach to risk, and an ability to anticipate shifts in policy and global power dynamics. The investment landscape has never been more complex, with heightened tensions between the U.S. and China, uncertainty surrounding Taiwan, and Europe’s economic fragility. The new reality is that trade realignments, subsidized industrial policies, and emerging trading blocs characterized by protectionism and localization are rising. Now What?Geopolitical risk is no longer an afterthought. The US-China rivalry, Taiwan’s strategic importance, Europe’s economic fragility, and shifting trade policies will shape the next decade of global markets. Savvy investors will anticipate these changes and allocate capital to industries and regions positioned for sustained growth. The key to success is flexibility, resilience, and the ability to recognize macro trends before they materialize fully. The future is uncertain but full of opportunities.
The United States and China play global economic and political chess games. There are many moves and defensive and offensive strategies, not only for trade but also for energy and natural resources (rare earths among the most recent flavors of discord), geopolitics (Russia, Ukraine, Iran, the Middle East generally), technology (Taiwan and AI), and global economic supremacy. It’s a long list, but China and the US drive the outcomes. Instead of working for mutual benefit, regardless of fundamental cultural and political differences, we are now drawing bright lines demarking battle zones (Ukraine and Russia; Taiwan; AI and advanced technologies). The result will be economic and technical inefficiency and degradation in the quality of life, safety, and prosperity. China must acknowledge the outrage caused by its overreaching bids for control, and America must adjust to China’s presence without selling honor for profit. Competition is not us-or-them; reality is us-and-them. The U.S. semiconductor industry gets 30% of its revenue from China. China’s resulting products service the world, and China’s producers need the U.S. as well. If allowed, such examples of mutual benefit will proliferate. It is naïve to imagine wrestling China back to the past. The project, now, is to contest its moral vision of the future. Connected, collaborative engagement is the only practical way. China has come a long way, and its trajectory cannot be ignored or dismissed. The U.S. and China will be much better off from this more enlightened, realistic perspective. See the whole board.
The “Thucydides Trap” occurs when a rising nation-state—for the Greek historian Thucydides, it was Athens—must eventually have a violent confrontation with the existing dominant nation-state—Sparta in his time. It is a zero-sum game where there can be only one dominant nation-state as the eventual winner, and it is usually assumed that the rising nation-state will outdo the dominant nation-state resolved only by military conflict.The United States and China are today’s Sparta and Athens. For several decades, their geopolitical relationship has been fundamentally based on collaboration and healthy competition, raising the bar for both countries. Now, it is turning into discordant competition, trade restrictions, and embargoes. The combined benefits of global collaboration and competitiveness, not trade restraint, will only enhance the benefits for the United States and China. The government creates friction and potential conflict, which is the biggest reason we fall into the Thucydides Trap. If appropriate, oversight, sensible regulation, and enforceable trade agreements do not interfere with fair competition and collaboration. There is no “Trap” to avoid. The sooner China and the US realize this, the better off each country (and the world) will be.
Significant VC activity and AI development opportunities are emerging in China. DeepSeek is the Vanguard of innovation from the artificial intelligence “moonshot” encouraged by the Chinese government. Not only will we see ongoing developments from Alibaba and Tencent, but there will also be a layer of elite AI companies at the forefront of China’s AI sector. US sanctions and restrictions have only increased innovation and groundbreaking AI development activity in China. Those sanctions will amount to nothing and encourage accelerated advancement.
Predicting what’s next has been a fool’s game, and it continues to be. The S&P 500 was up 26% in 2023 and 25% in 2024, for the best two-year stretch since 1997-98. That brings us to 2025. What lies ahead? Rationality, Optimism, exuberance, disappointment, correction, and more frequent and intense volatility—with uncertainty about the timing, extent, and outcome. Is enthusiasm for new technology creating a bubble, and will the bubble burst? Optimism has prevailed in the markets since late 2022, generating above-average valuations and astonishing returns for some (primarily AI-related) equities. Stocks in most industrial groups sell at high multiples, but enthusiasm for artificial intelligence and the persistence of the Magnificent 7 drive most market expectations. There is the implicit presumption that the top seven companies will continue to be successful and that the “new thing” (artificial intelligence) will drive valuations even higher. However, stocks may sit still for the next 10 years as earnings rise and multiples return to earth. Another possibility is that the multiple correction is compressed into a year or two, implying a significant decline in stock prices. Be aware of Mr. Market’s irrational behavior. It’s not going to be a smooth pathway forward; there will be great investment opportunities, as there are in any market, but overall, it’s a high starting point. It’s time to be neutral.
Apple can disrupt global finance. Visa and MasterCard are now vulnerable. Previously, it was believed that the capital required for infrastructure, systems, and processing was an insurmountable obstacle to any new competitor. But things have changed. Innovation and disruption in the credit card business pose a threat to established players like Visa and MasterCard. Apple can leverage its ecosystem, user experience focus, brand trust, strategic partnerships, and innovative use of data to succeed in the credit card business. Over time, as it scales and innovates, it could challenge Visa and MasterCard’s market dominance.
AI is not a data problem; it is a cognitive architecture problem. Data and computing power will become insurmountable hurdles for transformer-based models. A new generation of AI models requires fundamental breakthroughs. Large data models can’t learn, transfer knowledge or understanding, understand the relevance, or use analogous learning to transfer that relevance and predict. Current AI models require massive and increasing data and learn from reinforcement. This cannot scale and is massively inefficient. Real learning based on cognitive architecture, focused dynamic data, and referential data sets is a better solution. This is closer to real human learning, more effective and efficient, and offers a significantly better solution. Understanding the natural learning process — referential and analogous data, categorization, transferring and building upon that data, and creating knowledge applicable to new situations — learning builds upon itself and is exponentially effective. That is the real AI solution.
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