Physical Intelligence

Physical Intelligence

Robotics and related technology are ready for deployment, but the industry hasn’t crossed the threshold into full-scale production. Computational breakthroughs in stunning demonstrations are attention-grabbing, but the realities of industry quickly take over. There is a gap between robotics and artificial intelligence (“physical intelligence”) as it transitions from potential to hardware delivery in a demanding industrial setting. Physical AI and its integration into robotics may become one of the largest markets in history. But it is an industrial problem whose solution is not on a software timeline. In other words, its commercial deployment requires much more systems integration and real-world constraints than a software slide deck contemplates.

The Failure of Simplicity

The Failure of Simplicity

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.

Bubbles, AI, and the Economics of Belief

Bubbles, AI, and the Economics of Belief

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.

AI and the Economics of Ambition

AI and the Economics of Ambition

Artificial intelligence is no longer an engineering discipline. It is an economic one. The companies that win will be those that understand: Ambition requires capital. Capital requires compute. Compute requires global-scale infrastructure. Infrastructure requires a strategy measured in gigawatts and billions, not teams and timelines. This is not just the future of technology — it is the new architecture of global competition.

Innovation, Competitiveness, and a Fractured World

Innovation, Competitiveness, and a Fractured World

The US’s competitive advantage was developing the world’s best educational system, initiating innovative research and development, welcoming the world’s best students to thrive in an unrestricted environment, and accessing unique forms of capital for entrepreneurial ideas. The unique environment that combined academia and entrepreneurship, as seen at places like Bell Labs and Fairchild Semiconductor, was the spark that ignited Silicon Valley, the Life Sciences Corridor, the Innovation District, and the Research Triangle, among others, creating an unprecedented entrepreneurial environment and economic engine. This drove economic growth, disruptive innovation, and greater prosperity. This created a virtuous cycle that enhanced national wealth and economic opportunity. We are undermining all these advantages. The next 20 years will be defined by choices made today. Talent, energy, and technological innovation build the foundation for prosperity. Undermine them, and you guarantee decline.

Taiwan, Semiconductors, and U.S. Strategy

Taiwan, Semiconductors, and U.S. Strategy

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.

The Total Perspective Vortex

The Total Perspective Vortex

We are on the precipice of technological innovations that could potentially disrupt humanity, but they will not happen overnight, nor will they be out of our control. We have the time and hopefully the perspective to make wise choices.
It’s happened before.
A little over 100 years ago, and within a few decades, the automobile, the airplane, the telephone, and the electrical grid remade the physical and social fabric of life. For the first time, distances collapsed. Cities and homes glowed with electric light. Factories ran with continuous power. Communication traveled instantly across continents. People traveled unimaginable distances in hours rather than weeks or months.
What had been science fiction for centuries became everyday reality, and people felt both awe and dislocation. We can learn from the past, as the scale of disruption from that era was likely far greater than what we are experiencing today.
The Total Perspective Vortex is a form of torture because the truth of one’s insignificance is unbearable. Perhaps that truth is found in the disruptive innovations we admire and fear, the humanity that may be lost in this sea of technological innovation, and our anxiety about our own irrelevance.
We have a deeper responsibility. It’s happened before; perhaps humankind can make better use of the new era of disruptive innovation and our expanding powers more wisely.
In other words, get a perspective.

New Energy Innovation

New Energy Innovation

A new generation of clean, reliable, and flexible energy technologies, including, geothermal and advanced nuclear energy, is emerging. The story is no longer about clean and renewable energy. Solar and wind have their place, but capital investment and policy incentives are now focused on reliable, low-cost, controllable, domestic energy. For the first time in years, the policy, market, and demand signals are aligned in favor of a portfolio of solutions that are testing the edges of technology and are no longer narrow niches.

The AI Supercycle

The AI Supercycle

Artificial intelligence is driving technological disruption and economic transformation. It is a unique opportunity and, like PCs, the Internet, mobile, and cloud computing before it, AI is driving a new supercycle. Unlike previous technological revolutions, the current transformation is exponential, creating new industries and markets and impacting existing economic structures, costs, distribution, and employment. While productivity and economic growth are expected to surge, the most significant opportunity arises for capital owners, and therefore, investors. AI will be the most significant economic catalyst of the 21st century, fundamentally altering how we work, innovate, and create value.

Time for Hard Things

Time for Hard Things

With better models, more effective benchmarks, and a framework for constant improvement, now is the time to focus AI on complex, innovative, and transformational tasks. Essentially, AI and models should focus on hard tech. Hard tech refers to businesses rooted in advanced engineering and scientific innovation, often involving the development of physical products or systems that address complex challenges. Beyond drones, robots, and AI-driven hardware, the following are prominent examples of hard tech opportunities across industries. AI-driven hard tech is creating new business models and industries, such as personalized medicine, autonomous logistics, smart infrastructure, and agentic AI platforms that autonomously manage complex operations, reshaping the competitive landscape and unlocking new avenues for value creation. As a result, businesses and professionals who embrace interdisciplinary skills and continuous learning will thrive in the hard tech ecosystem.

Is AI Any Good?

Is AI Any Good?

So far, we’ve attempted to answer that question through benchmarks. These give models a fixed set of questions to answer and grade them on how many they get right. But just like exams, these benchmarks don’t always reflect deeper abilities. Lately, it seems as if a new AI model is released every week, and each time a company introduces one, it comes with fresh scores showing it surpassing the capabilities of its predecessors. AI research is a hypercompetitive infinite game. An infinite game is open-ended—the goal is to keep playing. However, in AI, a dominant player often produces a significant result, triggering a wave of follow-up papers that chase the same narrow topic. This race-to-publish culture puts enormous pressure on researchers, rewarding speed over depth and short-term wins over long-term insight. If academia chooses to play a finite game, it will lose.

This “finite vs. infinite game” framework also applies to benchmarks. So, do we have a truly comprehensive scoreboard for evaluating the true quality of a model? Not really. Many dimensions—social, emotional, interdisciplinary—still evade assessment. But the wave of new benchmarks hints at a shift. As the field evolves, a bit of skepticism is probably healthy.

The US, China, and Asia

The US, China, and Asia

The global investment landscape has reached a structural inflection point. Geopolitical realignments, industrial policy, and national security concerns are reshaping the era of frictionless globalization. At the center of this transformation is the intensifying strategic competition between the United States and China. The US is acting belligerently toward China in trade negotiations, threatening exorbitant tariff rates and trying to build walls around China’s international trade activity. All this may be a high-volume attempt to bring China to the table to strike a better trade arrangement. While this tactic is unprecedented, we may only be in the third inning of a nine-inning game. The current geopolitical and economic transition is both a challenge and a multi-decade opportunity. Capital will increasingly flow to regions that demonstrate policy consistency, innovation capacity, and demographic vibrancy. Strategic sectors such as AI, defense, semiconductors, energy, digital infrastructure, and cybersecurity will drive private and public investment. Embracing this new reality of regional diversification, thematic depth, and geopolitical foresight will position participants to thrive. As multipolarity replaces global uniformity, success lies with active, strategic alignment with the forces shaping the next economic era.