Every major technological revolution follows a familiar pattern. A breakthrough begins as expensive and exclusive, but as costs fall, adoption explodes and the technology becomes ubiquitous. Computers once filled entire rooms. Air travel was reserved for the wealthy. Mobile phones were luxury items. GPS was a military technology. The internet connected only a handful of research institutions. What transformed these inventions was not merely their existence, but their affordability. The invention creates possibility. Affordability changes the world. Apollo proved humanity could reach space. SpaceX may prove humanity can afford it. That distinction could have profound implications for artificial intelligence. Today, AI is running into physical constraints. Technology companies are investing hundreds of billions of dollars in data centers, yet power, cooling, land, water, and grid capacity are becoming major bottlenecks. Increasingly, the AI revolution looks less like a software upgrade and more like a massive infrastructure rebuild. Now imagine solar-powered data centers operating in orbit. What sounds like science fiction today may become practical if launch costs continue to fall. Unlike terrestrial facilities, orbital data centers could access near-continuous solar energy, avoid competition for land and water, and operate without burdening already stressed electrical grids. Most importantly, they could help address one of AI’s biggest challenges: heat. Every AI computation generates heat, and cooling has become one of the largest costs of large-scale AI infrastructure. Space offers unique advantages for managing this challenge. Cheaper access to space could eventually enable lower communication costs, faster global connectivity, more powerful AI systems, and entirely new industries that have yet to be imagined. That is why the real story is not rockets. The real story is infrastructure. The greatest opportunities created by SpaceX may not be inside SpaceX itself, but among the companies building advanced energy systems, next-generation semiconductors, orbital communications networks, high-efficiency solar technologies, and the broader infrastructure of a space-based economy. Today this sounds futuristic. In ten or twenty years it may seem obvious. The IPO story is fascinating, but the infrastructure story may ultimately be far more valuable. History shows that the largest fortunes are often created not by the breakthrough itself, but by the infrastructure that allows the breakthrough to scale.

SpaceX and the Question Most Investors Are Missing The largest IPO in history has now completed its first two full days of trading. Many expected a disappointing debut given the company’s enormous valuation and the hype surrounding it. Instead, SpaceX (SPCX) has surged nearly 40% above its IPO price, giving it a market capitalization of roughly $2.5 trillion. Options trading is expected to begin soon, and despite a relatively small public float, the company is likely to become a member of major market indices once it meets eligibility requirements. According to the S&P Dow Jones Indices Committee, that process typically requires at least 12 months of trading history. Let me be clear: I am not suggesting SpaceX is a buy at current levels. By conventional valuation measures, it appears extremely expensive. In fact, I suspect very few analysts truly know how to value it. Traditional models work well for mature businesses, but they often fail when a company is creating entirely new economic possibilities. That is why I believe investors may be asking the wrong question. Rather than asking what SpaceX is worth today, we should ask: What happens when access to space becomes cheap? History shows that whenever transportation costs collapse, entirely new industries emerge. Railroads created national commerce. Commercial aviation created global tourism. The internet enabled digital commerce. In many cases, the biggest winners were not the infrastructure providers themselves, but the businesses built on top of that infrastructure. One of the best examples is the humble shipping container. Before containerization, cargo was loaded and unloaded by hand. Shipping was slow, expensive, and inefficient. Standardized containers dramatically reduced transportation costs, accelerated global trade, and transformed supply chains. Few investors were excited about shipping containers themselves, but those who understood what cheaper transportation would enable saw the bigger opportunity. I believe SpaceX may be creating a similar moment. For decades, space was accessible only to governments and a handful of contractors because launch costs were prohibitively high. The Apollo and Space Shuttle programs consumed hundreds of billions of dollars. Imagine if every airline ticket cost hundreds of thousands of dollars. Modern aviation would never have existed. That is the equation SpaceX has changed. Reusable rockets have transformed launch economics. Falcon 9 boosters now routinely launch, land, and fly again. What once cost enormous sums now costs a fraction of what it did only a generation ago. And if Starship succeeds, launch costs could fall dramatically again. If that happens, SpaceX may become far more than another highly valued company. It could become the foundation of an entirely new economic infrastructure. History suggests that when infrastructure costs fall, innovation explodes. The most important question may not be what SpaceX is worth today, but what new industries become possible because of it. That is the subject of Part Two.

Gold, Inflation and a Potential Fed Regime Change On June 10, markets received one of the hottest inflation readings in recent memory, with CPI rising from 3.8% to 4.2%. Since the effective Fed funds rate is only a little above 3.6%, real interest rates have become even more negative, reaching their deepest level since 2023. Under normal circumstances, this should have been bullish for gold. Negative real rates reduce the attractiveness of cash and bonds and typically drive investors toward inflation hedges such as gold. Yet the opposite happened. Gold broke below a major trendline that had defined its rally for the past seventeen months and is now more than 30% below its all-time high. There are two obvious explanations. First, markets are forward-looking. Interest-rate markets are pricing roughly a 70% probability of a Fed rate hike by year-end, suggesting investors believe today’s deeply negative real rates may not last for long. Second, the geopolitical or “war premium” that helped fuel gold’s rise since September may be fading. The recent decline in gold has been accompanied by sharp falls in silver, platinum and crude oil, while the U.S. dollar has strengthened. However, there may be a deeper story. When the world emerged from the Global Financial Crisis, gold traded below $1,000 an ounce. This year it briefly exceeded $5,000. That fivefold increase was not primarily a rate story; it was a money-supply story. Massive quantitative easing, deficit financing and Federal Reserve balance-sheet expansion flooded the system with liquidity, lifting the nominal price of assets across the economy. As new Fed Chairman Kevin Warsh described it in congressional testimony, much of this amounted to “fiscal policy in disguise.” Gold prospered because investors sought protection against currency debasement and excessive money creation. That is why the upcoming Fed meeting on June 17 is so important. Investors are not merely watching for a rate decision; they are looking for signs of a genuine policy shift under Warsh. If Warsh follows through on his earlier comments, a real regime change could emerge. In such a scenario, gold could continue to decline even as interest rates fall, because markets would be pricing in less money creation, greater monetary discipline and lower long-term inflation expectations. The challenge is that such a transition will not be easy. The Federal Reserve is more divided than it has been in decades, and the recent rise in inflation gives policymakers even less room to maneuver. The key question for investors is whether the post-2008 era of quantitative easing, abundant liquidity and asset inflation is finally coming to an end—or whether this is merely a pause before the old playbook returns once again.

What once belonged in comic books, science fiction movies, and dystopian novels increasingly feels as though it is becoming reality. As we stand on the eve of the largest IPO in history, it is worth putting SpaceX (SPCX) into perspective and understanding what it could mean for technology, investors, and humanity itself. Until now, the record for the largest IPO belonged to Saudi Aramco, which raised approximately US$29 billion in 2019. SpaceX has now eclipsed that mark, raising US$75 billion at a valuation approaching US$1.8 trillion, with the potential to raise an additional US$11 billion through the underwriters’ greenshoe option if demand remains strong. The obvious question is: what does SpaceX plan to do with all this capital? The answer lies in one of the most ambitious visions ever pursued by a corporation. SpaceX aims to dramatically expand Starship production, achieve rapid rocket reusability, continue building out the Starlink constellation toward its long-term target of 42,000 satellites, create a global communications infrastructure, and ultimately establish a self-sustaining human presence on Mars. What makes these goals remarkable is that they are not purely theoretical. SpaceX has already revolutionized spaceflight through reusable rockets, conducts launches at an unmatched pace, and operates the world’s largest satellite constellation. Few companies have combined such an ambitious vision with such a strong record of execution. This credibility helps explain why the IPO has reportedly been several times oversubscribed. Investors are not simply buying a space company; they are buying into a platform that sits at the intersection of aerospace, communications, artificial intelligence, and next-generation infrastructure. The SpaceX offering also signals something larger. It demonstrates the enormous appetite for transformative technology companies and suggests that substantial capital remains ready to flow into future innovators. Many expect a new wave of major technology listings over the coming years, particularly in AI, advanced computing, robotics, and space infrastructure. History shows that every major technological revolution—from railroads and electricity to the internet and smartphones—created extraordinary wealth, interrupted by periodic corrections. The current AI and space revolution may prove no different. Whether SpaceX ultimately justifies its valuation remains to be seen. But there is little doubt that it has already transformed the economics of space and opened the door to entirely new industries. My conclusion remains simple: despite inevitable market corrections, the technological revolution driving AI, advanced computing, and space infrastructure is far from over. If anything, we may still be in its early stages.

There has never been a technology that democratized capability without first being feared by the people whose capability it democratized. Today, most discussions about Agentic AI fall into two camps. One argues that AI agents are simply productivity tools that make workers more efficient. The other warns that they are coming for our jobs. Both views miss the bigger picture. Agentic AI is not just a productivity tool, though it will likely become the most powerful productivity enhancer ever created. Nor is it simply a job killer. It is the first technology in history that gives ordinary people direct access to expert-level capabilities without requiring them to become experts first. History shows a consistent pattern. Reading, electricity, automobiles, computers, the internet, all began as elite privileges before becoming universal utilities. Every time this happened, entire industries were transformed and new economic opportunities emerged. The automobile was once a luxury toy for the wealthy until Henry Ford made it affordable and accessible. The result was not merely more cars, but the creation of suburbs, highways, modern logistics, tourism, and entire new industries. Similarly, the personal computer evolved from a hobbyist device into an essential tool that laid the foundation for the internet economy. The same transition is now occurring with AI. Nvidia itself reflects this pattern. What began as a gaming hardware company has become a cornerstone of the world’s AI infrastructure. Once again, a niche technology has evolved into critical infrastructure. The lesson is simple: when elite capability becomes universal capability, the floor of what is economically possible rises. Agentic AI represents that moment for software and knowledge work. Unlike a chatbot that merely answers questions, an AI agent can take action. It can analyze data, write code, access databases, manage workflows, generate reports, monitor markets, and coordinate complex tasks across multiple systems. A small business owner can increasingly use AI to analyze sales, manage inventory, adjust pricing, create marketing campaigns, and generate dashboards—tasks that once required teams of specialists and significant budgets. This is not simply productivity. It is capability democratization. The non-programmer can build applications. Entrepreneurs can operate with the leverage of an entire back-office team. Independent creators can produce studio-quality work. Students can conduct research that once required teams of analysts. Across industries, the distance between having an idea and executing it is collapsing. The real challenge is not jobs. It is that many professional moats were thinner than people believed. Capabilities that once commanded premium value are rapidly becoming commodities. Yet history suggests that when capability becomes cheaper, human ambition expands to fill the gap. A two-person company can increasingly operate like a fifty-person company. Startups can scale with far less capital. Small businesses gain access to capabilities once reserved for large enterprises. At the same time, an interesting reversal may emerge. For decades, society encouraged people toward office-based knowledge work while steering them away from the skilled trades. As software expertise becomes increasingly automated, the value of physical-world skills may rise significantly. Demand for electricians, plumbers, carpenters, mechanics, construction workers, and infrastructure specialists could surge. AI can write code, but it still cannot build a bridge, wire a skyscraper, or repair a water main. Agentic AI is therefore far more than a productivity tool and far more than a threat to employment. It is the next great democratization of capability. And every time humanity has crossed such a threshold, the economy that emerged on the other side has been larger, more productive, and filled with opportunities that were previously unimaginable.

Over the weekend Alexander Zverev finally got a chance to lay his hands on a grand slam cup . Before that he had been in 11 grand slam semis and four finals. When it comes to crunch games there was always something missing in him . He had all the works as a great tennis player . Can serve consistently at 220 km or even above . Great height and a good forehand. With most of the seeded players out in the first round or by quarter finals this was his greatest opportunity. It was now or never and I am happy to see that he delivered. Now to markets . On the back of a very strong jobs report markets sold off heavily on Friday. Payrolls were well above estimate and prior months were revised up . The reaction wasn’t a growth scare , but a rate repricing . The market now has clearly moved to price the next Fed move as a hike . December fed futures are indicating a 70 % chance for a hike by year - end . Having said that stocks bounced back yesterday. Not that much . But we get another challenge for the interest rate picture tomorrow when we get the May CPI numbers . Wednesday’s number should be the same as before or even higher . And with inflation around 3.8 % and effective Fed funds rate at 3.62 % real rates are already negative. The last time real rates crossed negative like this , the Fed did something unexpected and even the opposite of what one would expect . Instead of shrinking the expanded the balance sheet. What we know is when faced with liquidity stress or inflation, the Fed prioritises liquidity. So real rates went negative. We have the same play book now . The Fed flipped again last December. They responded to stress in money markets by returning to balance sheet expansion. adding liquidity which is inflationary into a rising inflationary scenario. So the Fed is caught in a catch 22 situation. The market is now pricing in a rate hike . That ignores the liquidity priority . But that’s not the advertised Kevin Warsh outlook. He is prioritizing lower rates and a smaller balance sheet in the face of liquidity issues and hotter inflation. We have discussed this before . Remember the speech Fed Governor Stephen Miran has given in Miami. He said the whole “ reserve scarcity “ problem is man made . It’s regulatory driven . He said banks are forced to hold trillions in reserves not by choice , but because of Dodd - Frank and Basel liquidity rules require it . So the path to a smaller Fed isn’t a blunt stop to bond - buying , which might at this point hurt the funding markets . According to Miran , ease the regulation first , which lowers the structural demand for reserves , let the balance sheet come down without creating scarcity , and in Miran’s own words, then offset the drag with lower rates . That is the plan but the markets are currently pricing the opposite.

Ever since the ChatGPT breakthrough in November 2022, software development activity has accelerated dramatically. What began as a steady improvement in developer productivity has, in recent months, turned into a near-vertical surge. During a recent keynote in Taiwan, Jensen Huang made a striking observation: roughly 30 million software developers earning about $3 trillion in annual salaries are now producing nearly three times as much output thanks to AI. In effect, $3 trillion of labor is generating productivity equivalent to almost $9 trillion. This is not merely a software upgrade—it is a productivity revolution. The timing aligns closely with the major leap in AI model capabilities earlier this year and the emergence of agentic AI systems such as OpenClaw. This may well be the “ChatGPT moment” for Agentic AI, where AI evolves from being an assistant into a digital worker capable of operating autonomously. Huang connected this explosion in software productivity to the broader global economy of over $100 trillion. Since software increasingly powers every industry, gains in software output eventually ripple across manufacturing, healthcare, finance, energy, transportation, and beyond. Does this mean the global economy is about to triple in size? Perhaps not immediately. Economic growth still faces constraints from infrastructure, energy, regulation, and physical production. However, the trend aligns closely with what Elon Musk has been saying for over a year: that advanced AI and humanoid robots could create a world with virtually no meaningful limit to economic growth. For most of history, labor has been the primary constraint on economic expansion. But if every human can be augmented by multiple AI agents and autonomous robots performing both digital and physical work, labor scarcity begins to disappear. And when output is no longer constrained by labor, productivity surges. Higher productivity drives stronger economic growth, greater prosperity, and rising living standards. This is why AI should be viewed not as another technology cycle, but as the foundation of a new economic infrastructure—one that may ultimately prove as transformative as electricity, the internet, or even the Industrial Revolution itself. We are still in the early stages, but the direction is becoming increasingly clear: intelligence is becoming abundant, labor is becoming scalable, and the productive capacity of the global economy is expanding in ways that were unimaginable just a few years ago. The coming decade promises to be one of the most extraordinary periods of economic and technological transformation in modern history.

At the outset, let me correct an error from my previous report and offer my apologies. I had mentioned that the upcoming Federal Reserve meeting would take place on June 8. In fact, the meeting is scheduled for June 16-17 and will be the first major policy gathering under the leadership of the new Fed Chairman, Kevin Warsh. The timing is important because it comes immediately after the historic SpaceX IPO, expected to be the largest public offering in history. More importantly, investors will be watching closely for signs of the much-discussed "regime change" at the Federal Reserve and how it could reshape economic policy not only in the United States but across the world. While we are on the Fed, it is worth revisiting what the outgoing regime represented. Last Sunday, Jerome Powell accepted a “Profile in Courage” award. In his speech, he argued that if governments remove central bankers over policy disagreements, the Federal Reserve risks losing its most valuable asset—its credibility and independence. But that raises an important question: what exactly did independence mean during the Powell era? For much of the past two decades, the Fed has been deeply intertwined with fiscal policy. Through repeated rounds of Quantitative Easing (QE), it purchased trillions of dollars of government debt, expanding its balance sheet to unprecedented levels. Kevin Warsh has described this as “fiscal policy in disguise” because monetary policy increasingly became a tool supporting government spending. The Powell Fed was also far from neutral. During President Trump’s first term, the Fed continued raising rates despite low inflation and a still-recovering economy, contributing to a liquidity squeeze that ultimately forced a reversal. When COVID struck, rates were slashed back to zero and massive stimulus programs were launched. Perhaps the bigger policy error came in 2021, when Powell repeatedly described inflation as “transitory” even as price pressures surged. Rates remained near zero while inflation climbed to four-decade highs. Critics argue that this assessment provided political cover for additional trillions of dollars in fiscal spending at a time when the economy was already overheating. From this perspective, the so-called independent Fed often functioned as a partner to fiscal policy rather than a counterbalance to it. What Powell is defending today is not merely central bank independence, but the Bernanke-Yellen-Powell framework that has dominated monetary policy since the Global Financial Crisis—an era defined by near-zero rates, repeated QE programs, and an ever-expanding central bank balance sheet. Warsh appears to have been chosen to bring that era to a close. His stated objective is to restore a more traditional model of central banking by shrinking the balance sheet, reducing reliance on QE, restoring market-based price discovery, and ending the perception that the Fed exists to finance government deficits. This does not mean QE disappears forever. In times of genuine crisis, the Fed may still deploy extraordinary measures. The difference is that such interventions would likely be temporary emergency tools rather than permanent features of economic management. The implications extend far beyond Washington. A meaningful shift in Federal Reserve doctrine would influence global capital flows, bond markets, currencies, and the policy decisions of central banks around the world. For nearly two decades, markets have operated on the assumption that central banks would always provide liquidity whenever trouble emerged. The June 16-17 meeting may offer the first real glimpse into whether that era is ending. If it is, investors should prepare for a world where capital once again has a real cost, market discipline returns, and central banks play a much smaller role in financing government ambitions. Such a transition would mark one of the most significant shifts in global monetary policy since the 2008 financial crisis.

Markets are beginning to wake up to what could become the largest IPO in financial Over the last few weeks, I have spent considerable time reading through the details surrounding the upcoming listing of SpaceX. The numbers involved are staggering. SpaceX is reportedly targeting a valuation of as much as $1.75 trillion, with more than twenty underwriting banks participating in the syndicate and Goldman Sachs leading the book. If all goes according to schedule, the company is expected to debut on Nasdaq on June 12 in what would be the biggest IPO ever attempted. For investment banks, this could be a record underwriting opportunity. And SpaceX may only be the beginning, with OpenAI and Anthropic also viewed as potential future blockbuster listings. The SpaceX roadshow begins on June 4, pricing is scheduled for June 11, and preparations appear to be on track. However, what interests me is not SpaceX as a stock. What interests me is what SpaceX could do to the market itself. Three weeks before SpaceX’s S-1 filing became public on May 20, Nasdaq quietly implemented a major rule change. On May 1, the exchange shortened the waiting period for Nasdaq-100 inclusion from three months to fifteen trading days, relaxed public-float requirements for large-cap listings, and introduced a methodology that effectively gives low-float companies greater index weight. These changes received little attention. The SpaceX filing did. Yet for investors, the rule changes may prove even more important than the IPO itself. SpaceX is reportedly seeking to raise about $80 billion. Given the likely oversubscription, hundreds of billions of dollars in institutional capital could be committed during the book-building process, temporarily reducing liquidity available elsewhere in the market. The timing is also notable. April CPI came in hotter than expected at 3.8%, and the Fed’s June 8 meeting falls just days before pricing. A more hawkish tone could cause institutions to reassess commitments before the IPO is finalized. The Nasdaq rule changes become even more significant when viewed through the lens of passive investing. Funds tracking the Nasdaq-100 will likely need to buy SpaceX shortly after inclusion. Because SpaceX is expected to have only about a 5% public float, the new weighting methodology could amplify its index impact despite limited tradable shares. A 5% float on a $1.75 trillion company represents roughly $87.5 billion of tradable stock, yet Nasdaq’s methodology could treat it as substantially larger for weighting purposes. As a result, index funds, ETFs, pension plans, and quantitative strategies may be required to buy more SpaceX shares than its float would normally justify. The key point is that this buying is not discretionary. It is systematic, rules-based, and likely to occur over a short period. To accommodate SpaceX, existing index constituents such as Apple, Microsoft, Nvidia, Amazon, and Meta would see their weights reduced, potentially creating selling pressure even without any change in fundamentals. This highlights a broader reality of modern markets. Passive funds, algorithms, derivatives, and benchmark-driven flows have made markets increasingly interconnected. A major index event can create ripple effects across many securities and funds. Whether this proves bullish or bearish is impossible to know. But that may be the wrong question. The real story is that markets are increasingly driven by rules, benchmarks, and automated capital flows rather than purely human judgment. The SpaceX IPO may become the first large-scale test of this shift. Investors who think they are on the sidelines may discover they are participating anyway. Because when a company of this size enters the market, it does not simply become another stock. It becomes a force that can reshape capital flows across the market.

For the past two years, we have spent considerable time discussing Artificial Intelligence and the technologies powering it. If there is one lesson investors should have learned by now, it is that the AI playbook is remarkably simple: More compute → More revenue → More profit → More compute. And then the cycle repeats. What we are witnessing is not merely another technology upgrade. It is the construction of a new economic infrastructure, comparable to railroads, electricity, and the internet. Like every major technological revolution, it begins with enormous capital investment. The evidence is no longer theoretical—it is showing up across earnings reports throughout the AI ecosystem. At the center stands Nvidia. The company recently reported roughly $82 billion in quarterly revenue, more than ten times its revenue of three years ago, and guided to approximately $91 billion next quarter. Growth of this magnitude rarely occurs without a fundamental shift in the economy. Even Nvidia may have underestimated the opportunity. Its CFO recently suggested annual AI infrastructure spending could reach $3–4 trillion by the end of the decade. To meet that demand, chips must be manufactured. TSMC, the world’s leading advanced chipmaker, recently reported 20% monthly revenue growth and approved $45 billion of additional capacity expansion. But chips cannot function without memory. Micron has become one of the biggest beneficiaries of the AI boom, with soaring revenue, expanding margins, and much of its future production already committed under long-term agreements. High Bandwidth Memory is increasingly being viewed as strategic infrastructure rather than a commodity. Legendary investor Stanley Druckenmiller recognized this shift early, rotating capital toward AI hardware suppliers. His thesis echoes an old lesson from the California Gold Rush: more fortunes were made selling picks and shovels than digging for gold. The story extends far beyond chips and memory. AI generates enormous volumes of data that must be stored, organized, and analyzed. Storage providers such as Sandisk are seeing rising demand, while Snowflake recently reported $1.33 billion in product revenue, raised guidance, increased AI customers from 9,100 to 13,600 in a single quarter, and signed a $6 billion infrastructure agreement with Amazon. Databases are benefiting as well. MongoDB reported strong growth and raised guidance as it positions itself as the data layer for the coming wave of AI agents. And all of this ultimately runs on servers. Dell recently reported an AI server backlog of roughly $43 billion after AI server revenue grew more than 340% last year. The message coming from every layer of the AI stack is remarkably consistent: Demand is accelerating. Guidance is rising. Supply remains constrained. While markets obsess over inflation prints, oil prices, and geopolitical headlines, those are largely cyclical forces. What is happening in AI is structural. One affects quarters. The other affects decades. When semiconductors, memory, storage, databases, software, and infrastructure providers all report surging demand simultaneously, it usually signals the beginning of a major economic transformation. The path will not be linear. There will be corrections, pullbacks, and periods when investors believe the boom is over. Every major secular bull market, including the internet revolution, experienced declines of 10–20% along the way. AI will likely be no different. But the broader story remains intact. The AI buildout is expanding across the global economy, driving investment, productivity, and potentially stronger economic growth for years to come. And perhaps the most important point is this: We may still be in the early innings. In the next issue, we will discuss another event that could become a defining moment of this cycle—the world’s largest IPO, scheduled for June 12.

If you have been following my writings over the last two years, you will understand why I remain strongly bullish on the US markets. We are living through what may become the largest infrastructure and technological transformation since the Industrial Revolution — the Fourth Industrial Revolution driven by artificial intelligence. Most investors still view AI as simply a technology story centered around semiconductors, software and companies like Nvidia. And rightly so. Nvidia positioned itself as the leader in accelerated computing, even deriving its name from the Latin word “Invidia,” meaning envy — symbolic of products that became the envy of the industry. But AI is quietly becoming far bigger than just technology. It is turning into one of the largest physical infrastructure buildouts in modern history. AI does not fit neatly into traditional market sectors like technology, industrials, utilities or energy. It is now spreading across all of them simultaneously. Just as the Industrial Revolution mechanized labor, railroads compressed distance and the Internet digitized information, AI is now industrializing intelligence itself. The difference is that this revolution comes with an enormous physical footprint. Before AI can change the world, someone has to physically build where it lives. The modern AI economy runs inside massive data centers filled with servers, cooling systems, fiber networks, backup power and extraordinary amounts of compute hardware. For years, the cloud felt abstract and invisible. But AI arrives with cement trucks, steel frameworks and gigantic industrial campuses. Some hyperscale AI facilities now span millions of square feet and require billions of dollars before a single AI model is even trained. And this is no longer limited to Silicon Valley. The buildout is spreading across America and will eventually become global, quietly reshaping regional economies around AI infrastructure demand. This is why investors who see AI only through software are missing the bigger picture. The opportunity now extends into industrial companies, engineering firms, power infrastructure, electrical equipment suppliers, utilities, construction firms and material providers. Every major technological cycle eventually creates its own winners and losers. Many companies built GPUs, but only Nvidia built a dominant AI ecosystem around them. That distinction matters. A major theme may lift an entire industry initially, but eventually a small group of companies separates itself through superior technology, execution, margins and institutional demand. Those companies often go on to define the entire cycle. And AI is only one part of a much larger transformation. Robotics, electrification, photonics, industrial automation, defense technology and advanced manufacturing are all building layered ecosystems beneath the surface. We are entering an era where infrastructure, energy, automation and intelligence are converging into one massive economic cycle. It is one of the most important technological transitions of our lifetime — and an extraordinary time to witness it unfold in real time. In the next report we will discuss some of the companies that has made the biggest gains so far throughout this transformation.

The geopolitical situation is becoming murkier by the day — and if your perspective comes only from mainstream outlets like Fox News, CNN, or the BBC, the picture can appear even more confusing. For weeks, the public has been told a deal with Iran was close, yet the U.S. has continued striking Iranian-linked targets. Iran calls those actions ceasefire violations. We have seen this cycle repeatedly over the past few months: diplomacy publicly, escalation operationally. The key is to focus on what leaders are actually emphasizing. Earlier in May, Benjamin Netanyahu stated in a 60 Minutes interview that the conflict is not over until Iran’s enriched uranium is removed or neutralized. President Trump reinforced that position days ago, saying the uranium must either be surrendered and destroyed or dismantled under inspection. Until that happens, much of the surrounding rhetoric should be viewed as political theater. At the center of this entire issue is oil. Oil funds the Iranian regime, its proxies, and its military infrastructure. It also gives Tehran leverage over global markets and energy stability. For that reason alone, a quick “deal” appears unlikely. An important clue emerged during Trump’s cabinet meeting yesterday when he asked Marco Rubio about Cuba and Venezuela. Rubio described Venezuela as being in a “three-phase process” — stabilization, recovery, and transition. He noted that since January 3rd, roughly 10 million barrels of Venezuelan oil have been delivered to the U.S., with revenues now flowing into Treasury-controlled and audited accounts instead of being siphoned off through corruption. If a similar framework were ever applied to Iran, it would likely involve influence over Kharg Island, the terminal responsible for most Iranian oil exports. This may also explain why Treasury Secretary Scott Bessent recently said he expects crude prices to fall below pre-conflict levels once this crisis ends. The broader strategy appears increasingly clear: the U.S. wants lower energy prices, and that requires influence over global swing production and critical oil chokepoints. That could eventually place Iran and Venezuela under a similar economic and energy framework, supported by Saudi Arabia, Gulf states, and Abraham Accord partners. At its core, this is no longer just about war or nuclear negotiations. It is about control over the global energy system that underpins geopolitical power itself.

Artificial intelligence may be the dominant theme of the current technological revolution, but blockchain is emerging as the second foundational pillar of the new digital economy. AI transforms how information is processed. Blockchain transforms how value is stored, verified, and transferred. Together, they are reshaping the future of finance, commerce, and global economic infrastructure. I remain a strong believer in blockchain technology as the next generation of financial infrastructure. Properly regulated, blockchain can reduce transaction costs, improve transparency, accelerate settlement systems, eliminate inefficiencies, and modernize the global financial system. This transition is already underway. Major institutions such as BlackRock, JPMorgan Chase, and Goldman Sachs are actively building tokenization platforms, stablecoin systems, and blockchain-based financial products. The key missing ingredient has been regulatory clarity. That is why the proposed CLARITY Act is so important. If passed — which now appears increasingly likely — it could establish the legal framework needed for institutional capital to fully enter the digital asset space. High-quality digital assets and blockchain infrastructure companies could then become major long-term investment opportunities. At the same time, concerns surrounding central bank digital currencies (CBDCs) were always legitimate. Projects such as Project Hamilton, developed by the Federal Reserve Bank of Boston and MIT, intensified fears that fully centralized digital currencies could eventually enable governments to monitor or even restrict personal spending behavior. Critics warned that programmable digital currencies could become tools of financial surveillance and social control. Supporters argued they would modernize payment systems and improve efficiency. The debate ultimately became one about technological progress versus financial freedom and privacy. The current U.S. administration has strongly opposed the development of a U.S. CBDC for precisely these reasons. Meanwhile, several European and Asian governments continue exploring CBDC frameworks. Instead, the United States is increasingly moving toward privately issued, regulated stablecoins backed by U.S. dollars and short-term Treasuries. This is a major strategic development. Stablecoin legislation ensures stronger reserve backing, reinforces confidence in digital dollars, and creates an entirely new structural buyer of U.S. Treasuries. As stablecoin adoption expands globally, issuers will continuously accumulate Treasury securities to support their reserves — helping offset declining purchases from countries such as China. In many ways, stablecoins could become the mechanism that extends U.S. dollar dominance into the digital age. The critical task now is for Congress to pass comprehensive digital asset legislation that clearly defines how cryptocurrencies, tokens, stablecoins, and blockchain networks will be regulated. Without clarity, innovation slows. With clarity, the global financial system can begin a structured transition toward onchain finance. And after years of regulatory uncertainty and political conflict, Washington finally appears to understand the scale and strategic importance of what is at stake.

Three years ago, NVIDIA delivered what may prove to be one of the most important earnings reports in modern history. In May 2023, Jensen Huang told the world that computing was entering a trillion-dollar transition from general-purpose computing to accelerated computing, driven by the “ChatGPT moment” — when generative AI moved from research labs into the mainstream economy. At the time, his projections sounded extraordinary. Jensen said demand for Nvidia’s AI chips was exploding so rapidly that growth would accelerate even further in the following quarters and continue for the foreseeable future. That became the “Nvidia moment” — the point when markets realized AI was not another software cycle, but the beginning of a complete reinvention of computing infrastructure. Remarkably, the transformation has unfolded even faster than Nvidia originally projected. This year alone, several major signals confirmed that the AI revolution is expanding across the entire technology stack. First came storage. SanDisk shocked markets by guiding for nearly 50% sequential revenue growth in just one quarter, reminding investors that AI does not only require chips — it requires enormous storage capacity to handle the vast oceans of data AI systems generate. Then came semiconductors. Taiwan Semiconductor Manufacturing Company reported a sharp jump in revenue during what is normally a slow period and simultaneously approved massive new capacity investments. The message was clear: the AI supply bottleneck is beginning to break. Then, in Nvidia’s February earnings call, Jensen declared that the “ChatGPT moment of agentic AI” had arrived. This may be the next major phase of the AI revolution. Agentic AI is not simply AI as a tool, but AI as an autonomous worker — systems that continuously reason, act and operate independently. Unlike traditional software, these systems are always inferencing, always computing and always generating output. That is why Jensen repeatedly emphasized a powerful idea: “Compute equals revenue.” And increasingly, “compute equals profit.” Nvidia’s latest numbers demonstrate exactly that. The company generated nearly $82 billion in quarterly revenue — more than ten times its revenue from just three years ago — while adding roughly $38 billion in incremental revenue compared to the same quarter last year. Few companies in history have ever expanded at this scale while maintaining such extraordinary profitability. Then came the guidance: Nvidia projected roughly $91 billion in revenue next quarter, signaling another major jump despite already operating at unprecedented size. Perhaps the most important statement of all came from Nvidia’s CFO, who said global AI infrastructure spending could reach three to four trillion dollars annually by the end of this decade. Not cumulatively — annually. That estimate has risen dramatically in real time. Last year, Jensen spoke of roughly half a trillion dollars in visible AI demand. By early this year, the figure approached one trillion. Now the discussion is about several trillion dollars per year flowing into AI infrastructure. This is no longer simply a technology trend. It is the largest industrial and infrastructure buildout of the modern era — spanning semiconductors, data centers, storage, networking, power systems and autonomous computing. Against that backdrop, the daily market noise — interest-rate speculation, tariff headlines and short-term volatility — increasingly looks insignificant. Beneath the surface, a far larger transformation is underway: a global AI infrastructure revolution that is already funded, profitable and accelerating. And NVIDIA remains at the center of it.

The Federal Reserve gets a new chairman tomorrow. Kevin Warsh takes over with 30-year Treasury yields above 5%, inflation near 3.8%, and one of the most divided Fed environments in decades. Warsh believes AI will become a powerful disinflationary force, potentially justifying lower interest rates. But cutting rates now could prove a major mistake because something far bigger than a normal economic cycle is unfolding. While Wall Street obsesses over tariffs, rate cuts, and daily market swings, the people actually building the future are describing the largest industrial and technological expansion in modern history. Jensen Huang called the launch of ChatGPT in 2022 a transformational moment that changed computing forever. What was once seen as a trillion-dollar opportunity now looks vastly underestimated. Jensen believes another historic turning point came on February 5th, when major AI firms introduced “always-on” AI systems capable of working continuously without human supervision. That changed the economics of AI completely. Before this, AI demand moved at human speed — people asked questions, logged off, slept, and went on vacation. Now machines increasingly interact with machines 24 hours a day. Every AI interaction consumes computing power, electricity, networking capacity, and datacenter infrastructure. Every second inference systems run, revenue is generated. This is the boom loop Jensen describes: more compute creates more output, more output generates more revenue, and that revenue funds even more compute. The cycle accelerates exponentially. That is why hyperscalers are spending hundreds of billions on datacenters, power infrastructure, semiconductors, cooling systems, and fiber networks. Customers are now capacity constrained because AI output is already proving enormously profitable. Jensen even suggested Nvidia could eventually become a multi-trillion-dollar revenue company and described a $10 trillion valuation as “extremely likely” and “inevitable.” At the same time, Elon Musk believes we are entering “hard takeoff” — the stage where AI systems begin improving themselves faster than humans can improve them. As Elon said: “I go to sleep, there’s a massive AI breakthrough. When I wake up, there’s another one.” He believes the global economy could become ten times larger within a decade as AI, robotics, and automation create effectively unlimited labor capacity. That outlook becomes even more important with Tesla’s humanoid robot project, Tesla Optimus, which Elon believes could eventually remove labor constraints across entire industries. So the two men closest to this revolution — Jensen building the AI computing backbone and Elon building AI, robotics, energy, and automation systems — are both pointing toward the same conclusion: We are entering an economic expansion unlike anything in human history. If they are even half right, today’s obsession with Fed transitions, tariffs, and daily market volatility may ultimately prove insignificant compared to the scale of the AI transformation now underway. As Elon asked: if a tsunami were coming, would you spend your time cleaning the beach? In a future driven by AI abundance, the greatest opportunities may lie in scarcity — energy, copper, semiconductors, electricity infrastructure, fiber networks, and the physical assets required to power the AI revolution. This is no longer just a software cycle. It is becoming the largest infrastructure and industrial buildout of the modern era.

Scott Bessent recently delivered the keynote address at the “No Money for Terror” conference in Paris — an event that surprisingly received very little mainstream media attention. Yet the message he delivered may prove highly significant in understanding the direction of current US geopolitical and economic strategy. Bessent stated bluntly: “The United States is hardly alone in facing the scourge of terrorism, especially from Iran. Yet too often, we seem to be alone in our resolve to thwart it.” The remark was clearly aimed at Europe. He directly called on European nations to expose and dismantle Iran’s shadow banking and financial networks, particularly the financial channels linking Iran and China. The broader message was unmistakable: under the current US administration, access to American security guarantees, dollar liquidity, capital markets and consumer markets is no longer viewed as unconditional. These benefits are increasingly becoming tied to political and strategic alignment with Washington. Bessent’s speech reflects a larger US strategy to restructure global trade and realign the world away from China and back toward a US-centered economic order. In this framework, allies are expected to share burdens and actively support American geopolitical objectives rather than remain neutral or ambiguous. The warning to Europe was implicit but clear: continue avoiding decisive action against Iran’s financial networks and eventually face what “conditional support” from the United States looks like in practice. The United States still possesses enormous leverage through the dollar system, global liquidity facilities, defense commitments and energy markets. The emerging strategy appears to involve using these financial and geopolitical tools not through persuasion, but through consequences. That could mean: forcing Europe to bear more defense costs, exposing Europe’s energy vulnerabilities, limiting emergency dollar liquidity support during crises, and allowing political pressure to build within European economies. From this perspective, Iran is not the ultimate target. The larger strategic objective is China. Washington increasingly sees China’s economic model and expanding global influence as the primary long-term challenge to American dominance. The broader goal appears to be aligning Europe and other allies into a coordinated effort to economically pressure and strategically contain China’s rise. Whether this strategy succeeds remains uncertain. Europe remains economically tied to China, and global supply chains are deeply interconnected. But the direction is becoming increasingly clear: the era of unconditional globalization is giving way to a world of strategic blocs, conditional alliances and economic nationalism. Bessent’s Paris speech may ultimately be remembered as an early signal of that global transition already underway.

Global bond yields are breaking out sharply across the world’s major free-market economies, signalling that markets are beginning to price in a major structural shift in global monetary policy. German Bund yields have risen to 15-year highs above 3.20%, UK 10-year Gilt yields have climbed beyond 5.20%, and the US 10-year Treasury is now trading near 4.68%, its highest level since President Donald Trump returned to office last year. The key catalyst is the arrival of Kevin Warsh as the new Federal Reserve Chairman this Friday. Markets increasingly believe his leadership could mark the end of the intervention-heavy Fed era that has dominated since the Global Financial Crisis. Warsh has consistently argued for a smaller Fed balance sheet, less market manipulation, and structural reform at the central bank. His view is that the Fed’s long-standing policies of quantitative easing and constant intervention distorted markets, encouraged fiscal excess, and turned the Fed into a backstop for bad government policy and reckless corporate behavior. The emerging message under Warsh is clear: the era of the Fed artificially suppressing long-term interest rates through bond buying and forward guidance may be ending. Markets are now adjusting to a regime with less Fed intervention, less telegraphing, less support for long-dated Treasuries, and significantly more price volatility. That is why bond yields are rising. Investors are entering a true price-discovery phase without the Fed’s “thumb on the scale.” Even if fiscal discipline improves, markets are unlikely to trust it immediately after nearly two decades of easy money and monetary intervention. The implications extend far beyond the United States. Since 2008, the Fed effectively acted as the global financial system’s stabilizer through dollar swap lines, emergency liquidity programs, and coordinated central bank actions. Under Warsh, that support is expected to become far more conditional. This is one of the major reasons European yields are also surging to levels not seen since the worst periods of the financial crisis. Markets are beginning to price a world where the Federal Reserve may no longer act as the automatic global backstop for sovereign debt markets. While the transition may initially create higher rates and greater volatility, supporters of this framework believe it could ultimately restore fiscal discipline, improve the integrity of bond markets, and strengthen confidence in US dollar assets over the long term.

There are two stocks I have consistently advocated investors to remain long on throughout this AI cycle — NVIDIA and Advanced Micro Devices. They can occasionally be sold to lock in profits when technical indicators become stretched, but every meaningful correction has ultimately been another buying opportunity. The reason is simple. The unprecedented global buildout of AI infrastructure has created demand so massive that Nvidia, AMD and several semiconductor companies can sell virtually every advanced processor they are capable of producing. This is no ordinary technology cycle. It is the industrialisation of artificial intelligence. I have followed AMD for more than two decades, including the period when the company was close to bankruptcy. The turning point came when Abu Dhabi injected nearly $2 billion into the company. Since then AMD has never looked back and has become one of the biggest beneficiaries of the AI boom. In just the last six weeks alone, the stock has nearly doubled. For years, Intel was considered dead money. It missed the wireless revolution, lost its manufacturing leadership and watched as Nvidia and AMD became the face of the AI era. But sentiment changed dramatically after the US government acquired nearly a 10% stake in Intel in August 2025, investing about $8.9 billion. Since then Intel has staged a remarkable comeback. From March 30 to May 14 this year, the stock surged from $41.20 to $121.85 — a rise of almost 200% in just over six weeks. Such a move is extraordinary for a mature semiconductor company that had spent more than a decade disappointing investors and even relying on Taiwan Semiconductor Manufacturing Company to manufacture some of its most advanced chips. What the market is now realizing is that AI demand is no longer concentrated in only a few companies. The infrastructure boom is spreading across the entire semiconductor ecosystem. The biggest driver behind this explosion in demand is agentic AI — systems where AI agents can independently write code, test software and rapidly iterate products. The role of human programmers is increasingly shifting toward supervision and validation. Google has already indicated that a large portion of its code generation process now involves AI assistance, while Microsoft believes the number could rise dramatically over the next five years. This transformation requires enormous computing power, which explains why semiconductor demand continues to accelerate. That enthusiasm was also reflected in the IPO of Cerebras Systems, one of the biggest technology listings of 2026. The Abu Dhabi-backed company reportedly priced at $185 in the pre-IPO market and opened near $385, highlighting investor appetite for AI infrastructure companies.I featured Cerebras systems in my list of the next magnificent 11 last year . Please look it up . The broader point is this: these companies are not merely participating in another market rally. They are foundational pillars of the largest AI infrastructure expansion the world has ever seen. And the reality is, nobody yet knows how far this cycle can ultimately run.

The world’s largest technology companies are now engaged in one of the biggest infrastructure expansions in modern history. This is not merely another software cycle or passing technology trend. What we are witnessing is the industrial buildout of artificial intelligence. The top four AI hyperscalers — Microsoft, Alphabet, Amazon and Meta — are projected to spend more than $700 billion on AI infrastructure in 2026 alone. And this figure represents only the largest players. Why is spending accelerating so aggressively? Because demand for AI compute continues to explode. Artificial intelligence is far more than software running in the cloud. It requires enormous physical infrastructure to train, operate and scale increasingly complex AI models. Modern AI data centers are becoming some of the most power-intensive industrial facilities ever built, with certain campuses consuming electricity comparable to that of small cities. The physical scale of these facilities is staggering. Hyperscale campuses require vast amounts of land, steel, concrete, backup power systems and advanced cooling technologies simply to support dense AI computing clusters. Modern AI chips from companies such as NVIDIA generate extraordinary levels of heat, forcing many next-generation facilities to adopt sophisticated liquid-cooling systems. The AI infrastructure ecosystem can broadly be divided into five key layers: • Land and buildings • Power and grid infrastructure • Cooling systems • Compute and memory • Networking and optics What makes this cycle unique is that growth is occurring simultaneously across all five layers. Memory manufacturers, optical networking firms, semiconductor equipment makers, utilities, cooling specialists and infrastructure providers are all participating in the same spending boom. The market is slowly beginning to understand a very important reality: Artificial intelligence is not just software. It is infrastructure. Railroads required steel. Electrification required power grids. The internet required fiber optics and wireless towers. Artificial intelligence requires massive data centers — and those data centers demand an enormous physical ecosystem to support them. The industrialization of intelligence may ultimately become one of the largest infrastructure buildouts of our lifetime, and the scale of this opportunity still appears widely underestimated. The opportunities arising from this transformation are already being reflected in the meteoric rise of many stocks connected to AI infrastructure and data center ecosystems. Tomorrow, I will discuss two companies — one a very old and established business, and the other a newly listed company — to further illustrate what is truly unfolding beneath the surface of this AI-driven industrial revolution.

The US stock markets continue to surge higher despite mounting geopolitical tensions, inflation concerns, and growing global uncertainty. To many investors, this seems irrational. How can markets remain so strong when the world appears increasingly unstable? The answer is that most market participants still have not fully grasped the magnitude of the innovation cycle now unfolding before us. What we are witnessing is not just another technology trend. This could become the largest and most transformative innovation wave in modern history. Human civilization has always moved forward through powerful waves of innovation, each reshaping economies and societies. The Industrial Revolution mechanized labor through steam engines, factories, railroads, and steel. Human muscle was amplified by machines, transforming production and economic growth. Then came the transportation revolution — automobiles, aviation, container shipping, and highways connected the physical world and collapsed distances. After that, communications changed everything through telephones, satellites, fiber optics, and wireless networks, allowing information to move instantly across the globe. The next great wave was the internet revolution, which digitized the global economy. Software, cloud computing, smartphones, and search engines transformed how people work, communicate, consume media, and build businesses. Many companies that are now considered mature cash-generating giants once began as exciting and highly speculative upstarts at the start of that cycle. And now we are entering the fifth wave. Artificial Intelligence. But unlike prior software revolutions, the AI boom requires an enormous physical infrastructure buildout beneath the surface of the economy. The cloud era made technology feel weightless — invisible streams of data moving silently through cyberspace. AI is making technology heavy again. Behind every AI model is a massive industrial ecosystem requiring electricity, semiconductors, fiber optics, cooling systems, water, steel, concrete, and land. Investors often focus only on GPUs, but the modern AI data center is really a giant industrial machine built to manufacture intelligence at massive scale. And that machine is expanding rapidly. New data centers are being announced constantly, power demand forecasts are surging, and entire industries — from utilities and energy producers to semiconductor firms and infrastructure companies — are becoming part of this new ecosystem. This is one of the key reasons why stock markets continue to move higher despite wars, politics, oil shocks, and economic uncertainty. Markets are forward-looking, and capital is beginning to price in what could become a multi-decade transformation of the global economy. Many still see AI as just another technology trend. History may ultimately view it as something far bigger — the next foundational layer upon which the future economy will be built. Will develop the remaining part tomorrow.