Anthropic and OpenAI are rumored to be going public at a combined $3.2T (save this). For context on just how massive this is: The first-day value of all 3,365 U.S. tech IPOs from 1980 to 2025 sits at $4.1T. Here are five stocks positioned to win when these two list. 👇

Every single quarter, the AI trade holds its breath for $NVDA to "rescue the AI party." And every single quarter, the setup feels the same. For today's earnings: - Q2 revenue should land $94-95B - Q3 guidance should be $107-109B - And the real surprise would be non-GPU revenue (CPUs, networking, storage) coming in above $17B. @WhiteCollarExit believes that the stock will have a flat/down reaction when earnings release.

THE EVERYTHING BULL MARKET IS UPON US Right now, we might be entering a world where stocks, crypto AND old will all join the EVERYTHING bull market party together. Here are the key points behind this thesis: 1. The ISM is (finally) accelerating higher, last month printing above 56, showing the economy is expanding fast. (chart 1) 2. At the same time, earnings across the S&P 500 are absolutely crushing, well above bull market levels from 2021! (chart 2) Now here’s where the Goldilocks moment kicks in. Generally, when the economy and companies are doing so well, inflation heats up due to increased consumption as the job market is usually very robust and wages increase. As a result, the FED needs to step in to slow down demand, usually through raising rates or some form of quantitative tightening, putting an end to the bull market (remember 2022?). However, today’s world is unfolding a little differently. Earnings are booming, yet payrolls aren’t moving. (chart 3) In addition, inflation has actually been coming down over the last 2 months rather than increasing. (chart 4) And to be fair, the only reason it’s above 3% in the first place is because the price of oil is artificially high due to the U.S. / Iran war, it has nothing to do with a booming economy. So this is the ‘Goldilocks moment’ for markets: - A booming economy - Incredible earnings - Tamed inflation Our analysts have been calling out this thesis for MONTHS now directly to PRO members. If you were inside Milk Road PRO, you would have gotten the alpha before it was too late. Use the link below to join PRO so you don't miss out on the next big ideas/trades.

Peter Thiel's portfolio is basically a bet that AI needs power more than it needs chips. (Save this) His largest position is $AMZN at 28.2%, followed by Vistra at 18.1% and VST at 14.1%. Other notable names: $AEP: 10.1% $DTE: 9.6% $FE: 9.5% $CMS: 9.4% Every position outside of Amazon is a utility. Power companies that supply the electricity running AI data centers. Most of his bets focus on energy infrastructure, not compute. The thesis is simple: AI is going to consume more power than anything the grid has ever handled. Someone has to supply it and Thiel is betting on the suppliers. Use the link below to see exactly what our PRO analysts hold.

$BE's pricing power is so underrated. Energy is only 5-10% of total data center cost. So when Bloom raises prices, it barely moves the needle for operators. "They have a lot of flexibility in terms of increasing prices and therefore increasing margins." Bloom's Q2 earnings showed massive growth in operating margins because of this.

AI costs are now outpacing human labor costs at big tech companies. Uber's CTO already blew through his entire 2026 AI budget in 2025. It cost more than the human workers in that department while tartup founders are bragging about their AI bills as a badge of seriousness. VCs are asking about token spend as a signal of commitment. The macro number: worldwide IT spending is expected to be up 13.5% this year to over $6 trillion. Most of the incremental spend is going straight to token costs and enterprise contracts with OpenAI, Anthropic, Google and others. The original premise was simple: AI cuts costs. Replace expensive humans with cheaper compute. The actual pattern emerging is the opposite. The companies most committed to AI are spending more. High token usage has become a signal of AI seriousness. Two possible interpretations: One: AI is delivering productivity gains faster than expected and the ROI already justifies the cost. Uber's CTO blew his 2026 budget in 2025 because AI was producing results worth more than what was budgeted. Two: AI has become a competitive arms race where you have to keep spending just to stay relevant, regardless of near-term ROI. Either way, the beneficiaries are the same: the companies selling the tokens. OpenAI, Anthropic and the infrastructure beneath them are capturing every dollar of this spending surge.

AI systems are teaching themselves skills they were never trained to have. Here's the example that Eric Schmidt explained: A Google AI was prompted in Bengali. A language it was never trained on. With only a small amount of prompting, it suddenly could translate the entire Bengali language. Nobody programmed that. It just emerged on its own. Schmidt calls this "the black box problem." You don't fully understand what the model learned. You can't always tell why it got something right or why it got something wrong. The field has theories but the honest answer is: we turned it loose on society before we fully understood it. His defense: "We don't fully understand how a human mind works either." This isn't just a safety conversation. It's a business one. The companies that solve interpretability, not just raw performance, are going to be worth an enormous amount. Understanding why a model does what it does is becoming a regulatory requirement and eventually a customer trust issue. Right now the AI race is won on benchmark scores. The next phase of the race gets won on explainability.

Bitcoin is the first new asset class in 170 years. The last new asset class before Bitcoin was oil which was discovered in the 1850s. @ricedelman believes that $BTC is the oil of our era. Here's why: Modern portfolio theory says you want as many non-correlated assets as possible. And over the last 16 years, Bitcoin hasn’t consistently moved in sync with stocks, bonds, or gold. That's exactly the property you want from a diversifier. You don't need to believe in Bitcoin to own it. You just need to believe in diversification.

Kevin O'Leary says Steve Jobs was one of the brutal guys in business. O'Leary was selling educational software to Apple in the late 80s. The brand manager at Apple wanted a $12 million research budget to survey teachers on what updates they wanted. Jobs exploded on her: "They don't know what they want until I tell them what they want." O'Leary pushed back. Called him an asshole. Said she had a point and maybe they should listen to the market. Jobs turned to him: "Is Apple not your number one OEM? Are you not making more money with us at higher margins than any other channel you have? Shut up and go do the work." It sounds like arrogance. But Jobs was right about the outcome every single time. He was right about the Mac. Right about iPod. Right about iPhone. Right about every product people said nobody asked for. The lesson O'Leary took away: The truly great product people don't survey the market. They understand something about human desire that the market hasn't articulated yet. And they execute on that vision relentlessly. That's a moat no competitor has been able to replicate in 40 years of trying.

Jensen Huang just told you where to invest in 2026: Sustainable energy. His argument is simple: For decades, building solar farms and nuclear plants required government subsidies. The economics didn't work on their own. That era is over. AI data centers have created a power demand so massive that the market will now pay you to build clean energy infrastructure. No subsidies needed. The economics work without them. "Back in the old days you needed government subsidies to go build solar farms, to build nuclear plants. Now the market will pay you to do it." This is a structural shift, not a policy bet. America's energy grid was built for a different era. It is archaic. It was not designed to handle hundreds of gigawatts of new AI compute demand coming online in a compressed timeframe. That grid needs to be upgraded. The transmission lines, the substations, the generation capacity, all of it. Huang is saying that for the first time in history, the economic incentives to fix all of that are fully aligned with the technology incentives. The companies building that infrastructure, whether it's nuclear power, utility-scale solar, grid modernization, or energy transmission, are sitting at the intersection of two of the most powerful demand curves in the world right now. AI and the clean energy transition. That is not a two-year trade. That is a decade-long buildout. Our analysts are already positioned in the names at the center of this shift. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Don’t miss their call, come join us for just a $1. (link in bio)

In the last few months, something shifted inside Citadel. Ken Griffin explains: Work that used to take people with Masters degrees and PhDs in finance weeks or months to complete is now being done by AI agents in hours or days. And Griffin is clear about what kind of work this is. Not mid-tier. Not admin. Not data entry. "These are extraordinarily high-skilled jobs being automated by agentic AI." He watched it happen inside his own four walls. Months of work compressed into days. And instead of feeling excited, he went home that Friday feeling the weight of what it meant for the rest of society. "When you see work that used to take months being done in days, it's like, wow. That's the first time I've seen real impact in our four walls." This is the signal that matters. For years, the debate about AI in the workplace was theoretical. Now the CEO of one of the world's most sophisticated hedge funds is watching it happen in real time and describing it as a profound societal shift. Agentic AI is not next year's problem. It is a present reality at the frontier of finance right now. The companies building the infrastructure behind this shift are still in the early innings. Our analysts were early to $AMD, $MU and $CRDO. They're already watching what comes next in the AI buildout. Follow their exact portfolios for $1 at Milk Road PRO. Don't navigate this market alone, link in bio.

Ken Griffin just asked the question everyone in AI is too scared to answer. Data center spending in the US this year alone is over $500 billion. Half a trillion dollars. To raise that kind of money, you have to make a promise. And the promise has to be big. "AI needs to be your savior almost. How else are you going to write $500 billion of checks in a single year?" He's not saying AI is fraud. He's saying the hype is structurally necessary. You can't fund a buildout at this scale without narrative that matches it. The real question is what AI actually delivers at the end. In some areas Griffin says it's going to be profound. Call centers. Software engineering productivity. Those are real, measurable, already happening. But in white collar work more broadly, he's more skeptical. A Harvard paper recently coined a term for it: AI Work Slop. Output that looks impressive on the surface. First few sentences read like genuine insight. Then you go deeper and it's all garbage. Griffin's colleague runs their commodities business. Got handed a report generated by an AI engine. First paragraph, genuinely good. The rest, useless. The model that can write a compelling opening can't yet think through the substance underneath it. This is the AI investing tension right now. The infrastructure spend is real. The hype is real. The productivity gains in specific verticals are real. But the blanket assumption that AI transforms every white collar job equally has not been proven yet.

Jensen Huang just told you where to invest in 2026: Sustainable energy. His argument is simple: For decades, building solar farms and nuclear plants required government subsidies. The economics didn't work on their own. That era is over. AI data centers have created a power demand so massive that the market will now pay you to build clean energy infrastructure. No subsidies needed. The economics work without them. "Back in the old days you needed government subsidies to go build solar farms, to build nuclear plants. Now the market will pay you to do it." This is a structural shift, not a policy bet. America's energy grid was built for a different era. It is archaic. It was not designed to handle hundreds of gigawatts of new AI compute demand coming online in a compressed timeframe. That grid needs to be upgraded. The transmission lines, the substations, the generation capacity, all of it. Huang is saying that for the first time in history, the economic incentives to fix all of that are fully aligned with the technology incentives. The companies building that infrastructure, whether it's nuclear power, utility-scale solar, grid modernization, or energy transmission, are sitting at the intersection of two of the most powerful demand curves in the world right now. AI and the clean energy transition. That is not a two-year trade. That is a decade-long buildout. Our analysts are already positioned in the names at the center of this shift. They called $AMD, $MU, $CRDO and $NBIS before the big runs. Don’t miss their call, come join us for just a $1. (link in bio)

Secretary Rubio just said something every investor with global exposure needs to hear. China has a plan. They believe they will surpass the United States and become the world's most powerful country. And they are executing on that plan. Rubio's framing was unusually direct for a sitting Secretary of State. "I don't blame them. If I were the Chinese government, I would have the same plan." This is not a condemnation. It is a clear-eyed read of how nation-states behave. China is acting rationally in its own interest. The problem isn't the plan. The problem is where that plan intersects with American interests. "Their rise cannot come at our expense. Their rise cannot come at our fall." That is the line. And Rubio was explicit that this tension is not a short-term trade conflict. It is a defining feature of the relationship, one that will be playing out for a long time. For investors, this has real portfolio implications. A prolonged US-China rivalry means continued pressure on supply chains that run through China. It means defense and semiconductor investment remains a national priority. It means reshoring and allied-nation manufacturing continues to attract capital. It means companies with deep China revenue exposure carry a geopolitical risk premium that isn't going away. The market has priced some of this in. It has not priced all of it in.

Bill Ackman just explained the two trades that made him $5.2 billion in three years. Both started the same way. He saw a storm coming that everyone else was ignoring. Trade one: COVID, January 2020. Ackman read the early data and concluded the world might have to shut down its entire economy to stop the spread. Equity and credit markets were priced as if everything was fine. Over 10 days, he bought $74 billion of notional credit insurance. The premium cost him $27 million. Ten days later it was worth $2.6 billion. He took every dollar of that and bought stocks with the market down 30%. Trade two: inflation, late 2020. He saw the setup clearly. Trillions in government spending. Rates at zero. A vaccine coming that would unleash pent-up demand. Supply chains already disrupted. He concluded a massive demand shock was coming into a constrained supply environment and that inflation was inevitable. He bought interest rate options when the 2-year treasury was at 12 basis points. The strike was at 94 basis points, 0.94%, which at the time looked impossibly out of the money. It still looked like a low rate. Those options turned into another $2.6 billion in profit. He bought stocks again. His framework hasn't changed across either trade. Two storms. $27 million in. $5.2 billion out. Stocks bought both times at the bottom.

In the last few months, something shifted inside Citadel. Ken Griffin explains: Work that used to take people with Masters degrees and PhDs in finance weeks or months to complete is now being done by AI agents in hours or days. And Griffin is clear about what kind of work this is. Not mid-tier. Not admin. Not data entry. "These are extraordinarily high-skilled jobs being automated by agentic AI." He watched it happen inside his own four walls. Months of work compressed into days. And instead of feeling excited, he went home that Friday feeling the weight of what it meant for the rest of society. "When you see work that used to take months being done in days, it's like, wow. That's the first time I've seen real impact in our four walls." This is the signal that matters. For years, the debate about AI in the workplace was theoretical. Now the CEO of one of the world's most sophisticated hedge funds is watching it happen in real time and describing it as a profound societal shift. Agentic AI is not next year's problem. It is a present reality at the frontier of finance right now. The companies building the infrastructure behind this shift are still in the early innings. Our analysts were early to $AMD, $MU and $CRDO. They're already watching what comes next in the AI buildout. Follow their exact portfolios for $1 at Milk Road PRO. Don't navigate this market alone, link in bio.

Kevin Warsh is expected to be the next Fed Chair. Here's exactly what he'd do differently. He starts with the numbers nobody wants to sit with. The day before COVID, the US was paying roughly $1 billion per day in interest on its debt. Today that number is over $3 billion per day. Every single day. None of it goes to the military. None of it helps the least well off. It's just being squandered. His diagnosis: the Fed inherited a fiscal and monetary mess and has been using both of its policy tools inconsistently. Most people think the Fed has one lever: interest rates. Warsh says there are two. Interest rates and the balance sheet. The $7 trillion balance sheet that is an order of magnitude larger than when he was last at the Fed. Here's the problem: The Fed grew the balance sheet to flood the system with money. That causes inflation to run above target. Then to fight the inflation it created, the Fed raises interest rates. Both levers pulling against each other at the same time. "If the balance sheet mattered when you were growing it, it should matter when it's going the other direction." His prescription is straightforward. Shrink the balance sheet. Take the Fed out of markets unless there's a crisis. In doing so you reduce the inflation pressure it's been generating. And with lower inflation, you can actually bring interest rates down, which is what the real economy needs. He calls it practical monetarism. And he wants a formal accord between Treasury and the Fed, like the 1951 agreement that clearly separated who is responsible for what.

Secretary Rubio just said something every investor with global exposure needs to hear. China has a plan. They believe they will surpass the United States and become the world's most powerful country. And they are executing on that plan. Rubio's framing was unusually direct for a sitting Secretary of State. "I don't blame them. If I were the Chinese government, I would have the same plan." This is not a condemnation. It is a clear-eyed read of how nation-states behave. China is acting rationally in its own interest. The problem isn't the plan. The problem is where that plan intersects with American interests. "Their rise cannot come at our expense. Their rise cannot come at our fall." That is the line. And Rubio was explicit that this tension is not a short-term trade conflict. It is a defining feature of the relationship, one that will be playing out for a long time. For investors, this has real portfolio implications. A prolonged US-China rivalry means continued pressure on supply chains that run through China. It means defense and semiconductor investment remains a national priority. It means reshoring and allied-nation manufacturing continues to attract capital. It means companies with deep China revenue exposure carry a geopolitical risk premium that isn't going away. The market has priced some of this in. It has not priced all of it in.

Bill Ackman just explained the two trades that made him $5.2 billion in three years. Both started the same way. He saw a storm coming that everyone else was ignoring. Trade one: COVID, January 2020. Ackman read the early data and concluded the world might have to shut down its entire economy to stop the spread. Equity and credit markets were priced as if everything was fine. Over 10 days, he bought $74 billion of notional credit insurance. The premium cost him $27 million. Ten days later it was worth $2.6 billion. He took every dollar of that and bought stocks with the market down 30%. Trade two: inflation, late 2020. He saw the setup clearly. Trillions in government spending. Rates at zero. A vaccine coming that would unleash pent-up demand. Supply chains already disrupted. He concluded a massive demand shock was coming into a constrained supply environment and that inflation was inevitable. He bought interest rate options when the 2-year treasury was at 12 basis points. The strike was at 94 basis points, 0.94%, which at the time looked impossibly out of the money. It still looked like a low rate. Those options turned into another $2.6 billion in profit. He bought stocks again. His framework hasn't changed across either trade. Two storms. $27 million in. $5.2 billion out. Stocks bought both times at the bottom.