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Micron will be a $3,000 stock within a few years and Jensen Huang just spent a week in Korea telling the world exactly why (Save this). Jensen announced four new products at the Korea event and every single one of them has memory at the center of its architecture. Vera Rubin, the next generation AI supercomputer, needs massive quantities of HBM. The new Vera CPU needs large amounts of LPDDR5. RTX Spark, the first major PC reinvention in 40 years according to Jensen, needs a lot of LPDDR5. And Nvidia's new robotics and autonomous driving platforms are being built in deep partnership with the Korean memory and electronics ecosystem. Every single growth vector for Nvidia in 2026 and 2027 runs directly through memory and Micron is the only US based company that manufactures all of it. Here is what the numbers look like right now. Fiscal Q2 2026 revenue came in at $23.86 billion, up 196% year over year, with 75% gross margins and $6.9 billion in free cash flow, a quarterly record. Management guided Q3 revenue to $33.5 billion at roughly 81% gross margins, with EPS of $19.15. These are not the numbers of a cyclical memory company but rather the numbers of a company that has been structurally repriced by the largest demand supercycle in the history of the semiconductor industry. The reason the bull case reaches $3,000 comes down to three things that have never been true at the same time in Micron's history. First, the entire 2026 HBM supply is already sold out under multi-year contracts. CEO Sanjay Mehrotra told analysts that Micron can currently only fulfill 50% to two thirds of key customers' HBM demand at any price. Second, Micron has begun volume shipment of HBM4 12-Hi specifically for Nvidia's Vera Rubin platform, the exact product Jensen was talking about in Korea and has signed its first five year strategic customer agreement, converting what was historically a quarterly negotiation business into something closer to a long-term recurring revenue model. Third, Wolfe Research's bull case model points to $160 billion in calendar year 2027 revenue and $80 in EPS. At even a 20x earnings multiple, modest for a company with this growth profile, that is a $1,600 stock. UBS has already tripled its price target to $1,625. The path to $3,000 requires HBM4 to ramp smoothly, supply constraints to persist into 2027 as Mehrotra says they will, and hyperscaler AI capex to continue growing at its current trajectory, all three of which Jensen Huang just confirmed in Seoul. The HBM total addressable market alone is projected to reach $100 billion by 2028, a forecast Micron itself already pulled forward two years ahead of schedule because demand arrived faster than anyone modeled. Micron trades at roughly 9x forward earnings today. That is cheaper than a grocery chain, for a company growing revenue at 196% year over year, with its entire production sold out, supplying the infrastructure for the most important technology buildout in history. Come join Milk Road Pro for our full breakdown of the Micron bull case how we think about the HBM4 transition timeline, what multi-year customer contracts mean for Micron's valuation multiple expansion, and our entire AI thesis. Link below!

Leopold Aschenbrenner's Situational Awareness just filed showing they own 12.4M shares of Nebius $NBIS, representing a 5.6% stake in the company

he Nebius CEO just confirmed what the entire AI industry already knows. There is not enough compute, and the companies that don't own their own capacity simply cannot grow as fast as they could. Data center GPU lead times are running 36 to 52 weeks, inference workloads alone will account for two thirds of all AI compute demand in 2026 up from one third in 2023. The AI data center GPU market is projected to grow from $111 billion today to $323 billion by 2030, a 23.8% CAGR. And even at current scale, the most optimized AI data centers are running at 60–85% GPU utilization meaning demand is already pressing hard against supply. Nebius isn't waiting for someone else to build the capacity, Arkady Volozh is doing it himself. The company exited 2025 with $1.25 billion in ARR 503% year over year growth and is guiding for $7–9 billion ARR by end of 2026. Nine new data centers announced and over 2 gigawatts of contracted power secured, with plans to exceed 3 gigawatts. A $27 billion, 5 year infrastructure deal with Meta to serve GPU dense workloads. Sales pipeline on track to exceed $4 billion in early 2026, with new contract durations extending by 50% and then the Eigen AI acquisition changed the thesis entirely. For $643 million, Nebius bought one of the most advanced inference optimization stacks in existence system level, model- evel, and kernel level techniques that deliver higher throughput and lower latency without adding complexity for customers. Volozh said it directly, they're not just selling bare metal or renting GPUs by the hour but rather building the full inference stack. That's where the next layer of margin lives. Milk Road Pro remain massively bullish on Nebius and the neocloud trade. Milk Road Pro analysts have held large positions and are up significantly this thesis keeps compounding with every data point Arkady puts out. Earnings drop May 13. Come join us at Milk Road Pro before then, link below

Leopold Aschenbrenner, former OpenAI safety researcher, fired at 22, now running one of the best performing hedge funds on the planet. He grew Situational Awareness LP from $225 million to $5.5 billion in roughly one year beating the S&P 500 by 47% in just his first six months. And the core bet wasn't Nvidia or OpenAI, it was electricity. Here's his actual mat and it's worth reading carefully (Save this). GPT-4 trained on roughly 10 megawatts of compute, a100-megawatt cluster followed in 2024. By 2026, the leading training cluster is approximately 1 gigawatt, the power of the Hoover Dam. By 2028, 10 gigawatts more power than most U.S. states. And by 2030, a single training run could hit 100 gigawatts and consume over 20% of all US electricity production. That's just the training cluster, Inference GPUs on top of that. US power production has barely grown in a decade. He turned that observation into his biggest position, Bloom Energy, a fuel cell company that generates power directly at data centers without touching the grid. He accumulated the $875 million position through 2025 while shares were in the mid teens and that position is now worth nearly more than $2.2 billion. The logic is that everyone is racing to build the most powerful models in history but those models require power that doesn't exist yet on the grid. The companies that control where the electricity comes from, that's where the leverage is. His fund now holds Bloom Energy, CoreWeave, Core Scientific, Lumentum, and a short on Infosys, the last one a bet that AI will gut traditional IT outsourcing. We at Milk Road have been saying it for months, the picks and shovels play in this AI cycle isn't the chip companies, it's the infrastructure keeping them running. Come join us so you can see our entire thesis. Link in bio!