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$IREN just secured a $3.4 billion deal with $NVDA. Before the deal was announced, Leopold Aschenbrenner strategically increased his $IREN position, making him the second-largest shareholder globally. You may not believe it, but $IREN could prove to be one of the biggest missed opportunities of this decade.

$IREN just secured a $3.4 billion deal with $NVDA. Before the deal was announced, Leopold Aschenbrenner strategically increased his $IREN position, making him the second-largest shareholder globally. You may not believe it, but $IREN could prove to be one of the biggest missed opportunities of this decade.

Leopold Stock Tracker

58,375 次观看 • 3 个月前

Dr. Eric Schmidt says AI needs “energy in all forms: renewable, non-renewable, whatever.” “It needs to be there, and it needs to be quickly.” “People are planning 10 gigawatt data centers.” “An average nuclear power plant in the United States is one gigawatt.” “Data centers will require an additional 29 gigawatts of power by 2027 and 67 more gigawatts by 2030.” “These things are industrial at a scale I have never seen in my life.” This is exactly why I believe the market is still underestimating the AI power and infrastructure opportunity in companies like $TE, $BE, $PUMP, $PSIX, $SMR, $FCEL, $MARA, $KEEL, and $OKLO. The biggest constraint to scaling AI remains electricity. The companies building power generation, grid infrastructure, electrical equipment, cooling systems, and AI data centers could be among the biggest beneficiaries over the next decade. Not financial advice. Do your own research.

Dr. Eric Schmidt says AI needs “energy in all forms: renewable, non-renewable, whatever.” “It needs to be there, and it needs to be quickly.” “People are planning 10 gigawatt data centers.” “An average nuclear power plant in the United States is one gigawatt.” “Data centers will require an additional 29 gigawatts of power by 2027 and 67 more gigawatts by 2030.” “These things are industrial at a scale I have never seen in my life.” This is exactly why I believe the market is still underestimating the AI power and infrastructure opportunity in companies like $TE, $BE, $PUMP, $PSIX, $SMR, $FCEL, $MARA, $KEEL, and $OKLO. The biggest constraint to scaling AI remains electricity. The companies building power generation, grid infrastructure, electrical equipment, cooling systems, and AI data centers could be among the biggest beneficiaries over the next decade. Not financial advice. Do your own research.

Leopold Stock Tracker

20,643 次观看 • 1 个月前

Jensen Huang just laid out the exact playbook for the next leg of the AI infrastructure boom. The future of data centers isn't where people live, it's moving to the most remote corners of the planet to tap into massive, under-utilized sources of sustainable energy. The real bottleneck isn't a lack of global energy; it's a geographic mismatch. The winning strategy is to build hyperscale compute infrastructure directly on top of stranded, off-grid power generation. "Train the models there. When they graduate, bring them back." A powerful insight into how the next generation of AI infrastructure will be built and scaled. Watch him break down the macro infrastructure thesis below: 👇

Jensen Huang just laid out the exact playbook for the next leg of the AI infrastructure boom. The future of data centers isn't where people live, it's moving to the most remote corners of the planet to tap into massive, under-utilized sources of sustainable energy. The real bottleneck isn't a lack of global energy; it's a geographic mismatch. The winning strategy is to build hyperscale compute infrastructure directly on top of stranded, off-grid power generation. "Train the models there. When they graduate, bring them back." A powerful insight into how the next generation of AI infrastructure will be built and scaled. Watch him break down the macro infrastructure thesis below: 👇

Leopold Stock Tracker

16,736 次观看 • 2 个月前

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