AI's electricity shortfall creates a massive opportunity for companies solving the power bottleneck. Morgan Stanley estimates a 32 GW US data-center power shortfall by 2028. Constellation Energy and Vistra are nuclear names, Bloom Energy in fuel cells, GE Vernova in power generation and Eaton in grid infrastructure. x.com 

Electricity is a clear bottleneck for AI, favoring AI-focused power and data-center infrastructure names over residential utilities. The US could be short 107 GW to power data centers through 2029, while China adds capacity year after year. Medium-term preferences are Cipher, Hut 8, Riot, TeraWulf, Galaxy, Equinix, Bloom Energy, Solaris, Vistra, GE Vernova, INIO, Williams, Liberty Energy, EROC and Cummins. x.com  x.com 

AI infrastructure names such as Vertiv, Bloom Energy and Sterling are an attractive, asymmetric short because slowing data-center builds should slow their order growth. Semis are historically overbought, a $200 billion company jumped 40% on its CEO calling it undervalued, companies may start rationalizing AI spend, Anthropic's revenue acceleration could slow, and a $1.5 trillion space IPO looms. Any waning momentum could cause severe unraveling. This is a high-conviction playbook into September. … Show more

Constellation Energy, Vistra, Oklo, GE Vernova, IREN and Bloom Energy make up the power infrastructure stack an AI economy will need, because every GPU cluster Nvidia sells requires power infrastructure that does not exist yet. Nvidia CEO Jensen Huang says AI inference demand will grow 1,000x and that this is the best time in history to invest in sustainable energy. He knows what his customers are building because he ships it, and he was early on semis and neoclouds in 2025. x.com 

AI data-center spending should reach chips first, then racks, power and cooling, benefiting Nvidia, AMD, Vertiv, Bloom Energy, Credo, Marvell, Lumentum and Micron. BofA forecasts the global data-center market at about $1T in 2026, $2.1T in 2028 and nearly $3T by 2030, a 37% annual rise; roughly 80% of a new AI site's $57M per MW cost goes to servers, networking and storage. x.com 

Constellation Energy, Talen, NRG and Modine look weak because of the data-centers-in-space narrative. Once the first big solar-powered rack of GPUs reaches orbit, the market will react and cooling names will crash too, whether or not many space GPUs arrive this decade. @InvestsCletus adds that regulatory hurdles to deals between existing power plants and data centers also weigh on these names, while distributed-generation builders like Bloom Energy stay strong. x.com  x.com  x.com 

Power scarcity and specialized technology could help these six under-$30 stocks create generational wealth over the next decade. MARA is buying a gas plant; IREN has over 5 GW secured for AI growth. Oklo aims to turn spent fuel into reactor supply, while Nano Nuclear's portable microreactors could reach remote sites if they work. Rigetti builds quantum chips in-house and has a $100 million Commerce Department letter of intent. Navitas makes chips that reduce power waste in AI data centers. x.com  … Show more

AI data centers' power needs support a portfolio spanning onsite generation, nuclear, grid hardware and fuel. Oklo offers onsite nuclear and Bloom fuel cells that bypass the grid; Constellation has nuclear baseload under a 20-year Microsoft PPA and Vistra a 20-year Meta deal. GE Vernova supplies grid hardware, Vertiv cooling and power systems, Eos long-duration storage and NextEra a renewable pipeline, while Centrus supplies HALEU for modular reactors and Energy Fuels domestic uranium. x.com 

Energy infrastructure looks like the next memory trade, as the AI race shifts from software to energy. China produces about three times as much energy as the US, and Musk and Jensen Huang said every 5GW of new energy adds about 1% to US GDP. AI needs power, cooling and infrastructure, so the companies enabling the buildout, from Vistra, Constellation and GE Vernova to Bloom Energy, Vertiv, BWXT, Cameco, Enphase and Tesla, are worth accumulating on weakness. x.com  x.com 

Deliverable electricity is by far the most important AI bottleneck, the backdrop for owning energy infrastructure such as Williams. BloombergNEF now expects 118GW of US data-center capacity by 2030, 52% above its December 2025 forecast, and 194GW by 2035, about 20% of US energy use. Expected AI-chip sales imply 207GW of US capacity, 63GW more than BNEF's realistic forecast, so chips are outrunning power and something has to give. Data centers are also faster to build than grid expansions. x.com