According to @StockMKTNewz, Mark Zuckerberg said Meta ($META) is planning to invest a “significantly higher number” than $600 billion in the United States through the end of the decade; source: @StockMKTNewz on X, Sep 6, 2025. That magnitude implies an annualized run-rate well above $100B (> $600B over ~5 years) versus Meta’s previously guided 2024 capex of $35–40B focused on AI infrastructure, a setup that historically boosts demand expectations for AI chips (NVDA, AMD) and U.S. data center buildouts; source: Meta Platforms 2024 capex guidance in Q1–Q2 2024 earnings materials; NVIDIA FY2025 earnings call commentary on hyperscaler demand. In crypto, AI-linked tokens such as RNDR, FET, and AKT have historically rallied around major AI equity catalysts, so traders often monitor these pairs when hyperscaler capex headlines hit; source: Kaiko Research 2024 analyses on AI token performance around NVIDIA earnings; Binance Research 2024 AI sector reports.

According to @LexSokolin, the AI grid is being built now, with compute centers as the new power plants, API calls as the new power lines, and prompts as the new switches, highlighting where infrastructure value may concentrate, source: @LexSokolin. According to @LexSokolin, this framing directs traders to focus on capacity, throughput, and reliability at the compute, API, and prompt layers when constructing exposure, source: @LexSokolin. According to @LexSokolin, the call to “bet accordingly” implies positioning in the infrastructure stack rather than purely application-layer bets as the intelligence “electrification” proceeds, source: @LexSokolin. According to @LexSokolin, crypto market participants can map this thesis to infrastructure-aligned themes that mirror power plants, grids, and switches, focusing on decentralized compute, data, and interface layers that align with the buildout he describes, source: @LexSokolin.

According to @nic__carter, the positioning can be read as either name-specific alpha versus the semiconductor basket or a barbell that is long AI infrastructure such as data centers and power while bearish chipmakers, with the book still net long despite a gigantic SMH put. Source: @nic__carter on X, Aug 15, 2025. SMH’s largest exposures are NVIDIA NVDA, Taiwan Semiconductor TSMC, and Broadcom AVGO, so a short via SMH put concentrates downside risk to these names. Source: VanEck Semiconductor ETF SMH fund documentation and holdings. A long AI infrastructure tilt is consistent with surging data center electricity needs, with the IEA estimating global data center power use could reach 620–1050 TWh in 2026 from about 460 TWh in 2022, which supports utilities and power-equipment beneficiaries over chipmakers in relative terms. Source: International Energy Agency, Electricity 2024 report. For crypto, AI infrastructure demand is already flowing to Bitcoin miners’ revenue lines as miners sign AI compute hosting deals, exemplified by Core Scientific’s multi-year agreements totaling 200 MW plus with CoreWeave, linking AI buildout to BTC miner cash flows. Source: Core Scientific press releases, June 2024. Trading takeaway: monitor the relative spread between SMH and listed power and data center beneficiaries, and watch BTC miner equities and hashrate-linked plays for flow-through when AI infrastructure outperforms chips. Source: @nic__carter on X; VanEck SMH documentation; IEA Electricity 2024; Core Scientific June 2024 press releases.