Jag tror inte att folk fullt ut förstår den mängd efterfrågan som inferens kommer att skapa för AI-infrastruktur. Träning av biljontalsparametermodeller kommer att blekna i jämförelse med volymer av biljoner samtidiga tokens som presterar 24/7/365 över varje företag, organisation och konsumentaktivitet. Jag är så hausse på den här utbyggnaden. Och naturligtvis går $NVDA bra, men namn inom chips, servrar, energi, nätverk och agentplattformar kommer alla att stiga med det. 💪🏻 Markera det 😎🚀

Highlights from AMZN call: -AI Infrastructure Capacity Shortfall: AWS has "more demand than we have capacity" with power being the single biggest constraint; expects supply issues to persist for "several quarters" despite $31.4 billion quarterly CapEx in "chips, data centers and power" -Multi-Year Infrastructure Buildout: Acknowledges building sufficient AI capacity will take "several quarters" but expects improvement each quarter; views AI as "biggest technology transformation in our lifetime" requiring sustained heavy investment -Inference Economics Driving Strategy: Expects 80-90% of AI costs will shift from training to inference at scale; positions custom silicon as critical advantage since customers will anchor for better price performance like they did with CPUs -Massive Revenue Opportunity Constrained: AWS at $123 billion annualized run rate but "could be doing more revenue and helping customers more" if capacity existed; generative AI already a "triple-digit year-over-year percentage multibillion-dollar business"