Jensen Huang

Jensen states we are in a "once in a generation infrastructure build-out." The Guest Investor notes that Nvidia is their largest public position and they want their net worth "levered against AI." Demand is stripping supply. Jensen notes a critical distinction from the Dot-com crash: there is no unused inventory ("dark GPUs"). Every GPU is rented, and demand is so high that even obsolete hardware (sold 6 years ago) is appreciating in value. "Demand is sky high." "100% of the GPUs are rented." Regulatory hurdles or a sudden ceiling in AI model scaling capabilities.

The Guest Investor defends the massive CapEx spending ($660B combined) by comparing it to Amazon investing in AWS in 2008. Jensen points to Meta specifically, noting their earnings have already moved because AI improved their ad targeting and recommendations. The market views high spending as "burning cash," but the speakers view it as "digging a gold mine." You must spend upfront to extract the gold (intelligence/tokens). Once built, these platforms will generate significantly higher cash flows, similar to how AWS became a profit engine for Amazon. Meta's earnings growth driven by AI recommender systems; AWS currently generating $30B/year in profit from investments made in 2008. If the "gold mine" is empty—meaning if AI applications do not generate the expected revenue to justify the upfront cost.

Jensen states, "Car companies that are building autonomous vehicles... The robotaxi era is coming. And so there's a whole bunch of computing being built for that." Jensen confirms that massive compute clusters are currently being built specifically for AVs. This implies the technology is nearing deployment maturity. TSLA (Cybercab/FSD) and GOOGL (Waymo) are the leaders in this space. If NVDA is selling them the compute *now*, the rollout is imminent. LONG. A direct bet on the "Robotaxi era" Jensen predicts. Regulatory hurdles for Level 4/5 autonomy or safety accidents.

Jensen explicitly highlights "Our big partnership with Lily [Eli Lilly]" and notes that "Scientific computing is being completely revolutionized by artificial intelligence." While most investors focus on AI for tech/coding, Jensen identifies BioTech/Pharma as a major growth vertical. LLY is using NVDA's platform to accelerate drug discovery. This validates LLY not just as a GLP-1 play, but as a tech-enabled pharma leader. LONG. LLY is the specific winner named in the "AI for Science" vertical. Clinical trial failures unrelated to AI efficiency.

Jensen states, "Car companies that are building autonomous vehicles... The robotaxi era is coming. And so there's a whole bunch of computing being built for that." Jensen confirms that massive compute clusters are currently being built specifically for AVs. This implies the technology is nearing deployment maturity. TSLA (Cybercab/FSD) and GOOGL (Waymo) are the leaders in this space. If NVDA is selling them the compute *now*, the rollout is imminent. LONG. A direct bet on the "Robotaxi era" Jensen predicts. Regulatory hurdles for Level 4/5 autonomy or safety accidents.

The Guest Investor defends the massive CapEx spending ($660B combined) by comparing it to Amazon investing in AWS in 2008. Jensen points to Meta specifically, noting their earnings have already moved because AI improved their ad targeting and recommendations. The market views high spending as "burning cash," but the speakers view it as "digging a gold mine." You must spend upfront to extract the gold (intelligence/tokens). Once built, these platforms will generate significantly higher cash flows, similar to how AWS became a profit engine for Amazon. Meta's earnings growth driven by AI recommender systems; AWS currently generating $30B/year in profit from investments made in 2008. If the "gold mine" is empty—meaning if AI applications do not generate the expected revenue to justify the upfront cost.

The Guest Investor defends the massive CapEx spending ($660B combined) by comparing it to Amazon investing in AWS in 2008. Jensen points to Meta specifically, noting their earnings have already moved because AI improved their ad targeting and recommendations. The market views high spending as "burning cash," but the speakers view it as "digging a gold mine." You must spend upfront to extract the gold (intelligence/tokens). Once built, these platforms will generate significantly higher cash flows, similar to how AWS became a profit engine for Amazon. Meta's earnings growth driven by AI recommender systems; AWS currently generating $30B/year in profit from investments made in 2008. If the "gold mine" is empty—meaning if AI applications do not generate the expected revenue to justify the upfront cost.