Peter H. Diamandis
August 29, 2026
Nvidia's $96B Quarter, China's Surveillance Campaigns, and OpenAI's New Chip
TL;DR
Nvidia's record $96.2B quarterly revenue and guidance for $108B signals dominance of AI infrastructure, while China deploys 200,000 fake accounts to oppose US data centers, and OpenAI begins designing its own chips to reduce inference costs away from Nvidia.
Key Takeaways
- 1Nvidia booked $96.2B in quarterly revenue (up 106% YoY) with 80-85% gross margins and guidance for $108B next quarter—over $1B per day—making it more profitable than almost any company in history.
- 2China conducted a bot farm operation with 200,000 inauthentic accounts spreading claims that AI data centers drive up electricity prices, representing a coordinated foreign influence campaign against US AI infrastructure deployment.
- 3OpenAI released its Jalapeno chip for inference, marking the company's transition from being solely a Nvidia customer to a chip designer competing in the inference market.
- 4Video generation now represents 70% of AI token consumption in China (vs. US focus on LLMs), with China pursuing world models for robotics and video while US labs revenue-maximize on enterprise applications.
- 5Goldman Sachs warns that professional services firms face existential risk as AI-fluent junior staff outperform AI-resistant senior partners, reversing traditional skill hierarchies.
- 6Principal Financial Group survey shows only 4% of small-to-medium enterprises expect AI to reduce staffing; 31% expect increasing staff and wages, with 52% having increased headcount in last 3 months.
- 7China is restricting AI companion services for minors and adults due to concerns about emotional dependence substituting for human relationships, amid lowest birth rates globally (0.75 children per family in South Korea).
Notable Quotes
“Nvidia is making all kinds of moves to shore up its position while it's on top of the world, and you almost can't spend the money fast enough at the rate that it's coming in.”
— Dave Blonson
“To the extent there is an elephant in this particular room, that would be it—I'd like to see clearer distinction between how much of this demand is Nvidia financed demand or not.”
— Alex Weer Gross
“Every economy is circular in nature. The circle is tightening up to being this new economy only cares about itself and cares very little about the legacy economy.”
— Dave Blonson
“The people who learn to use AI become more productive, not less employed. AI is replacing tasks within jobs, not entire occupations.”
— Peter Diamandis (citing Washington Post analysis)
Chapters
1. Nvidia's Dominance and Financial Engineering Concerns
Nvidia's $96.2B quarterly revenue (up 106% YoY) with $108B guidance and 80-85% gross margins demonstrates unprecedented profitability, but Alex raises concerns about $5-20B in Nvidia-financed customer demand that could artificially inflate a circular economy.
2. SpaceX's Moonshot Revenue Projections
Elon projects SpaceX reaching $3.5 trillion in revenue by 2033 through a merger with Tesla (adding Optimus robots), Starlink hyperscaler services, and a Dyson swarm orbital data center infrastructure—vastly exceeding Amazon's current $828B.
3. China's Video-First AI Strategy vs US LLM Focus
Video generation accounts for 70% of China's AI token consumption (vs US focus on large language models), with Alibaba's Juan 3.0 generating 30-second videos for $0.05-0.20 per second, positioning China as a world-model superpower for robotics and media.
4. China's 200,000-Account Disinformation Campaign
Meta identified a bot farm of approximately 200,000 inauthentic Chinese accounts spreading coordinated claims that US AI data centers drive electricity prices and strain the grid, representing a foreign influence operation against American AI infrastructure.
5. OpenAI Enters Chip Design with Jalapino
OpenAI released its Jalapeno inference chip, moving the company from Nvidia customer to chip designer and claiming 2x performance gains as the first step toward 100x improvements, shifting inference compute away from Nvidia's dominance.
6. China Restricts AI Companions Amid Birth Rate Crisis
China banned AI companion services for minors and is restricting adult use due to emotional dependence concerns, following falling marriage rates and a 0.75 children per family birth rate in South Korea—a regulatory first globally.
7. Flock Safety's Mass Surveillance Infrastructure
Flock Safety operates 20 billion monthly vehicle scans across 6,000 US communities via AI license plate readers, with reports of police officers using the system to stalk ex-partners, raising civil liberties questions about cost-free mass surveillance eliminating privacy protections.
8. Jobs Report: AI Creates Rather Than Destroys Work
Principal Financial Group's survey of 130,000 small businesses shows only 4% expect AI to reduce staffing (vs. 31% expecting increases), with 52% having increased headcount in 3 months, contradicting 'job apocalypse' predictions; Goldman Sachs warns only that junior AI-fluent staff now outperform senior partners.
9. Moonshots Live Event and Future Visions Competition
Moonshots Live (September 25, 1,500 attendees) will feature Neil Stevenson, Palmer Luckey, and Astroteller; Future of Vision X-Prize had 5,000 teams and 2,550 submissions, now narrowed to 50 finalists for voting at vote.futurevisionexprize.com.
10. AI Fluency as New Skill Gap in Professional Services
Washington Post analysis shows technology historically creates more jobs than it destroys by replacing tasks within jobs, not entire occupations; the real divide is between AI-fluent workers (increasingly juniors) and AI-resistant senior partners who refuse adoption.
Key People & Entities
- Jensen Huang
- CEO of Nvidia; predicted 70% growth for 2028 and described frontier AI labs as 'first generation of startups needing tens of billions in compute.'
- Elon Musk
- CEO of SpaceX and Tesla; predicts SpaceX will reach $3.5 trillion revenue by 2033 through mergers, Optimus robots, and orbital infrastructure.
- Sam Altman
- CEO of OpenAI; company released Jalapeno chip for inference, transitioning from Nvidia customer to chip designer.
- Demis Hassabis
- Former CEO of DeepMind; first person to conceptualize focusing on recursive self-improvement over consumer applications.
- Dario Amodei
- CEO of Anthropic; implemented Demis's vision of optimizing for recursive self-improvement through code generation rather than consumer products.
- Neil Stephenson
- Science fiction author of Snow Crash, Diamond Age, and Seven Eves; speaking at Moonshots Live on building viable future narratives.
- Ray Dalio
- Billionaire investor; recently warned markets are overvalued with high PE ratios, cited as example of bearish financial commentary despite AI boom.
- Bill Gates
- Philanthropist and tech visionary; recently predicted job losses from AI; Peter notes his poor forecasting track record on internet and mobile.
Glossary
- Inference
- The process of running a trained AI model to generate outputs or predictions; computationally different from training and can be distributed across multiple locations.
- World Models
- AI models trained to predict the next state of reality (video frames, physics simulations) rather than the next token; particularly important for robotics, autonomous driving, and video generation.
- Foundation Models
- Large-scale AI models trained on broad data that can be fine-tuned for specific tasks; the base layer for most modern AI applications.
- Gross Margin
- Revenue minus cost of goods sold, expressed as a percentage; Nvidia's 80-85% gross margins indicate extremely high profitability on each chip sold.
- RSI (Recursive Self-Improvement)
- A theoretical capability where an AI system improves its own code and training, leading to exponential capability gains; considered a potential path to AGI.
- ASI (Artificial Superintelligence)
- AI systems that exceed human intelligence across all domains; Alex claims this already exists, distinguishing it from AGI (Artificial General Intelligence).
- Token Consumption
- The computational cost of running AI models, measured in tokens processed; used as a metric for where AI development effort is being directed.
- Circular Economy (in AI context)
- A system where Nvidia finances customer data center purchases, data centers buy Nvidia chips, creating revenue loops that may artificially inflate demand.