Ben Thompson on Big Tech, China, and the AI Boom Running Out of Money - [Invest Like the Best, EP.487]
In this discussion, Ben Thompson shares insights on the AI race between the U.S. and China, the evolving semiconductor industry, and the implications of AI on businesses and economy. He explores how major tech companies like Microsoft, Meta, and NVIDIA are navigating these challenges while impacting their respective fields.
Summary
Ben Thompson dives into the implications of the U.S. winning the AI race, suggesting that it could pose risks, particularly in military dominance, which may lead to escalated tensions with China. He highlights the dependency of the U.S. tech industry on China, asserting that solutions to this issue are complex and not easily solvable outside a significant geopolitical conflict. The conversation also examines the concept of AI equilibriums, noting the present balance in research and development between major AI firms in the U.S. and China, and expressing skepticism about the sustainability of the current AI advancements.
Thompson elaborates on the financial aspects of AI investments, emphasizing a potential risk of oversaturation in capital and the need for companies to transition back to free cash flow models. He pinpoints that while tech companies are currently experiencing cash burn, the fear of a slowdown or capital blow-up looms large, threatening the stability of progress made in AI.
The talk then shifts towards TSMC and semiconductor manufacturing, where Thompson critiques the conservative growth strategies of chip manufacturers amid rising demand from AI advancements. He discusses how NVIDIA's strategic approach ensures their role in this evolving landscape, balancing risk while being a key supplier to major tech companies. The insights cover how firms like Microsoft, Amazon, and others are leveraging their positions to maintain market dominance while navigating challenges surrounding commoditization in the semiconductor and AI markets.
Lastly, the potential for AI to become a commodity itself is debated, with Thompson arguing that intelligence could ultimately follow the path of other tech commodities if infrastructure and systems development do not keep pace with demand. He articulates the challenges that companies face in creating sustainable, profitable business models around these technologies, highlighting how market dynamics may shift as capacity and technology update rapidly.
About this episode
My guest today is Ben Thompson, the founder and author of Stratechery. Ben is one of my favorite business thinkers and I love talking to him about everything happening in markets and technology. We go through every important company, including OpenAI, Nvidia, Intel, Apple, Microsoft, Google, and Amazon. We also discuss why he thinks it would be dangerous for the United States to win the AI race outright, what container shipping and the railroads of the 1870s tell us about the buildout, and why the binding constraint on all of this may be capital rather than compute. Please enjoy my conversation with Ben Thompson. For the full show notes, transcript, and links to mentioned content, check out the episode page here. ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at colossus.com/subscribe. ----- Ramp’s mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to ramp.com/invest to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, Vanta continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to vanta.com/invest. ----- WorkOS is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- Ridgeline has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit ridgeline.ai. ----- Editing and post-production work for this episode was provided by The Podcast Consultant. Timestamps: (00:00:00) Welcome to Invest Like The Best (00:02:16) Winning the AI Race With China (00:08:28) Timing, Capital, and the Railroads (00:11:34) Berkshire, Google, and Absolute Profits (00:14:23) Verifiable and Unverifiable Domains (00:20:20) Aggregation Theory in the AI Era (00:22:06) The Real Cost of Inference (00:25:40) Why Consumer AI Needs Advertising (00:30:08) Compute Shortages and Commodity Markets (00:35:46) Memory Cycles and Boom Bust Dynamics (00:42:08) TSMC, Intel, and Where Risk Goes (00:44:51) The Best Setups in Big Tech (00:52:14) The Frontier Model Contenders (00:54:27) Microsoft's IBM Playbook (01:00:45) Meta, Attention, and Advertising (01:07:29) NVIDIA, Commodities, and Power
Key Insights
- Thompson argues that a U.S. victory in the AI race could lead to dangerous geopolitical tensions, notably if military superiority is achieved.
- He points out that the U.S. technology industry is significantly dependent on China, which complicates the resolution of supply chain issues.
- The current moment represents an equilibrium in AI development, with leading companies like OpenAI and Anthropic keeping pace with Chinese AI advancements.
- Thompson expresses skepticism about the sustainability of ongoing AI investments due to a looming capital shortage.
- He highlights the challenge of returning to free cash flow models for tech companies after years of capital-intensive growth.
- The conservative growth strategies of semiconductor manufacturers, particularly TSMC, are critiqued as overly cautious in the face of rising demand.
- NVIDIA's strategic partnerships and risk-sharing approach allow it to maintain high margins while addressing the challenges posed by competitors.
- Thompson argues that the hyperscale cloud companies like Amazon and Google are threats to NVIDIA due to their ability to develop and sell their chips.
- He discusses how the commoditization of compute might impact the business models of tech firms, potentially leading to lower margins.
- Thompson notes that the integration of AI in advertising has the potential to revolutionize how companies generate revenue.
- He emphasizes the importance of energy availability for the future of AI and tech industries, suggesting that power constraints may affect the growth trajectory.
- Thompson points out the societal benefits of advertising, arguing that it supports new businesses and drives consumer satisfaction.
Topics
Transcript
Ramp is the only platform built to make your finance team leaner, faster, and better, saving businesses 5% annually on average so you can stay focused on growth. Ramp customers grow revenue 3.2 times faster than the average American business. Visa, Vercel, Cursor, Stripe, Notion, 11Lab, Shopify, and 70,000 other businesses all now run on Ramp. Mine does too, and so should yours. Learn more at ramp.com slash invest. Open AI, Cursor, Anthropic, Perplexity, and Vercel all have something in common. They all use WorkOS. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, SCIM, RBAC, and audit logs. Instead of spending months building these mission-critical capabilities yourself, you can just use WorkOS APIs…
Full transcript available for MurmurCast members
Sign Up to AccessMore from Invest Like the Best with Patrick O'Shaughnessy
Eric Vishria - A Decade of Lessons Investing in Software & Hardware - [Invest Like the Best, EP.486]
Eric Vishria discusses the evolving landscape of investing in software and hardware, emphasizing the importance of scalable infrastructure in AI and the nuanced role of traditional companies in rapidly changing markets. He shares insights on the complexities of hardware investing, the potential of AI, and the necessary traits for successful partnerships in venture capital.
Gavin Baker - AI Market Jitters - [Invest Like the Best, EP.485]
Gavin Baker discusses the recent market volatility in AI stocks despite improving fundamental metrics, arguing that hyperscalers are under-earning and that operating cash flows will accelerate as GPU contracts reprice higher. He emphasizes that negative sentiment is disconnected from quantitative data showing accelerating demand, token growth, and infrastructure metrics across AI labs and open source models.
Sam Altman - How to Make an Abundant Future - [Invest Like the Best, EP.484]
Sam Altman discusses OpenAI's refocus on core AI development after overextending in 2024, explains the company's early conviction to secure massive compute resources, and outlines his vision for abundant, democratized AI that maintains human agency while addressing critical security concerns like the Hugging Face incident.
Matthew Smith — How America Runs Out of Natural Gas by 2030 - [Invest Like the Best, EP.483]
Matthew Smith argues that the U.S. faces an impending natural gas crisis by 2028-2030 driven by AI data center demand and LNG exports, which will exhaust working gas storage and cause electricity prices to spike dramatically. The problem stems from infrastructure constraints in production, processing, and pipeline capacity rather than resource scarcity, requiring urgent investment in nuclear energy and pipeline infrastructure to prevent economic disruption.
John Kim - How to Raise a Few Billion Dollars - [Invest Like the Best, EP.482]
John Kim, a prolific fundraiser and author of 'The Dow of Fundraising,' explains that successful fundraising is fundamentally about understanding human psychology—specifically the equation 'persuasion equals desire minus fear.' He shares three laws of fundraising (differentiation, trade-offs, and pipeline) and emphasizes that trust, not logic, drives capital allocation decisions.