The demand for infinite compute

The AI boom isn’t just about chatbots.In this video, I explain why cloud companies and chipmakers are exploding in value: we’re moving into an economy where computation becomes a fundamental input – like steel, electricity or oil.If that’s true, our demand for compute could approach infinity.I also break down new data from Wharton’s 2025 AI Adoption Report, which shows how AI agents and automated workflows are already spreading through major U.S. companies: https://knowledge.wharton.upenn.edu/special-report/2025-ai-adoption-report/Timestamps:(00:00) The economic shift to computation (00:40) The surprising Cloud business boom (02:52) Is the hardware industry growth a bubble? (03:18) What is computing, really? (04:31) Our insatiable appetite for computing (09:15) Our economic dependence on computation (10:54) The rise of agentic workforces (13:05) What does infinite demand actually mean? (15:23) The future of compute demandWhere to find me:Exponential View newsletter: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azharTwitter/X: https://x.com/azeemProduction by supermix.io and EPIIPLUS1Production and research: Chantal Smith, Hannah Petrovic and Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, I speak with Jordan Schneider, creator of Chinatalk, to explore the new phase of US–China competition. Both countries are using trade policy, export controls and industrial strategy to shift the balance of global power. Yet, their economies remain tightly bound. We cover: (01:34) The US and China’s decoupling (07:28) Why attempts to control China backfired (08:51) Understanding the Oct. 9th rare Earth rules (11:27) The modern iteration of Chinese communism (14:23) Is decoupling a strategy to avoid weaponization? (16:12) US leadership might be shooting from the hip (19:22) Are system changes inherently messy? (21:27) “Vibe-based” sovereignty (26:03) AI incumbents aren’t entrenched—yet (29:07) Why China remains focused on AI deployment (32:45) The different versions of tech-accelerationism (33:37) How will societies withstand rapid change? (36:54) What the West can learn from China (40:10) Where China is most misunderstood (43:14) Imagining an improved US-China relationship Where to find Jordan:Substack: https://substack.com/@chinatalkYouTube: @ChinaTalkMedia‬Linkedin: / jorschneiderX: https://x.com/jordanschnycWhere to find me:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn:/ azharX: https://x.com/azeemProduced by EPIIPLUS1 Ltd and supermix.io Production and research: Chantal Smith, Hannah Petrovic and Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Azeem Azhar sat down with Matthew Prince, co-founder & CEO of Cloudflare. Matthew is a rare operator with the vantage point to answer a simple question: if agents do the reading, who gets paid? This conversation is a practical map of how AI “answer engines” upend the web’s traffic-funded model – and what could replace it.Chapters: (00:46) The currency of the web is dying (06:08) Google's inflection point (10:08) Why a broken business model might save the internet (14:44) The incentivization of ragebait (20:38) Content scarcity as a solution (24:35) What could a new content business model look like? (28:51) The challenge of pricing information (29:31) How Cloudflare thinks about the creator economy (32:06) Should smaller companies pay less? (34:24) Can markets solve this without Congress? (39:11) How does the agentic web affect content? (43:40) A rare chance to redesign the internet Produced by EPIIPLUS1 Ltd and supermix.io Production and research: Chantal Smith, Hannah Petrovic, Nathan Warren and Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode, I spoke with Dan Wang, author of “Breakneck: China’s Quest to Engineer the Future”, shortlisted for the FT & Schroders Business Book of the Year.Dan is one of the most astute observers of China’s technological and industrial development, and his annual letters from Beijing have long been required reading for those seeking to understand the country’s evolving role in the world.We unpacked a bold thesis: China is not merely a competitor in AI and tech, but is re-imagining its entire state apparatus as an engineering state - in contrast to the more “lawyerly” institutions of the US and UK.If you’re interested in AI, energy or geopolitics, this conversation is for you.We covered: (00:47) Why China is an engineering state(03:40) China’s pro-engineering disposition(06:08) The role of market competition in China(08:07) Living through Zero COVID(11:35) What political science terms get wrong(12:58) Characteristics of a lawyerly society(15:23) What Americans misunderstand about China(21:54) Has China produced essential tech?(23:50) The AI divide: China vs. US(27:45) Differences in energy production(32:07) The inherent value of process knowledge(38:34) Is the US developing pro-engineering policies?(44:23) What does it take for countries to compete?Where to find me:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azharTwitter/X: https://x.com/azeemWhere to find Dan:Website: https://danwang.co/LinkedIn: https://www.linkedin.com/in/danwang15/Twitter/X: https://x.com/danwwangProduction by supermix.io and EPIIPLUS1 Ltd, including Chantal Smith, Marija Gavrilov, Nathan Warren and Hannah Petrovic. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Is AI a bubble? In this episode, I unpack a new five-gauge framework for understanding the biggest question in tech. Drawing on lessons from past manias – railways, telecoms, the dot-com boom – and grounding our analysis in fresh data, we examine economic strain, revenue growth, valuations, and the quality of capital fueling AI’s ascent. This is our effort to cut through hype and fatalism to provide a clear dashboard: where today’s AI build-out looks like a genuine boom, and where early warning signs of bubble dynamics may be emerging. Whether you’re an investor, policymaker, or executive, this framework offers a disciplined way to navigate the noise.Jump to the best parts:(00:29) Echoes of the past (01:31) The 5 gauge framework (01:54) Gauge #1: Investment intensity(03:45) Gauge #2: Monetization level (04:48) Gauge #3: Revenue trajectory (06:23) Gauge #4: Valuation level(07:24) Gauge #5: Quality of capital (10:10) Overall assessmentProduced by EPIIPLUS1 and Supermix. Thanks to my team: Nathan Warren, Hannah Petrovic, Chantal Smith & Marija Gavrilov Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

GPT-5 was the most advanced AI when it was released, but most people were disappointed. Why? In this episode, I unpack the two key paradoxes that shape how we judge new technology: shifting goalposts and negative space.Timestamps: (0:00) The reaction to GPT-5 (0:40) First paradox (2:55) Second paradox (5:29) Why this matters Dig deeper: https://www.exponentialview.co/p/the-paradox-of-gpt-5  Production by supermix.io and EPIIPLUS1 Ltd, including Chantal Smith, Marija Gavrilov, Nathan Warren and Hannah Petrovic. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Can AI stocks beat Big Tech? In this episode, I discuss OpenAI and its decision to expand a secondary share sale that lets insiders sell about $10.3 billion of stock at roughly a $500 billion valuation. Although skeptical at first, the calculations reveal there is a path for OpenAI to deliver outsized returns.I cover:(0:00) The $500B question (01:11) Why the Nasdaq Index is the benchmark (03:35) Inside the OpenAI-Microsoft deal (05:50) The bull case: OpenAI’s trillion-dollar path (09:33) The AI market explosion (12:39) The bear case: Competition and constraints (17:13) Exploring the models of tomorrow (20:58) The disruption premium (23:21) Where will OpenAI’s revenue come from? (29:14) The final verdict Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This is the single most important paper to come out in tech in recent weeks. Erik Brynjolfsson, Bharat Chandar and Ruyu Chen investigated whether generative AI is leading to job losses in roles most exposed to AI – and how these effects differ by age and the way AI is used. In this episode, I break down these results and their implications. I covered: (01:17) Key finding (03:32) What’s going on here? (06:13) A canary in the coal mine? (8:21) The dataset studied and why it matters (10:34) The sectors impacted and why it matters (12:37) Why don't firms just reduce salaries? (14:34) Historical parallels with electricity (17:20) How leadership impacts job losses (20:46) Implications for policy, education, equity (24:53) Outro Where to find me: - Substack: https://www.exponentialview.co/ - Website: https://www.azeemazhar.com/ - LinkedIn: https://www.linkedin.com/in/azhar?originalSubdomain=uk - Twitter/X: https://x.com/azeem ----Production by supermix.io and EPIIPLUS1 Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Nick Thompson, CEO of The Atlantic, led one of the first major content licensing deals with OpenAI in 2024. In this conversation, he joins Azeem to unpack how AI is transforming media – and what that means for every business navigating the shifting economics of attention, trust, and discovery. We cover: (01:49) Journalism’s four horsemen (5:33) The collapse of search (9:07) Cloudflare’s counterattack (13:56) Is this the search-traffic fix? (17:42) Rise of the sovereign creator (22:57) Do great writers need editors? (26:22) Why conservatives win new media (27:17) How Substack drives discovery (31:08) East Coast vs. West Coast ethics (35:11) How Nick uses AI in writing (42:13) Is AI friend or foe to journalism? (45:32) The Atlantic’s survival plan Nick's links: The Atlantic: https://www.theatlantic.com/LinkedIn: https://www.linkedin.com/in/nicholasxthompson/ Twitter/X: https://x.com/nxthompson Substack: https://nxthompson.substack.com Azeem's links: Substack: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azhar Twitter/X: https://x.com/azeem ----Produced by supermix.io and EPIIPLUS1 Ltd Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

At the start of the year, I made seven predictions about how 2025 would unfold. Six months in, it's time to mark my own work. From AI capability breakthroughs to autonomous vehicles, climate extremes to workforce transformation, I examine what I got right, what I missed, and why the 2027-2028 period will be when vertical AI hits the real economy in force.In this episode you’ll hear:The AI wall that never came: Ten-million-token models exist, O3 scores 25% on Frontier Math vs GPT-4's 2%, but some models are inconsistent and overthink problemsWhen bots officially out-talk humans: My modeling shows LLMs crossed the threshold of producing more text than humans sometime this summerThe Waymo vs Uber SF battle: They've beaten Lyft and expanded to New York, but Tesla's Austin robo-taxi fleet changes the competitive landscapeClimate and energy predictions that were "too easy": Record climate extremes, 30% solar growth, and Indonesia's stunning EV jump from 20% to 80% in two yearsWhat I completely missed: The AI capex boom, humanoid robots at Figure/BMW/Amazon, and workforce impact with CEOs reporting 20-50% AI assistanceWhy getting too many predictions right is a problem: I reflect on whether scoring too well means I didn't push boundaries enough in my forecastingThe 2027-2028 turbulence ahead: Why four-year-old AI startups challenging incumbents while early adopters reap deep organizational benefits will create economic turbulenceOur new showThis was originally recorded for “Friday with Azeem Azhar”, a new show that takes place every Friday at 9am PT and 12pm ET. You can tune in through my Substack linked below.The format is experimental and we’d love your feedback, so feel free to comment or email your thoughts to our team at [email protected]’s links:Substack: https://www.exponentialview.co/Website: https://www.azeemazhar.com/LinkedIn: https://www.linkedin.com/in/azhar?originalSubdomain=ukTwitter/X: https://x.com/azeemTimestamps:(00:00) Grading my predictions from January 2025(01:23) #1: No AI Wall(03:59) #2: Warp-speed deployment(05:16) #3: Bots out-talk humans(06:24) #4: Waymo overtakes Uber in SF(08:31) #5: Climate extremes intensify(09:09) #6: Solar keeps breaking records(10:06) #7: EVs shift up a gear(11:12) The problem with predicting too accurately(12:01) What I missed(12:14) The CapEx boom around AI(13:56) The rise of humanoid robots(14:36) AI's impact on the workforce(18:40) Looking ahead(18:48) Infrastructure first, apps next(19:52) 2027/2028 will be a "period of fireworks"(21:39) When we'll find out if AI is a bubble(23:02) A question for the futureProduction:Production by supermix.io and EPIIPLUS1 Ltd Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.