Better Offline (Cool Zone Media & iHeartPodcasts)
Episode: AI Is Worse Than The Dot Com Bubble: Part Two
Release Date: January 28, 2026

Episode Overview

In this episode, host Ed Zitron continues his critical exploration of today's AI investment frenzy, arguing that the ongoing "AI bubble" poses economic risks that far outstrip those of the dot com bubble. Drawing on tech-industry history, striking anecdotes, and financial insights, Ed lays out why today's AI hype—built largely around Nvidia and the so-called "Magnificent Seven" tech giants—is setting up millions for disappointment and the entire market for a possibly catastrophic fallout.

Key Discussion Points & Insights

1. Comparing the AI Bubble to the Dot Com Bubble

• Dot com bubble: Characterized by wild venture deals and pointless, unprofitable websites driven by widespread, unfounded optimism about the internet’s growth.
  • Quote: “The dot com bubble was a mixture of dodgy venture capital deals and websites that could never turn a profit, combined with a global mania around the interconnectivity of high SPE Internet companies.” (02:00)
• AI Bubble: Defined by a handful of companies (notably Nvidia) selling high-cost GPUs, massive data center build-outs, and startups burning money with little consumer appetite for their products.
  • Quote: “The AI bubble is one company selling expensive AI GPUs, a bunch of companies building data centers to put them in, and a bunch of companies building shit that runs on GPUs that only loses money and that customers kind of fucking hate.” (02:11)

2. Venture Capital’s Desperation and Systemic Risk

• VC investments are now over-concentrated in AI, despite bad economics:
  • “AI startups now make up more than half of venture investment. And I believe that most of these startups will die because of their horrib[le] margins, no path to profitability and products that people really don't want to pay for at scale.” (02:44)
• Predicts an industry-wide crisis: Once venture firms can’t generate returns or raise fresh capital, they will collapse.
  • “They won't have any way of raising more capital as their limited partners won't fucking trust them.” (03:16)

3. Economic Myths Driving Bubbles

• Both bubbles are fueled by “ridiculous myths” (AI’s “insatiable” compute demand, dropping cost of ‘intelligence’; dot-com’s exaggerated internet growth rates).
  • “This continental rewiring was also justified by another powerful myth, that Internet traffic was doubling every 90 days… But the mathematics were fiction.” (04:10)
  • Quote from researcher Justin Kohler and AT&T’s Andrew Odlyzko is used to emphasize how facts were overlooked in favor of viral, fictional claims.

4. Infrastructure & Economics: Then vs. Now

• Dot com era: Overbuilt real, useful infrastructure (fiber optic lines) despite exaggerated demand projections.
  • “It was actually pretty useful to lay millions of miles of fiber optic cable. This is in no way, shape or form remotely comparable to large language models, GPUs or any nebulous VC spec spunk around generative AI.” (09:00)
• AI era: No real infrastructure limits—LLMs (large language models) are instantly available and globally accessible. The bottleneck is not access, but the fundamental usefulness and cost of the technology.
  • “There is very little stopping anyone from using an LLM. ChatGPT is free...” (10:56)
  • “Anyone claiming this is just like the early days of the Internet is a fucking liar or a fucking moron.” (11:37)

5. The Centrality and Risk of Nvidia

• Nvidia is the key beneficiary and sole significant profit-maker in the AI boom.
  • “The AI bubble rests fundamentally on one company, Nvidia, and to a lesser extent, the valuations of the remainder of the Magnificent Seven.” (12:19)
• The market is highly leveraged: Major cloud firms now buy GPUs through intermediaries to mask true volumes and are increasingly reliant on debt. Exposure is global, affecting Taiwanese manufacturers as well.
  • “They order through Taiwan and then those servers are put together and shipped to their data centers. This allows them to Hide how many GPUs they're buying from their investors...” (13:56)
• The AI economics are brutal: Infrastructure and GPU buying are massively capital intensive, with virtually no public proof of sustainable revenue from AI services.
  • “I'm not sure anybody renting them can ever make a profit due to either or both the upfront cost and debt necessary to pay it and the power intensive nature of providing AI compute.” (15:03)
  • “It's so crazy. How do we not know? How the fuck do we not know this?” (15:21)

6. Market and Environmental Risks

• Unlike fiber, GPUs and data centers are rapidly depreciating assets with short useful lives (not “railroads” or century-long infrastructure).
  • “Imagine if all of that fiber was useless in five or six years at best... What if all of that fiber required such massive amounts of power that it threatened rolling blackouts of the east coast of America?” (17:48)
  • Quote from Purple Kudrowski: “We are in a historically anomalous moment. Regardless of what one thinks about the merits of AI or explosive data center expansion. The scale and pace of capital deployment into a rapidly depreciating technology is remarkable.” (17:18)

7. Stock Market Systemic Threat

• AI, Nvidia, and the “Magnificent Seven” account for the lion’s share of US equity growth—making the entire market dangerously beholden to a single, hype-driven industry.
  • “The Magnificent Seven stocks accounted for 47.87% of the Russell 1000 index's returns in 2024.” (19:10)
  • “The US stock market would be in incredibly rough shape” without this tech bubble, and a crash could quickly become global market contagion.
• Nvidia’s required future earnings are “impossible”: By 2028, they’d need Walmart-scale revenue to support their valuation:
  • “Nvidia will have to be making 500 to $600 billion, which puts it in the realm of Walmart. It can’t happen. It can’t happen. It can’t happen.” (20:41)

Notable Quotes & Memorable Moments

• Ed Zitron on AI Hype:
  • “LLMs have now spread to every nook and cranny of the Internet. Anybody can use one. Anybody can experience the so called power of AI. Users are not sitting frothing at the mouth unable to access ChatGPT due to a lack of infrastructure.” (11:30)
• Cynicism about Venture Capital:
  • “To be clear, these ass wipes have cocked it up many years at a time. Look at crypto, look at NFTs, look at AR, VR, metaverse, all of that.” (03:30)
• On data center demand and GPU economics:
  • “What we do know is that the only company making any kind of profit during the AI bubble appears to be Nvidia or companies selling ram.” (15:29)
  • “The only company making any profit is Nvidia. Everybody else is eating shit.” (paraphrase, 15:32)
• On market risk:
  • “The result, I fear, is that the American stock market takes a shit the size of Iowa and due to the unique way the tech industry functions, the contagion will be global.” (21:17)
• On future outlook:
  • “Every time I think of this stuff I feel very, very sad. Anyway, very optimistic.” (21:35)

Important Timestamps

• 02:00–03:55: Opening argument & VC dynamics
• 04:08–07:25: Dot com bubble myth busting
• 09:00–10:18: Contrasts between infrastructure eras
• 10:52–12:05: Accessibility & uselessness of AI infrastructure
• 12:19–17:48: Nvidia’s dominance, structural debt, and global exposure
• 17:18–18:39: Depreciation, environmental/asset risk (Purple Kudrowski quote)
• 19:10–21:45: Stock market systemic risk, Nvidia’s impossible path, and closing emotional reflection

Summary Takeaway

Ed Zitron paints a dire picture of AI’s economic bubble: unlike the dot com era, where misguided optimism built beneficial infrastructure, today’s AI fervor is funnelling capital into quickly-obsolescing, deeply polluting, debt-funded tech managed by a handful of unaccountable giants. The entire US stock market (and by extension the world) is now hitched to the fate of Nvidia, whose future promises are mathematically impossible. If and when the bubble bursts, not only startups but entire financial systems could be dragged down—a risk no one seems eager to acknowledge.

Episode tone: cutting, sarcastic, and deeply skeptical of mainstream tech optimism — delivered with urgency and a streak of gallows humor.