Listen "TruthAmp: Episode 10 - Don't Go Chasing Waterfalls (Chase AI Bubbles)"
Episode Synopsis
Watch here: https://youtu.be/NQHTdb5_Af8
Craig and Emmanuella tackle the burning question: Is AI just another dotcom-style bubble waiting to burst? The Bubble Debate Emmanuella has been hearing concerns across industries that AI might be overhyped like the dotcom boom. She wonders if people deep in AI dismiss these concerns because admitting it would hurt them. As an outsider, she wanted an objective analysis. Why This Time Is Different The Dotcom Lesson: Jeff Bezos noted that industry movements require experimentation, which costs money. During dotcom, infrastructure (fiber optic cables) survived even when companies failed. Amazon shares dropped from IPO to $6, but one original share is now worth ~$48,000. Bubbles punish speculators but reward those who identify real value. AI's Key Distinctions: Actual usage: Unlike hypothetical dotcom projections, AI infrastructure is used immediately as it's deployed Tangible products: OpenAI went from zero to $500 billion in two years with something people actually use daily Fast prototyping: At the Indigenous Australian Datathon Conference, participants built working health/food systems in 1.5 days (five years ago, they just made PowerPoint slides) The Three-Layer Framework Infrastructure Layer (Bottom): Data centers and compute being used and paid for as deployed. Competitive pressure will drive efficiency. This is real, not hypothetical. Business Layer (Middle): Companies building on infrastructure—lots of experimentation, not all will succeed. This is where the "bubble" risk lives. Consumer Layer (Top): People using AI daily for research, scheduling, advice. Already embedded in life with genuine utility. What Determines Winners The pets.com cautionary tale: They had a great name but terrible user experience. PetSmart crushed them with a better website. Winners marry user experience with new tech. Losers trade on hype. Companies that survived dotcom (Amazon, early Yahoo, later Facebook) had genuine utility that compelled continued use. The Democratisation Opportunity You no longer need coding skills—just understand systems, business, and customers. Barriers to entry have collapsed. Emmanuella has been buying shares for her daughters since birth; what might fund one startup could now fund 10 experiments. The Reality Check No substance = failure. Hypothetical AI companies without humans putting in grunt work won't succeed. Value requires the end-to-end human experience—people identifying problems and experiencing solutions. Don't judge success at one point in time. See what survives market corrections. Takeaway This isn't a bubble—it's a punctuated equilibrium. Infrastructure is solid, consumer utility is real, but not all businesses building on top will succeed. If you identify genuine long-term value and ride out volatility, history suggests patience pays off.
Craig and Emmanuella tackle the burning question: Is AI just another dotcom-style bubble waiting to burst? The Bubble Debate Emmanuella has been hearing concerns across industries that AI might be overhyped like the dotcom boom. She wonders if people deep in AI dismiss these concerns because admitting it would hurt them. As an outsider, she wanted an objective analysis. Why This Time Is Different The Dotcom Lesson: Jeff Bezos noted that industry movements require experimentation, which costs money. During dotcom, infrastructure (fiber optic cables) survived even when companies failed. Amazon shares dropped from IPO to $6, but one original share is now worth ~$48,000. Bubbles punish speculators but reward those who identify real value. AI's Key Distinctions: Actual usage: Unlike hypothetical dotcom projections, AI infrastructure is used immediately as it's deployed Tangible products: OpenAI went from zero to $500 billion in two years with something people actually use daily Fast prototyping: At the Indigenous Australian Datathon Conference, participants built working health/food systems in 1.5 days (five years ago, they just made PowerPoint slides) The Three-Layer Framework Infrastructure Layer (Bottom): Data centers and compute being used and paid for as deployed. Competitive pressure will drive efficiency. This is real, not hypothetical. Business Layer (Middle): Companies building on infrastructure—lots of experimentation, not all will succeed. This is where the "bubble" risk lives. Consumer Layer (Top): People using AI daily for research, scheduling, advice. Already embedded in life with genuine utility. What Determines Winners The pets.com cautionary tale: They had a great name but terrible user experience. PetSmart crushed them with a better website. Winners marry user experience with new tech. Losers trade on hype. Companies that survived dotcom (Amazon, early Yahoo, later Facebook) had genuine utility that compelled continued use. The Democratisation Opportunity You no longer need coding skills—just understand systems, business, and customers. Barriers to entry have collapsed. Emmanuella has been buying shares for her daughters since birth; what might fund one startup could now fund 10 experiments. The Reality Check No substance = failure. Hypothetical AI companies without humans putting in grunt work won't succeed. Value requires the end-to-end human experience—people identifying problems and experiencing solutions. Don't judge success at one point in time. See what survives market corrections. Takeaway This isn't a bubble—it's a punctuated equilibrium. Infrastructure is solid, consumer utility is real, but not all businesses building on top will succeed. If you identify genuine long-term value and ride out volatility, history suggests patience pays off.
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