Episode #95: Schrodinger's Bubble: Nobody's Keeping Up, And That's Okay

In this episode of the Stewart Squared podcast, host Stewart Alsop sits down with his father, guest Stewart Alsop II, to tackle corrections from last week's show before diving into the rapid pace of AI development and whether anyone can truly keep up. They explore Brian Chesky's new AI lab venture, Anthropic's controversial Fable release and subsequent restrictions by the US government, and Stewart's increasingly frustrating relationship with what he calls an "abusive superintelligence." The conversation shifts to immersive art experiences as Stewart Alsop II reports from Japan, comparing his visit to TeamLab's digital projection exhibits with his investment in Meow Wolf's physical installations. They discuss the business models behind immersive entertainment, the limits of current AI capabilities (spoiler: AGI definitely isn't here yet), and why FFMPEG might be the unsung hero of modern video software. The episode wraps with reflections on Japan's art island Naoshima and the future of live streaming the podcast.

Timestamps

00:00 Welcome and experiment announcement: Stewart introduces a new fact-checking approach for the podcast, explaining how they'll correct previous episodes while maintaining their improvisational conversation style.
05:00 Correcting last week's record: The hosts address three mistakes from the previous episode regarding Brian Chesky staying as Airbnb CEO, Anthropic's revenue numbers, and NVIDIA's history with Apple's Mac computers.
10:00 The impossibility of catching up: Discussion of Stewart II's newsletter concept about falling behind in the AI race, examining Meta and XAI's struggles to compete with leading AI companies despite massive investments.
15:00 Schrodinger's bubble theory: Stewart explores whether we're experiencing a tech bubble, comparing current AI acceleration to past technological shifts and discussing uncertainty around market valuations.
20:00 Abusive superintelligence relationship: Stewart describes his frustrating experience with Anthropic's constant changes, quality degradations, and trust issues while building applications dependent on their AI models.
25:00 Enterprise focus and philosophical concerns: Analysis of Anthropic's shift toward enterprise customers, their cult-like hiring practices, and concerns about effective altruism ideology influencing AI alignment decisions.
30:00 Geographic restrictions and sovereignty: Discussion of Fable's sudden unavailability to non-US citizens, prompting exploration of Chinese AI models as alternatives for maintaining independence.
35:00 Immersive entertainment comparison: Stewart II shares impressions from visiting TeamLab in Tokyo, comparing their digital projection-based experiences with Meow Wolf's physical installations and business models.
40:00 TeamLab versus Meow Wolf analysis: Detailed comparison of how TeamLab uses programmable projections for repeatability while Meow Wolf builds physical environments, discussing advantages and challenges of each approach.
45:00 Business model differences: Exploration of capital costs, repeat visitors, and sustainability challenges between TeamLab's digital flexibility and Meow Wolf's expensive physical build-outs in multiple cities.
50:00 Live streaming ambitions: Stewart reveals plans to livestream future episodes using FFMPEG technology, discussing the technical challenges and open-source philosophy behind modern video streaming infrastructure.
55:00 Japan's art island experience: Stewart II describes visiting Naoshima, an island dedicated entirely to art installations including works by David Hockney and Yayoi Kusama's famous pumpkin sculptures.

Key Insights

1. The podcast experimented with a new format of correcting factual errors from previous episodes, including clarifications about Brian Chesky remaining as Airbnb CEO while building a separate AI lab, corrections to Anthropic revenue figures, and historical facts about NVIDIA providing GPUs to Apple products until around 2012-2013. This represents an effort to maintain journalistic accuracy despite the improvised nature of their conversations.
2. A central thesis emerged around the impossibility of catching up in the AI race once a company falls behind. Examples include Meta's struggles despite aggressive researcher hiring and expensive talent acquisition, and XAI renting out unused data center capacity to competitors like Anthropic and Google for billions per quarter, suggesting their product is not achieving comparable usage to competitors despite massive infrastructure investment.
3. The concept of Schrodinger's bubble was introduced to describe the current technological moment, where we exist in an uncertain state between revolutionary transformation and speculative excess. Unlike previous acceleration periods in the 1980s-2000s with personal computers or social media's emergence, this acceleration with AI appears unrelenting, and determining whether we are in a bubble is impossible until the bubble either continues or bursts, creating anxiety and excitement simultaneously.
4. Anthropic faces criticism for degrading service quality and implementing paternalistic guardrails on their Fable model, including downgrading performance in certain domains like biotech and cybersecurity, sometimes without user notification. This approach to AI alignment, rooted in effective altruism philosophy, is viewed as potentially deluded and cult-like, prioritizing enterprise customers over individual users while destroying trust through policies like restricting non-US citizens from accessing certain features.
5. The comparison between immersive entertainment experiences TeamLab in Japan and Meow Wolf reveals fundamentally different business models, with TeamLab using digital projection that can be easily reprogrammed versus Meow Wolf's expensive physical builds. TeamLab likely achieves more repeat business through constantly changing digital experiences, while Meow Wolf struggles with high capital costs and limited reasons for visitors to return, suggesting future convergence between these approaches.
6. Current AI capabilities fall short of artificial general intelligence, as demonstrated by persistent failures to solve complex technical problems like real-time video lip syncing despite access to advanced models like Anthropic's Fable. While AI excels at deterministic software tasks with automated tests, it cannot handle subjective domains requiring taste like video production or immersive experiences, revealing fundamental limitations in current large language models.
7. Open source technology like FFMPEG demonstrates how fundamental video and audio processing capabilities remain available to everyone on a level playing field, with major platforms like YouTube, Netflix, and Rumble all using the same underlying tools. This represents a successful counter-model to proprietary complexity from the 1990s, suggesting opportunities for new competitors to build sophisticated streaming and video capabilities without requiring the resources of established tech giants.