On this episode of Crazy Wisdom, host Stewart Alsop speaks with Ivan Vendrov for a deep and thought-provoking conversation covering AI, intelligence, societal shifts, and the future of human-machine interaction. They explore the "bitter lesson" of AI—that scale and compute ultimately win—while discussing whether progress is stalling and what bottlenecks remain. The conversation expands into technology's impact on democracy, the centralization of power, the shifting role of the state, and even the mythology needed to make sense of our accelerating world. You can find more of Ivan’s work at nothinghuman.substack.com or follow him on Twitter at @IvanVendrov.

Check out this GPT we trained on the conversation!

Timestamps

00:00 Introduction and Setting

00:21 The Bitter Lesson in AI

02:03 Challenges in AI Data and Infrastructure

04:03 The Role of User Experience in AI Adoption

08:47 Evaluating Intelligence and Divergent Thinking

10:09 The Future of AI and Society

18:01 The Role of Big Tech in AI Development

24:59 Humanism and the Future of Intelligence

29:27 Exploring Kafka and Tolkien's Relevance

29:50 Tolkien's Insights on Machine Intelligence

30:06 Samuel Butler and Machine Sovereignty

31:03 Historical Fascism and Machine Intelligence

31:44 The Future of AI and Biotech

32:56 Voice as the Ultimate Human-Computer Interface

36:39 Social Interfaces and Language Models

39:53 Javier Malay and Political Shifts in Argentina

50:16 The State of Society in the U.S.

52:10 Concluding Thoughts on Future Prospects

Key Insights

1. The Bitter Lesson Still Holds, but AI Faces Bottlenecks – Ivan Vendrov reinforces Rich Sutton’s "bitter lesson" that AI progress is primarily driven by scaling compute and data rather than human-designed structures. While this principle still applies, AI progress has slowed due to bottlenecks in high-quality language data and GPU availability. This suggests that while AI remains on an exponential trajectory, the next major leaps may come from new forms of data, such as video and images, or advancements in hardware infrastructure.
2. The Future of AI Is Centralization and Fragmentation at the Same Time – The conversation highlights how AI development is pulling in two opposing directions. On one hand, large-scale AI models require immense computational resources and vast amounts of data, leading to greater centralization in the hands of Big Tech and governments. On the other hand, open-source AI, encryption, and decentralized computing are creating new opportunities for individuals and small communities to harness AI for their own purposes. The long-term outcome is likely to be a complex blend of both centralized and decentralized AI ecosystems.
3. User Interfaces Are a Major Limiting Factor for AI Adoption – Despite the power of AI models like GPT-4, their real-world impact is constrained by poor user experience and integration. Vendrov suggests that AI has created a "UX overhang," where the intelligence exists but is not yet effectively integrated into daily workflows. Historically, technological revolutions take time to diffuse, as seen with the dot-com boom, and the current AI moment may be similar—where the intelligence exists but society has yet to adapt to using it effectively.
4. Machine Intelligence Will Radically Reshape Cities and Social Structures – Vendrov speculates that the future will see the rise of highly concentrated AI-powered hubs—akin to "mile by mile by mile" cubes of data centers—where the majority of economic activity and decision-making takes place. This could create a stark divide between AI-driven cities and rural or off-grid communities that choose to opt out. He draws a parallel to Robin Hanson’s Age of Em and suggests that those who best serve AI systems will hold power, while others may be marginalized or reduced to mere spectators in an AI-driven world.
5. The Enlightenment’s Individualism Is Being Challenged by AI and Collective Intelligence – The discussion touches on how Western civilization’s emphasis on the individual may no longer align with the realities of intelligence and decision-making in an AI-driven era. Vendrov argues that intelligence is inherently collective—what matters is not individual brilliance but the ability to recognize and leverage diverse perspectives. This contradicts the traditional idea of intelligence as a singular, personal trait and suggests a need for new frameworks that incorporate AI into human networks in more effective ways.
6. Javier Milei’s Libertarian Populism Reflects a Global Trend Toward Radical Experimentation – The rise of Argentina’s President Javier Milei exemplifies how economic desperation can drive societies toward bold, unconventional leaders. Vendrov and Alsop discuss how Milei’s appeal comes not just from his radical libertarianism but also from his blunt honesty and willingness to challenge entrenched power structures. His movement, however, raises deeper questions about whether libertarianism alone can provide a stable social foundation, or if voluntary cooperation and civil society must be explicitly cultivated to prevent libertarian ideals from collapsing into chaos.
7. AI, Mythology, and the Need for New Narratives – The conversation closes with a reflection on the power of mythology in shaping human understanding of technological change. Vendrov suggests that as AI reshapes the world, new myths will be needed to make sense of it—perhaps similar to Tolkien’s elves fading as the age of men begins. He sees AI as part of an inevitable progression, where human intelligence gives way to something greater, but argues that this transition must be handled with care. The stories we tell about AI will shape whether we resist, collaborate, or simply fade into irrelevance in the face of machine intelligence.