• A Possible Path to ASI

  • Apr 8 2025
  • Duración: 11 m
  • Podcast
  • Resumen

  • The conversation around AGI and ASI is louder than ever—but the definitions are often abstract, technical, and disconnected from what actually matters. In this episode, I break down a human-centered way of thinking about these terms, why they’re important, and a system that could help us get there.

    I talk about:

    • A Better Definition of AGI and ASI
    Instead of technical abstractions, AGI is defined as the ability to perform most cognitive tasks as well as a 2022 U.S.-based knowledge worker. ASI is intelligence that surpasses that level. Framing it this way helps us immediately understand why it matters—and what it threatens.

    • Invention as the Core Output of Intelligence
    The real value of AGI and ASI is their ability to generate novel solutions. Drawing inspiration from the Enlightenment, we explore how humans innovate—and how we can replicate that process using AI, automation, and structured experimentation.

    • Scaling the Scientific Method with AI
    By building systems that automate idea generation, recombination, and real-world testing, we can massively scale the rate of innovation. This framework—automated scientific iteration—could be the bridge from human intelligence to AGI and beyond.

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    Chapters:

    00:00 - Why AGI and ASI Definitions Should Be Human-Centric
    01:55 - Defining AGI as a 2022-Era US Knowledge Worker
    03:04 - Defining ASI and Why It’s Harder to Conceptualize
    04:04 - The Real Reason to Care: AGI and ASI Enable Invention
    05:04 - How Human Innovation Happens: Idea Collisions and Enlightenment Lessons
    06:56 - Building a System That Mimics Human Idea Generation at Scale
    09:00 - The Challenge of Testing: From A/B Tests to Biotech Labs
    10:52 - Creating an Automated, Scalable Scientific Method With AI
    12:50 - A Timeline to AGI and ASI: Predictions for 2027–2030

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