For decades, Artificial General Intelligence has been a moving target, a nebulous concept that shifts every time a new AI masters a complex task. This ambiguity fuels unproductive debates and obscures the real gap between today's specialized models and true human-level cognition.
This episode changes everything.
We unpack a groundbreaking, quantifiable framework that finally stops the goalposts from moving. Grounded in the most empirically validated model of human intelligence (CHC theory), this approach introduces a standardized "AGI Score"—a single number from 0 to 100% that measures an AI against the cognitive versatility of a well-educated adult.
The scores are in, and they are astonishing. While GPT-4 scores 27%, the next generation leaps to 58%, revealing dizzying progress. But the total score isn't the real story. The true revelation is the "jagged profile" of AI's capabilities—a shocking disparity between superhuman brilliance and profound cognitive deficits.
This is your guide to understanding the true state of AI, moving beyond the hype to see the critical bottlenecks and the real path forward.
In this episode, you will discover:
(00:59) The AGI Scorecard: How a new framework, based on 10 core cognitive domains, provides a concrete, measurable definition of AGI for the first time.
(02:56) The Shocking Results: Unpacking the AGI scores for GPT-4 (27%) and the next-gen GPT-5 (58%), revealing both massive leaps and a substantial remaining gap.
(08:37) The Jagged Frontier & The 0% Problem: The most critical insight—why today's AI scores perfectly in math and reading yet gets a 0% in Long-Term Memory Storage, the system's most significant bottleneck.
(13:12) "Capability Contortions": The non-obvious ways AI masks its fundamental flaws, using enormous context windows and RAG to create a brittle illusion of general intelligence.
(16:21) AGI vs. Replacement AI: The provocative final question—can an AI become economically disruptive long before it ever achieves a perfect 100% AGI score?
