Rethinking AI: Beyond AGI – The Cognitive Cone
Artificial General Intelligence (AGI) is a vague concept, often debated over what truly qualifies as "general" intelligence. Some might argue that systems like ChatGPT have achieved AGI because they handle many tasks. However, these systems, like all intelligent ones, have limitations and aren't universally "clever." In other words, AGI is a poor metric for measuring progress and therefore cannot effectively guide development.
In his 2019 paper, "The Computational Boundary of a 'Self': Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition, Michael Levin articulates this idea:
"Any Self is demarcated by a computational surface – the spatio-temporal boundary of events that it can measure, model, and try to affect. This surface sets a functional boundary—a cognitive 'light cone' which defines the scale and limits of its cognition."
Michael Levin’s concept of the cognitive cone, as visualized in the diagram, provides a powerful framework for understanding and guiding AI progress. It reframes intelligence not as a binary achievement but as a continuum defined by the breadth and depth of a system's perceptive and actionable range. Here’s how this perspective can shape how we think about AI development.
This as tons of useful application regarding AI.
Full post there:
damien-henry.com/writings/rethinking-ai-beyond-agi-the-cognitive-cone