The AGI Index: A New Yardstick for Measuring Artificial General Intelligence
Artificial General Intelligence (AGI) is a concept that has intrigued scientists, engineers, and entrepreneurs for years. While most existing AI systems excel in specific tasks, AGI aims for a comprehensive, adaptable intelligence comparable to human cognition. However, quantifying AGI’s capability has been an elusive endeavor—until now. Introducing the AGI Index, a straightforward metric that measures the efficiency of AGI systems.
Defining the AGI Index
The AGI Index is calculated using a simple formula:
AGI Index = Number of Interactions / Number of Tasks
Here, “Number of Interactions” refers to the measurable actions a user takes to interact with a system—be it taps, clicks, or keystrokes. “Number of Tasks” refers to the outcomes or operations completed by the AI system. The ultimate goal is to minimize the numerator and maximize the denominator. In an ideal AGI system, minimal human interaction would be required to accomplish a multitude of tasks.
The Current Reality
Today, the ratio is skewed heavily towards high interaction for low task accomplishment. Whether it’s logging into an account or placing an order, each action—entering a user ID, typing a password, clicking ‘Submit’—counts as an individual interaction. Consequently, the AGI Index for current systems is far from optimal.
The Autoplay Paradigm
To understand the impact of reducing interactions, one need not look further than the introduction of autoplay in online video platforms. Before autoplay, users had to manually click the ‘Play’ button to watch a video on platforms like YouTube and Facebook. The introduction of autoplay—one less click—revolutionized user engagement with digital content.
Autoplay and the AGI Index
Autoplay serves as a microcosm for what AGI aspires to achieve: higher efficiency with less human input. The elimination of just one click significantly changed the way users interact with video content. Extrapolating this to AGI, reducing the number of interactions while increasing the tasks performed could have a profound impact on human-AI synergy.
The Future of the AGI Index
As AGI systems evolve, the AGI Index will serve as a crucial metric to gauge progress. A decline in the index would signify a move towards more autonomous, efficient systems, fundamentally altering human interaction with technology, much like autoplay did for online video.
The AGI Index offers a quantifiable measure of AGI efficiency, drawing a parallel to the autoplay feature’s transformative effect on digital interaction. As we advance towards realizing AGI, the AGI Index will be instrumental in tracking this journey, pushing us to create systems that require fewer interactions but deliver more tasks, thereby enriching human-AI collaboration.