What are Collective Superintelligence Systems?
The basic principle of any collective superintelligence system is that when a group works collectively, even if individual members have relatively weak intelligence or expertise, they can reliably outperform individual experts and even experts paired with supercomputers. The question “Can a set of weak learners create a single strong learner?” was first posed in 1988 by Michael Kearns, which was answered in the affirmative by Robert Schapire in 1990, leading to “Boosting” in Machine Learning (ML).
Concepts and implementations of collective superintelligence systems have come a long way in the past 30 years, moving well beyond the domain of ML. This type of system comes in many different forms, such as Swarm Intelligence, Hiveminds, and Hybrid Collectives:
Continue reading “Collective Superintelligence Systems, in a Nutshell”
