arxiv preprint - Open-Endedness is Essential for Artificial Superhuman Intelligence

In this episode, we discuss Open-Endedness is Essential for Artificial Superhuman Intelligence by Edward Hughes, Michael Dennis, Jack Parker-Holder, Feryal Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktaschel. The paper argues that the development of open-ended, self-improving AI systems is achievable using current foundation models trained on extensive internet data. It provides a formal definition of open-endedness based on novelty and learnability and suggests a path to artificial superhuman intelligence (ASI) through such systems. The paper emphasizes the importance of considering safety in the development of these highly capable and open-ended AI systems.