Summary: Ken and I discuss open-endedness, the pursuit of ambitious goals by seeking novelty and interesting products instead of advancing directly toward defined objectives. We talk about evolution as a prime example of an open-ended system that has produced astounding organisms, Ken relates how open-endedness could help advance artificial intelligence and neuroscience, and we discuss a range of topics related to the general concept of open-endedness, and Ken takes a couple questions from Stefan Leijnen and Melanie Mitchell. Related: Ken's website.Twitter: @kenneth0stanley.The book:Why Greatness Cannot Be Planned: The Myth of the Objective by Kenneth Stanley and Joel Lehman.Papers:Evolving Neural Networks Through Augmenting Topologies (2002)Minimal Criterion Coevolution: A New Approach to Open-Ended Search Some key take-aways: Many of the best inventions were not the result of trying to achieve a specific objective.Open-endedness is the pursuit of ambitious advances without a clearly defined objective.Evolution is a quintessential example of an open-ended process: it produces a vast array of complex beings by searching the space of possible organisms, constrained by the environment, survival, and reproduction.Perhaps the key to developing artificial general intelligence is by following an open-ended path rather that pursing objectives (solving the same old benchmark tasks, etc.). 0:00 - Intro 3:46 - Skip Intro 4:30 - Evolution as an Open-ended process 8:25 - Why Greatness Cannot Be Planned 20:46 - Open-endedness in AI 29:35 - Constraints vs. objectives 36:26 - The adjacent possible 41:22 - Serendipity 44:33 - Stefan Leijnen question 53:11 - Melanie Mitchell question 1:00:32 - Efficiency 1:02:13 - Gentle Earth 1:05:25 - Learning vs. evolution 1:10:53 - AGI 1:14:06 - Neuroscience, AI, and open-endedness 1:26:06 - Open AI
