# Kenneth Stanley
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Kenneth Owen Stanley is an artificial intelligence researcher, author, and former professor of computer science at the University of Central Florida known for creating the Neuroevolution of augmenting topologies (NEAT) algorithm. He coauthored Why Greatness Cannot Be Planned: The Myth of the Objective with Joel Lehman which argues for the existence of the "objective paradox", a paradox which states that "soon as you create an objective, you ruin your ability to reach it". While a professor at the University of Central Florida, he was the director of the Evolutionary Complexity Research Group (EPlex) which led the development of Galactic Arms Race.
Sangeet Paul Choudary — AI and our System Reshuffle (EP.282)
Sangeet Paul Choudary, bestselling author of Platform Revolution and Reshuffle, and senior fellow at UC Berkeley, joins the show to challenge the conventional wisdom about AI's impact on our economy. We explore why knowledge workers risk falling "below the algorithm," how curiosity and judgment b...
Kenneth Stanley — The Trap of the Objective (EP.288)
Ken Stanley – AI researcher and author of "Why Greatness Cannot Be Planned" – joins me to explore why ambitious objectives can blind us to the stepping stones that make breakthroughs possible. Ken is the inventor of the novelty search algorithm and co-creator of Picbreeder, a crowdsourced evoluti...
Dr. Kenneth Stanley – Uber AI Labs – Improving Business Operations Through the Development of Machine Learning and Neuroevolutionary Tools
Dr. Kenneth Stanley is a professor at the University of Central Florida and the founder of Geometric Intelligence, a machine learning company that was renamed Uber AI Labs after being acquired by Uber in later 2016. "Uber recognized that AI and machine learning are ultimately fundamental to their...
How to actually achieve greatness (Why Greatness Cannot Be Planned by Joel Lehman and Kenneth Stanley)
Lessons from reading Why Greatness Cannot Be Planned by Joel Lehman and Kenneth Stanley.
#154 – Why Objectives Are the Enemy of Greatness | Kenneth Stanley
What if the surest way to fail at something ambitious is to have a clear plan to achieve it? What if a robot that doesn’t know it’s trying to walk learns faster than one explicitly...
Sam Arbesman: Complex Systems, Code, and Human Understanding | Episode 167
Sam Arbesman is a complexity scientist, writer, and Scientist in Residence at Lux Capital, known for his books The Half-Life of Facts, Overcomplicated, and The Magic of Code. In this episode, we explore human understanding, its limits, the power and unpredictability of technology, our relationshi...
The Benchmark With No Instructions — ARC-AGI-3 (winning team!)
Tim Scarfe travels to Zurich to sit down with the Tufa Labs ARC-AGI-3 team — founder Benjamin Crouzier, with Jeroen Cottaar, Dries Smit, Stefano Viel and Michal Tesnar — to work out what their leaderboard-topping system does and what the benchmark is really testing.The cut opens on the games: a w...
Why Creativity Cannot Be Interpolated - MLST
Jeremy Budd, Assistant Professor at the University of Birmingham, and Tim Scarfe, CEO of Machine Learning Street Talk, discuss the paper “Why Creativity Cannot Be Interpolated”, which argues that genuine creativity requires respect for constraints that today’s AI lacks.
Building on ideas from Fr...
Kenneth Stanley: Set The Right Objectives
Artificial intelligence researcher and author Kenneth Stanley has argued that “as soon as you create an objective, you ruin your ability to reach it.” So what should you consider when thinking about your objectives, and what will set you up for success? On this episode Stanley discusses how to se...
What Most People Get Wrong About Evolution | Akarsh Kumar
A lot of people in AI treat evolution as a dumb fallback, basically random search for when you can't take a gradient. Akarsh Kumar thinks that is wrong. Selection hangs on to partial solutions, so mutations only need to be useful about 1% of the time for the search to keep making progress.Akarsh ...
