Flash Forward is a show about possible (and not so possible) future scenarios. What would the warranty on a sex robot look like? How would diplomacy work if we couldn’t lie? Could there ever be a fecal transplant black market? (Complicated, it wouldn’t, and yes, respectively, in case you’re curious.) Hosted and produced by award winning science journalist Rose Eveleth, each episode combines audio drama and journalism to go deep on potential tomorrows, and uncovers what those futures might re ...
…
continue reading
Content provided by The Jim Rutt Show. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Jim Rutt Show or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Player FM - Podcast App
Go offline with the Player FM app!
Go offline with the Player FM app!
EP 316 Ken Stanley on the AI Representation Problem
MP3•Episode home
Manage episode 499040016 series 2569859
Content provided by The Jim Rutt Show. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Jim Rutt Show or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Jim talks with Ken Stanley about the Fractured Entanglement Representation hypothesis in deep learning neural networks. They discuss open-endedness in AI systems & evolution, the Picbreeder experiment & its significance, the objective paradox of finding things by not looking for them, comparisons between Picbreeder & SGD networks, visual differences in internal representations, weight sweep experiments, modular vs tangled decomposition, implications for creativity & continual learning & generalization abilities, Unified Factored Representation as an alternative to FER, the relationship to grokking in neural networks, scaling considerations & evidence in larger models, potential methods to achieve UFR, connections to biological evolution and DNA representation, and much more. Episode Transcript Why Greatness Cannot Be Planned: The Myth of the Objective, by Kenneth Stanley and Joel Lehman "Questioning Representational Optimism in Deep Learning: The Fractured Entanglement Representation Hypothesis" by Akarsh Kumar, Jeff Clune, Joel Lehman, and Kenneth Stanley JRS EP137 - Ken Stanley on Neuroevolution JRS EP130 - Ken Stanley on Why Greatness Cannot Be Planned Kenneth O. Stanley is the Senior Vice President of Open-Endedness at Lila Sciences. He previously led a research team at OpenAI also on the challenge of open-endedness. Before that, he was Charles Millican Professor of Computer Science at the University of Central Florida and was also a co-founder of Geometric Intelligence Inc., which was acquired by Uber to create Uber AI Labs, where he was head of Core AI research. He is an inventor of popular algorithms including NEAT, novelty search, and CPPNs. He has won more than 10 best paper awards and his original 2002 paper on NEAT also received the 2017 ISAL Award for Outstanding Paper of the Decade 2002 - 2012 from the International Society for Artificial Life. He is also a coauthor of the popular science book, Why Greatness Cannot Be Planned: The Myth of the Objective (published originally in the US by Springer), and has spoken widely on its subject.
…
continue reading
435 episodes
MP3•Episode home
Manage episode 499040016 series 2569859
Content provided by The Jim Rutt Show. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The Jim Rutt Show or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Jim talks with Ken Stanley about the Fractured Entanglement Representation hypothesis in deep learning neural networks. They discuss open-endedness in AI systems & evolution, the Picbreeder experiment & its significance, the objective paradox of finding things by not looking for them, comparisons between Picbreeder & SGD networks, visual differences in internal representations, weight sweep experiments, modular vs tangled decomposition, implications for creativity & continual learning & generalization abilities, Unified Factored Representation as an alternative to FER, the relationship to grokking in neural networks, scaling considerations & evidence in larger models, potential methods to achieve UFR, connections to biological evolution and DNA representation, and much more. Episode Transcript Why Greatness Cannot Be Planned: The Myth of the Objective, by Kenneth Stanley and Joel Lehman "Questioning Representational Optimism in Deep Learning: The Fractured Entanglement Representation Hypothesis" by Akarsh Kumar, Jeff Clune, Joel Lehman, and Kenneth Stanley JRS EP137 - Ken Stanley on Neuroevolution JRS EP130 - Ken Stanley on Why Greatness Cannot Be Planned Kenneth O. Stanley is the Senior Vice President of Open-Endedness at Lila Sciences. He previously led a research team at OpenAI also on the challenge of open-endedness. Before that, he was Charles Millican Professor of Computer Science at the University of Central Florida and was also a co-founder of Geometric Intelligence Inc., which was acquired by Uber to create Uber AI Labs, where he was head of Core AI research. He is an inventor of popular algorithms including NEAT, novelty search, and CPPNs. He has won more than 10 best paper awards and his original 2002 paper on NEAT also received the 2017 ISAL Award for Outstanding Paper of the Decade 2002 - 2012 from the International Society for Artificial Life. He is also a coauthor of the popular science book, Why Greatness Cannot Be Planned: The Myth of the Objective (published originally in the US by Springer), and has spoken widely on its subject.
…
continue reading
435 episodes
All episodes
×Welcome to Player FM!
Player FM is scanning the web for high-quality podcasts for you to enjoy right now. It's the best podcast app and works on Android, iPhone, and the web. Signup to sync subscriptions across devices.