Professor Karl Friston (University College London) speaks at the University of Edinburgh, 31st March 2017. Abstract: This talk offers a formal account of insight and learning in terms of active (Bayesian) inference. It deals with the dual problem of inferring states of the world and learning its statistical structure. In contrast to current trends in machine learning (e.g., deep learning), we focus on how agents learn from a small number of ambiguous outcomes to form insight. Karl will present simulations of abstract rule-learning and approximate Bayesian inference to show that minimising (expected) free energy leads to active sampling of novel contingencies. This epistemic, curiosity-directed behaviour closes ‘explanatory gaps’ in knowledge about the causal structure of the world; thereby reducing ignorance, in addition to resolving uncertainty about states of the known world. We then move from inference to model selection or structure learning to show how abductive processes emerge when agents test plausible hypotheses about symmetries in their generative models of the world. The ensuing Bayesian model reduction evokes mechanisms associated with sleep and has all the hallmarks of ‘aha moments’.
How can we ‘measure’ how conscious someone is, using brain imaging? Are our conscious experiences ‘controlled hallucinations’? What does it mean to experience being a ‘self’? Are other animals conscious? What about machines, now or in the future? Consciousness is, for each of us, the presence of a world. Without consciousness there is no world, no self: there is nothing at all. But we know surprisingly little about the material and biological basis of this most central feature of our lives. How do rich multisensory experiences, the senses of self and body, and volition, agency, and ‘will’ emerge from the joint activity of billions of neurons locked inside a bony skull? Once the province of philosophy and theology, understanding consciousness has emerged as a one of the great scientific challenges for this century. This evening, Anil Seth will sketch the state-of-the-art in the new science of consciousness, with a focus on what neuroscience has to offer. He will distinguish between conscious level (how conscious we are), conscious content (what we are conscious of), and conscious self (the ‘I’ behind the eyes), describing in each case how new experiments are shedding light on the underlying neural mechanisms, in normal life and in neurological and psychiatric conditions. Throughout, he will emphasize phenomenology – the way things seem – as the target for any satisfying explanation of how the brain, in conjunction with the body and the environment, gives rise to and shapes conscious experience.
Karl Friston, Wellcome Principal Research Fellow and Scientific Director at Wellcome Trust Centre for Neuroimaging and Professor of Neurology at University College London speaks at the event "Prediction: How Forecasting and Prospection Shape Thought" held on 4/18/16 at Columbia University. The event is part of the "Seminars in Society and Neuroscience" series organized by the Presidential Scholars in Society and Neuroscience program.
Rupert Sheldrake, Robin Carhart-Harris and Stephen Reid In Conversation Wednesday 26th June 2019 at EartH, Hackney, London, UK Facebook event https://www.facebook.com/events/24450... Conversation starts at 04:50
Simons Institute Theoretically Speaking Series https://simons.berkeley.edu/events/brain Moderator: Anil Ananthaswamy (Fall 2018 Simons Institute Journalist in Residence) Panelists: Celeste Kidd (UC Berkeley) Bruno Olshausen (UC Berkeley) Christos Papadimitriou (Columbia University) Michael Pollan (UC Berkeley)
Full talk title: REBUS and the Anarchic Brain: A Unified Model of the Brain Action of Psychedelics REBUS and the Anarchic Brain: A Unified Model of the Brain Action of Psychedelics Robin Carhart-Harris moved to Imperial College London in 2008 after obtaining a PhD in Psychopharmacology from the University of Bristol and an MA in Psychoanalysis from Brunel University. At Imperial, Robin has designed and overseen brain imaging studies involving LSD, psilocybin, MDMA and DMT, plus a clinical trial of psilocybin for treatment-resistant depression, another trial comparing psilocybin with escitalopram for major depressive disorder and another imaging study in healthy volunteers receiving a high-dose of psilocybin. Robin is head of the Centre for Psychedelic Research at Imperial and has an honorary position with the University of Oxford. This talk was filmed at Breaking Convention 2019 and is sponsored by Synthesis.
Neuroscientist Karl Friston on split personality, the nature of mental disorders, and the possibility of a therapeutic cure of schizophrenia.
Mark Solms, Cape Town Discussion of Karl Friston: Consciousness and the Bayesian brain.
Neuroscientist Karl Friston on different types of brain measurement techniques, people's reaction on emotional stimuli, and possibility of brain mapping.
Neuroscientist Karl Friston on the Markov blanket, Bayesian model evidence, and different global brain theories.
Professor Karl Friston (University College London) speaks at the University of Edinburgh, 31st March 2017. Abstract: This talk offers a formal account of insight and learning in terms of active (Bayesian) inference. It deals with the dual problem of inferring states of the world and learning its statistical structure. In contrast to current trends in machine learning (e.g., deep learning), we focus on how agents learn from a small number of ambiguous outcomes to form insight. Karl will present simulations of abstract rule-learning and approximate Bayesian inference to show that minimising (expected) free energy leads to active sampling of novel contingencies. This epistemic, curiosity-directed behaviour closes ‘explanatory gaps’ in knowledge about the causal structure of the world; thereby reducing ignorance, in addition to resolving uncertainty about states of the known world. We then move from inference to model selection or structure learning to show how abductive processes emerge when agents test plausible hypotheses about symmetries in their generative models of the world. The ensuing Bayesian model reduction evokes mechanisms associated with sleep and has all the hallmarks of ‘aha moments’.
The worlds most cited neuroscientist Karl Friston and colleagues David Rudrauf and Ken Wiliford explain their new theory of consciousness and its links to AI and VR. According to Wired magazine Friston is "the genius neuroscientist who may hold the keys to true AI" and in this film we will explain how the model may do that and much more. Topics discussed are: 00: Introduction 00:43 Beginnings 2:50What is consciousness? 3:48How can science tackle the subjective? 5:03 Answering critics of a scientific approach to consciousness 5:30 What is the free energy principle ? 7:58 What is active inference? 9:46 What is projective geometry ? 11:34 The PCM explained 14:40 Contrast with Tenoni's IIT 17:31 Consciousness in animals and AI 25:18 Virtual Reality 27:55 The Hard Problem of Consciousness 29:33 Experimental Testing 38:46 Autism, Clinical Implications and Pyschopathologies 41:28 The future of the model
"Karl Friston’s free energy principle might be the most all-encompassing idea since Charles Darwin’s theory of natural selection." This week we take a deep dive into one of the most recent and groundbreaking theories related to human behavior, Karl Friston's Predictive Coding and Free Energy Concept. Julien goes into it's application to nutrition, training, behavior and how it has worked it's way into being one of the new cornerstones of StrongFit. If you want to learn more about Karl Friston, read this article... https://www.wired.com/story/karl-fris...