The Theory of Anything

Learn about reinforcement learning and its stunning victory in Alpha Go. Discover the theory of reinforcement learning and how it solves Markov Decision Problems. Explore important concepts such as state transition and reward functions. Find out the origins of dynamic programming and its challenges without knowledge of these functions. Gain insight into key concepts in reinforcement learning and its potential as a general learning algorithm. Lastly, delve into the learning abilities of animals and comparison to humans and machine learning.

In this episode, we interview Chiara Marletto about her recent book The Science of Can and Can't: A Physicist's Journey Through the Land of Counterfactuals as well as discussing Constructor Theory in general and how it might help us form a new mode of explanation in physics. We ask her some tough questions about constructor theory and she fields the questions very well.  For those interested in q-numbers vs real numbers, see Sam Kupyer's lecture on our Youtube channel. Follow us on Twitter. Check out our blog.

This episode examines whether the Universal Darwinism algorithm applies to knowledge creation in AI and machine learning. It explores examples like Gradient Descent and the Naive Bayes Classifier, questioning their relationship with variation and selection. Counter examples challenge Donald Campbell's prediction about evolutionary algorithms being the sole source of knowledge creation. The podcast also delves into the theory of critical rationalism and the value of testable explanations. Overall, it highlights the exciting epistemological problems that Machine Learning presents.

The podcast explores the debate between David Deutsch, Karl Popper, and Donald Campbell regarding knowledge creation in evolutionary algorithms. It discusses the overlap between artificial intelligence and Popper's epistemology, the steps of the algorithm for improving solutions, the omission of the third step in blind variation selective retention, and the creation of knowledge through variation in selection. It also delves into competing views on knowledge creation, blindness in variation and selective retention, and the concept of blindness in the Universal Darwinism algorithm.

The popular media confuses Artificial Intelligence and Artificial General Intelligence. All the progress is in the first while all the interest is in the second. But what is Artificial Intelligence? In this episode, we explain the umbrella term and its subfields. Plus we introduce how Artificial Intelligence actually ties to all four of David Deutsch's four strands. That makes it an exciting field all of its own even though it's not a path to AGI. Youtube video with optional visuals

Many Worlds Quantum Mechanics is the only current explanation we have of quantum physics. Yet most scientists today still prefer to not have an explanation at all rather than accept it.  Sam Kuypers joins us to discuss his paper "Everettian relative states in the Heisenberg picture" that he co-authored with David Deutsch. He explains why the Heisenberg picture of quantum physics lends itself naturally to a local many worlds view of quantum physics.  Also, we discuss if King Arthur could possibly be both real and fictional at the same time. Whaaaattt!? This audio podcast requires no mathematical knowledge. However, for those interested in reading the actual paper, Sam prepared a math primer available on our youtube channel. 

"Intuitive Eating (A Revolutionary Anti-Diet Approach)" by RDN Evelyn Tribole and RDN Elyse Resch is a book about how to use the natural signals in your body instead of a self coercive diet. It's a strong example of what David Deutsch calls "The Fun Criteria" where you align the implicit information in your mind and body rather than coerce yourself because 'you know it's what's best.' Julene Nielson joins us to compare her experience with dieting vs the Intuitive Eating program.  Also, we discuss the fact that recipes are hard-to-vary yet also parochial.

This podcast explores the intersection of Michael Levine's work with the Noble's and Donald Campbell's. It discusses the bioelectrical system as an error correction process in evolution, challenging gene-centric Neo-Darwinism. The potential breakthroughs in anti-aging and medical treatments without gene therapy or CRISPR are also highlighted. Other topics include constant adaptation, bioelectrical signals in cellular communication, evolving word meanings, Xenobot as a new life form, and the concept of software operating systems in biological intelligence.

Our discussion with Bart Vanderhaegen finishes with a discussion about why businesses prefer to tell their employees what to do and why this is preferred to chaos. Yet if they want to survive in the modern era, this is no longer the best way to lead your company because it doesn't lead to knowledge creation. We also discuss the difference between a good and a bad compromise as well as male and female stereotypes in business. And should math tests be timed? Or is that just sexist? Enquiring minds want to know.  If you are enjoying this show, please give us a 5-star view on Apple Podcast

Bruce, Cameo, and Bart Vanderhaegen continue their conversation about implementing Karl Popper's theory of knowledge in a work environment. In this episode, Bart continues to explain his company's process. We also discuss why Karl Popper's philosophy is so little known and why, even when good error correction processes come along (like Agile Development), it's more an accident than intentional when Popperian epistemology gets worked into the business environment.  And, for the first time ever, I discuss "Neo-Popperian" epistemology. Is that even really a thing?  If you are enjoying this show, please retweet us and give us a 5-Star Review. Follow us on Twitter