Episode 77: Counter Examples To Deutsch's Theory of Knowledge?

The Theory of Anything

#Society #Philosophy #Bruce Nielson

1:14:43

Artificial intelligence is evolving at an unprecedented pace—what does that mean for the future of technology, venture capital, business, and even our understanding of ourselves? Award-winning journalist and writer Anil Ananthaswamy joins us for our latest episode to discuss his latest book Why Machines Learn: The Elegant Math Behind Modern AI . Anil helps us explore the journey and many breakthroughs that have propelled machine learning from simple perceptrons to the sophisticated algorithms shaping today’s AI revolution, powering GPT and other models. The discussion aims to demystify some of the underlying mathematical concepts that power modern machine learning, to help everyone grasp this technology impacting our lives–even if your last math class was in high school. Anil walks us through the power of scaling laws, the shift from training to inference optimization, and the debate among AI’s pioneers about the road to AGI—should we be concerned, or are we still missing key pieces of the puzzle? The conversation also delves into AI’s philosophical implications—could understanding how machines learn help us better understand ourselves? And what challenges remain before AI systems can truly operate with agency? If you enjoy this episode, please subscribe and leave us a review on your favorite podcast platform. Sign up for our newsletter at techsurgepodcast.com for exclusive insights and updates on upcoming TechSurge Live Summits. Links: Read Why Machines Learn, Anil’s latest book on the math behind AI https://www.amazon.com/Why-Machines-Learn-Elegant-Behind/dp/0593185749 Learn more about Anil Ananthaswamy’s work and writing https://anilananthaswamy.com/ Watch Anil Ananthaswamy’s TED Talk on AI and intelligence https://www.ted.com/speakers/anil_ananthaswamy Discover the MIT Knight Science Journalism Fellowship that shaped Anil’s AI research https://ksj.mit.edu/ Understand the Perceptron, the foundation of neural networks https://en.wikipedia.org/wiki/Perceptron Read about the Perceptron Convergence Theorem and its significance https://www.nature.com/articles/323533a0…

рік тому 1:35:51

M4A•Головна епізоду

Bruce continues to consider what our best theories tell us about knowledge. Is there something special (or even physically different) about the knowledge created by nature through biological evolution and human minds (i.e. the 'two sources hypothesis')? How should we think about knowledge created in human minds that could take us to the moon and beyond or divert an asteroid? Is it physically different from the kind of adapted information created by animals or the immune system? Or does it merely a broader and deeper search for solutions?

Along the way, he delves into machine learning, animal behavior, the immune system, trade secrets, robots, and many other concepts related to David Deutsch’s ideas about knowledge but are outside the 'two sources' and thus not considered 'knowledge' by David Deutsch.

104 епізодів

Episode 77: Counter Examples To Deutsch's Theory of Knowledge?

The Theory of Anything

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M4A•Головна епізоду

104 епізодів

#Society #Philosophy #Bruce Nielson

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Episode 103: Neo-Darwinism vs Post-Darwinism 1:53:36

14 днів тому1:53:36

1:53:36

This week we discuss neo-Darwinism vs post-Darwinism. Neo-Darwinism meaning a gene centric view of evolution, which is also called the great synthesis since it unifies natural selection with genetics and paleontology and perhaps even human psychology. Post-Darwinism is a view that emphasizes factors outside random mutation, like epigenetics or the assertion that organisms and cells can alter their own genome in a beneficial way. Here Bruce specifically concentrates on the work of biologist James Shapiro’s critical look at Richard Dawkins’ neo-Darwinism.We consider, does it really make sense to see our bodies and minds as tools governed by our masters DNA? Does post-Darwinism, also called “third way evolution,” offer a meaningful alternative to both neo-Darwinism and the theism of intelligent design? Does this way of looking at biology say something about the very nature of reality and the laws of physics? This is part 1 of a loose series. Part 2 will cover criticisms of Noble and Shapiro. Part 3 will cover the work of Michael Levin. However, you don't really need to listen to them in order and we provide context each time. James Shapiro's Evolution: A View from the 21 Century Support us on Patreon…

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Episode 102: Is IQ a Bit Scientifically Valid? 1:25:51

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1:25:51

This time we discuss Nassim Nicholas Taleb's article "IQ is Largely a Pseudoscientific Swindle" -- a title whose compliment is that he's claiming IQ is a bit scientifically valid. But which bits does he claim are valid? We use this article as a springboard to consider: Do the numbers produced by an IQ test say something meaningful or useful about human minds? Would these tests be better off in the dustbin of history? Are they ever useful? And is there overlap between Taleb's take on IQ and the negative view of these tests held by many critical rationalists? What does Taleb agree (or disagree) with CritRats over when it comes to IQ? Taleb's original article found here .…

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Episode 101: Wolfram, Rucker, and the Computational Nature of Reality 2:16:27

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2:16:27

Bruce takes a deep dive into Stephen Wolfram’s ideas regarding computational universality, which may go further than the Church-Turing-Deutsch thesis in that Wolfram’s theories imply that all of nature could be simulated even by relatively simple systems, so even nature itself may be computational rather than something that can just be simulated on a turning machine or quantum computer. Stephen Wolfram is a renowned physicist, computer scientists, and entrepreneur. Bruce also talks about the related ideas on philosophy of computation promoted by Rudy Rucker, who is a mathematician, computer scientist, and science fiction author associated with cyberpunk genre. Both thinkers believe, rightly or wrongly, that the complexity of life and the universe can be explained by relatively simple computational rules.…

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Episode 100: Interview with David Deutsch 2:27:25

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2:27:25

Our Christmas gift to you this year is episode 100: an interview with The Man (TM) himself! Bruce stumbles over himself fan-boying as he asks all his burning (but geeky) questions about cosmology, the omega point, and probability. How do Deutsch and Tipler differ on optimistic end-time cosmology? Is the Omega point refuted by observation (Deutsch) or not (Tipler)? Does heat death contradict the principle of optimism? Is it a bummer? Does stochasticity really not exist? And is it rational to wear a mask during COVID? How do you apply epistemology to a question like that when you lack enough data to severely test your theories but still need to make a decision? Peter asks: Are free will and downward causation related? Do our genes attempt to coerce us? Why are explanatory and computational universality so confusing? And what if studies show that authoritative parenting is best for children? Support us on Patreon…

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Episode 99: Critical Rationalism and Solipsism 1:31:31

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1:31:31

AKA "David Deutsch DESTORYS the Simulation Hypothesis" Bruce take a deep dive into solipsism in the form of the brain in a vat thought experiment, Nick Bostrom’s simulation hypothesis, and related ideas. Does the Church-Turing-Deutsch thesis suggest we could live in a simulation? What does critical rationalism say about these theories? Support us on Patreon…

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Episode 98: Objectively Beautiful Flowers? 1:58:05

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1:58:05

This week we discuss the chapter “Why are Flowers Beautiful?” from the book Beginning of Infinity by David Deutsch. Through our discussion we consider: Does relativism make any sense? Is preferring Mozart to a child banging on a piano really just an arbitrary preference? If progress in art is real, will human minds ever stop increasing the level of beauty in the world? Are humans more objectively beautiful than other species? (And are women more beautiful than men?) Is music “cheesecake for the ears,” as Steven Pinker puts it? And is cheesecake itself even “cheesecake for the mouth”? Is progress in science also intertwined with aesthetic progress?…

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Episode 97: Karl Popper On Conservatism in Music (w/Chris Johansen) 1:31:41

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1:31:41

We take a deep dive into Karl Popper’s philosophical ideas about music that he outlines in four chapters in this intellectual autobiography Unended Quest: “Music,” Speculations about the Rise of Polyphonic Music,” “Two Kinds of Music,” and “Progressivism in Art, Especially in Music.” We are joined by Peter’s brother, Chris Johansen, who is a straight-ahead jazz tenor saxophonist living in NYC. We discuss how Popper’s ideas on classical music intersect with Chris’s ideas on jazz, as well as the role of conservatism in music. We examine how Popper’s thinking on music influenced his concept of the 3 worlds and his ideas on such concepts as dogmatism, essentialism, and historicism. Plus, you get Bruce's rant about the importance of constraints in music, science, criticism, and Popper's epistemology. Bruce argues that absent at least the attempt to outline epistemological conventions (i.e. constraints) you can't error correct Popper's epistemology and you lose what makes it special. You can listen to more of Chris’s music here .…

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Episode 96: Kenneth Stanley on the Pursuit of What’s Interesting 1:28:33

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1:28:33

Here we interview AI researcher Kenneth Stanley, who makes the case that in complex systems, pursing specific objectives can actually be counterproductive. Instead, whether in machine learning, business, science, education, or art, we should pursue what is interesting. It is in this search for novelty—fueled by curiosity—where innovation and open-ended knowledge creation occurs. Get Ken's book! Why Greatness Cannot Be Planned: The Myth of the Objective Also: Can Bruce find a counter example to Ken's thesis? How does one 'detect novelty' using an algorithm? Is creativity really a search algorithm?…

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Episode 95: On Morality, Moralizing, and Elephant Jockeys (Round Table) 2:48:50

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2:48:50

This time we invited some of the coolest and smartest people we know to have a freewheeling discussion on morality loosely centered on Jonathan Haidt's “rider and the elephant” metaphor. We take a deep dive into this idea that moral reasoning is a slave to our passions. Guests: • Lulie Tanett (https://open.spotify.com/show/6OPFnEt6uTOTGeSpnZ1YDp?si=4exIQOUfQzOg4TIU2hZ5hA) • Vaden Masrani (https://open.spotify.com/show/1gKKSP5HKT4Nk3i0y4UseB?si=Iu1WkwJMR1GHlm3OLrUwNA) • Ivan Phillips (https://www.amazon.com/dp/B08VGCFVJB?ref=cm_sw_r_mwn_dp_33ZJEY7V0RP00CG7566Z&ref_=cm_sw_r_mwn_dp_33ZJEY7V0RP00CG7566Z&social_share=cm_sw_r_mwn_dp_33ZJEY7V0RP00CG7566Z&language=en_US) • Ray Scott Percival (https://www.amazon.com/Myth-Closed-Mind-Understanding-Rational-ebook/dp/B007ED2YOG/ref=mp_s_a_1_1?crid=18OW1OJ7SHU0F&dib=eyJ2IjoiMSJ9.JSCCp7cMzHYl926ph94huzUH8e6nS5VFbeyXnBuWHk_8xfeA3aYMNGdbPKf51RTbatD5MJ6psFT9Md-wcXMohLMIVZMTtZYFZPkdvMPLieZem163A_H5xch8hiTt28hByPAtMm3xFqIUtQ9GLpkOI_5Pr7TzJ8Fw7bfiYqt36gnx4yeJSb8a4eOSff3p5QJ04oLY9PUNBdGPtxcILt_ung.cTeFXFI-PZaMPhyBZtFcJ7mIY2k4Kkq1fTEIafAEsxs&dib_tag=se&keywords=ray+scott+percival&qid=1728763752&sprefix=ray+scott+percival+%2Caps%2C156&sr=8-1⁠; https://open.spotify.com/artist/3B1Bh10uUljUX9iNmPOYZo?si=NWnRyuv1T7aHRGWZIXZYzA)…

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Episode 94: Stephen Hicks on Critical Rationalism vs Objectivism 1:01:44

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1:01:44

This episode we interview Professor of Philosophy Stephen Hicks. In his excellent books Explaining Postmodernism and Nietzsche and the Nazis it becomes clear that the history of bad and good ideas—which he sees through the lens of Enlightenment and counter-Enlightenment philosophers—is more than an academic issue but something with monumental importance for human life and prosperity. Rather than focus on this aspect of his work, which is widely known, we thought we’d ask him questions on epistemology, focusing on contrasting critical rationalism and objectivism.…

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Episode 93: Philosophical Theories vs Bad Explanations 2:07:05

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2:07:05

Can philosophical theories be refuted? What is a bad explanation? Can all theories be made more empirical? In search of an answer to these questions, Bruce takes a deep dive into what he believes is the correct way to apply “Popper’s ratchet” to metaphysical or philosophical theories. Along the way, Bruce puts forward a generalization of testability he calls “checkability” and explains why “vague-maning” our theories is “worse than dogmatism.”…

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Episode 92: Popper on Philosophical Theories 1:55:50

рік тому1:55:50

1:55:50

Continuing from episode 91, we continue our deep dive into Popper's Conjectures and Refutations Chapter 8 where Popper explains how to use his epistemology on philosophical theories that (by definition) can't be 'refuted'. Despite agreeing with most of Popper's specific arguments, we offer some considerable criticisms to Popper's approach to criticizing philosophical theories -- particularly to Popper's criticisms of the theory of Determinism which is a 'best theory' by any fair standard but Popper (incorrectly) thought was false. Bruce argues that Popper's approach in C&R Ch. 8 is problematic because it opens the 'Crit Rat Loophole', which is a common way CritRats interpret Popper that allows any preferred theory to be declare a 'best theory' based on the scantest of criticisms. Bruce argues that Chapter 8 of C&R fails in this important regard because it doesn't give a good answer to the question "How does one tell the difference between a good philosophical explanation and a bad explanation?"…

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Episode 91: The Critical Rationalist Case For Induction!? 1:45:46

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1:45:46

Forgive the clickbait title. The episode should probably actually be called "The (Lack of) Problem of Induction" because we primarily cover Popper's refutation of induction in C&R Chapter 8. This episode starts our deep dive into answering the question "What is the difference between a good philosophical explanation and a bad explanation?" To answer that question we go over Karl Popper's "On the Status of Science and of Metaphysics" from his book Conjectures and Refutations Chapter 8. In this chapter Popper first explains why he believes 'there is no such thing as induction' (from page 18 of Logic of Scientific Discovery) by offering his historical and logical refutation of induction. In this episode we go over Popper's refutation of induction in chapter 8 of C&R in detail and then compare it to Tom Mitchell's (of Machine Learning fame) argument of the 'futility of bias free learning.' We show that Mitchell's and Popper's arguments are actually the same argument even though Mitchell argues for the existence of a kind of induction as used in machine learning. Bruce argues that the difference is not a conceptual or theoretical difference but just a difference in use of language and that the two men are actually conceptually fully in agreement. This makes machine learning both a kind of 'induction' (though not the kind Popper refuted) and also gives machine learning an interesting and often missed relationship with critical rationalism. Then Bruce asks the most difficult question of all: "Is there anyone out there in the world other than me that is interested in exploring how to apply Karl Popper's epistemology to machine learning like this?" You can find a copy of Mitchell's text here if you want to check out his argument for the futility of bias free learning for yourself. As I mention in the podcast, I'm shocked Critical Rationalists aren't referencing Mitchell's argument constantly because it is so strongly critical rationalist in nature. But the whole textbook is just like this.…

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Episode 90: Bayesianism for Critical Rationalists!? 2:55:47

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2:55:47

Today our guest Ivan Phillips methodically explains what Bayesianism is and is not. Along the way we discuss the validity of critiques made by critical rationalists of the worldview that is derived from Thomas Bayes’s 1763 theorem. Ivan is a Bayesian that is very familiar with Karl Popper's writings and even admires Popper's epistemology. Ivan makes his case that Bayesian epistemology is the correct way to reason and that Karl Popper misunderstood some aspects of how to properly apply probability theory to reasoning and inference. (Due in part to those theories being less well developed back in Popper's time.) This is a video podcast if you watch it on Spotify. But it should be consumable as just audio. But I found Ivan's slides quite useful. This is by far the best explanations for Bayesianism that I've ever seen and it does a great job of situating it in a way that makes sense to a critical rationalist like myself. But it still didn't convince me to be a Bayesian. ;)…

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Episode 89: Tradition as a Source of Knowledge: Popper vs. Chesterton 1:26:19

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