American theoretical physicist
Dr. Leroy Hood and Dr. Nathan Price, with over a century of combined experience in the industry, have written a book titled The Age of Scientific Wellness: Why the Future of Medicine is Personalized, Predictive, Data Rich, and in Your Hands. The book explores cutting-edge technology that can help people live longer, healthier lives regardless of age. In today's interview, they discuss the role of AI in improving human lifespan, immunotherapy, NMN, gene editing, Alzheimer's, and other related topics. No 'stupid question' of James' goes unanswered!They also share insights about their personal experiences, including stories about Dr. Hood's one-on-one experience as a graduate student of Richard Feynman while Feynman was compiling his classic 3-volume Lectures on Physics. The Age of Scientific Wellness is an excellent resource for readers interested in learning more about modern medicine.------------What do YOU think of the show? Head to JamesAltucherShow.com/listeners and fill out a short survey that will help us better tailor the podcast to our audience!Are you interested in getting direct answers from James about your question on a podcast? Go to JamesAltucherShow.com/AskAltucher and send in your questions to be answered on the air!------------Visit Notepd.com to read our idea lists & sign up to create your own!My new book Skip the Line is out! Make sure you get a copy wherever books are sold!Join the You Should Run for President 2.0 Facebook Group, where we discuss why you should run for President.I write about all my podcasts! Check out the full post and learn what I learned at jamesaltucher.com/podcast.------------Thank you so much for listening! If you like this episode, please rate, review, and subscribe to “The James Altucher Show” wherever you get your podcasts: Apple PodcastsStitcheriHeart RadioSpotifyFollow me on Social Media:YouTubeTwitterFacebook
Here we discuss the inherent differences between classical and quantum physics. Systems representing both can exhibit "unpredictable" behaviour - so what is the difference? In classical physics chaos theory is a genuine phenomena - but only in theory. The real world does not obey classical physics. It obeys quantum theory and there, that kind of "chaos" simply does not happen. The Butterfly effect is therefore false in reality for reasons explained herein. Those classical effects cause classical systems to be unpredictable due to the sensitivity of systems to initial conditions which cannot be specified, or known, with perfect precision. But quantum systems can be "intractable" making them unpredictable for different reasons. Rather than being a barrier to knowledge and computation this is an opportunity. We discuss Feynman and then Deutsch's own contribution to the field of quantum computation.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Learning How to Learn (And 20+ Studies), published by maxa on February 26, 2023 on LessWrong. I have been interested in cognitive science and effective learning methods for years. I've read multiple books and articles and put many ideas to test. In this post, I aim to synthesize my notes and provide references to scientific studies. Summary (TL;DR) Effective Learning Strategies Distributed learning. Study less in each session but more frequently. Active recall. Actively test your knowledge and skills. Distributed recall. Space the tests in time and adjust the intervals based on performance. Interleaving. Practice multiple related yet different skills/concepts simultaneously. Elaborative interrogation (quiz-and-recall). Ask yourself questions and use the material you've learned to answer them. Self-explanation and the Feynman technique. Explain what you've just learned in simple terms. Physiology and Brain's Health Sleep Exercise Nutrition Disclaimer and Introduction I have no formal background in cognitive science or neuroscience, and this has been more of a side interest. My understanding is limited, and I still need to learn how to effectively and consistently apply all these ideas to practice. That being said, I found some of the methods described in this article very useful. For example, I've used them to learn foreign languages, the basics of programming, and various disciplines covered during the two-year MBA program. Effective Learning Strategies Strategy #1: Distributed (Spaced) Learning Practice In short, it's better to distribute one's practice over a period of time than cram it into one day. In one study, elementary school students were asked to study in one of the three ways: massed, clumped, and spaced. Massed = four lessons at a time Clumped = two lessons on one day and two lessons on the next day Spaced = one lesson per day for four days The “spaced” group performed best, followed by the “clumped” group: Another study compared comprehension scores under three different conditions: Read a text once (“single”) Read a text twice (“massed”) Read a text twice with a week-long gap (“distributed”) When tested immediately, the second group performed best. But when tested with a delay of two days, the third group performed best. This method is also superior for learning motor skills. How to apply this in practice: Create a learning schedule or find time to practice a little bit every day or every few days instead of cramming all your learning into one or just a few days. If you'd like to learn more, read the Wikipedia article on distributed practice. Strategy #2: Active Recall (Retrieval) Practice It might be more effective to actively retrieve the information you've already learned than passively re-read or try to learn it once again. One study that compared a method that emphasized study sessions with a method that emphasized tests and found the latter to be more effective for delayed recall. SSSS = four study sessions SSST = three study sessions, followed by one test STTT = one study session, followed by three tests Even imagining that you might be tested on the material you're learning might help improve the recall. How to apply this in practice: If a few days ago you learned how past tense works in the Spanish language, try to remember the rules or even test yourself on your knowledge — instead of simply re-reading the same material once again. You can read more about the active recall practice on Wikipedia. Strategy #3: Distributed (Spaced) Recall Practice Distributed recall practice is basically a combination of the two ideas above. You test yourself frequently and modify the test intervals depending on how familiar you're with the material or how strong your skill is. How to apply this in practice: Many apps simplify the process by tracking one's perfor...
Alexander Unzicker is a theoretical physicist, historian, and author whose award-winning work focuses on the great unanswered questions of physics. He's also the host of Unzicker's Real Physics ( @TheMachian ) where he explores the path forward after a century of particle madness. We talk variable speed of light, the veil of differential geometry, why unification is so difficult, the bright line between mathematics and reality, and much, much more. Support the channel and Dr. Unzicker by buying one of his books: https://amzn.to/3KfcMbL Support the scientific revolution by joining our Patreon: https://bit.ly/3lcAasB Check out our @MaterialAtomics animation of Spin 1/2: https://youtu.be/CWjGO8sukpA Let us know what you think in the comments or on our Discord: https://discord.gg/MJzKT8CQub (00:00:00) Go! (00:05:03) Variable Speed of Light (00:18:27) Einstein, Eddington & Differential Geometry (00:26:41) Refraction (00:41:28) Vacuum Energy & the Mathematical Universe (00:50:47) Size of the Universe (00:59:54) Einstein & Feynman (01:08:56) Simplification & Intuition (01:18:08) Renormalization (01:28:25) The Big Picture (01:34:59) Unification and the Large Number Hypothesis (01:50:15) Unsolved Problems (01:56:44) Incompleteness & Boundary Conditions (02:04:21) Quaternions & the Gods of Modernity (02:10:54) Closing Thoughts #physics #atomic #quantum Check our short-films channel, @DemystifySci: https://www.youtube.com/c/DemystifyingScience AND our material science investigations of atomics, @MaterialAtomics https://www.youtube.com/@MaterialAtomics Join our mailing list https://bit.ly/3v3kz2S PODCAST INFO: Anastasia completed her PhD studying bioelectricity at Columbia University. When not talking to brilliant people or making movies, she spends her time painting, reading, and guiding backcountry excursions. Michael Shilo also did his PhD at Columbia studying the elastic properties of molecular water. When he's not in the film studio, he's exploring sound in music. They are both freelance professors at various universities. - Blog: http://DemystifySci.com/blog - RSS: https://anchor.fm/s/2be66934/podcast/rss - Donate: https://bit.ly/3wkPqaD - Swag: https://bit.ly/2PXdC2y SOCIAL: - Discord: https://discord.gg/MJzKT8CQub - Facebook: https://www.facebook.com/groups/DemystifySci - Instagram: https://www.instagram.com/DemystifySci/ - Twitter: https://twitter.com/DemystifySci MUSIC: -Shilo Delay: https://g.co/kgs/oty671
Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Does Stephen play any musical instrumentals? Would you consider songs formal systems? I've been imagining a multi-way graph for all of the chords on a guitar. - How do you think the behavior of innovation changes with scale? That is, what's the difference in innovation between startups, small businesses, and enterprises? - Do you have electronic-off day/time-window (no electronic communication and no computers etc)? - How do you deal with back pain or eye strain from reading too much? - If you started your business again, what would you avoid or do differently? - As we are eliminating jobs at light speed, how do you think society will cope with mass unemployment after we can automate majority of trade related jobs? - How did you manage the sales side when you started that first company? - If you were to go back in time, would you be able to get the world to 2020 tech within 20 years? - But what happens in the future when we have AIs that can simulate realities that are indistinguishable from reality? What if you can simulate people doing jobs? - Does Stephen Wolfram think that people should specialize in education earlier, instead of taking general classes in high school, focus on one field, get to undergrad level of education earlier? - Didn't Feynman study Mayan Hieroglyphs? - Can an old dog learn new tricks? (i.e. can a middle aged person learn math, programing, and be successful anywhere near someone that started when they were young.) - What innovations, if any, do you think may be most useful for K-12 public education in the US?
Episode: 2838 The World of Small Dimensions; Nano-Dimensions and Pico-Times. Today, we explore Small.
KARMASUTRA : Nouvelle édition du livre best-seller disponible partout en France ! ► https://bysteve.net/karmasutraRichard Feynman est l'un des physiciens théoriciens les plus influents de l'histoire moderne. Prix Nobel de physique, il avait le pouvoir de transmettre ses connaissances aux autres d'une manière compréhensible. En fait, Richard Feynman était surnommé « le grand vulgarisateur » et, pour le reste du monde en dehors de la science, sa méthode d'apprentissage simple, la technique de Feynman, est peut-être sa plus grande contribution à la société.La technique de Feynman vous permet non seulement d'identifier les points faibles du concept que vous essayez d'apprendre, mais elle vous offre également un moyen rapide et efficace de remédier à ces problèmes grâce à un apprentissage ciblé. Il s'agit d'une technique simple, mais qui vous aidera à étudier beaucoup plus efficacement une fois mise en pratique.Mais comment l'utiliser concrètement ? Nous allons vous l'expliquer dans ce podcast !
Nearly none of the plastic we use gets recycled. Even the plastic we throw into the recycling bin often ends up in landfills since it's just not economical to recycle the plastic, especially now that China has banned imports of American plastic waste. So what are we going to do with the vast oceans of plastic we love to use? Shelly Zhang has an idea. As you'll hear in this episode, the death of Shelly's father led to the birth of her company, Molten Materials. Armed with her PhD in engineering, Shelly has pioneered a method of taking plastic waste and upcycling it into pavement sealers, asphalt rejuvenators, and more. In other words, she's betting that she can take our trash and turn it into her treasure, all while solving the pressing problem of what to do with all our plastic waste. Already, Shelly's earned seed investment, hired a dozen team members, filed for various patents, and is now readying her first-ever product, an upcycled-plastic DIY pavement sealer you can use on your own driveway or other cracked surfaces. Her story is an inspirational one, moving to the US from China, earning her PhD, and now founding her own company. I think you'll be impressed, so let me allow Shelly to tell you her story herself. Discussed in this episode Shelly recommends Shoe Dog by Phil Knight Surely You're Joking, Mr. Feynman, by Richard Feynman Our past episode on nuclear waste with Deep Isolation CEO Elizabeth Muller More about Shelly Zhang Shelly Zhang earned her PhD from California Institute of Technology (Caltech). In 2020 Shelly founded Molten Materials, her vision is to create a clean and sustainable world for future generations by replacing big oil. She believes that through technological innovation, it is achievable to solve the toughest problems our world faces."
In this episode we talk about the Feynman learning technique, and some learning opertunities. We also touch on Learning Management Systems. If you want to reach out to us you can do so at: Email: LandD101podcast@gmail.com Instagram: learning_and_development_101 LinkedIn: Joseph Carse Patreon: patreon.com/learninganddevelopment101
Nous sommes tous noyés sous les informations, alors c'est difficile au quotidien de s'y retrouver quand on cherche quoi que ce soit. Google c'est sympa mais ça ne permet pas toujours de filtrer efficacement. C'est là qu'intervient le filtre de Feynman.
The Field Guide to Particle Physics
The Reason for Antiparticles.The Field Guide to Particle Physics : Season 3. Episode 8.https://pasayten.org/the-field-guide-to-particle-physics©2022 The Pasayten Institute cc by-sa-4.0The eBookThe Field Guide to Particle Physics eBook is now available! If you're looking to support the show, we've got some fun options for you here, or you could buy us a coffee!ReferencesThe definitive resource for all data in particle physics is the Particle Data Group: https://pdg.lbl.gov. This episode also pays tribute to Richard Feynman's 1986 Memorial Dirac Lecture.Terrell-Penrose rotation can be viewed from a human perspective in at "A Slower Speed of Light" by MIT's GameLab. That demo also includes the relativistic doppler effect. Some other great videos by Ute Kraus and Corvin Zahn at spacetimetravel.org. See in particular their dice demo.The Reason for Antiparticles.Antimatter is uncommon, but it's not exactly rare. Antiparticles - especially those generated by cosmic radiation - are all around us, all the time. But just what is it doing here?Antimatter is just like MatterIn a lot of ways, antimatter behaves just like matter does. Quarks make up protons? Antiquarks make up antiprotons… and antineutrons, too!Antiprotons and antielectrons - that is, positrons - combine to form antihydrogen atoms.The Antihydrogen Laser PHysics Apparatus - the ALPHA Experiment at CERN - studies the spectroscopic properties of antihydrogen. That is, it uses photons to give a little extra energy boost to those positrons. As those positrons relax to their ground state, they emit distinct wavelengths of light.Just like regular hydrogen atoms.Photons, you see, are their own antiparticles. They interact with matter and antimatter in precisely the same way.If there were any difference between hydrogen and antihydrogen - any difference in mass, spin or the magnitude of their electric charge - those wavelengths of emitted light would also be different. And the ALPHA experiment would be able to detect those differences.But no such differences have been observed.So again, what exactly is antimatter doing here in our physical reality?Antimatter annihilates MatterThe one thing antimatter does *not* do is hang around.Antimatter annihilates with ordinary matter. Electrons and positrons annihilate to form a pair of gamma rays, a pair of photons.If the universe were balanced between matter and antimatter, we wouldn't be here. Or… perhaps worse… we'd rapidly disintegrate into a bursts of gamma radiation as our particles and those antiparticle partners annihilated.So if antimatter is so uncommon - why is it even here? What is the point, the reason for antimatter? Why does the universe need antimatter?To understand that, we need to talk about time travel.The Light ConeOur reality has four dimensions. Three space and one time. Famously, Einstein's special theory of relativity tell us that these four dimensions are related.That relationship is nature's conspiracy to make sure that nothing travels faster than the speed of light.One way to think about how this works is time travel. Literally traveling through time. When we are still, we are traveling forward, through time. When we spring up to go for a run, we're still traveling through time, but we *rotate* our perceived motion through time into space. This is a four-dimensional sort of rotation. Sometimes this is called a Terrell rotation. There are some stunning visualizations of Terrell rotation linked in the show notes.The amount of Terrell rotation varies without speed. In a sense, we exchange some of our speed in the time direction to travel through space. The faster we go through space, the slower we go through time. There is a limit to this kind of rotation. We cannot rotate our motion so deep into space that we travel backwards in time. The most we can do is cause time to stand almost still, which happens when we travel just shy of the speed of light.Light of course always and only travels at the speed of light, in the absence of matter anyway. And because everything that must travel slower than light - everything that has mass - like protons, electrons, atoms and US - is subject to the ultimate cosmic constraint: the light cone.To visualize this four-dimensional cone, think of a camera flash. It's a sphere of light moving outwards from a point. The tip of the cone is us snapping the photo, and the vertical part of the cone corresponds to the dimension of time.At any moment, our reality can be cut into two regions: inside or outside the light cone. All those points that light can touch - and those that it can't. Inside the light cone represents everything we can possibly hope to effect later in time. Outside the light cone is outside of our agency to do so.The light cone - in other words - represents the boundary of causality.Because we cannot travel faster than the speed of light, any Terrell rotation we experience inside our light cone retains a positive flow of time - however slow.But outside the light cone, that same rotation can cause our perception of time to reverse. Outside our light cone, if we are traveling fast enough, we can perceive time as flowing backwards.It's a fun thought exercise to figure out how we might perceive an event outside our own light cone - I'll leave that one for you to figure out - but here's a hint: “wait and see”.If you're curious, check out our instagram account in the coming days for the answer.Time flowing backwards might seem terrible for cause an effect. It would literally reverse the two! But time flowing backwards outside our light cone - outside our sphere of influence - has no bearing on our physical reality. As long as our causal influence is restricted to inside the light cone, the observable universe makes sense.Now let's tie this back to particle physics. You'd see, the relationship between the world inside and outside the light cone is intimately related to the relationship between matter and antimatter.The Feynman-Stückelberg Interpretation of Negative EnergiesThe celebrated Dirac equation - the mathematics which describes particles likethe electron - suggests that positrons are just electrons with negative energy. But what is negative energy? This interpretation was confusing for quite some time.But energy you see is intimately related to time. As time is to space, energy is to motion through space. Energy, in other words, can be thought of as motion through time.So an antiparticle with negative energy can be thought of as a particle with positive energy moving backwards though time.In his 1986 lecture commemorating Dirac, Feynman - who is credited with formalizing this interpretation - gave a concise, technical and frankly satisfying explanation for this phenomena.It went something like this:Quantum Theory also predicts that particles tend to smear out like a wave. In atoms, electrons smear out to form standing waves, which we call electron orbitals. In modern language, we say that these waves are really probability distributions for a particles position and momentum.Left to their own devices, quantum mechanics tells us that these probability distributions spread out in space.For example, when an alpha particle's smeared probability distribution spreads outside the nucleus, there is a nonzero chance that it will tunnel through, and escape as radiation: alpha radiation.So you might ask. Can the probability distribution of an electron spread outside the light cone?Unfortunately, the answer is yes.And if you've studied quantum mechanics, this is probably no surprise. The path integral formulation requires us to consider every conceivable motion of the electron - including those moving faster than the speed of light.So it might seem that Quantum Mechanics and Einstein's theory of special relativity are fundamentally incompatible. If true, this would be a huge problem. Anything moving faster than the speed of light - even by means of quantum mechanics - could mess with our notion of cause and effect. Causality is central to our ability to perform experiments - to make sense of our physical world.And yet. Quantum Mechanics is compatible with relativity.You see, the smeared probability distribution for the positron can also leak through the light cone.Taken together, fortunately, the probability amplitudes for particle and antiparticles to be outside the light cone cancel each other out exactly. Why exactly? Because matter and matter are identical - at least up to that overall minus sign.It's just that what we call reality - sometimes - occasionally splits into particle / antiparticle pairs - or not - depending on how fast we're moving.In short. The reason for antiparticles is causality. The Alpha Experiment, RevistedThis is a simplification, to be sure. There are plenty of details to discuss about so-called virtual particles, parity and particle-antiparticle annihilation. Perhaps another time.If you're interested in more of the details, a good place to start looking would be Feynman's 1986 Dirac Lecture at Cambridge, linked in the show notes.With any mature scientific theory, there are nuances and details that are exciting to explore. We'll see more soon enough. But for now, let's just say that the ALPHA experiment - that experiment at CERN looking for differences between Hydrogen and AntiHydrogen - has searched for violations in causality - that is, violations to the CPT theorem - and has excluded them at the level of 200 parts per trillion.The Pasayten Institute is on a mission to build and share physics knowledge, without barriers! Get in touch.
Hello Interactors,Last week we explored the role naturalists brought to a more open, flexible, and pragmatic approach to the Enlightenment. Today we expand on how our dominant economic ideology remains beholden to dogmatic, sterile, and abstract mathematical models the naturalists were trying to shake. One of the more popular figures in popularizing and perpetuating this pernicious economic perspective was Britain's Prime Minister, Margaret Thatcher. As interactors, you're special individuals self-selected to be a part of an evolutionary journey. You're also members of an attentive community so I welcome your participation.Please leave your comments below or email me directly.Now let's go…Thank you for reading Interplace. This post is public so feel free to share it.THE TINA SCHEMAAs British Prime Minister Margaret Thatcher was gaining traction with her hardline policies many of her conservative colleagues thought she was too harsh. In response she began calling them ‘wets' which in Britain meant ‘inept, ineffectual, and effete'. She was famously proud of her resolute, often binary, moral convictions. In response to the economic disarray Britain was facing as she came to power, she said these words in a speech at a conservative women's conference in 1980,“There's no easy popularity in what we are proposing but it is fundamentally sound. Yet I believe people accept there's no real alternative…What's the alternative? To go on as we were before? All that leads to is higher spending. And that means more taxes, more borrowing, higher interest rates more inflation, more unemployment."The phrase “there is no alternative” became a refrain for Thatcher. It was used so often it prompted one the ‘wets', Norman St John-Stevas, to abbreviate it forming a retaliatory derogatory name for Thatcher – TINA. He, and other ‘wets', took to calling her ‘Tina'. He later wrote in a book that Thatcher saw "everything in black and white [but] the universe I inhabit is made up of many shades of grey".I suspect Thatcher was confident in her resoluteness because the neoclassical economists she relied on, both in the UK and the US, were themselves certain there was no alternative. Their confidence was, and still is, buoyed by the certainty that can come with the mathematics behind their economic models. But that certainty can be an illusion that can lead to delusion.Education researcher, Don Ambrose, says it can start early in math education and over time this “dogmatic thinking can trap professionals, policymakers, and others into perceiving only the sterile certainty of the surface of mathematics while remaining oblivious to its messy, creative inner workings.”He continues, “While mathematics provides us with a considerable amount of analytic precision it still is at least somewhat susceptible to the vagaries of the human mind and open to impressive creativity.” He quotes the prominent economist Thomas Piketty who in his 2014 book, Capital in the Twenty-First Century, saying,“For far too long economists have sought to define themselves in terms of their supposedly scientific methods. In fact, those methods rely on an immoderate use of mathematical models, which are frequently no more than an excuse for occupying the terrain and masking the vacuity of the content.”He says it can create a ‘scientific illusion' that ignores the messy realities that, again, Adam Smith viewed as essential to a healthy economy; a shared cultural understanding, a socially just labor market, and a trustworthy government.But even some mathematicians agree mathematics can lead one astray. The mathematician William Byers, who researches dynamical systems and the philosophy of mathematics, writes,“What we usually call mathematics—results, proofs, and structure—is the unambiguous face of the subject…[But] looking at mathematics as a human activity, as mind-dependent, forces one to confront the ambiguous dimension of math.”These are the very ‘shades of grey' the ‘wet' set Tory's unsuccessfully settled with Margaret ‘Tina' Thatcher. And the man Thatcher liked to blame for the economic mess she inherited was someone who would have agreed with the uncertainty these ‘wets' were pointing to – Britain's most famous 20th century economist, John Maynard Keynes.Keynes made a name for himself in the 1930s devising economic policies that proved to ease the effects of the depression that had wracked the world. His ideas were counter to neoclassical ideas, and those later championed by Thatcher. He believed, like Adam Smith, that markets should include some governmental intervention to minimize the adverse effects of recessions and depressions.Every capitalistic government in the world had instituted his policies until the 1950s, soon after he passed away. From that point until now, the neoclassical ideology of America's most famous 20th century economist, Milton Friedman, reigns supreme. A philosophy that promotes free-wheeling, free-trade, and free markets that are free of government restraint, and are backed by rigid and sterile mathematical and statistical models.Keynes was no stranger to mathematics; he was awarded a scholarship to study it at Cambridge. But he did believe that it was being dogmatized, misused, and misconstrued to bolster the legitimacy of economics by wrapping it in perceived certainty, logic, and accuracy. So much so, it led people to believe there is no alternative.In Keynes's 1936 groundbreaking book The General Theory of Employment, Interest and Money, he asserts this as his criticism of neoclassical economics.“our criticism of the accepted classical theory of economics has consisted not so much in finding logical flaws in its analysis as in pointing out that its tacit assumptions are seldom or never satisfied, with the result that it cannot solve the economic problems of the actual world.THE NEWTONIAN BABYLONIANKeynes's General Theory was to generalize existing neoclassical theories and methods. In other words, marry the ‘shades of grey' of the real world with existing mathematical methods and analysis. He was particularly focused, as much economic work is, on being able to predict economic outcomes in the future. A future that is uncertain. And with that, Keynes called for “at least a partial attempt to incorporate the fact of uncertainty into an economic theory.”He believed this required an approach that embraced the uncertainties of the real world as clues or observed evidence that could then be scrutinized with analysis, reason, and mathematics. One person he believed personified this approach was a man he idled, Isaac Newton. His thoughts were captured in a lecture he wrote to celebrate the life of Isaac Newton in 1946 but was unable to deliver. He died three months before the event.He wrote, “Newton was not the first of the age of reason. He was the last of the magicians, the last of the Babylonians and Sumerians…Why do I call him a magician? Because he looked on the whole universe and all that is in it as a riddle, as a secret which could be read by applying pure thought to certain evidence, certain mystic clues which God had laid about the world to allow a sort of philosopher's treasure hunt...”Some scholars have latched onto Keynes use of the word ‘Babylonians'. This term is associated with an ongoing controversy in academia about two logical approaches to the social sciences. Finance, economics, and philosophy professor, Mark Stoh, characterizes it like this: “There are two basic approaches. The first, the Cartesian-Euclidian approach, is ‘the familiar axiomatic one in which the fundamental principles of a science are taken as axioms, from which the rest are derived as theorems.' Because it comes closest of all the social sciences to attaining this axiomatic ideal, economics has occasionally been considered to be the queen of the social sciences. The second approach is the Babylonian. According to it, there is no single logical chain from axioms to theorems; but there are several parallel, intertwined, and mutually reinforcing sets of chains, such that no particular axiom is logically basic.”In this context, Keynes views on uncertainty fall more in line with the Babylonians. Further, Keynes characterizes Newton as using methods of inquiry that date back to the ancient times of the Babylonians. Because the mathematics and economics of Babylonian times were captured in stone and since translated, we know a great deal about how they solved mundane and complex problems. Many scholars believe they used pragmatic problem solving that embraced uncertainty and holistic approaches of various mathematical constructs.Another famous great mind of the 20th century concurs, the renowned physicist Richard Feynman. In a 1965 lecture he talks about the distinction between what he called ‘Babylonian' and ‘Greek' approaches to mathematical problem solving. He asserts students learning math in these times were taught different techniques for calculating various mathematical problems. They were then given practical problems whereby they had to determine which techniques were to be linked in a chain to solve a particular problem.Feynman describes it as a constellation of techniques that could be linked together in a variety of ways to arrive at an answer. For example, the equivalent of the Pythagorean theorem could be linked to calculating the volume of a cube. It was a holistic approach to pragmatic problem solving given the context of the situation at hand, even if the situation were to change.What Descartes came along and did was reduce the common elements of these constellations to form a set of ordered axioms. Mathematics was then taught from the bottom up as ordered steps, each layer of the constellation building on itself to form theorems. Mathematical problem solving was then taught as ordered and deterministic with no regard for how one might leap from one technique to another should the conditions of the problem set change.Feynman says, “the method of starting from [the bottom] axioms is not efficient in obtaining the theorems…Working something out in geometry is not very efficient if you always have to start at the axioms, but if you had to remember a few things in [the constellation] of geometry you can always get somewhere else [in the constellation] which is much more efficient than if you do it the other way.”Feynman believed solving problems in physics requires a Babylonian approach due to the changing nature of the natural physical world. This is in contrast with pure mathematics, as derived by Descartes and Euclid, that yields universally consistent solutions within the context of an abstracted world.OPEN TO ALTERNATIVE SYSTEMSIn the context of economics, British economist Sheila Dow offers that in a constellation of economic mathematical tools “One chain of reasoning might rely on statistical analysis, while another might rely on historical research, for example.” Dow is a Post-Keynesian economist who expands on the work of Stoh and Feynman in her paper on the “Babylonian Mode of Thought”.Dow expresses ‘Mode of thought' as “the way in which arguments (or theories) are constructed and presented, how we attempt to convince others of the validity or truth of our arguments.” Her interpretation of Keynes reflection on Newton was that he “relied on intuition in order to arrive at explanations for natural phenomena, on the one hand, with the rational proofs he constructed after the fact, on the other.” This was his ‘mode of thought', she argues, that enabled him to make the discoveries he did. And like Feynman, she implores others to learn and apply this more ‘Babylonian' approach to solving complex problems. That is, a pragmatic and wholistic approach through the practical application of an array of mathematical methods which are traversed over time as situations, contexts, and variables change.Dow equates the Babylonian approach with an open system – a system of infinite unknown variables that change in relation and response to each other, and the environment in which they exist, over time. This is contrast to a closed system where all the variables, their interactions, and relationships are known and isolated in the environment in which they exist. Closed systems are divided into dual atomic parts, the internal, or endogenous, and the external, or exogenous.Dow believes, “Babylonian thought is neither dualistic nor atomistic. The categories used to account for social life in an evolving environment are not seen as readily falling into duals. Indeed vagueness of categories is seen to have the benefit of adaptability within a changing environment where institutions, understanding and behaviour undergo change. In a system of thought with a variety of incommensurate strands of argument, variables may be exogenous to one strand but endogenous to another. Knowledge is in general held with uncertainty (by economic agents and by economists), so the analysis points to degrees of uncertainty. Further, some strands of argument may refer to individuals, and others to the group level, since causal forces may act in either direction. Indeed individuals are not seen as independent, and their behaviour may change as the environment changes.”She continues, “Similarly, Babylonian thought provides a rationale for pluralism. It justifies both methodological pluralism (methodologists analysing a range of methodologies) and pluralism of method (economists using a range of methods).”Dow then warns that many who subscribe to conventional economic approaches, or Cartesian modes of thought, sometimes claim that ‘pluralism' is just an excuse for sloppiness leading to an ‘anything goes' approach and attitude. But she argues, as Feynman illustrates, that “Babylonian mode of thought requires some criteria by which to choose segmentations of the subject matter for analysis, the chains of reasoning to pursue, and the methods employed to pursue them.” In this regard, not only is there is a high degree of mastery of various methods required, but that their application is highly structured. This leads her to claim Babylonian modes of thought are not ‘pure pluralism', but ‘structured pluralism.' She adds, as did Feynman, this may require not only traversing within the domain of mathematics, economics, or in the case of Feynman, physics, but also into other domains of science and humanities.Sorry ‘Tina', in the pursuit of answers in complex, uncertain, and changing environments it seems alternatives are not only desirable, but necessary. Those alternatives, however, have yet to be pursued despite record income inequality. After Thatcher came John Major who, despite being responsible for a raft of immoral behavior known as ‘Tory sleaze', was part of Britain's longest running economic prosperity. He was replaced in 1997 by the opposition Labour Party candidate Tony Blair. Three years into his term Thatcher was asked what she thought her greatest accomplishment was. She replied, “Tony Blair and New Labour" because he, like U.S. Democratic President Bill Clinton, adopted most of her policies. She said she "forced [her] opponents to change their minds."The irony of the Iron Lady, and all those who cling to the belief there is no economic policy alternative, is that the illusion of certainty represented by neoclassical and Cartesian closed systems has created more social and environmental uncertainty than ever. We live in organic, ever changing open system in uncertain times, in an uncertain world. If ever there's a time for an alternative, it seems it would be now. It's time we change our ‘mode of thought' and convince others that the pragmatic and wholistic Babylonian approach is a viable alternative. Let's turn ‘TINA' into ‘TAMA' – There are many alternatives. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit interplace.io
Sommerfeld Theory Colloquium (ASC)
Feynman integrals are indispensable for precision calculations, not only for high-energy particle physics experiments, but also for example for QED precision experiments at lower energies or precision studies in gravitational wave physics. In recent years there has been a significant progress in our abilities to compute Feynman integrals, revealing a rich and fascinating mathematical structure, relating Feynman integrals to (algebraic) geometry. In this talk I will review these recent developments.
Sommerfeld Theory Colloquium (ASC)
After a short introduction to the swampland program and the challenges one faces in explicit tests of some conjectures, this talk will focus on the computation of periods and their application to the swampland program. A detailed understanding of periods allows to answer questions about the existence of solutions or the finiteness of the string landscape, as well as explicit constructions of models. Moreover, applications of periods outside of string compactifications are discussed, such as the computation of Feynman integrals, the tameness of QFTs and the appearance of periods in many other physical systems.
This is how I remember everything I read, watch, or study to acquire high profit skills, interests, and traits. This is a key component of creative work, solopreneurship, or in the one person business model as a creator. The Feynman technique is great for learning, but what if I told you that you can turn your LIFE into a way to retain more knowledge. I hope this helps. Video I referenced on the Fill Empty Use framework: https://youtu.be/qdXFeyzq7HE This podcast was originally a YouTube video, you can watch that video here: YouTube version: https://youtu.be/2L0TjTIHEFo The Koe Letter (written version): https://thedankoe.com/how-i-remember-everything-i-learn/ If you enjoyed this episode, consider leaving a rating. It truly helps. Thank you again for listening. Writing & Content Course: https://2hourwriter.com Business Strategy Library & Private Community (Join For $5): https://modernmastery.co/podcast 10X Your Creative Output (free): https://7daystogeniusideas.com The Power Planner (free): https://shop.thedankoe.com/planner Enroll In The Next Digital Economics Cohort: https://digitaleconomics.school Twitter: https://twitter.com/thedankoe Instagram: https://instagram.com/thedankoe YouTube: https://youtube.com/c/DanKoeTalks LinkedIn: https://linkedin.com/in/thedankoe
Le monde d'aujourd'hui est de plus en plus complexe. L'apprentissage ne s'arrête pas à l'école, ni à l'université : nous avons besoin d'apprendre tout au long de notre vie. Pour cette raison, connaître et utiliser la bonne stratégie pour apprendre vite et bien est un vrai avantage pour notre carrière. L'objectif de Stephen Bluementhal à travers son livre « Apprentissage accéléré » est de partager une méthode qui permet de simplifier et rendre plus efficace tout le processus d'apprentissage. Dans cette vidéo, je vais vous présenter 3 aspects centraux : 1. la lecture rapide : nous passons beaucoup de temps à lire des nouvelles informations, développer notre capacité de lecture est donc une compétence très utile. La lecture rapide ne permet pas uniquement de lire vite, mais surtout de mieux comprendre et mieux retenir le contenu de ce que l'on a lu. Avec quelques astuces, il est possible de multiplier par trois sa vitesse de lecture. 2. l'amélioration de la mémoire : la mémoire est le processus qui nous permet de stocker et ensuite de nous rappeler des informations et des expériences que nous rencontrons chaque jour. C'est un aspect central de l'apprentissage accéléré. Adoptez des habitudes de vie saine, favorisez votre concentration, impliquez tous vos sens dans l'apprentissage et entraînez régulièrement votre cerveau. Cela vous permettra d'améliorer significativement vos capacités de mémorisation. 3. la méthode Feynman : c'est la méthode pédagogique d'un physicien américain qui a gagné un prix Nobel. Elle permet d'améliorer significativement son efficacité d'apprentissage. Elle se base sur 4 étapes essentielles : listez tout ce que vous connaissez sur un concept, simulez d'enseigner ce concept à une autre personne, analyser à nouveau vos sources pour tout ce qui n'est pas claire, expliquez ce que vous avez appris en utilisant vos propres mots. Quelles sont actuellement vos plus grandes difficultés pour apprendre des nouvelles choses ? Comment vous vous prenez pour améliorer votre apprentissage ? N'hésitez pas à partager votre expérience : laissez un commentaire ci-dessous. Ressources disponibles Soutenez Mind Parachutes et téléchargez l'audio de cette vidéo : http://www.tipeee.com/mind-parachutes Mind carte (l'image de synthèse à la fin de la vidéo) : http://mindparachutes.com/mindcartes Livre sur amazon : https://amzn.to/2lwYLth #devperso, #developpementpersonnel, #apprendre, #apprendrevite, #apprentissage --- Send in a voice message: https://anchor.fm/mindparachutes/message
Owner Occupied with Peter Lohmann
Special Episode of the Owner Occupied podcast with Peter Lohmann & special guest Jon Matzner. In this episode we discuss: (00:00) - Intro (01:47) - Jon's background and career (03:17) - How are you utilizing Notion in your work? (06:06) - Expanding the Garage Upgrade business (11:09) - The 3 parts of value for people entering the world of Property Management (22:44) - When starting or buying a PM company, what is something that people think is important, that your experience tells you people can skip entirely? (25:31) - What's something you're doing every day now that you wish you had started earlier in your journey? (28:55) - What channels have led you to building your highest-quality relationships? (33:36) - What's something you did radically different from your industry peers that ultimately paid off? (37:34) - What's the biggest struggle you're facing right now? (40:41) - What's something you didn't give enough attention to early on that you had to pay for down the road? (43:55) - Where people can go to learn more Learn more about Jon Matzner & how to connect with him here: Jon on Twitter Organized Garage Learn more about Peter Lohmann & how to connect with him here: Follow Peter on Twitter Join Peter's Newsletter Visit Peter's Website RL Property Management Mentioned in this episode: PMbusinessinabox.com Notion Getting Things Done by David Allen Cal Newport Books “Surely You're Joking, Mr. Feynman!” by Richard Feynman Who by Geoff Smart
Mishlei 22:29 - Being Seen as Swift Your Work (Part 2)חָזִיתָ אִישׁ מָהִיר בִּמְלַאכְתּוֹ לִפְנֵי מְלָכִים יִתְיַצָּב בַּל יִתְיַצֵּב לִפְנֵי חֲשֻׁכִּים:Synopsis: This morning (11/1/22), in our morning Mishlei shiur, we continued working on yesterday's pasuk. Although we didn't manage to develop yesterday's approach much further, we did develop three nice ideas, thanks to the meforshim. -----מקורות:משלי כב:כט"Bruce Lee: Artist of Life," p.205שד"ל - ישעיהו טז:הRichard Feynman, "Surely You're Joking, Mr. Feynman!"אבן עזרא כתב ידמאירירביני יונה-----This week's Torah content has been sponsored by my friend and colleague, Rabbi Dr. Elie Feder. Rabbi Feder recently published a book called Gematria Refigured: A New Look at How the Torah Conveys Ideas Through Numbers (2022, Mosaica Press). The approach to gematria he presents in this book is neither fluffy nor fanciful, but rational. If you're interested in some sample chapters, check out the link below. If you have a social media platform and are interested in promoting or reviewing Rabbi Feder's book, let me know and I'll put the two of you in touch. The book is available for purchase at https://mosaicapress.com/product/gematria-refigured/.Link to sample chapters: https://tinyurl.com/3xmrufuv-----If you have questions, comments, or feedback, I would love to hear from you! Please feel free to contact me at rabbischneeweiss at gmail.-----If you've gained from what you've learned here, please consider contributing to my Patreon at www.patreon.com/rabbischneeweiss. Alternatively, if you would like to make a direct contribution to the "Rabbi Schneeweiss Torah Content Fund," my Venmo is @Matt-Schneeweiss, and my Zelle and PayPal are mattschneeweiss at gmail.com. Even a small contribution goes a long way to covering the costs of my podcasts, and will provide me with the financial freedom to produce even more Torah content for you.If you would like to sponsor a day's or a week's worth of content, or if you are interested in enlisting my services as a teacher or tutor, you can reach me at rabbischneeweiss at gmail.com. Thank you to my listeners for listening, thank you to my readers for reading, and thank you to my supporters for supporting my efforts to make Torah ideas available and accessible to everyone.-----Substack: rabbischneeweiss.substack.com/Patreon: patreon.com/rabbischneeweissYouTube Channel: youtube.com/rabbischneeweissBlog: kolhaseridim.blogspot.com/"The Mishlei Podcast": mishlei.buzzsprout.com"The Stoic Jew" Podcast: thestoicjew.buzzsprout.com"Rambam Bekius" Podcast: rambambekius.buzzsprout.com"Machshavah Lab" Podcast: machshavahlab.buzzsprout.com"The Tefilah Podcast": tefilah.buzzsprout.comWhatsApp Group: https://chat.whatsapp.com/GEB1EPIAarsELfHWuI2k0HAmazon Wishlist: amazon.com/hz/wishlist/ls/Y72CSP86S24W?ref_=wl_sharel
Theories of Everything with Curt Jaimungal
YouTube link: https://youtu.be/fU1bs5o3nss This episode has been released early in an ad-free audio version for TOE members at http://theoriesofeverything.org. Sponsors: - Brilliant: https://brilliant.org/TOE for 20% off *New* TOE Website (early access to episodes): https://theoriesofeverything.org/ Patreon: https://patreon.com/curtjaimungal Crypto: https://tinyurl.com/cryptoTOE PayPal: https://tinyurl.com/paypalTOE Twitter: https://twitter.com/TOEwithCurt Discord Invite: https://discord.com/invite/kBcnfNVwqs iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 Pandora: https://pdora.co/33b9lfP Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything LINKS MENTIONED: TIMESTAMPS: 00:00:00 Introduction 00:01:53 The philosophy of physics 00:04:18 Physics without numbers 00:20:20 Truth and mathematics 00:29:08 Pythagoras didn't scorn irrational numbers 00:31:31 Geometry is at the core of reality 00:39:11 Sometimes the data is incorrect (efficiency of detectors) 00:45:02 Bell's theorem, quantum mechanics, non-locality, and realism 00:50:38 Superdeterminism and Retrocausality 01:27:08 Quantum Foundations (five books to become an expert) 01:31:10 "Beables" - What physically exists? 01:33:57 The Mathematical Universe is a confusion 01:38:31 Spatialize time? Or temporalize space? 01:46:37 Against Occam's Razor, Feynman, and Backward Time 01:56:56 Time is not an illusion 02:01:50 Quantum mechanics with observers 02:08:36 Classifying different quantum theories (and thoughts on Penrose) 02:16:25 Overview of Pilot Wave Theory (Bohmian Mechanics) 02:20:18 Philosophy vs. Physics vs. Math 02:28:53 Consciousness is the hardest question 02:32:28 Disproofs of functionalism and computational consciousness 02:37:15 Wolfram 02:38:56 Arrow of time (entropic / thermal time) 02:41:49 Bergson, Einstein, and Bohm 02:44:48 Bell was the sweetest man (personal stories from Tim) 02:50:54 Causation, Pearle, and keeping your mind sharp Learn more about your ad choices. Visit megaphone.fm/adchoices
Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Are there any models that predict how society behaves? - What knowledge helps weather prediction and how? Like pressure, temperature, wind, distances, etc..? - When you (Stephen Wolfram) count in your head, do you count verbally or visually (or another way)? Feynman wrote an interesting story about this in one of his books. - If you write enough errors that cancel each other out perfectly, your code is perfect. - How do we improve our inductions towards producing creative results for science? - Which side of the quarter has better aerodynamics? If a quarter was flipped by a human hand 100,000 times on a windy day, and another 100,000 times on a non windy day, would the overall outcome still be 50/50 heads/tales in both instances? - How can you end up with a different set of rules while describing a system with definite and observable behavior? No matter alien consciousness or not, the rules will remain the same - How do you spell that? ooogleriffousness? - Why can't logic be easier to understand? What I mean is all this academic stuff that teaches logic, it seems all Greek to me. When I try to learn more, I get bored fast because they explain it too complicated.
Eunice Goes é doutorada em ciência Política pela London School of Economics e é há quase 15 anos professora na Richmond University em Londres. As suas principais áreas de investigação são a política britânica e o papel das ideias e das ideologias na política e nas decisões políticas. -> Apoie este projecto e faça parte da comunidade de mecenas do 45 Graus em: 45graus.parafuso.net/apoiar _______________ Índice da conversa: (3:40) O Partido Conservador | O Brexit. | Capitalismo de Renânia | Mont Pelerin Society | Institute of Economic Affairs (20:28) Como compara o P. Conservador com os partidos da direita da Europa continental? | As especificidades do sistema eleitoral britãnico. (29:52) Porque é que o P. Trabalhista não tem conseguido aproveitar? | A imprensa tem um viés de direita? Inquérito Pew Research Center | (41:00) A crise da identidade do P. Trabalhista -- e a relação com a “crise da Social-democracia europeia” | A “red wall” | Ordoliberalismo | Predistribution | (57:43) O papel das ideias na política. Peter Hall (1:04:14) A importância de desenvolver pensamento crítico nos alunos. | Livro: «Está a Brincar, Sr. Feynman!» de Richard P. Feynman Livros recomendados: Capitalism on Edge, de Albena Azmanova; Anti-System Politics, de Jonathan Hopkin; In the Shadow of Justice, de Katrina Forrester _______________ Festival Folio Uma conversa muito oportuna com Eunice Goes, professora de Ciência Política na Richmond University em Londres, sobre as causas mais profundas da instabilidade da política britânica nos últimos anos. Falámos do Partido Conservador, do Partido Trabalhista, do papel da imprensa, da "crise de identidade da Social-democracia europeia e de... pensamento crítico. Há já alguns anos que a política do Reino Unido não sai das notícias -- sobretudo desde o referendo do Brexit em 2016. Desde então, a instabilidade instalou-se na política britânica. O Partido Conservador, que tem governado nos últimos 12 anos, já vai, desde 2016, no 4.º líder -- e, consequentemente, o país no 4º Primeiro Ministro. A última mudança aconteceu há menos de um mês, com a saída de Boris Johnson e a vitória de Liz Truss nas eleições internas de um Partido Conservador muito dividido. Mal tomou posse, a nova Primeira-ministra anunciou um conjunto de medidas arrojadas que têm gerado enormes críticas e uma reacção negativa nos mercados financeiros. Para compreender as origens desta instabilidade que a política do Reino Unido tem vivido, o papel dos dois maiores partidos e as particularidades do sistema político britânico dificilmente poderia encontrar pessoa melhor que a convidada. Nesta conversa, começamos por examinar as causas da instabilidade na política britânica, cujas causas vão desde o Brexit à existência de diferentes facções dentro do PC e mesmo à própria arquitetura do sistema eleitoral, que dificulta a expressão dos restantes partidos. Mas existe, ao mesmo tempo, um mistério grande: com esta instabilidade, e os 12 anos de governo que o Partido Conservador já leva, como é que o Partido Trabalhista não tem conseguido afirmar-se como alternativa? Isto levou-nos a discutir se os trabalhistas são vítimas do viés de direita de que a imprensa britânica é frequentemente acusada. Com ou sem imprensa difícil, a verdade é que o PT vive hoje uma crise de identidade, a qual pode ser enquadrada na crise da social-democracia europeia que abordei recentemente num episódio com Pedro Magalhães. Mesmo no final da conversa, abordámos ainda uma iniciativa inovadora que a convidada tem aplicado nas suas aulas para melhorar a aprendizagem e estimular o pensamento crítico entre os alunos. _______________ Obrigado aos mecenas do podcast: Julie Piccini, Ana Raquel Guimarães Galaró family, José Luís Malaquias, Francisco Hermenegildo, Nuno Costa, Abílio Silva, Salvador Cunha, Bruno Heleno, António llms, Helena Monteiro, BFDC, Pedro Lima Ferreira, Miguel van Uden, João Ribeiro, Nuno e Ana, João Baltazar, Miguel Marques, Corto Lemos, Carlos Martins, Tiago Leite Tomás Costa, Rita Sá Marques, Geoffrey Marcelino, Luis, Maria Pimentel, Rui Amorim, RB, Pedro Frois Costa, Gabriel Sousa, Mário Lourenço, Filipe Bento Caires, Diogo Sampaio Viana, Tiago Taveira, Ricardo Leitão, Pedro B. Ribeiro, João Teixeira, Miguel Bastos, Isabel Moital, Arune Bhuralal, Isabel Oliveira, Ana Teresa Mota, Luís Costa, Francisco Fonseca, João Nelas, Tiago Queiroz, António Padilha, Rita Mateus, Daniel Correia, João Saro João Pereira Amorim, Sérgio Nunes, Telmo Gomes, André Morais, Antonio Loureiro, Beatriz Bagulho, Tiago Stock, Joaquim Manuel Jorge Borges, Gabriel Candal, Joaquim Ribeiro, Fábio Monteiro, João Barbosa, Tiago M Machado, Rita Sousa Pereira, Henrique Pedro, Cloé Leal de Magalhães, Francisco Moura, Rui Antunes7, Joel, Pedro L, João Diamantino, Nuno Lages, João Farinha, Henrique Vieira, André Abrantes, Hélder Moreira, José Losa, João Ferreira, Rui Vilao, Jorge Amorim, João Pereira, Goncalo Murteira Machado Monteiro, Luis Miguel da Silva Barbosa, Bruno Lamas, Carlos Silveira, Maria Francisca Couto, Alexandre Freitas, Afonso Martins, José Proença, Jose Pedroso, Telmo , Francisco Vasconcelos, Duarte , Luis Marques, Joana Margarida Alves Martins, Tiago Parente, Ana Moreira, António Queimadela, David Gil, Daniel Pais, Miguel Jacinto, Luís Santos, Bernardo Pimentel, Gonçalo de Paiva e Pona , Tiago Pedroso, Gonçalo Castro, Inês Inocêncio, Hugo Ramos, Pedro Bravo, António Mendes Silva, paulo matos, Luís Brandão, Tomás Saraiva, Ana Vitória Soares, Mestre88 , Nuno Malvar, Ana Rita Laureano, Manuel Botelho da Silva, Pedro Brito, Wedge, Bruno Amorim Inácio, Manuel Martins, Ana Sousa Amorim, Robertt, Miguel Palhas, Maria Oliveira, Cheila Bhuralal, Filipe Melo, Gil Batista Marinho, Cesar Correia, Salomé Afonso, Diogo Silva, Patrícia Esquível , Inês Patrão, Daniel Almeida, Paulo Ferreira, Macaco Quitado, Pedro Correia, Francisco Santos, Antonio Albuquerque, Renato Mendes, João Barbosa, Margarida Gonçalves, Andrea Grosso, João Pinho , João Crispim, Francisco Aguiar , João Diogo, João Diogo Silva, José Oliveira Pratas, João Moreira, Vasco Lima, Tomás Félix, Pedro Rebelo, Nuno Gonçalves, Pedro , Marta Baptista Coelho, Mariana Barosa, Francisco Arantes, João Raimundo, Mafalda Pratas, Tiago Pires, Luis Quelhas Valente, Vasco Sá Pinto, Jorge Soares, Pedro Miguel Pereira Vieira, Pedro F. Finisterra, Ricardo Santos _______________ Esta conversa foi editada por: Hugo Oliveira
Pillole di Coaching. Max Bravin
Gli insegnamenti di un Premio Nobel per la Fisica, per avere successo in ciò che facciamo ogni giorno
Alberto Giannone"Meglio curiosi che intelligenti"Mondadori Editorehttps://www.mondadori.it/"L'intelligenza in sé non ha nulla di speciale, ogni persona la possiede a modo suo. In fondo, altro non è che il complesso di facoltà psichiche e mentali che ci consentono di pensare, comprendere o spiegare i fatti o le azioni. Fa parte della natura intrinseca degli esseri umani: il nostro cervello si è sviluppato perché potessimo adattarci, sopravvivere, comunicare con gli altri, insomma per essere intelligenti. Ma quindi, cos'è che rende scienziati, artisti, inventori così speciali? Qual è la caratteristica che permette loro di pensare o immaginare cose che prima di allora nessuno aveva mai pensato? Be', semplice: la curiosità.Se ci pensate, in effetti, quante persone realmente curiose avete conosciuto nella vita? Quante persone che adorano scoprire sempre qualcosa di nuovo, studiare per il puro gusto di farlo e perdersi nei meandri di libri e, perché no, di internet, e assorbire come spugne qualsiasi informazione trovino? Rispondo io per voi: poche. Questo perché la curiosità richiede fatica e a nessuno piace farla. È come se il cervello (e quindi la nostra intelligenza) cercasse di rinchiudere la curiosità in un angolo buio per potersi così concentrare sul suo passatempo preferito: fare quello che ha sempre fatto. Siamo così intelligenti che invece di cercare esperienze nuove, preferiamo starcene a poltrire sul divano.Meglio curiosi che intelligenti è un viaggio pieno di aneddoti, esercizi e informazioni attraverso le vite di persone che non si sono limitate a essere intelligenti, ma hanno osato fare qualcosa di più. Da Einstein a Beethoven, da Irène Curie a Samantha Cristoforetti, da Feynman a Escher e molti altri; artisti, scienziati e pensatori che non si sono accontentati di essere intelligenti ma hanno trascorso la vita nello stimolare continuamente la loro curiosità, finendo per cambiare il mondo per come lo conosciamo."Alberto GiannoneAlberto Giannone è da sempre un curioso. Ha conseguito la laurea magistrale in Economia e parallelamente coltivato diverse passioni, in particolare quella per il mondo scientifico. Dal 2019 si dedica al progetto social "DivulgaMente", che ha come obiettivo divulgare alcuni argomenti scientifici o culturali e stimolare la curiosità in tutte le sue forme.IL POSTO DELLE PAROLEAscoltare fa Pensarehttps://ilpostodelleparole.it/
@HPCpodcast with Shahin Khan and Doug Black
How did Richard Feynman end up playing the bongo drums? How did a new take on Amdahl's Law helped propel massively parallel computing and become Gustafson's Law? And what's wrong with IEEE 754 number format that the new Posit format fixes? We go to the source as we welcome special guest John Gustafson in another very lively conversation. [audio mp3="http://orionx.net/wp-content/uploads/2022/09/037@HPCpodcas_John-Gustafson_Amdahls-Law_Unum-Posit-format_20220914.mp3"][/audio] The post @HPCpodcast-37: John Gustafson on Feynman, Gustafson’s Law, Posit Format appeared first on OrionX.net.
It is difficult to overstate China's rise in terms of economic development in the four decades - growing from one of the poorest countries to becoming the world's second-largest economy. China has also become an important geopolitical partner to many developing countries, and it is quite common to encounter talk of the ‘‘China model'' of development as being more suitable for many African countries that have struggled with economic transformation. Joining me on today's episode is political scientist Yuen Yuen Ang to unpack what China did during the reform years and the many ways that process is misunderstood. She has two excellent books (linked here) on China, and she is one of the most careful, thoughtful, and perceptive scholars I have read.TranscriptTobi; Welcome to Ideas Untrapped, and my guest today is Yuen Yuen Ang who is a professor of political science at the University of Michigan. She has written two very important books on China. And I want to talk to her today about the first book, How China Escaped the Poverty Trap. Welcome, Yuen.Yuen; Well, thank you very much, Tobi, thank you for having me. And I very much appreciate your support.Tobi; In global development today, it's almost impossible not to talk about China. China has become so important both economically and geopolitically, and we know that the picture or the situation was quite different 40 years ago. Another thing with what China has done in the last four decades, I mean, two-thirds of the global reduction in poverty is in China and so many other amazing things, is that there's a lot of, should I say, content on China and in my experience, it feels a bit like quantum physics and that Feynman quote, which is the more you read on China, the less we understand. But, reading your book for me as being quite illuminating. Again, I want to thank you for writing it. So the first question I'll ask you is, very early in your first book you made what I think was an important distinction, which is the difference between market-creating institutions and market-preserving institutions. Can you elaborate more on that? And how China was able to take advantage of the former?Yuen; Sure. Well, first of all, I really love the quote that you used. And before I jump into the question that you just asked, I think it's useful to respond to your comments, which I think it's very insightful, which is that everyone is very interested in China. There's a lot of talk about it, but it feels confusing. And so at the outset, when I write my books, I think one of the things that I wanted to set out to do was to provide an integrative account of China's development since its market opening in 1978. And I stress the word integrative, because I think one of the sources of confusion that you alluded to comes from the fact that there are many, many accounts about China's development, but they tend to focus on only one aspect. So some will talk about trade, others might talk about economic policy, so there are so many different topics about China. But what people need is an integrative account that puts all of these different elements and variables together. I really put them on a timeline to help people to understand, sort of, the different factors that were salient at different points in time. And this is important for correcting the misconception that there is one China model, like some kind of blueprint that was created at the outset and designed to help China take off. So that was the kind of broader backdrop that motivated the way that I write my book, in particular, the first one. Let me now come back to your original question, which is the concept of market-building and market-preserving institutions. And the important thing to understand about institutions is that economists have all agreed that good institutions, such as rule of law, such as formal accountability, such as modern courts, that all of these good institutions are essential for growth. And you have famous books like Why Nations Fail pretty much making similar arguments. And that then translated into the good governance agenda that was advanced by International Development Agencies, such as the World Bank. So for about, I would say, 1990s to the present day or so, there was a great deal of attention and hope that if poor countries could get institutions, right, if they could have first-world institutions, then they will be able to have economic growth and become developed. And when I look at the China case, that obviously does not follow that formula, because if you look at the early parts of China's growth, and even until today, there are so many dimensions of China's institutional design - everything from the ownership of companies, to the property rights, to the design of bureaucracies that just don't conform with what we think first-world good institutions should look like. So why is it that China has been able to grow its economy without those first-world institutions that economists say are the preconditions for growth, and this has been a long-standing puzzle in political economy? So from my investigation, what I find is that the fallacy with the conventional wisdom is that it thinks that there is just one universal set of institutions that are necessary for growth, namely, the first-world rich country institutions. But in fact, what really happens in the course of development is that countries actually have to develop qualitatively different institutions for early and late stages of growth. And those institutions at early stages of growth, that can support the growth process can actually look very, very different from the first-world norms. They can look in ways that conventionally we would dismiss as dysfunctional or corrupt. But those institutions can actually work very well at early growth stages. And subsequently, however, when the economy takes off, and it enters into a more mature stage of development, and then you begin to see that, yes, you do need institutions that are more like fist-world institutions, such as formal regulations, private property rights, and so forth. So that is why I make a distinction between market-building institutions and market-preserving institutions.Tobi; I mean, one important thing that I also learnt from your first book, and you can please correct me if I'm getting this wrong, is that (it's interesting you alluded to economics accounts of China's rise) ever since the works of people like [Robert] Wade and [Alice] Amsden talking about the East Asian miracle, there has always been this importance for the role of the states. And then the discussion then polarizes into, do you use the State? Or do you use the markets? And policymakers in different developing countries choose what they see, you know, and some stressed the importance of state capitalism. But what I learned from your book was that it really doesn't matter the kind of political system you run. Every political system in history that has gone through that stage has used market-building institutions. One thing you also talked about quite early in the book is this concept of directed improvisation. What is that? And how did China use that?Yuen; Yes. The conventional wisdom when people look at China's case is to assume that the recipe for its economic growth must be centralized political control because it is an authoritarian regime. So when people talk about the China model today, it's reduced or dumbed down into, basically, authoritarianism, plus some elements of capitalism. And I question that conventional wisdom in my book. If the answer was simply authoritarianism and centralized control, then China would have prospered long ago, under the reign of Mao, where you had absolute centralized power under one leader, even more centralized back then than it was today. So it couldn't be that centralized political control or authoritarianism is the answer to China's development. Instead, what really happened is that the central government under Deng Xiaoping was the reformist leader who took over thus helping change the role of the central government from that of a dictator to a director. And what the director does is that it focuses its job on setting up conducive conditions for bottom-up innovation and bottom-up adaptation, primarily among local governments. So China is politically centralized, but it's economically and administratively decentralized. But in encouraging local governments to adapt and to find local solutions to local problems. The central government still plays a crucial role in terms of providing direction, setting up the rules of the game, defining what the goals and targets should be. So these were the ways in which the central government “directed” the process of adaptation. So directed improvisation simply means you have the merger of direction from above, with bottom-up adaptation among local governments. So in the first 30 years of reform, which most people call the reform period, which is up to 2012, what you can see in China is actually a diverse range of regional economic models, and not just one. And if you take even any county or city in China, and you trace the history of development over those 30 years, you'll find that the role of the government and the development strategies that that particular city undertook kept changing over time. So I think it is this highly adaptive element of the Chinese experience that is often neglected, or not understood in the global discourse about China because people are overly distracted by stereotypes about authoritarian control. But the point that I think is most valuable, and that China should talk about more is the adaptive element under the reformist Deng government and the amount of diversity that they were able to create despite being a formerly authoritarian state. Tobi; One distinction I'll also like you to elaborate [on] is control versus influence, which was something I also got from your book and found interesting. I remember reading Robert Bates, writing about the political economy of Africa. He talked about the importance of control regimes, you know, having a closed economy, price distortion, regulation of industrial outputs, regulation of markets, these were things that were also part of China's economy and policymaking during the Mao era, you know. But we also observed that during the reform years after 1978 policymaking also was not thrown into chaos, you know, like the opposite of control. So how did China manage that balance, particularly substituting influence for direct administrative control of policy?Yuen; I'm really glad that you raised this subtle point, but an important point. So let me give some theoretical background before I elaborate on the China case. If you look at the conventional thinking about politics and economics, it is really a literature that is obsessed with control. Right? So it's always about someone controlling someone, it's like the state controlling civil society, or politicians controlling bureaucracy, central governments controlling local governments. And this fixation with control is, I think, an extension of a mechanical intellectual paradigm. So if you look at the beginning of my book, I talked about how and why I use a complexity paradigm to interpret the Chinese development process. The conventional paradigm is a mechanical one. So things about how things work as if it functions as a machine. And indeed, the top economists do explicitly say that they think in machine mode. So when you think in machine mode, everything looks like a control problem. And so that's why you see the literature and Political Economy being so fixated on control. But what we don't talk about enough, or sometimes not at all, is the other element of human activity, which is, apart from trying to control we also adapt all the time, including in Nigeria, and we have very little understanding in the political economy context of how do people adapt? Why do they adapt? What are the conditions that make adaptation possible? What are the products of adaptation? These are the various questions that we don't ask in political economy. So once you move to the Chinese context, and you apply the lens of adaptation, it immediately opens up a very different story from the traditional one that was entirely about control. One of the things that is important to know when we think about China is that control is always an element present in the Chinese political context. And it's present in a big way because it is a top-down political system. So I'm not saying that there is no control in China. Of course, there is; such as censorship. But what I'm saying is that as the reformed leadership under Deng took over from Mao, it dramatically change the role of government as well as the mixture of control and adaptation. So on under Deng, of course, there were still policies of repression and control. The family planning policy, for instance, required a great deal of forceful implementation. But it also dramatically increase the amount of adaptive activity that the government carried out. So the distinction I make is that when you are fixated on control, what we conceptualize is that politicians want to control the outcome. So they already have a predetermined outcome or solution, and they're just trying to control everyone so that they can get there. Right? When I use the term influence, however, the assumption is that oftentimes, the leaders actually do not know what the best outcome should be. They don't have the solutions to the problems that they face. And this was absolutely evident in China's market transition process, because that was something that China had never tried before, it had never tried to move from communism to a market economy. So oftentimes, these leaders themselves do not actually know what is the best solution that they should create. And so what they did is instead of trying to control outcomes, which presumes that you have a lot of knowledge and know exactly what's best for you, they instead try to influence the process of coming up with solutions by, for example, encouraging local governments to come up with solutions that are tailored to local conditions, but at the same time setting up some guardrails in this process of experimentation. So that is what I mean by the difference between trying to control an outcome versus influencing the process of problem-solving.Tobi; One thing I so love about your first book, which you've also alluded to in your answer is appreciating that a society and the economy is a complex system. And you said that an alternative to control in complex systems is to influence the process of adaptation and change. So I want you to talk briefly about how these influence the design of the reform packages themselves in the China reform experience, particularly the three key mechanisms you talked about in the book, which were variation, selection, and niche creation. How did that work?Yuen; Yes, I'm happy to do that. Let me focus on the first two parts because of time, which are variation and selection. And these terms come from the well-established scientific literature about how adaptation happens. So adaptation begins with generating a variety of possible solutions. So that's why the first mechanism is variation. And this is followed by selection. So from the possible pool of solutions, you pick one, and you test it out, collect feedback and decide "do you want to continue with this solution? Do you want to share this solution with others, or perhaps you find out the solution I picked didn't actually work so well, so let's select another one."And niche creation is about creating differences among members of the units so that these members can coexist, instead of competing head-on with one another. So I use these mechanisms to organize different parts of the book in explicating what were the mechanisms that the central government designed in order to structure the process of adaptive governance in China.And on variation, I look specifically at the system of political communication in China. China is a top-down political system. So the way the top government sends commands - written directives to the local governments - is the primary and most important mechanism by which it commands, instructs, and guides the whole bureaucracy. And normally, this is a system that, frankly, almost nobody studies because it doesn't really seem interesting. It's a command system. So you think that, you know, whatever, if Beijing wants to send a command. But what I argue and actually show in the book is that the command system in China actually functions in ways much more interesting way can imagine. And specifically, what I show is that in the Chinese political system, the central government would send out three different types of signals. The first signal is what I call black signals. These are written directives, where the language is explicitly clear, saying, "yes, you can do this. Yes, the local governments all over China, you can do this." And the second type of directive is what I call red signals, which explicitly says, "no, you cannot do this." So, for example, "no, you cannot exceed the amount of water use by this amount." And then the most interesting one is the third category, which is the grey directives. So commands that are deliberately ambiguous. And there are a lot of ambiguous commands and instructions that occur in the Chinese political system. And they still do today. And I argue that what these ambiguous commands do is that they actually provide room for experimentation. Because from the perspective of the local officials when the command is vague and ambiguous, and broadly stated, it means that they are free to interpret how to implement that particular instruction. And when they experiment and try things out, it produces, generates a variety of possible solutions. And from these possible solutions, the regulators in Beijing can then take a look at these options, many of which they had never thought about before and then decide, "among these possible solutions, are there some really good ones that we should scale up to regional or national levels," or sometimes they might also realize, oh, some local experiments turn out to be not good. And we are going to change our commands from grey to red and say, No, I don't want you guys to try this anymore. So through this varied and dynamic system of commands, is one example of a mechanism by which the central government in China is able to calibrate the amount of discretion that it gives local officials, allowing them to experiment when the central government wants to experiment, and then also providing a mechanism for the central government to collect feedback to scale things up if they want to. And also to scale things down, if they decide that that is the right thing to do.Tobi; So it's really hard to talk about China, at least the way China is being written about generally, without talking about state capacity. Like you talked about in the early part of the discussion that analysts and scholars usually take one thing and focus on that when discussing China, and there is always this talk about state capacity being the be-all of how China was able to reform itself and become rich. You know.Some say it's the bureaucracy that was inherited from the communist regime, some talk about the 5000-year history of civilization, and so many other theories. But you've discussed this often on your Twitter feed, and in other appearances, that when we talk about the bureaucracy, we usually have the Weberian Western-type democracy in mind, and that the way scholars and people discuss this is like, it's the only way to achieve bureaucratic coordination. But you've also challenged the idea that there are other forms of bureaucracy. So I want to ask you, how did China achieve that bureaucratic coordination without feeding into the Weberian archetype? You know, so to speak, because the challenge with most developing countries like Nigeria, which I am familiar with, is that you often have pockets of effectiveness in different arms of the government, but it's usually difficult for one vision to be projected, you know, and be implemented. So how did China achieve this through its bureaucracy, what were the design elements?Yuen; I am very glad that you brought up this important point. It is a point that I keep making in my books and in other forms of speaking. It is also a point that many people find hard to accept. The reason for this is that for a very long time, the conventional wisdom has always subscribed to the view that there is only one standard for good institutions, for stake capacity, for good governance and that is to look like rich Western nations. Now, the conventional wisdom doesn't put it this way, but if you look at all of the global metrics that are created, regardless of the names that are coined for them, it's always the same countries that are ranked in the top 10. And it's always the same group of countries, including Nigeria, and sometimes China that's ranked at the bottom, right?And so this is very deeply entrenched in both academic and popular thinking that there is only one standard in this world for good governance and good institutions. And that we should only use that benchmark. And when we look at developing countries, their situation is only accessed in terms of their distance from this ideal type. So things in developing countries are not perceived as being qualitatively different, they are instead perceived as deficient because they don't comply with the standard expectation of how things should function. And so including in the discussion about state capacity, one of the core elements of state capacity is bureaucratic capacity. And so as you alluded to, everyone subscribes to the legal-rational model that Max Weber had portrayed 100 years ago. And it is assumed that the only kind of effective bureaucracies are the ones that have these Weberian qualities, and everything else must be corrupt or dysfunctional. And the reason that I questioned this conventional wisdom is that I think it is... first of all, it reflects a first-world bias that people are either unaware of or unwilling to admit. And second of all, it is limiting and distorting. Because when you assume that there is only one standard, you cannot see qualitative or categorical differences. Meaning that perhaps in this world, we are actually comparing apples, oranges, bananas and guavas. But when you say only the Apple is the legitimate fruit, and then you look at the banana, and you think, "Oh no, the banana is deficient, because it doesn't look like an apple," right? So that is why it becomes this very narrowing logic. And what I find from both my historical research and my field research, in the case of China, as a very good example is that the qualities of an effective bureaucracy were actually very different at the early and late growth stages. So the given example, I show that in the early 1980s, 1990s, when markets first opened in China, the country actually relied on bureaucracies that had non-Weberian characteristics. So they were not specialized. Local governments would mobilize every agency to go and recruit investors. And this defies Weber's rule of specialization and technocracy. They also create a mechanism where these bureaucrats were basically taking a cut from the investments they could bring in which in economics, we say high-powered incentives. And in Weberian bureaucracy, you're not supposed to provide high-powered incentives, you're supposed to have these very modest rule-abiding and somewhat boring bureaucrats in office. And the reason why these non-Weberian qualities work very well, in the beginning, is because they made the best use of what China had in the beginning, which is it had a communist apparatus and a communist apparatus [that] is good at mobilization. It made use of the personal connections of local government officials and these personal connections substituted for formal property rights, and so forth. And so even though these individual characteristics would appear to be wrong from the first-world perspective, they were actually functionally a good fit with the objectives of early development. However, as the process goes on, income rises, the markets become more complex, businesses grow and so forth, the society and the economy had different objectives, had different priorities about growth. They no longer wanted just any type of growth they wanted, instead, quality growth in states-selected priority sectors. And that's when you begin to see an evolution in the bureaucracy towards the more specialized and technocratic forms that we see in first-world countries today. So to sum it all up, there are two takeaways. The first takeaway is [that] the good institutions that are often touted as universally ideal institutions are actually good institutions suitable for advanced stages of growth. But early stages of growth may actually require functionally and qualitatively different institutions that make the best use of what low-income societies have. So that is the first takeaway. And the second takeaway is that we should drop this assumption that there is only one standard because that prevents us from seeing potentially creative solutions throughout the developing world.Tobi; So your second book, "China's Gilded Age: the paradox of economic boom and vast corruption," I would say, also slayed another dragon for me personally, only that the dragon is not China. So from my experience in Nigeria, when you talk about corruption, the almost - I should say, self-interested response you get from politicians is that there is corruption in other places. And from somebody coming from a civil society background or even an average citizen, that answer is unpalatable, because the way we have been made to think about corruption is usually about the overall level of corruption, the quantitative level of corruption. But in your book, you made it important that the qualitative aspect of corruption is also important. So can you please briefly explain the difference? How did you come about this insight of unbundling corruption, so to speak?Yuen; Yes. So the second book is called China's Gilded Age. And it is a sequel to my first where I zoom in on the relationship between corruption and capitalism. And the core argument of the second book is actually quite simple. What I argue is that corruption comes in different types. And different types of corruption have different forms of harm. And I focus on one particular type of corruption that I call access money: elite exchanges of power and wealth. And I show that in many contexts, not just in China, access money can actually encourage businesses to do more business; because politicians provide them with conducive conditions. But that this form of corruption results in indirect risk and harm that is nearly impossible to quantify. And so once we, in particular, zoom in on access money, we can understand why there are many economies that are prosperous, on the one hand, but on the other hand, have many structural distortions and risks. And in addition to China, the other country that fits this model is actually the United States. So whether you look at the United States in the late 19th century, the original Gilded Age, or whether you look at the United States during the 2008 financial crisis and today, you'll find that these are wealthy capitalist economies that produce rapid growth, but also [produce] inequality - a great deal of inequality and a great deal of policy distortions and systemic risk. And that is the kind of corruption that is neglected that people don't look at. The reason for this is that most people, when they think about corruption, they immediately think about the forms of illegal corruption that they encounter in their daily lives. So when a policeman stops you and extracts a bribe from you. Now that is obviously corrupt. It is an act of bribery, it is illegal, it is extortion. And so the focus is on this type of corruption. Whereas a lot of the popular discourse neglects the other type of corruption - access money - which has always been actually central to the history of capitalism.Tobi; I find that book very insightful. I'll give you a brief anecdote. The former president during one of his media appearances went on television and made, I would say, the error at the time of saying that corruption is different from stealing. And it happened to be one of the things that became a public relations nightmare for him. So I just want to ask you, for countries that are dominated by the destructive types of corruption, can they transition to access money types of corruption, and can they also avoid the inequalities that come with it? And I should say that you stressed in the book that corruption is not good, which is another wrong message that a lot of people take from the book.Yuen; So my book, China's Gilded Age, unfortunately, as you pointed out, is widely misunderstood. As soon as people see the story of corruption coexisting with growth, they take that argument out of context, and start screaming that, "oh, my god, she's saying corruption is good for growth, and she's saying we should do more corruption."And so there have been quite a lot of nonsensical reactions to the argument. So at the outset, let me stress that actually, I made clear throughout the book, and over and over again in my speaking that all corruption is bad. This is not an argument about corruption being good in any way. All corruption is bad, but the harm is expressed in different ways. And so that is why I use the analogy of drugs. I used the analogy of toxic drugs to refer to extortion and embezzlement. These types of corruption have absolutely no benefit, you immediately see the harm, and it immediately destroys the economy. And Nigeria is a good example of this type of highly destructive corruption. And the second type of corruption I call speed money, I refer to that as painkillers. So you can think about a business that pays a small bribe so that it can get a business license faster. And that corruption is a painkiller in the sense that it allows the business to buy some conveniences, gets rid of some headaches, but that doesn't actually help the business to make more money. Ultimately, for the business owner, it is a hassle. And it is a cost. So that's not good, either. And the last type of corruption, access money, I call it steroids. So steroids, as we know, is a kind of drug that dishonoured athletes use to help them grow muscles and perform superhuman feats. But if you keep using steroids, then ultimately it's really going to have a whole range of serious side effects that accumulate over time. And access money is a type of corruption that you find in high growth or wealthy, crony capitalist economies, right? So what people should take away from this book is not that corruption is good, or that countries should do more corruption, which obviously would be nonsensical. Instead, they should really think about the following issues. First of all, countries should take a look at what is the dominant type of corruption that exists in their country, and think about the appropriate methods to fight the dominant type of corruption. For instance, in the United States, extortion, petty bribery, these sometimes happen, but it's not common in the United States. But over there, the dominant type of corruption is legalized access money. So lobbying has become a gigantic industry. And so the United States would have to come up with very different ways of fighting the kind of corruption that dominates in their society. Conversely, when you look at Nigeria, it has all four types of corruption that I talk about and so in a country like Nigeria, there has to be a focus on fighting all of these four types of corruption, but particularly the toxic ones. So embezzlement, extortion, imposing petty bribes, and thuggery on people. These types of corruption have no benefits at all. They drain the economy and the burden falls most heavily on the poor. So countries have to think about what are the measures they can take to bring down this overtly, growth-dampening corruption. And if you look at the Chinese experience, what happens as it developed over time is that the structure of corruption changed, and it invested at least 20 years of efforts to really bring down extortion and embezzlement.And although I had an entire chapter devoted to that topic, a lot of people just ignore it. And instead, they run with the misleading conclusion that oh, we should do more corruption. They ignore my discussion about the 20 years of effort that China put into bringing down extortion and embezzlement. So for readers in Nigeria, start with the obvious things, things like extortion, embezzlement… of course, they're wrong; of course, they're terrible; of course, they're damaging, so do something about that first before you even attempt to think about how can we transition to more advanced forms of crony capitalism like we might see in some advanced economies. The other takeaway I would add... the third takeaway that I would emphasize is that the part about access money, it's not about how do we encourage more access money corruption… the way to think about that takeaway is how do countries like Nigeria, create incentives for government officials to have a personal stake in economic outcomes? Right.And so what happened in the Chinese case is the system that I call profit sharing. Meaning local officials have a stake in economic growth, which comes both in terms of their career, as well as in their financial payoffs. And that shows up as access money.It doesn't mean that other countries should have more of that kind of corruption. Instead, the real lesson is, if not this type of corruption, are there other less damaging ways in which we can create incentives for government officials to actually have a personal stake in economic development?Tobi; One final question, I know our time is gone. I know scholars usually, sometimes, shy away from making policy proposals but for countries that are also interested or ambitious about escaping the poverty trap, what… maybe theoretically speaking, or practically, what are the three things that you would recommend from your research on the China experience? Not necessarily copying China, we know that has pitfalls, so what would you recommend? Yuen; It's a good final question to wrap up. Um, I would sum up with three takeaways. The first takeaway is, really work hard on fighting the overtly growth damaging types of corruption. It is a simple takeaway, but a lot of people actually forget about it. So things like embezzlement, things like extortion. If Nigeria could bring down the level of these damaging types of corruption, of course, immediately, you will see the economic and social benefits. So work hard on that. And then the second takeaway is, how is it possible for government officials in Nigeria to have a personal stake in collective outcomes? I don't have the answer. But I think it is a question that Nigerians have to sit down and think about. One of the things that are often missing in developing countries is a discussion about incentives and also about a sense of personal ownership in shared outcomes. People prefer to invest their energies in criticizing politicians and so forth. But if you think about it from an institutional perspective, why should that particular politician care about the collective outcome? Right. So how can we create those incentives, which doesn't necessarily have to be monetary. It could also be non-monetary, it could be reputational, how do we make them care? Right? So that's the second thing to think about. The third thing I would emphasize is a principle that I call using what you have, and China illustrates that principle, richly. Using what you have means that every society, even one that is a low-income society has a lot of indigenous resources, they have human capital, they have creativity. So the first step of development is not to go and copy rich countries, it is also not to sell your oil resources, but to really make the best use of these indigenous resources. And so for those who know my first book, actually, in the conclusion, I have a chapter about Nollywood. And that's an excellent example whereby under desperate circumstances, the people in Nigeria actually created an industry from the bottom up using what Nigeria had at that particular time. And so there are so many instances throughout the developing world where there are actually a lot of indigenous resources, they are untapped, or they are ignored or they're dismissed. Because we are so used to thinking that the only right solution is to look like rich countries. And we have to drop that mindset. I think it's part of an extension of a colonial mindset as well. And developing countries have to develop a certain sense of intellectual independence, as well as confidence in seeing the potential that is already existent in every society, and make the best use of those resources to kickstart entrepreneurship and new industries.Tobi; Thank you very much, Yuen Yuen Ang, it's been fantastic talking to you.Yuen; Thank you very much. It's a real pleasure to speak with you. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.ideasuntrapped.com/subscribe
Saved by the swapcast! This was originally scheduled as a guest appearance on the excellent Where Did the Road Go? podcast with Seriah, but our plans for our regular episode this week fell through, so Seriah kindly allowed us to use this episode as a swapcast. We discuss Charles Fort and the Book of the Damned, Feynman, cosmology, physics, electric universe, cryptids, UFOs, and the limits of human knowledge, as well as reading a few news stories and discussing those.
Steve Hsu is a Professor of Theoretical Physics at Michigan State University and cofounder of the company Genomic Prediction.We go deep into the weeds on how embryo selection can make babies healthier and smarter. Steve also explains the advice Richard Feynman gave him to pick up girls, the genetics of aging and intelligence, & the psychometric differences between shape rotators and wordcels.Watch on YouTube. Listen on Apple Podcasts, Spotify, or any other podcast platform.Subscribe to find out about future episodes!Read the full transcript here.Follow Steve on Twitter. Follow me on Twitter for updates on future episodes.Please share if you enjoyed this episode! Helps out a ton!Timestamps(0:00:14) - Feynman’s advice on picking up women(0:11:46) - Embryo selection(0:24:19) - Why hasn't natural selection already optimized humans?(0:34:13) - Aging(0:43:18) - First Mover Advantage(0:53:49) - Genomics in dating(1:00:31) - Ancestral populations(1:07:58) - Is this eugenics?(1:15:59) - Tradeoffs to intelligence(1:25:01) - Consumer preferences(1:30:14) - Gwern(1:34:35) - Will parents matter?(1:45:25) - Word cells and shape rotators(1:57:29) - Bezos and brilliant physicists(2:10:23) - Elite educationTranscriptDwarkesh Patel 0:00 Today I have the pleasure of speaking with Steve Hsu. Steve, thanks for coming on the podcast. I'm excited about this.Steve Hsu 0:04 Hey, it's my pleasure! I'm excited too and I just want to say I've listened to some of your earlier interviews and thought you were very insightful, which is why I was excited to have a conversation with you.Dwarkesh Patel 0:14That means a lot for me to hear you say because I'm a big fan of your podcast.Feynman’s advice on picking up womenDwarkesh Patel 0:17 So my first question is: “What advice did Richard Feynman give you about picking up girls?”Steve Hsu 0:24 Haha, wow! So one day in the spring of my senior year, I was walking across campus and saw Feynman coming toward me. We knew each other from various things—it's a small campus, I was a physics major and he was my hero–– so I'd known him since my first year. He sees me, and he's got this Long Island or New York borough accent and says, "Hey, Hsu!" I'm like, "Hi, Professor Feynman." We start talking. And he says to me, "Wow, you're a big guy." Of course, I was much bigger back then because I was a linebacker on the Caltech football team. So I was about 200 pounds and slightly over 6 feet tall. I was a gym rat at the time and I was much bigger than him. He said, "Steve, I got to ask you something." Feynman was born in 1918, so he's not from the modern era. He was going through graduate school when the Second World War started. So, he couldn't understand the concept of a health club or a gym. This was the 80s and was when Gold's Gym was becoming a world national franchise. There were gyms all over the place like 24-Hour Fitness. But, Feynman didn't know what it was. He's a fascinating guy. He says to me, "What do you guys do there? Is it just a thing to meet girls? Or is it really for training? Do you guys go there to get buff?" So, I started explaining to him that people are there to get big, but people are also checking out the girls. A lot of stuff is happening at the health club or the weight room. Feynman grills me on this for a long time. And one of the famous things about Feynman is that he has a laser focus. So if there's something he doesn't understand and wants to get to the bottom of it, he will focus on you and start questioning you and get to the bottom of it. That's the way his brain worked. So he did that to me for a while because he didn't understand lifting weights and everything. In the end, he says to me, "Wow, Steve, I appreciate that. Let me give you some good advice."Then, he starts telling me how to pick up girls—which he's an expert on. He says to me, "I don't know how much girls like guys that are as big as you." He thought it might be a turn-off. "But you know what, you have a nice smile." So that was the one compliment he gave me. Then, he starts to tell me that it's a numbers game. You have to be rational about it. You're at an airport lounge, or you're at a bar. It's Saturday night in Pasadena or Westwood, and you're talking to some girl. He says, "You're never going to see her again. This is your five-minute interaction. Do what you have to do. If she doesn't like you, go to the next one." He also shares some colorful details. But, the point is that you should not care what they think of you. You're trying to do your thing. He did have a reputation at Caltech as a womanizer, and I could go into that too but I heard all this from the secretaries.Dwarkesh Patel 4:30 With the students or only the secretaries? Steve Hsu 4:35 Secretaries! Well mostly secretaries. They were almost all female at that time. He had thought about this a lot, and thought of it as a numbers game. The PUA guys (pick-up artists) will say, “Follow the algorithm, and whatever happens, it's not a reflection on your self-esteem. It's just what happened. And you go on to the next one.” That was the advice he was giving me, and he said other things that were pretty standard: Be funny, be confident—just basic stuff. Steve Hu: But the main thing I remember was the operationalization of it as an algorithm. You shouldn’t internalize whatever happens if you get rejected, because that hurts. When we had to go across the bar to talk to that girl (maybe it doesn’t happen in your generation), it was terrifying. We had to go across the bar and talk to some lady! It’s loud and you’ve got a few minutes to make your case. Nothing is scarier than walking up to the girl and her friends. Feynman was telling me to train yourself out of that. You're never going to see them again, the face space of humanity is so big that you'll probably never re-encounter them again. It doesn't matter. So, do your best. Dwarkesh Patel 6:06 Yeah, that's interesting because.. I wonder whether he was doing this in the 40’–– like when he was at that age, was he doing this? I don't know what the cultural conventions were at the time. Were there bars in the 40s where you could just go ahead and hit on girls or? Steve Hsu 6:19 Oh yeah absolutely. If you read literature from that time, or even a little bit earlier like Hemingway or John O'Hara, they talk about how men and women interacted in bars and stuff in New York City. So, that was much more of a thing back than when compared to your generation. That's what I can’t figure out with my kids! What is going on? How do boys and girls meet these days? Back in the day, the guy had to do all the work. It was the most terrifying thing you could do, and you had to train yourself out of that.Dwarkesh Patel 6:57 By the way, for the context for the audience, when Feynman says you were a big guy, you were a football player at Caltech, right? There's a picture of you on your website, maybe after college or something, but you look pretty ripped. Today, it seems more common because of the gym culture. But I don’t know about back then. I don't know how common that body physique was.Steve Hsu 7:24 It’s amazing that you asked this question. I'll tell you a funny story. One of the reasons Feynman found this so weird was because of the way body-building entered the United States. They were regarded as freaks and homosexuals at first. I remember swimming and football in high school (swimming is different because it's international) and in swimming, I picked up a lot of advanced training techniques from the Russians and East Germans. But football was more American and not very international. So our football coach used to tell us not to lift weights when we were in junior high school because it made you slow. “You’re no good if you’re bulky.” “You gotta be fast in football.” Then, something changed around the time I was in high school–the coaches figured it out. I began lifting weights since I was an age group swimmer, like maybe age 12 or 14. Then, the football coaches got into it mainly because the University of Nebraska had a famous strength program that popularized it.At the time, there just weren't a lot of big guys. The people who knew how to train were using what would be considered “advanced knowledge” back in the 80s. For example, they’d know how to do a split routine or squat on one day and do upper body on the next day–– that was considered advanced knowledge at that time. I remember once.. I had an injury, and I was in the trainer's room at the Caltech athletic facility. The lady was looking at my quadriceps. I’d pulled a muscle, and she was looking at the quadriceps right above your kneecap. If you have well-developed quads, you'd have a bulge, a bump right above your cap. And she was looking at it from this angle where she was in front of me, and she was looking at my leg from the front. She's like, “Wow, it's swollen.” And I was like, “That's not the injury. That's my quadricep!” And she was a trainer! So, at that time, I could probably squat 400 pounds. So I was pretty strong and had big legs. The fact that the trainer didn't really understand what well-developed anatomy was supposed to look like blew my mind!So anyway, we've come a long way. This isn't one of these things where you have to be old to have any understanding of how this stuff evolved over the last 30-40 years.Dwarkesh Patel 10:13 But, I wonder if that was a phenomenon of that particular time or if people were not that muscular throughout human history. You hear stories of Roman soldiers who are carrying 80 pounds for 10 or 20 miles a day. I mean, there's a lot of sculptures in the ancient world, or not that ancient, but the people look like they have a well-developed musculature.Steve Hsu 10:34 So the Greeks were very special because they were the first to think about the word gymnasium. It was a thing called the Palaestra, where they were trained in wrestling and boxing. They were the first people who were seriously into physical culture specific training for athletic competition.Even in the 70s, when I was a little kid, I look back at the guys from old photos and they were skinny. So skinny! The guys who went off and fought World War Two, whether they were on the German side, or the American side, were like 5’8-5’9 weighing around 130 pounds - 140 pounds. They were much different from what modern US Marines would look like. So yeah, physical culture was a new thing. Of course, the Romans and the Greeks had it to some degree, but it was lost for a long time. And, it was just coming back to the US when I was growing up. So if you were reasonably lean (around 200 pounds) and you could bench over 300.. that was pretty rare back in those days.Embryo selectionDwarkesh Patel 11:46 Okay, so let's talk about your company Genomic Prediction. Do you want to talk about this company and give an intro about what it is?Steve Hsu 11:55 Yeah. So there are two ways to introduce it. One is the scientific view. The other is the IVF view. I can do a little of both. So scientifically, the issue is that we have more and more genomic data. If you give me the genomes of a bunch of people and then give me some information about each person, ex. Do they have diabetes? How tall are they? What's their IQ score? It’s a natural AI machine learning problem to figure out which features in the DNA variation between people are predictive of whatever variable you're trying to predict.This is the ancient scientific question of how you relate the genotype of the organism (the specific DNA pattern), to the phenotype (the expressed characteristics of the organism). If you think about it, this is what biology is! We had the molecular revolution and figured out that it’s people's DNA that stores the information which is passed along. Evolution selects on the basis of the variation in the DNA that’s expressed as phenotype, as that phenotype affects fitness/reproductive success. That's the whole ballgame for biology. As a physicist who's trained in mathematics and computation, I'm lucky that I arrived on the scene at a time when we're going to solve this basic fundamental problem of biology through brute force, AI, and machine learning. So that's how I got into this. Now you ask as an entrepreneur, “Okay, fine Steve, you're doing this in your office with your postdocs and collaborators on your computers. What use is it?” The most direct application of this is in the following setting: Every year around the world, millions of families go through IVF—typically because they're having some fertility issues, and also mainly because the mother is in her 30s or maybe 40s. In the process of IVF, they use hormone stimulation to produce more eggs. Instead of one per cycle, depending on the age of the woman, they might produce anywhere between five to twenty, or even sixty to a hundred eggs for young women who are hormonally stimulated (egg donors).From there, it’s trivial because men produce sperm all the time. You can fertilize eggs pretty easily in a little dish, and get a bunch of embryos that grow. They start growing once they're fertilized. The problem is that if you're a family and produce more embryos than you’re going to use, you have the embryo choice problem. You have to figure out which embryo to choose out of say, 20 viable embryos. The most direct application of the science that I described is that we can now genotype those embryos from a small biopsy. I can tell you things about the embryos. I could tell you things like your fourth embryo being an outlier. For breast cancer risk, I would think carefully about using number four. Number ten is an outlier for cardiovascular disease risk. You might want to think about not using that one. The other ones are okay. So, that’s what genomic prediction does. We work with 200 or 300 different IVF clinics in six continents.Dwarkesh Patel 15:46 Yeah, so the super fascinating thing about this is that the diseases you talked about—or at least their risk profiles—are polygenic. You can have thousands of SNPs (single nucleotide polymorphisms) determining whether you will get a disease. So, I'm curious to learn how you were able to transition to this space and how your knowledge of mathematics and physics was able to help you figure out how to make sense of all this data.Steve Hsu 16:16 Yeah, that's a great question. So again, I was stressing the fundamental scientific importance of all this stuff. If you go into a slightly higher level of detail—which you were getting at with the individual SNPs, or polymorphisms—there are individual locations in the genome, where I might differ from you, and you might differ from another person. Typically, each pair of individuals will differ at a few million places in the genome—and that controls why I look a little different than youA lot of times, theoretical physicists have a little spare energy and they get tired of thinking about quarks or something. They want to maybe dabble in biology, or they want to dabble in computer science, or some other field. As theoretical physicists, we always feel, “Oh, I have a lot of horsepower, I can figure a lot out.” (For example, Feynman helped design the first parallel processors for thinking machines.) I have to figure out which problems I can make an impact on because I can waste a lot of time. Some people spend their whole lives studying one problem, one molecule or something, or one biological system. I don't have time for that, I'm just going to jump in and jump out. I'm a physicist. That's a typical attitude among theoretical physicists. So, I had to confront sequencing costs about ten years ago because I knew the rate at which they were going down. I could anticipate that we’d get to the day (today) when millions of genomes with good phenotype data became available for analysis. A typical training run might involve almost a million genomes, or half a million genomes. The mathematical question then was: What is the most effective algorithm given a set of genomes and phenotype information to build the best predictor? This can be boiled down to a very well-defined machine learning problem. It turns out, for some subset of algorithms, there are theorems— performance guarantees that give you a bound on how much data you need to capture almost all of the variation in the features. I spent a fair amount of time, probably a year or two, studying these very famous results, some of which were proved by a guy named Terence Tao, a Fields medalist. These are results on something called compressed sensing: a penalized form of high dimensional regression that tries to build sparse predictors. Machine learning people might notice L1-penalized optimization. The very first paper we wrote on this was to prove that using accurate genomic data and these very abstract theorems in combination could predict how much data you need to “solve” individual human traits. We showed that you would need at least a few hundred thousand individuals and their genomes and their heights to solve for height as a phenotype. We proved that in a paper using all this fancy math in 2012. Then around 2017, when we got a hold of half a million genomes, we were able to implement it in practical terms and show that our mathematical result from some years ago was correct. The transition from the low performance of the predictor to high performance (which is what we call a “phase transition boundary” between those two domains) occurred just where we said it was going to occur. Some of these technical details are not understood even by practitioners in computational genomics who are not quite mathematical. They don't understand these results in our earlier papers and don't know why we can do stuff that other people can't, or why we can predict how much data we'll need to do stuff. It's not well-appreciated, even in the field. But when the big AI in our future in the singularity looks back and says, “Hey, who gets the most credit for this genomics revolution that happened in the early 21st century?”, they're going to find these papers on the archive where we proved this was possible, and how five years later, we actually did it. Right now it's under-appreciated, but the future AI––that Roko's Basilisk AI–will look back and will give me a little credit for it. Dwarkesh Patel 21:03 Yeah, I was a little interested in this a few years ago. At that time, I looked into how these polygenic risk scores were calculated. Basically, you find the correlation between the phenotype and the alleles that correlate with it. You add up how many copies of these alleles you have, what the correlations are, and you do a weighted sum of that. So that seemed very simple, especially in an era where we have all this machine learning, but it seems like they're getting good predictive results out of this concept. So, what is the delta between how good you can go with all this fancy mathematics versus a simple sum of correlations?Steve Hsu 21:43 You're right that the ultimate models that are used when you've done all the training, and when the dust settles, are straightforward. They’re pretty simple and have an additive structure. Basically, I either assign a nonzero weight to this particular region in the genome, or I don't. Then, I need to know what the weighting is, but then the function is a linear function or additive function of the state of your genome at some subset of positions. The ultimate model that you get is straightforward. Now, if you go back ten years, when we were doing this, there were lots of claims that it was going to be super nonlinear—that it wasn't going to be additive the way I just described it. There were going to be lots of interaction terms between regions. Some biologists are still convinced that's true, even though we already know we have predictors that don't have interactions.The other question, which is more technical, is whether in any small region of your genome, the state of the individual variants is highly correlated because you inherit them in chunks. You need to figure out which one you want to use. You don't want to activate all of them because you might be overcounting. So that's where these L-1 penalization sparse methods force the predictor to be sparse. That is a key step. Otherwise, you might overcount. If you do some simple regression math, you might have 10-10 different variants close by that have roughly the same statistical significance.But, you don't know which one of those tends to be used, and you might be overcounting effects or undercounting effects. So, you end up doing a high-dimensional optimization, where you grudgingly activate a SNP when the signal is strong enough. Once you activate that one, the algorithm has to be smart enough to penalize the other ones nearby and not activate them because you're over counting effects if you do that. There's a little bit of subtlety in it. But, the main point you made is that the ultimate predictors, which are very simple and addictive—sum over effect sizes and time states—work well. That’s related to a deep statement about the additive structure of the genetic architecture of individual differences. In other words, it's weird that the ways that I differ from you are merely just because I have more of something or you have less of something. It’s not like these things are interacting in some incredibly understandable way. That's a deep thing—which is not appreciated that much by biologists yet. But over time, they'll figure out something interesting here.Why hasn’t natural selection already optimized humans?Dwarkesh Patel 24:19 Right. I thought that was super fascinating, and I commented on that on Twitter. What is interesting about that is two things. One is that you have this fascinating evolutionary argument about why that would be the case that you might want to explain. The second is that it makes you wonder if becoming more intelligent is just a matter of turning on certain SNPs. It's not a matter of all this incredible optimization being like solving a sudoku puzzle or anything. If that's the case, then why hasn't the human population already been selected to be maxed out on all these traits if it's just a matter of a bit flip?Steve Hsu 25:00 Okay, so the first issue is why is this genetic architecture so surprisingly simple? Again, we didn't know it would be simple ten years ago. So when I was checking to see whether this was a field that I should go into depending on our capabilities to make progress, we had to study the more general problem of the nonlinear possibilities. But eventually, we realized that most of the variance would probably be captured in an additive way. So, we could narrow down the problem quite a bit. There are evolutionary reasons for this. There’s a famous theorem by Fisher, the father of population genetics (aka. frequentist statistics). Fisher proved something called Fisher's Fundamental Theorem of Natural Selection, which says that if you impose some selection pressure on a population, the rate at which that population responds to the selection pressure (lets say it’s the bigger rats that out-compete the smaller rats) then at what rate does the rat population start getting bigger? He showed that it's the additive variants that dominate the rate of evolution. It's easy to understand why if it's a nonlinear mechanism, you need to make the rat bigger. When you sexually reproduce, and that gets chopped apart, you might break the mechanism. Whereas, if each short allele has its own independent effect, you can inherit them without worrying about breaking the mechanisms. It was well known among a tiny theoretical population of biologists that adding variants was the dominant way that populations would respond to selection. That was already known. The other thing is that humans have been through a pretty tight bottleneck, and we're not that different from each other. It's very plausible that if I wanted to edit a human embryo, and make it into a frog, then there are all kinds of subtle nonlinear things I’d have to do. But all those identical nonlinear complicated subsystems are fixed in humans. You have the same system as I do. You have the not human, not frog or ape, version of that region of DNA, and so do I. But the small ways we differ are mostly little additive switches. That's this deep scientific discovery from over the last 5-10 years of work in this area. Now, you were asking about why evolution hasn't completely “optimized” all traits in humans already. I don't know if you’ve ever done deep learning or high-dimensional optimization, but in that high-dimensional space, you're often moving on a slightly-tilted surface. So, you're getting gains, but it's also flat. Even though you scale up your compute or data size by order of magnitude, you don't move that much farther. You get some gains, but you're never really at the global max of anything in these high dimensional spaces. I don't know if that makes sense to you. But it's pretty plausible to me that two things are important here. One is that evolution has not had that much time to optimize humans. The environment that humans live in changed radically in the last 10,000 years. For a while, we didn't have agriculture, and now we have agriculture. Now, we have a swipe left if you want to have sex tonight. The environment didn't stay fixed. So, when you say fully optimized for the environment, what do you mean? The ability to diagonalize matrices might not have been very adaptive 10,000 years ago. It might not even be adaptive now. But anyway, it's a complicated question that one can't reason naively about. “If God wanted us to be 10 feet tall, we'd be 10 feet tall.” Or “if it's better to be smart, my brain would be *this* big or something.” You can't reason naively about stuff like that.Dwarkesh Patel 29:04 I see. Yeah.. Okay. So I guess it would make sense then that for example, with certain health risks, the thing that makes you more likely to get diabetes or heart disease today might be… I don't know what the pleiotropic effect of that could be. But maybe that's not that important one year from now.Steve Hsu 29:17 Let me point out that most of the diseases we care about now—not the rare ones, but the common ones—manifest when you're 50-60 years old. So there was never any evolutionary advantage of being super long-lived. There's even a debate about whether the grandparents being around to help raise the kids lifts the fitness of the family unit.But, most of the time in our evolutionary past, humans just died fairly early. So, many of these diseases would never have been optimized against evolution. But, we see them now because we live under such good conditions, we can regulate people over 80 or 90 years.Dwarkesh Patel 29:57 Regarding the linearity and additivity point, I was going to make the analogy that– and I'm curious if this is valid– but when you're programming, one thing that's good practice is to have all the implementation details in separate function calls or separate programs or something, and then have your main loop of operation just be called different functions like, “Do this, do that”, so that you can easily comment stuff away or change arguments. This seemed very similar to that where by turning these names on and off, you can change what the next offering will be. And, you don't have to worry about actually implementing whatever the underlying mechanism is. Steve Hsu 30:41 Well, what you said is related to what Fisher proved in his theorems. Which is that, if suddenly, it becomes advantageous to have X, (like white fur instead of black fur) or something, it would be best if there were little levers that you could move somebody from black fur to white fur continuously by modifying those switches in an additive way. It turns out that for sexually reproducing species where the DNA gets scrambled up in every generation, it's better to have switches of that kind. The other point related to your software analogy is that there seem to be modular, fairly modular things going on in the genome. When we looked at it, we were the first group to have, initially, 20 primary disease conditions we had decent predictors for. We started looking carefully at just something as trivial as the overlap of my sparsely trained predictor. It turns on and uses *these* features for diabetes, but it uses *these* features for schizophrenia. It’s the stupidest metric, it’s literally just how much overlap or variance accounted for overlap is there between pairs of disease conditions. It's very modest. It's the opposite of what naive biologists would say when they talk about pleiotropy.They're just disjoint! Disjoint regions of your genome that govern certain things. And why not? You have 3 billion base pairs—there's a lot you can do in there. There's a lot of information there. If you need 1000 to control diabetes risk, I estimated you could easily have 1000 roughly independent traits that are just disjoint in their genetic dependencies. So, if you think about D&D, your strength, decks, wisdom, intelligence, and charisma—those are all disjoint. They're all just independent variables. So it's like a seven-dimensional space that your character lives in. Well, there's enough information in the few million differences between you and me. There's enough for 1000-dimensional space of variation.“Oh, how considerable is your spleen?” My spleen is a little bit smaller, yours is a little bit bigger - that can vary independently of your IQ. Oh, it's a big surprise. The size of your spleen can vary independently of the size of your big toe. If you do information theory, there are about 1000 different parameters, and I can vary independently with the number of variants I have between you and me. Because you understand some information theory, it’s trivial to explain, but try explaining to a biologist, you won't get very far.Dwarkesh Patel 33:27 Yeah, yeah, do the log two of the number of.. is that basically how you do it? Yeah.Steve Hsu 33:33 Okay. That's all it is. I mean, it's in our paper. We look at how many variants typically account for most of the variation for any of these major traits, and then imagine that they're mostly disjoint. Then it’s just all about: how many variants you need to independently vary 1000 traits? Well, a few million differences between you and me are enough. It's very trivial math. Once you understand the base and how to reason about information theory, then it's very trivial. But, it ain’t trivial for theoretical biologists, as far as I can tell.AgingDwarkesh Patel 34:13 But the result is so interesting because I remember reading in The Selfish Gene that, as he (Dawkins) hypothesizes that the reason we could be aging is an antagonistic clash. There's something that makes you healthier when you're young and fertile that makes you unhealthy when you're old. Evolution would have selected for such a trade-off because when you're young and fertile, evolution and your genes care about you. But, if there's enough space in the genome —where these trade-offs are not necessarily necessary—then this could be a bad explanation for aging, or do you think I'm straining the analogy?Steve Hsu 34:49 I love your interviews because the point you're making here is really good. So Dawkins, who is an evolutionary theorist from the old school when they had almost no data—you can imagine how much data they had compared to today—he would tell you a story about a particular gene that maybe has a positive effect when you're young, but it makes you age faster. So, there's a trade-off. We know about things like sickle cell anemia. We know stories about that. No doubt, some stories are true about specific variants in your genome. But that's not the general story. The general story you only discovered in the last five years is that thousands of variants control almost every trait and those variants tend to be disjoint from the ones that control the other trait. They weren't wrong, but they didn't have the big picture.Dwarkesh Patel 35:44 Yeah, I see. So, you had this paper, it had polygenic, health index, general health, and disease risk.. You showed that with ten embryos, you could increase disability-adjusted life years by four, which is a massive increase if you think about it. Like what if you could live four years longer and in a healthy state? Steve Hsu 36:05 Yeah, what's the value of that? What would you pay to buy that for your kid?Dwarkesh Patel 36:08 Yeah. But, going back to the earlier question about the trade-offs and why this hasn't already been selected for, if you're right and there's no trade-off to do this, just living four years older (even if that's beyond your fertility) just being a grandpa or something seems like an unmitigated good. So why hasn’t this kind of assurance hasn't already been selected for? Steve Hsu 36:35 I’m glad you're asking about these questions because these are things that people are very confused about, even in the field. First of all, let me say that when you have a trait that's controlled by 10,000 variants (eg. height is controlled by order 10,000 variants and probably cognitive ability a little bit more), the square root of 10,000 is 100. So, if I could come to this little embryo, and I want to give it one extra standard deviation of height, I only need to edit 100. I only need to flip 100 minus variance to plus variance. These are very rough numbers. But, one standard deviation is the square root of “n”. If I flip a coin “n” times, I want a better outcome in terms of the number of ratio heads to tails. I want to increase it by one standard deviation. I only need to flip the square root of “n” heads because if you flip a lot, you will get a narrow distribution that peaks around half, and the width of that distribution is the square root of “n”. Once I tell you, “Hey, your height is controlled by 10,000 variants, and I only need to flip 100 genetic variants to make you one standard deviation for a male,” (that would be three inches tall, two and a half or three inches taller), you suddenly realize, “Wait a minute, there are a lot of variants up for grabs there. If I could flip 500 variants in your genome, I would make you five standard deviations taller, you'd be seven feet tall.” I didn't even have to do that much work, and there's a lot more variation where that came from. I could have flipped even more because I only flipped 500 out of 10,000, right? So, there's this quasi-infinite well of variation that evolution or genetic engineers could act on. Again, the early population geneticists who bred corn and animals know this. This is something they explicitly know about because they've done calculations. Interestingly, the human geneticists who are mainly concerned with diseases and stuff, are often unfamiliar with the math that the animal breeders already know. You might be interested to know that the milk you drink comes from heavily genetically-optimized cows bred artificially using almost exactly the same technologies that we use at genomic prediction. But, they're doing it to optimize milk production and stuff like this. So there is a big well of variance. It's a consequence of the trait's poly genicity. On the longevity side of things, it does look like people could “be engineered” to live much longer by flipping the variants that make the risk for diseases that shorten your life. The question is then “Why didn't evolution give us life spans of thousands of years?” People in the Bible used to live for thousands of years. Why don't we? I mean, *chuckles* that probably didn’t happen. But the question is, you have this very high dimensional space, and you have a fitness function. How big is the slope in a particular direction of that fitness function? How much more successful reproductively would Joe caveman have been if he lived to be 150 instead of only, 100 or something? There just hasn't been enough time to explore this super high dimensional space. That's the actual answer. But now, we have the technology, and we're going to f*****g explore it fast. That's the point that the big lightbulb should go off. We’re mapping this space out now. Pretty confident in 10 years or so, with the CRISPR gene editing technologies will be ready for massively multiplexed edits. We'll start navigating in this high-dimensional space as much as we like. So that's the more long-term consequence of the scientific insights.Dwarkesh Patel 40:53 Yeah, that's super interesting. What do you think will be the plateau for a trait of how long you’ll live? With the current data and techniques, you think it could be significantly greater than that?Steve Hsu 41:05 We did a simple calculation—which amazingly gives the correct result. This polygenic predictor that we built (which isn't perfect yet but will improve as we gather more data) is used in selecting embryos today. If you asked, out of a billion people, “What's the best person typically, what would their score be on this index and then how long would they be predicted to live?”’ It's about 120 years. So it's spot on. One in a billion types of person lives to be 120 years old. How much better can you do? Probably a lot better. I don't want to speculate, but other nonlinear effects, things that we're not taking into account will start to play a role at some point. So, it's a little bit hard to estimate what the true limiting factors will be. But one super robust statement, and I'll stand by it, debate any Nobel Laureate in biology who wants to discuss it even, is that there are many variants available to be selected or edited. There's no question about that. That's been established in animal breeding in plant breeding for a long time now. If you want a chicken that grows to be *this* big, instead of *this* big, you can do it. You can do it if you want a cow that produces 10 times or 100 times more milk than a regular cow. The egg you ate for breakfast this morning, those bio-engineered chickens that lay almost an egg a day… A chicken in the wild lays an egg a month. How the hell did we do that? By genetic engineering. That's how we did it. Dwarkesh Patel 42:51 Yeah. That was through brute artificial selection. No fancy machine learning there.Steve Hsu 42:58 Last ten years, it's gotten sophisticated machine learning genotyping of chickens. Artificial insemination, modeling of the traits using ML last ten years. For cow breeding, it's done by ML. First Mover AdvantageDwarkesh Patel 43:18 I had no idea. That's super interesting. So, you mentioned that you're accumulating data and improving your techniques over time, is there a first mover advantage to a genomic prediction company like this? Or is it whoever has the newest best algorithm for going through the biobank data? Steve Hsu 44:16 That's another super question. For the entrepreneurs in your audience, I would say in the short run, if you ask what the valuation of GPB should be? That's how the venture guys would want me to answer the question. There is a huge first mover advantage because they're important in the channel relationships between us and the clinics. Nobody will be able to get in there very easily when they come later because we're developing trust and an extensive track record with clinics worldwide—and we're well-known. So could 23andme or some company with a huge amount of data—if they were to get better AI/ML people working on this—blow us away a little bit and build better predictors because they have much more data than we do? Possibly, yes. Now, we have had core expertise in doing this work for years that we're just good at it. Even though we don't have as much data as 23andme, our predictors might still be better than theirs. I'm out there all the time, working with biobanks all around the world. I don't want to say all the names, but other countries are trying to get my hands on as much data as possible.But, there may not be a lasting advantage beyond the actual business channel connections to that particular market. It may not be a defensible, purely scientific moat around the company. We have patents on specific technologies about how to do the genotyping or error correction on the embryo, DNA, and stuff like this. We do have patents on stuff like that. But this general idea of who will best predict human traits from DNA? It's unclear who's going to be the winner in that race. Maybe it'll be the Chinese government in 50 years? Who knows?Dwarkesh Patel 46:13 Yeah, that's interesting. If you think about a company Google, theoretically, it's possible that you could come up with a better algorithm than PageRank and beat them. But it seems like the engineer at Google is going to come up with whatever edge case or whatever improvement is possible.Steve Hsu 46:28 That's exactly what I would say. PageRank is deprecated by now. But, even if somebody else comes up with a somewhat better algorithm if they have a little bit more data, if you have a team doing this for a long time and you're focused and good, it's still tough to beat you, especially if you have a lead in the market.Dwarkesh Patel 46:50 So, are you guys doing the actual biopsy? Or is it just that they upload the genome, and you're the one processing just giving recommendations? Is it an API call, basically?Steve Hsu 47:03 It's great, I love your question. It is totally standard. Every good IVF clinic in the world regularly takes embryo biopsies. So that's standard. There’s a lab tech doing that. Okay. Then, they take the little sample, put it on ice, and ship it. The DNA as a molecule is exceptionally robust and stable. My other startup solves crimes that are 100 years old from DNA that we get from some semen stain on some rape victim, serial killer victims bra strap, we've done stuff that.Dwarkesh Patel 47:41 Jack the Ripper, when are we going to solve that mystery?Steve Hsu 47:44 If they can give me samples, we can get into that. For example, we just learned that you could recover DNA pretty well if someone licks a stamp and puts on their correspondence. If you can do Neanderthals, you can do a lot to solve crimes. In the IVF workflow, our lab, which is in New Jersey, can service every clinic in the world because they take the biopsy, put it in a standard shipping container, and send it to us. We’re actually genotyping DNA in our lab, but we've trained a few of the bigger clinics to do the genotyping on their site. At that point, they upload some data into the cloud and then they get back some stuff from our platform. And at that point it's going to be the whole world, every human who wants their kid to be healthy and get the best they can– that data is going to come up to us, and the report is going to come back down to their IVF physician. Dwarkesh Patel 48:46 Which is great if you think that there's a potential that this technology might get regulated in some way, you could go to Mexico or something, have them upload the genome (you don't care what they upload it from), and then get the recommendations there. Steve Hsu 49:05 I think we’re going to evolve to a point where we are going to be out of the wet part of this business, and only in the cloud and bit part of this business. No matter where it is, the clinics are going to have a sequencer, which is *this* big, and their tech is going to quickly upload and retrieve the report for the physician three seconds later. Then, the parents are going to look at it on their phones or whatever. We’re basically there with some clinics. It’s going to be tough to regulate because it’s just this. You have the bits and you’re in some repressive, terrible country that doesn’t allow you to select for some special traits that people are nervous about, but you can upload it to some vendor that’s in Singapore or some free country, and they give you the report back. Doesn’t have to be us, we don’t do the edgy stuff. We only do the health-related stuff right now. But, if you want to know how tall this embryo is going to be…I’ll tell you a mind-blower! When you do face recognition in AI, you're mapping someone's face into a parameter space on the order of hundreds of parameters, each of those parameters is super heritable. In other words, if I take two twins and photograph them, and the algorithm gives me the value of that parameter for twin one and two, they're very close. That's why I can't tell the two twins apart, and face recognition can ultimately tell them apart if it’s really good system. But you can conclude that almost all these parameters are identical for those twins. So it's highly heritable. We're going to get to a point soon where I can do the inverse problem where I have your DNA and I predict each of those parameters in the face recognition algorithm and then reconstruct the face. If I say that when this embryo will be 16, that is what she will look like. When she's 32, this is what she's going to look like. I'll be able to do that, for sure. It's only an AI/ML problem right now. But basic biology is clearly going to work. So then you're going to be able to say, “Here's a report. Embryo four is so cute.” Before, we didn't know we wouldn't do that, but it will be possible. Dwarkesh Patel 51:37 Before we get married, you'll want to see what their genotype implies about their faces' longevity. It's interesting that you hear stories about these cartel leaders who will get plastic surgery or something to evade the law, you could have a check where you look at a lab and see if it matches the face you would have had five years ago when they caught you on tape.Steve Hsu 52:02 This is a little bit back to old-school Gattaca, but you don't even need the face! You can just take a few molecules of skin cells and phenotype them and know exactly who they are. I've had conversations with these spooky Intel folks. They're very interested in, “Oh, if some Russian diplomat comes in, and we think he's a spy, but he's with the embassy, and he has a coffee with me, and I save the cup and send it to my buddy at Langley, can we figure out who this guy is? And that he has a daughter who's going to Chote? Can do all that now.Dwarkesh Patel 52:49 If that's true, then in the future, world leaders will not want to eat anything or drink. They'll be wearing a hazmat suit to make sure they don't lose a hair follicle.Steve Hsu 53:04 The next time Pelosi goes, she will be in a spacesuit if she cares. Or the other thing is, they're going to give it. They're just going to be, “Yeah, my DNA is everywhere. If I'm a public figure, I can't track my DNA. It's all over.”Dwarkesh Patel 53:17 But the thing is, there's so much speculation that Putin might have cancer or something. If we have his DNA, we can see his probability of having cancer at age 70, or whatever he is, is 85%. So yeah, that’d be a very verified rumor. That would be interesting. Steve Hsu 53:33 I don't think that would be very definitive. I don't think we'll reach that point where you can say that Putin has cancer because of his DNA—which I could have known when he was an embryo. I don't think it's going to reach that level. But, we could say he is at high risk for a type of cancer. Genomics in datingDwarkesh Patel 53:49 In 50 or 100 years, if the majority of the population is doing this, and if the highly heritable diseases get pruned out of the population, does that mean we'll only be left with lifestyle diseases? So, you won't get breast cancer anymore, but you will still get fat or lung cancer from smoking?Steve Hsu 54:18 It's hard to discuss the asymptotic limit of what will happen here. I'm not very confident about making predictions like that. It could get to the point where everybody who's rich or has been through this stuff for a while, (especially if we get the editing working) is super low risk for all the top 20 killer diseases that have the most life expectancy impact. Maybe those people live to be 300 years old naturally. I don't think that's excluded at all. So, that's within the realm of possibility. But it's going to happen for a few lucky people like Elon Musk before it happens for shlubs like you and me. There are going to be very angry inequality protesters about the Trump grandchildren, who, models predict will live to be 200 years old. People are not going to be happy about that.Dwarkesh Patel 55:23 So interesting. So, one way to think about these different embryos is if you're producing multiple embryos, and you get to select from one of them, each of them has a call option, right? Therefore, you probably want to optimize for volatility as much, or if not more than just the expected value of the trait. So, I'm wondering if there are mechanisms where you can increase the volatility in meiosis or some other process. You just got a higher variance, and you can select from the tail better.Steve Hsu 55:55 Well, I'll tell you something related, which is quite amusing. So I talked with some pretty senior people at the company that owns all the dating apps. So you can look up what company this is, but they own Tinder and Match. They’re kind of interested in perhaps including a special feature where you upload your genome instead of Tinder Gold / Premium. And when you match- you can talk about how well you match the other person based on your genome. One person told me something shocking. Guys lie about their height on these apps. Dwarkesh Patel 56:41 I’m shocked, truly shocked hahaha. Steve Hsu 56:45 Suppose you could have a DNA-verified height. It would prevent gross distortions if someone claims they're 6’2 and they’re 5’9. The DNA could say that's unlikely. But no, the application to what you were discussing is more like, “Let's suppose that we're selecting on intelligence or something. Let's suppose that the regions where your girlfriend has all the plus stuff are complementary to the regions where you have your plus stuff. So, we could model that and say, because of the complementarity structure of your genome in the regions that affect intelligence, you're very likely to have some super intelligent kids way above your, the mean of your you and your girlfriend's values. So, you could say things like it being better for you to marry that girl than another. As long as you go through embryo selection, we can throw out the bad outliers. That's all that's technically feasible. It's true that one of the earliest patent applications, they'll deny it now. What's her name? Gosh, the CEO of 23andme…Wojcicki, yeah. She'll deny it now. But, if you look in the patent database, one of the very earliest patents that 23andme filed when they were still a tiny startup was about precisely this: Advising parents about mating and how their kids would turn out and stuff like this. We don't even go that far in GP, we don't even talk about stuff like that, but they were thinking about it when they founded 23andme.Dwarkesh Patel 58:38 That is unbelievably interesting. By the way, this just occurred to me—it's supposed to be highly heritable, especially people in Asian countries, who have the experience of having grandparents that are much shorter than us, and then parents that are shorter than us, which suggests that the environment has a big part to play in it malnutrition or something. So how do you square that our parents are often shorter than us with the idea that height is supposed to be super heritable.Steve Hsu 59:09 Another great observation. So the correct scientific statement is that we can predict height for people who will be born and raised in a favorable environment. In other words, if you live close to a McDonald's and you're able to afford all the food you want, then the height phenotype becomes super heritable because the environmental variation doesn't matter very much. But, you and I both know that people are much smaller if we return to where our ancestors came from, and also, if you look at how much food, calories, protein, and calcium they eat, it's different from what I ate and what you ate growing up. So we're never saying the environmental effects are zero. We're saying that for people raised in a particularly favorable environment, maybe the genes are capped on what can be achieved, and we can predict that. In fact, we have data from Asia, where you can see much bigger environmental effects. Age affects older people, for fixed polygenic scores on the trait are much shorter than younger people.Ancestral populationsDwarkesh Patel 1:00:31 Oh, okay. Interesting. That raises that next question I was about to ask: how applicable are these scores across different ancestral populations?Steve Hsu 1:00:44 Huge problem is that most of the data is from Europeans. What happens is that if you train a predictor in this ancestry group and go to a more distant ancestry group, there's a fall-off in the prediction quality. Again, this is a frontier question, so we don't know the answer for sure. But many people believe that there's a particular correlational structure in each population, where if I know the state of this SNP, I can predict the state of these neighboring SNPs. That is a product of that group's mating patterns and ancestry. Sometimes, the predictor, which is just using statistical power to figure things out, will grab one of these SNPs as a tag for the truly causal SNP in there. It doesn't know which one is genuinely causal, it is just grabbing a tag, but the tagging quality falls off if you go to another population (eg. This was a very good tag for the truly causal SNP in the British population. But it's not so good a tag in the South Asian population for the truly causal SNP, which we hypothesize is the same). It's the same underlying genetic architecture in these different ancestry groups. We don't know if that's a hypothesis. But even so, the tagging quality falls off. So my group spent a lot of our time looking at the performance of predictor training population A, and on distant population B, and modeling it trying to figure out trying to test hypotheses as to whether it's just the tagging decay that’s responsible for most of the faults. So all of this is an area of active investigation. It'll probably be solved in five years. The first big biobanks that are non-European are coming online. We're going to solve it in a number of years.Dwarkesh Patel 1:02:38 Oh, what does the solution look like? Unless you can identify the causal mechanism by which each SNP is having an effect, how can you know that something is a tag or whether it's the actual underlying switch?Steve Hsu 1:02:54 The nature of reality will determine how this is going to go. So we don't truly know if the innate underlying biology is true. This is an amazing thing. People argue about human biodiversity and all this stuff, and we don't even know whether these specific mechanisms that predispose you to be tall or having heart disease are the same in these different ancestry groups. We assume that it is, but we don't know that. As we get further away to Neanderthals or Homo Erectus, you might see that they have a slightly different architecture than we do. But let's assume that the causal structure is the same for South Asians and British people. Then it's a matter of improving the tags. How do I know if I don't know which one is causal? What do I mean by improving the tags? This is a machine learning problem. If there's a SNP, which is always coming up as very significant when I use it across multiple ancestry groups, maybe that one's casual. As I vary the tagging correlations in the neighborhood of that SNP, I always find that that one is the intersection of all these different sets, making me think that one's going to be causal. That's a process we're engaged in now—trying to do that. Again, it's just a machine learning problem. But we need data. That's the main issue.Dwarkesh Patel 1:04:32 I was hoping that wouldn't be possible, because one way we might go about this research is that it itself becomes taboo or causes other sorts of bad social consequences if you can definitively show that on certain traits, there are differences between ancestral populations, right? So, I was hoping that maybe there was an evasion button where we can't say because they're just tags and the tags might be different between different ancestral populations. But with machine learning, we’ll know.Steve Hsu 1:04:59 That's the situation we're in now, where you have to do some fancy analysis if you want to claim that Italians have lower height potential than Nordics—which is possible. There's been a ton of research about this because there are signals of selection. The alleles, which are activated in height predictors, look like they've been under some selection between North and South Europe over the last 5000 years for whatever reason. But, this is a thing debated by people who study molecular evolution. But suppose it's true, okay? That would mean that when we finally get to the bottom of it, we find all the causal loci for height, and the average value for the Italians is lower than that for those living in Stockholm. That might be true. People don't get that excited? They get a little bit excited about height. But they would get really excited if this were true for some other traits, right?Suppose the causal variants affecting your level of extraversion are systematic, that the average value of those weighed the weighted average of those states is different in Japan versus Sicily. People might freak out over that. I'm supposed to say that's obviously not true. How could it possibly be true? There hasn't been enough evolutionary time for those differences to arise. After all, it's not possible that despite what looks to be the case for height over the last 5000 years in Europe, no other traits could have been differentially selected for over the last 5000 years. That's the dangerous thing. Few people understand this field well enough to understand what you and I just discussed and are so alarmed by it that they're just trying to suppress everything. Most of them don't follow it at this technical level that you and I are just discussing. So, they're somewhat instinctively negative about it, but they don't understand it very well.Dwarkesh Patel 1:07:19 That's good to hear. You see this pattern that by the time that somebody might want to regulate or in some way interfere with some technology or some information, it already has achieved wide adoption. You could argue that that's the case with crypto today. But if it's true that a bunch of IVF clinics worldwide are using these scores to do selection and other things, by the time people realize the implications of this data for other kinds of social questions, this has already been an existing consumer technology.Is this eugenics?Steve Hsu 1:07:58 That's true, and the main outcry will be if it turns out that there are massive gains to be had, and only the billionaires are getting them. But that might have the consequence of causing countries to make this free part of their national health care system. So Denmark and Israel pay for IVF. For infertile couples, it's part of their national health care system. They're pretty aggressive about genetic testing. In Denmark, one in 10 babies are born through IVF. It's not clear how it will go. But we're in for some fun times. There's no doubt about that.Dwarkesh Patel 1:08:45 Well, one way you could go is that some countries decided to ban it altogether. And another way it could go is if countries decided to give everybody free access to it. If you had to choose between the two, you would want to go for the second one. Which would be the hope. Maybe only those two are compatible with people's moral intuitions about this stuff. Steve Hsu 1:09:10 It’s very funny because most wokist people today hate this stuff. But, most progressives like Margaret Sanger, or anybody who was the progressive intellectual forebears of today's wokist, in the early 20th century, were all that we would call today in Genesis because they were like, “Thanks to Darwin, we now know how this all works. We should take steps to keep society healthy and (not in a negative way where we kill people we don't like, but we should help society do healthy things when they reproduce, and have healthy kids).” Now, this whole thing has just been flipped over among progressives. Dwarkesh Patel 1:09:52 Even in India, less than 50 years ago, Indira Gandhi, she's on the left side of India's political spectrum. She was infamous for putting on these forced sterilization programs. Somebody made an interesting comment about this where they were asked, “Oh, is it true that history always tilts towards progressives? And if so, isn't everybody else doomed? Aren't their views doomed?”The person made a fascinating point: whatever we consider left at the time tends to be winning. But what is left has changed a lot over time, right? In the early 20th century, prohibition was a left cause. It was a progressive cause, and that changed, and now the opposite is the left cause. But now, legalizing pot is progressive. Exactly. So, if Conquest’s second law is true, and everything tilts leftover time, just change what is left is, right? That's the solution. Steve Hsu 1:10:59 No one can demand that any of these woke guys be intellectually self-consistent, or even say the same things from one year to another? But one could wonder what they think about these literally Communist Chinese. They’re recycling huge parts of their GDP to help the poor and the southern stuff. Medicine is free, education is free, right? They're clearly socialists, and literally communists. But in Chinese, the Chinese characters for eugenics is a positive thing. It means healthy production. But more or less, the whole viewpoint on all this stuff is 180 degrees off in East Asia compared to here, and even among the literal communists—so go figure.Dwarkesh Patel 1:11:55 Yeah, very based. So let's talk about one of the traits that people might be interested in potentially selecting for: intelligence. What is the potential for us to acquire the data to correlate the genotype with intelligence?Steve Hsu 1:12:15 Well, that's the most personally frustrating aspect of all of this stuff. If you asked me ten years ago when I started doing this stuff what were we going to get, everything was gone. On the optimistic side of what I would have predicted, so everything's good. Didn't turn out to be interactively nonlinear, or it didn't turn out to be interactively pleiotropic. All these good things, —which nobody could have known a priori how they would work—turned out to be good for gene engineers of the 21st century. The one frustrating thing is because of crazy wokeism, and fear of crazy wokists, the most interesting phenotype of all is lagging b
In this final episode of our book report on The Character of Physical Law, we go through Dr. Feynman's final lecture, Seeking New Laws, in which he describes how science works, and the methods physicists must use to attempt to discover new fundamental aspects of the natural world.
Continuing our book report on The Character of Physical Law, we read through the 5th and 6th lectures, The Distinction of Past and Future and Probability and Uncertainty. These are discussions on entropy and quantum mechanics, done in Dr. Feynman's unique style.
Abandoning the idea of one God leads to the invention of other gods, because the invention of meaning must happen. And if you can invent gods and meaning, then you can invent anything. This slope becomes slippery fast, like a Minnesota sidewalk on the first autumn sleet when the temperature hovers around 30 degrees: you may be falling down soon. Once you reject a singular God and make a golden statue or animal or mascot into a god, then it's no longer something to be taken seriously. Why? Because a statue or animal is ridiculous as an object of power. Yes, an eagle or cougar or lion is cool because they are strong and wild, but that doesn't give them divine powers. It just means they are good hunters for fish and rabbits and wildebeasts and it's fascinating for us to watch them. They cannot ponder ideas like justice or mercy or the best way to organize an economy. The idea of God as something contained in this world is too small and not worthy of worship. It's a completely different concept of God from the idea of “being itself” or the creator of the universe. This is why when Moses asks what is God's name, he gets the answer, "I AM WHO I AM." God is. He is existence itself. I guess the Bible translators like to put that in all capital letters, because without him nothing else exists. There is nothing before God. We are only because he said so, and he can unsay so whenever he wants, too. We don't believe that Zeus really exists. We just wink and repeat the tale because it's a fun story. But Zeus is more like a mascot, because he doesn't demand anything from his “followers.” In fact, Artemis in Ephesus is basically like the modern day worship of the Bulls in Chicago or the Giants in New York. It's funny that many of the modern team mascots can be mapped to old world idols or myths. These small gods are much like the sports teams of the ancient world, or you could say our sports teams are much like the idolatry of the ancient world. Sports fans today give as much time and energy to their animals and icons as the old world did to lower case gods. I'll probably do a future episode on this because sports teams and mascots match up too well to old city-state idolatry. We even have statues and clothing and rituals for our worship of these sports franchises and teams that represent our cities and schools. The problem with these small gods is this: if you can make a statue into a god, then a trophy or a diploma or a team or a house or a woman or a drug can just as easily become the object of worship, the giver of meaning. Many say that Catholics worship statues, so I should point to a correction here. We don't worship statues, we have sacred art and pray for intercession, but rather than get derailed, here's a good article about statues in Catholic churches. The point of all sacred art is to elevate the one true God, the Trinity. The object has no power or force or spirit, but aids in worship.What about spirits? What about the attacks and spiritual combat and all that jazz? Isn't this just about monotheism versus polytheism? If there is only one God, then what's with the spirits and demons and angels? It's not just a word game if the one true God is real. Both the Apostle's Creed and Nicene Creed begin with words about believing in God, which means it is the most important statement of faith, as it leads the charge for the remainder of the creeds. Since the cultures surrounding Israel tell the tales of other gods, its like there are warring propaganda campaigns happening. Just as the the Bible argues for the one god, the Egyptians and Greeks and others argue for the many. It is critical that the Israelites protect and worship the correct God, otherwise they will fall into the trap of those cultures around them. And that's exactly what happens whenever they fall for idols; once in the trap, they tumble into disorder. The story of Noah is about falling into mayhem, sin, and disorder. The Golden Calf incident happens when the people abandon the one God. The book of Judges is full of these cycles of order, disorder, and re-order as the people believe, then rebel, and then return to the one God. It's the story of the Prodigal Son on repeat, but instead of one man it's a nation.The whole story of the Bible is a re-assertion of the proper order where the Most High God, the one God, rules over the people and all creation. The story of Jesus is the story of the one true God, the one power of the universe, coming back to reclaim his creation from the lesser gods, to steer the whole thing back to the start, to the simple beginning. The "turning away" from God reached all nations. The city-states and tribes believed that this was the proper state of affairs. For example, the Greeks had statues of Athena in Athens, as she was the patron goddess of the city. As should come as no surprise, Athens saw itself as wise and strong, like Athena. The city modeled itself after its selected gods. Athens and Athena do a spiritual mirroring, just as the 115th Psalm explains to us how idols work. The creator of the idol becomes like the idol. “Their makers will be like them, and anyone who trusts in them.” (Ps 115:4-8) Corinth, a sea-port city, venerated Poseidon. Not exactly a shock, since a port city hugs the sea. Rhodes had it's famous giant named Colossus and worshiped Helios, the sun god. A more interesting story around the old world of patron gods is Ephesus, a city that is in modern Turkey. Ephesus held Artemis as the goddess. St. Paul shows up and causes a riot when he starts converting people to Christ, away from Artemis. Interestingly, the local silversmith is upset because he will no longer be able to sell trinkets and worship material if everyone becomes a Christian, so the riot is more about money than devotion. (The silversmiths probably didn't realize they could start selling all kinds of new souvenirs, as people today like to buy and sell Christian souvenirs, and I'm not going to dive into that question right now, but I will say I am all-in on sacred art.) The riot upsets the balance of the city, as there is a perceived order around the goddess Artemis. Introducing a new centerpiece of faith and culture scares the people because they are already settled into their existing structure. Where there is order, any hint of disorder will cause worry, and when the riots begin the disorder has arrived. When the anchors for our life are in place and the wind is calm, we don't want to pull up anchor and move. In the case of Ephesus, the city was comfortable in its undemanding idolatry. You can see this happening today. A power struggle between those who believe in one God is underway. There is a third column in the battle with those of no god, but they were certainly present in the past as well. The gods of modernity are not as obvious to us, but they are there. This is the story of human history. You can read about it in the mythology of peoples, just like you can read an allegorical unfolding of it in the novel, Lord of the Flies. The first humans, when we first stood up in the Africa savanna, in that first garden, we became aware of our difference from the other animals. We had to discover how to live, how to act, and how to rule. Eventually, we had to figure out what to worship. We had to spend a lot of time mulling over the idea of origins. Most importantly, we had to decide if there were no gods, many gods, or one God, because only one of those things could be true. We have tried all three options. In thirty thousand years of human drama, the experiments surely happened more than once and maybe several hundred times. The story of the Bible is the story of a nation that has cast their vote for the one God, while the story of the Greeks, Romans, and Babylonians is the story of nations that followed many gods. Surely the claim sounds dramatic. To say that every nation but one has fallen prey to the devil or spirits makes the claim extreme. But that is exactly the claim. That is what the story of the Tower of Babel describes, as the scattering of the peoples of the world led to the invention of strange gods. The reason the Tower of Babel is the last story before Abraham's entrance in the next scene is because the scattering explains the world that Abraham is born into, which is the pagan world of many gods. In the Tower of Babel story, God withdrew from people when they attempted to pull him down to earth, which is just a way of saying that they tried to become God. They wanted to become god or make a deal with God. When neither of those plans worked, they turned from god and the nations were born. With the nations came the lesser gods. That is how the first half of Genesis concludes, which leads to Abraham. This is where things start to get interesting, if the ancient language and lists of names don't make your eyes glaze over. I can quickly lose focus when I dive into the begat, begat, begat paragraphs and miss the gold in them “begats.” I'll do a brief and possibly bad retelling of Abraham's life, hitting only the important points that may help me tie this together with Uranus. Abraham lived in a place called Haran, named after one of his own relatives. Haran is believed to have been a place of a moon-cult, meaning Abraham's family likely worshiped a god of the Mesopotamian or Sumerian pantheon. In other words, Abraham is born in a world that is fully pagan and worships many gods. His people are not believers in the one true God. No, his people are like everyone else. They have rejected the one true God. That is why Abraham's story is so important in the Bible. When Abraham is born, Uranus and Osiris and all of the other primary pantheon gods have been overthrown by child gods. There are god and goddesses and idols all over the place. The rebellion has already occurred and the one true God is not in the ballgame. Abraham is living in the age where mythology is everywhere. These events occur somewhere around 1800 or 1600 B.C. The story of Abraham begins when he is called by God to venture out from his home, leaving his relatives, his country, and his father's house, which includes leaving the old familiar moon-god behind, too. When called, he goes without questioning the call, in a kind of “drop the nets” move like that of Peter and Andrew when the call from Jesus happens, or like Mary's Fiat when the angel Gabriel visits her. This break from Abraham's family starts a new life for him, one of total trust in the one God that he hears speaking to him. This is a radical change from the human pride that happened just one chapter earlier in the Tower of Babel story. Without a doubt, this marks a turning point of Act I of the Bible. Since the word repent means to “turn” you might say that this the point of repentance, the return to the one God. There is much to go into on that, but I only want to go into one more thing here about Abraham. The reason why Abraham is the Patriarch, the big P, is because he represents the return of worship to the one true God. No one else is doing this. It's not cool or trendy at all. So God promises Abraham land, descendants, and fame. Abraham sojourns in Canaan, Egypt, and Bethel. After various adventures and material success, he gets caught up in a local war. We learn that he has some money and a small army by now, as he takes his soldiers into battle to save his nephew. With only 318 men, he defeats four local kings. Victorious, Abraham returns from the war with all kinds of loot, not to mention glory. Local kings come to meet him. A mysterious king arrives, the king of Salem. Now wait a minute, I've heard of Salem before. Where have I heard this? There is Salem, the setting for Days of Our Lives, the soap opera, where Bo and Hope live. Then there is Salem, Massachusetts where the famous witch trials happened and the setting of Henry Miller's play, the Crucible. But wait, no, I've heard of Salem in another place before, but part of a larger word: Jerusalem.Not only do we have the one God coming back into the game of human life, but we have the city of Jerusalem being introduced. Oh, and what's this? He's brought food and something to drink. But he hasn't brought the usual barbecue pot-luck goat or bull, he's brought something different to this celebration. He has brought bread and wine. Yes, bread and wine. Now we have Abraham in Jerusalem with a king that brought bread and wine and it's starting to feel eery and weird because we know all of these elements from the life of Christ, but that happens nearly 2,000 years after this event. Then it gets weirder and more eery. This king lived in the time when a king was also a priest. Those job titles were one and the same, so even more interesting, he comes to meet with Abraham and offer this bread and wine as a sacrifice. (This might begin to raise the hairs on your neck at this point if you haven't heard this before.) But that's not all that's interesting about this dude with the long name of Melchizedek. He is not just a priestly king, he is a priestly-king of the “God Most High.” This is important. He is not a priest of a moon-god, no, he is said to be a priest of the one God, the true God, the only God, which is referred to in the passage as the '“Most High God” or “God Most High.” And if that were not enough, there is more to this little verse, something that my blind eyes passed right over every time I saw this passage, is that this God Most High is directly referred to as the “creator of heaven and earth.” In other words, this ain't Uranus. This isn't Osiris. This isn't Odin, or the moon-cult, or Hawaiian Pele, or the Spirit Horse, or the Great Pumpkin. This isn't any of the primary gods of any pantheon. This is clearly a reference to the God of Genesis, Chapter 1, Verse 1. This guy came to Salem with bread and wine and he wants to praise the one God. This priest-king of Salem just shows up out of the blue, and he is either one of the last people on planet earth along with Abraham that speaks of the “Most High God,” or, perhaps he is God himself visiting Abraham. I don't know what to make of it, but that is one option for interpretation. Some people believe this is a theophany, an event where God reveals himself, like in the burning bush or in the Transfiguration. I'm not sure about that so I'll leave it to the experts and many centuries of more well-versed thinkers. Either way, whether Melchizedek is an ordinary man or a manifestation of the God Most High, this is the moment where Abraham is blessed and where Jerusalem becomes the sacred site of the chosen people. (Note: he's still called Abram at this point, not yet Abraham)Melchizedek, king of Salem, brought out bread and wine. He was a priest of God Most High. He blessed Abram with these words:“Blessed be Abram by God Most High,the creator of heaven and earth;And blessed be God Most High,who delivered your foes into your hand.” (Gen 14:18)This is huge. I know it probably doesn't seem like it, but this is huge. This is the moment where Jerusalem becomes tied into everything to follow, where bread and wine become important for future references regarding sacrifice, and where we hear this interesting term, God Most High. There's more here too. There's always more. Briefly, I need to point out this last line where Melchizedek blesses Abraham and praises God, saying he “delivered your foes into your hand.” This battle that took place is the compelling event that brings Melchizedek to make this blessing. Interestingly, the battle was a rescue mission. Abraham's nephew is Lot, who lives near the infamous cities of Sodom and Gomorrah, which have not yet been destroyed. Earlier on in chapter 13, Lot and Abraham went separate ways. The buddy movie ended when Lot moved to the fertile Jordan Valley, which is the best land, and Abraham takes Canaan. But later, the local tribes invade Lot's land and he is captured. This is the first of three times that Lot finds himself in deep water. Abraham's entry into the war is for the purpose of saving Lot and his people, which he does. After saving the people and goods of Lot and Sodom, Abraham refuses to receive a reward, having sworn to the “Lord God Most High, maker of heaven and earth” that he will not profit from this war, and instead Abraham gives ten percent of his property to God. This means that Abraham went to war, won the war, received nothing, and ended up giving away his own property. Immediately after Melchizedek brings out the bread and wine and makes the blessing, Abraham becomes generous and magnanimous. When Melchizedek states that it was God that delivered the foes, Abraham seems to be changed because generosity flows from him. I'm just going to leave this episode with this thought: Lot chooses the easier path and ends up suffering for it. The land he chose was fertile and lush, but it leads him to a hard life and eventually his own kidnapping. All that glistens is not gold, it seems. Abraham must save him, but only wins the battle with God's help. The cities that Lot occupies return to corruption and lawlessness, as does he. Abraham pleads with God for another rescue, for mercy, but this time God obliterates the people and the cities. This is the angry God, the hellfire God. The rescue mission for the sinners of Lot's world happens only once. Mercy has already been shown with the rescue mission, and in the second round comes judgement. That is food for thought. The hard thing about reading the Bible is that you can so easily pass over something like a phrase, “God Most High” because we're thinking in the 21st century instead of 1600 B.C. That little phrase refers to the God that was first and foremost and came before anything that existed, including Uranus. This is the one God, before Uranus or anyone or anything else. Nothing exists without this God speaking up and saying so. (Literally, God spoke and made all things.) Reading mythology can get confusing real fast. Each ancient storyteller has a slightly different take on the tale, along with different motives. The mythologies of the ancient past can lead into endless caves of exploration because it becomes complicated, as the family trees and interactions cross into one another. Then there is war and culture clash, which leads to re-writing and re-purposing conquered gods and neighboring heroes into the dominant myth, and of course the dominant myths of the ancient world were Greek and Roman and Egyptian, but even those mythologies are extremely complicated. There is a overarching theme of might makes right, of the powerless overthrowing the powerful, like a food chain or pecking order that keeps changing and squirming around. This leads me to a point that I've taken far to long to arrive at, but it's a quote by a famous physicist named Richard Feynman, which goes like this: You can recognize truth by its beauty and simplicity. When you get it right, it is obvious that it is right—at least if you have any experience—because usually what happens is that more comes out than goes in.... The inexperienced, the crackpots, and people like that, make guesses that are simple, but you can immediately see that they are wrong, so that does not count. Others, the inexperienced students, make guesses that are very complicated, and it sort of looks as if it is all right, but I know it is not true because the truth always turns out to be simpler than you thought.This is exactly how it feels to discover, or re-discover, the “one God” theory. The one God makes sense, while the mess and tangle and overcomplicated tales of mythological systems lead to confusion and endless searching. There is a restlessness, like that of Odysseus, a constant searching and changing and shape-shifting. If you go down the rabbit-hole of mythology, you can spend a lifetime digging for the truth and be as confused in the end as when you started. I'm not saying myths are bad, because they exist as stories because we like stories. We are all people defined by stories. There is a story and a myth for everyone. We each have one that fits us. However, the myth that suits us will change over the five act play that makes up our life. The myth that describes you in your childhood will not be the same myth that describes your teens, and the myth that fits will shift again in your twenties. This happens with every decade of life, as the view changes when you change roles. But these stories we use to explain ourselves are still only stories. They are explanations but they are not the truth. The truth is always simple and pure and beautiful. That is what the one God provides. The creator of heaven and earth is simple and beautiful and gives you rest. Why? Because the one God is the only explanation that can cut through all the decades and give focus. What we lack is focus, which is a central point, a point of concentration where all rays of light meet. We need something simple and beautiful to look through, something clear of cobwebs and dust and grime. The myths are confusing and changing. The one God cleans up and gives meaning to all of creation and all of time, because only the one God is the God that can make sense no matter what part of the five act play you are in. A child, a teenager, a twenty-something, a worker, a father or mother, a grandparent, a retiree, and especially someone on their deathbed: all of these stages of life can understand what the idea of one God means. You cannot do that with Uranus. Simplicity and beauty: Einstein and Feynman knew that the truth had those qualities, and these were scientists, some of the finest ever. The Big Bang Theory is oddly simple. More odd still is that the Big Bang Theory was discovered by an astronomer who was also a priest (of all people). Oddest of all, what really takes the cake here, is that this same theory supports the universe being “created,” and by that, I mean it points to the universe having a beginning which fits with the cosmology of Genesis. When you consider the Big Bang Theory versus the complicated instructions that come along with string theory or the multiverse, it's clear that the Big Bang is far more simple and beautiful. After awhile those other explanations begin to look like Uranus' family tree.Yes, we are small and finite and cannot know the mind of God, nor fully understand, I get that. But we can recognize beauty and truth and goodness. We can see those things in a baby, in a tree, in a bird nest, in Einstein's equations, in Shakespeare sonnets, or in the simple and humble carpenter who showed up two thousand years ago and offered us some bread and wine. (Kind of like Melchizedek, huh? Right? Right? Who's with me?!)The thing about our minds is that we fall. We fall. We hide. We lie. We cheat. We do all of the things that go against what is simple, true, and beautiful when we serve our selves. Our default setting is to sin, to turn away from the one God and the truth. What the simple stories of the Garden of Eden and the Tower of Babel are trying to convey is how we find ourselves always returning to a state of sin. That's it. What the rest of the Bible is attempting to tell us is how to get out of the muck. The good news is that the devil always overplays his hand, because he has to bluff. He has no real power over God, so the spirits try to destroy God's creation, which means us. The humbling reality is that we are children taken hostage in a larger battle, or like pawns in a cosmic game of chess. We are attacked by temptations and face spiritual combat all the time. Spirits seek our attention in many ways, with strategies and tactics. They can steer us at any time toward the wrong choice, as free will gives us ample opportunity to stray.You can see this happen in the chosen people, where the nation declares its position of fidelity to God, but individuals stray and often the whole nation wanders. Even leaders cannot uphold the belief when tested, such as Solomon who builds temples for his pagan wives. Yes, Solomon, the wisest king, even makes the classic blunder. But there is always the remnant who remain, who believe, and who follow the Commandments. To declare belief in one true God is easy, but to live out that statement of faith is difficult. This is exactly why people leave the one God, because sticking with the demands of God is difficult. Why did Adam and Eve turn away? Because the fun things drew them away, tempted them. They wanted to be like gods, as advertised by the shiny one. Most of the “fun” things are not allowed, but the problem is not the rules but what you consider to be “fun.” The problem is in the heart. Jesus could not be more clear about this, but everyone skips over these parts where he forbids something to get to the “fun” part of “judge not” where he appears to affirm the exact sins he denies. We really want the hippy Jesus because that version is more like Zeus and Dionysus and Eros. Obviously Jesus teaches forgiveness, but he most certainly does not say, “Boys will be boys!” or “Here's some money for beer, have fun” or “A little pornography never hurt anyone” or “Ignore those Puritans, sex is no big deal.” We want the undemanding version of Christianity, we don't want the actual Christianity that has difficult requirements. The reality is that we all turn from God because we have favorite sins. It's going to happen, it will happen, and anyone who pretends it hasn't happened or that they have risen above it are spewing pride like the Bellagio dancing fountains in Vegas. We all decide somewhere in life, often daily, that it is easier to ask for forgiveness than to ask for permission, because Jesus does not grant permission. He knows this, knowing that we would rather reign in hell than serve in heaven. He knows our hearts have a problem and he even lists the problems out for us. “From within people, from their hearts, come evil thoughts, unchastity, theft, murder, adultery, greed, malice, deceit, licentiousness, envy, blasphemy, arrogance, folly. All these evils come from within and they defile.” (Mk 7:18-23)Perhaps it has always been this way, but America in the 21st century chooses to ignore these difficult sayings of Jesus. It's pretty safe in most groups to bring up the cool version of Jesus. But mention quotes like this and you may get the stink-eye. People don't want the hard sayings, because that's where the going gets tough. If you stick to the forgiveness parts, you make more friends. Yes, Jesus forgives sins. Yes, we will sin because we are fallen. Yes, we must turn back to him to receive the forgiveness. But nowhere does it suggest, in any terms, that the laundry list of sins that he mentions are to be blessed or affirmed. What he is trying to tell us, in metaphor, in teachings, in literal words, and in his life itself is that you must recognize that you are a sinner, that your interior self has a fatal flaw, which is why you sin. Somehow we twist this around and say there is no such thing as sin, which is the opposite of what Jesus is trying to say. We're just so good at finding arguments to eat of the fruit of the garden and inventing reasons to build the Tower of Babel. This is the point. It's the point of Israel preserving the faith in one God and the point of Jesus as the one God coming here to straighten us out. He has to chase out the bad spirits, because they are everywhere and reigning supreme. These spirits harass and bother us in order for them to have power over God's creation. Since they can never defeat God, they try to destroy us, God's most beloved creatures. For a long time, as the mythologies openly tell us, the powers of the world had turned away from the "Most High God," and only by the path of the chosen nation did we return to worship of the one true God. Without Israel we would be engaging only in tree worship and building golden calves.The story of Israel is literally the story of a people setting their faces like flint and stepping into a storm of slings and arrows to return the true God to glory in this world. His glory was never lost in reality, but the nations, the "powers and principalities," had distracted us from the truth. The salvation history of Israel is a noble story of suffering and hope, a fight for truth, against an onslaught of falsehoods and cruelty. Yes, the Israelites committed many war crimes themselves in this journey, which is why all of it is recorded. They slaughtered and were slaughtered, but all of this history was for the greater glory of the God that the world wanted to kill once and for all.What God accomplished through the people of Israel is so powerful that I have yet to fully appreciate it, because it is a long and forbidding act of faith, hope, and love for the one true God that allowed for the savior to come to us, and while I know the will of God obviously guided it to completion, much heartache and suffering traveled with them in those many years of swimming upstream. The real ending to the story, as I see it, is this:The cultures surrounding had already moved on from the one God. He was considered dead, something from the past, an artifact of history. Only one group of people knew that he was real, that he was still present, that he was alive, and that he was tending to his sheep. The world wanted to kill God, just as many do today, and the declaration of Nietzsche that "God is dead" is as false when he wrote those words, as it was in the desert of the Exodus, as it is today with the New Atheists claim. The truth is that people who have rejected God want the comfort of believing that God is dead. Those in rebellion desire certainty that God is dead. Oddly enough, the Pharisees who were trying to protect the one true God, also wanted God dead, and in the twist of all twists, the chosen people and the pagan polytheist Romans banded together to do just that. They literally killed God.Or they tried. They tried so hard. They nailed the incarnated one true God to a cross and then to be certain he was dead, they ran a spear into his side. They got what they wanted.But that's the funny thing about getting what you want. In the end it's what you want the most that will purify you, will burn you, will leave you empty, will destroy you, and finally will set you free. Because just when the Romans and Pharisees got what they wanted, in killing God, they wiped their hands and considered the task taken care of once and for all. Three days later, they discovered that they could not kill God.Getting what they want did not play out as expected, because it never does. Instead, like it always does, it purified them. The Romans, hoping to avoid religious disputes and stick with the easy, non-demanding false gods, were complicit in God's murder and soon after were converted away from their polytheism, back to the one true God. The death of Jesus unwound thousands of years of false idols. The Pharisees, thinking they would gain power, saw the temple destroyed 40 years after the crucifixion, and with it their power and influence faded away. Those who converted, like Saul who became Paul, found new life. The rule always holds. What you desire most, if you get it, will take you somewhere very unexpected. This is a public episode. 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