Podcasts about Bayes

This episode covers: Cardiology This Week: A concise summary of recent studies AI and the future of the Electrocardiogram The heart in rheumatic disorders and autoimmune diseases Statistics Made Easy: Bayesian analysis Host: Susanna Price Guests: Carlos Aguiar, Paul Friedman, Maya Buch  Want to watch that episode? Go to: https://esc365.escardio.org/event/1801 Disclaimer: ESC TV Today is supported by Bristol Myers Squibb. This scientific content and opinions expressed in the programme have not been influenced in any way by its sponsor. This programme is intended for health care professionals only and is to be used for educational purposes. The European Society of Cardiology (ESC) does not aim to promote medicinal products nor devices. Any views or opinions expressed are the presenters' own and do not reflect the views of the ESC. Declarations of interests: Stephan Achenbach, Antonio Greco, Nicolle Kraenkel and Susanna Price have declared to have no potential conflicts of interest to report. Carlos Aguiar has declared to have potential conflicts of interest to report: personal fees for consultancy and/or speaker fees from Abbott, AbbVie, Alnylam, Amgen, AstraZeneca, Bayer, BiAL, Boehringer-Ingelheim, Daiichi-Sankyo, Ferrer, Gilead, GSK, Lilly, Novartis, Novo Nordisk, Pfizer, Sanofi, Servier, Takeda, Tecnimede. Maya Buch has declared to have potential conflicts of interest to report: grant/research support paid to University of Manchester from Gilead and Galapagos; consultant and/or speaker with funds paid to University of Manchester for AbbVie, Boehringer Ingelheim, CESAS Medical, Eli Lilly, Galapagos, Gilead Sciences, Medistream and Pfizer Inc; member of the Speakers' Bureau for AbbVie with funds paid to University of Manchester. Davide Capodanno has declared to have potential conflicts of interest to report: Bristol Myers Squibb, Daiichi Sankyo, Sanofi Aventis, Novo Nordisk, Terumo. Paul Friedman has declared to have potential conflicts of interest to report: co-inventor of AI ECG algorithms. Steffen Petersen has declared to have potential conflicts of interest to report: consultancy for Circle Cardiovascular Imaging Inc. Calgary, Alberta, Canada. Emma Svennberg has declared to have potential conflicts of interest to report: Abbott, Astra Zeneca, Bayer, Bristol-Myers, Squibb-Pfizer, Johnson & Johnson.

Did Jeffrey Epstein die by murder or suicide? In this episode, I argue that we should use Bayesian statistics to frame the debate. Indeed, we should use this approach to frame most "conspiracy theories". Most such theories are derided as compelling storytellers weaving half truths to fit their narrative.Bayes offers a more analytical approach.1. Make an educated guess about the probability of an event occurring. The likelihood of Epstein dying by suicide.2. Identify authenticated clues that support that hypothesis.3. Assess the odds of each clue happening independently, i.e. jail cameras not working, hyoid bone being broken, both guards falling asleep.4. Then calculate odds of those happening together.5. Perform calculation and then update original probability estimate based upon the probability those clues happening.Using Bayes with a "little" help from Grok, I identify the odds of murder versus suicide.I also identify ways that you should attack this analysis and not just my use of Grok.This approach should be used more frequently as we try to resolve debates surrounding "conspiracies". I don't even really like that word. We're really trying to assess whether Event x was caused by y or z.

The White House wants to hear from you regarding what it should do about AI safety. Now's your chance to spend a few minutes to make someone read your thoughts on the subject! Submissions are due by midnight EST on … Continue reading →

 This is the 170th episode of my podcast, ‘Soccernostalgia Talk Podcast'.  For this episode, I interview English Football fan Mr. Chris Bayes, as we discuss Liverpool FC in the 2000/01 UEFA Cup. Mr. Bayes has been on the podcast on a number of occasions discussing the Liverpool FC history.    For any questions/comments, you may contact us: You may also contact me on this blog, on twitter @sp1873 and on facebook under Soccernostalgia. https://linktr.ee/sp1873  Mr. Paul Whittle, @1888letter on twitter and https://the1888letter.com/contact/ https://linktr.ee/BeforeThePremierLeague  You may also follow the podcast on spotify and Apple podcasts all under ‘Soccernostalgia Talk Podcast' Please leave a review, rate and subscribe if you like the podcast. Mr. Bayes' contact info: Facebook: https://www.facebook.com/chris.bayes.77  Listen on Spotify / Apple Podcasts:  https://open.spotify.com/episode/6kMBlqXY3NZGngU3oHWIBC?si=rHi6rtFlTECmnXyr8NUKRA&nd=1&dlsi=07f51da769534efehttps://podcasts.apple.com/us/podcast/soccernostalgia-talk-podcast-episode-170-interview/id1601074369?i=1000697018819 Youtube Link:  https://www.youtube.com/watch?v=_jO0EyXjc9I&t=10s Blog Link: https://soccernostalgia.blogspot.com/2025/03/soccernostalgia-talk-podcast-episode.htmlSupport the show

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This episode is sponsored by Thuma. Thuma is a modern design company that specializes in timeless home essentials that are mindfully made with premium materials and intentional details. To get $100 towards your first bed purchase, go to http://thuma.co/eyeonai   In this episode of the Eye on AI podcast, Pedro Domingos, renowned AI researcher and author of The Master Algorithm, joins Craig Smith to explore the evolution of machine learning, the resurgence of Bayesian AI, and the future of artificial intelligence. Pedro unpacks the ongoing battle between Bayesian and Frequentist approaches, explaining why probability is one of the most misunderstood concepts in AI. He delves into Bayesian networks, their role in AI decision-making, and how they powered Google's ad system before deep learning. We also discuss how Bayesian learning is still outperforming humans in medical diagnosis, search & rescue, and predictive modeling, despite its computational challenges. The conversation shifts to deep learning's limitations, with Pedro revealing how neural networks might be just a disguised form of nearest-neighbor learning. He challenges conventional wisdom on AGI, AI regulation, and the scalability of deep learning, offering insights into why Bayesian reasoning and analogical learning might be the future of AI. We also dive into analogical learning—a field championed by Douglas Hofstadter—exploring its impact on pattern recognition, case-based reasoning, and support vector machines (SVMs). Pedro highlights how AI has cycled through different paradigms, from symbolic AI in the '80s to SVMs in the 2000s, and why the next big breakthrough may not come from neural networks at all. From theoretical AI debates to real-world applications, this episode offers a deep dive into the science behind AI learning methods, their limitations, and what's next for machine intelligence. Don't forget to like, subscribe, and hit the notification bell for more expert discussions on AI, technology, and the future of innovation!    Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Introduction (02:55) The Five Tribes of Machine Learning Explained   (06:34) Bayesian vs. Frequentist: The Probability Debate   (08:27) What is Bayes' Theorem & How AI Uses It   (12:46) The Power & Limitations of Bayesian Networks   (16:43) How Bayesian Inference Works in AI   (18:56) The Rise & Fall of Bayesian Machine Learning   (20:31) Bayesian AI in Medical Diagnosis & Search and Rescue   (25:07) How Google Used Bayesian Networks for Ads   (28:56) The Role of Uncertainty in AI Decision-Making   (30:34) Why Bayesian Learning is Computationally Hard   (34:18) Analogical Learning – The Overlooked AI Paradigm   (38:09) Support Vector Machines vs. Neural Networks   (41:29) How SVMs Once Dominated Machine Learning   (45:30) The Future of AI – Bayesian, Neural, or Hybrid?   (50:38) Where AI is Heading Next  

Hugh Macdonald-Brown – Co-Founder & CEO of Roebuck joins me on the People Property Place Podcast

Eneasz tells Jen about Sympathetic Opposition's How and Why to be Ladylike (For Women with Autism), and the podcast takes a 1-episode break

Proudly sponsored by PyMC Labs, the Bayesian Consultancy. Book a call, or get in touch!My Intuitive Bayes Online Courses1:1 Mentorship with meOur theme music is « Good Bayesian », by Baba Brinkman (feat MC Lars and Mega Ran). Check out his awesome work!Visit our Patreon page to unlock exclusive Bayesian swag ;)Takeaways:Bayesian statistics offers a robust framework for econometric modeling.State space models provide a comprehensive way to understand time series data.Gaussian random walks serve as a foundational model in time series analysis.Innovations represent external shocks that can significantly impact forecasts.Understanding the assumptions behind models is key to effective forecasting.Complex models are not always better; simplicity can be powerful.Forecasting requires careful consideration of potential disruptions. Understanding observed and hidden states is crucial in modeling.Latent abilities can be modeled as Gaussian random walks.State space models can be highly flexible and diverse.Composability allows for the integration of different model components.Trends in time series should reflect real-world dynamics.Seasonality can be captured through Fourier bases.AR components help model residuals in time series data.Exogenous regression components can enhance state space models.Causal analysis in time series often involves interventions and counterfactuals.Time-varying regression allows for dynamic relationships between variables.Kalman filters were originally developed for tracking rockets in space.The Kalman filter iteratively updates beliefs based on new data.Missing data can be treated as hidden states in the Kalman filter framework.The Kalman filter is a practical application of Bayes' theorem in a sequential context.Understanding the dynamics of systems is crucial for effective modeling.The state space module in PyMC simplifies complex time series modeling tasks.Chapters:00:00 Introduction to Jesse Krabowski and Time Series Analysis04:33 Jesse's Journey into Bayesian Statistics10:51 Exploring State Space Models18:28 Understanding State Space Models and Their Components

How shitcoins work, plus the Dumb Money movie about the GameStop squeeze.

Why you definitely should kill your friend's cat if you promised to kill your friend's cat. (+Q&A) This is a lightning talk given at the Rationalist MegaMeetup 2024. Based on this Twitter Poll

Send your questions or provocations to Adam or Budi here!In the first episode of the year, Budi sits down with Micha Espinosa, the Artistic Director of the Fitzmaurice Voice Institute, and Christopher Bayes, Professor in the Practice of Acting and Head of Physical Acting at David Geffen School of Drama, to talk about their most recent Bali Retreat they hosted of the New Years. Support the showIf you enjoyed this week´s podcast, please leave a review on Apple Podcasts. To submit a question: Voice- http://www.speakpipe.com/theatreofothers Email- podcast@theatreofothers.com Show Credits Co-Hosts: Adam Marple & Budi MillerProducer: Jack BurmeisterMusic: https://www.purple-planet.comAdditional compositions by @jack_burmeister

Wie Verzerrungen unsere Geldanlage erschweren können. Bei Interesse und/oder für mehr Informationen zu meinem 2-Tägigen Finanzseminar (Frühjahr 2025), schreibe mir einfach eine kurze E-Mail an:  krapp@abatus-beratung.com Viel Spaß beim Hören,Dein Matthias Krapp(Transkript dieser Folge weiter unten) NEU!!! Hier kannst Du Dich kostenlos für meinen Minikurs registrieren und reinschauen. Es lohnt sich: https://portal.abatus-beratung.com/geldanlage-kurs/   

Já não faltavam evidências sobre os malefícios dos vapes e cigarros eletrônicos em 2019, quando falamos pela primeira vez sobre o assunto. Mas quais as novas evidências? E o seu consumo já se configura um problema de saúde pública?Este episódio é apresentado pela ACT Promoção da Saúde, organização não governamental que atua na promoção e defesa de políticas de saúde pública, especialmente nas áreas de controle do tabagismo, alimentação saudável, controle do álcool e atividade física. Esse trabalho é realizado por meio de ações de advocacy, que incluem incidência política, comunicação, mobilização, formação de redes e pesquisa, entre outras. Conheça mais em https://actbr.org.br/Confira o papo entre o leigo curioso, Ken Fujioka, e o cientista PhD, Altay de Souza.>> OUÇA (57min 41s)*Naruhodo! é o podcast pra quem tem fome de aprender. Ciência, senso comum, curiosidades, desafios e muito mais. Com o leigo curioso, Ken Fujioka, e o cientista PhD, Altay de Souza.Edição: Reginaldo Cursino.http://naruhodo.b9.com.br*APOIO: ACTEste episódio é apresentado pelo Sebrae Rio. Sabe aquelas pessoas que a gente admira pela criatividade, pela capacidade de liderar projetos ou de transformar ideias em realidade? Você pode ser uma dessas pessoas com o apoio do Sebrae Rio, desenvolvendo habilidades com a educação empreendedora, que não é só pra quem quer abrir um negócio: essas habilidades são superimportantes pra qualquer profissional.E se você é gestor ou professor de uma instituição de ensino, você pode levar a Educação Empreendedora para os seus alunos.É de graça e ainda emite certificado!Saiba mais, acessando atitude.sebraerj.com.br. E compartilhe suas habilidades empreendedoras nas redes sociais com a hashtag #TáNaSuaAtitude.Sebrae Rio: empreender tá na sua atitude.*REFERÊNCIASRethink Vape: Development and evaluation of a risk communication campaign to prevent youth E-cigarette usehttps://www.sciencedirect.com/science/article/pii/S0306460320307942?casa_token=stt22CU9-6AAAAAA:YPkZZ53Ftu3nkkekilolsWuJNKUbryiRjeLSIDReCt7I_VzpUe7m00pMu7x8ekXPen_tBRSmplYImpact of messages about scientific uncertainty on risk perceptions and intentions to use electronic vaping productshttps://www.sciencedirect.com/science/article/pii/S0306460318312140?casa_token=cLYGPqH_5ycAAAAA:ENqaVvNiFavJdpveZm6twD9JcfZP-EziEL0Vzt9gTE6wY4TLGguWJSDbG0-qZvIyTnMnkIyh3oIComics and Morals: Communicating the Risks of Vaping to Young Adults Through Moralized Graphic Comicshttps://www.proquest.com/openview/30046a092e0b52154768a5774baf4607/1?pq-origsite=gscholar&cbl=18750&diss=yHealth Messaging Strategies for Vaping Prevention and Cessation Among Youth and Young Adults: A Systematic Reviewhttps://www.tandfonline.com/doi/full/10.1080/10410236.2024.2352284Nicotina é até seis vezes maior em quem fuma cigarro eletrônico do que 20 cigarros comuns por diahttps://jornal.usp.br/ciencias/nicotina-e-ate-seis-vezes-maior-em-quem-fuma-cigarro-eletronico-do-que-20-cigarros-comuns-por-dia/Vaping in Youthhttps://jamanetwork.com/journals/jama/article-abstract/2822166?casa_token=AOMeZZluas0AAAAA:sLpdsaUTGQ6B9626AzCUq92sKEiOiQb4ZukceE2Z_lWxzYOfJ69UkK2sLlCNLiN9ulGOk1OzkJE&casa_token=j41vokSLcaUAAAAA:N7nCcnNEPuRTSdhY5abaMDWnmHMatAyw265mnYE3YUj1DOzb8Bt_VVuVMuPLwDh-amcoVdJ6_J8Trends in long term vaping among adults in England, 2013-23: population based studyhttps://www.bmj.com/content/386/bmj-2023-079016.shortA Systematic Review of Predictors of Vaping Cessation Among Young Peophttps://academic.oup.com/ntr/advance-article/doi/10.1093/ntr/ntae181/7717604A Vaping Cessation Text Message Program for Adolescent E-Cigarette Usershttps://jamanetwork.com/journals/jama/article-abstract/2822082?casa_token=jFrwYbTuE00AAAAA:cjSPTgP0FeIYTFS13Uli6akYcN37xjahDcnuCGSEXrgJQMpxExcD2GExrwPO4gNPdb2HqQ9Nyqc&casa_token=TrYwGgae_xEAAAAA:XCLLhI4Ku1KjcxxJ1tIi74OJmwW2Y1eNjq60LVYbJ7B8M2TNh7GPdQwBQIBjDefqVwlkmcaW7TUSmoking and vaping alter genes related to mechanisms of SARS-CoV-2 susceptibility and severity: a systematic review and meta-analysishttps://publications.ersnet.org/content/erj/64/1/2400133.abstractThe Impact of Vaping on the Ocular Surface: A Systematic Review of the Literaturehttps://www.mdpi.com/2077-0383/13/9/2619Drug Use Frequency Variation and Mental Health During the COVID-19 Pandemic: an Online Surveyhttps://pmc.ncbi.nlm.nih.gov/articles/PMC8404543/Vaping among adults in England who have never regularly smoked: a population-based study, 2016–24https://www.thelancet.com/journals/lanpub/article/PIIS2468-2667(24)00183-X/fulltextAssociation of vaping with respiratory symptoms in U.S. young adults: Nicotine, cannabis, and dual vapinghttps://www.sciencedirect.com/science/article/pii/S009174352400330XTobacco Harm Reduction: The Industry's Latest Trojan Horse?https://exposetobacco.org/wp-content/uploads/tobacco-harm-reduction-cop10.pdfU.S. retail sales data show 86% of e-cigarette sales are for illegal productshttps://truthinitiative.org/research-resources/tobacco-industry-marketing/us-retail-sales-data-show-86-e-cigarette-sales-are?trk=feed_main-feed-card_feed-article-contentThe Normalization of Vaping on TikTok Using Computer Vision, Natural Language Processing, and Qualitative Thematic Analysis: Mixed Methods Studyhttps://www.jmir.org/2024/1/e55591/From Smoking to Vaping: The Motivation for E-Cigarette Use at the Neurobiological Level – An fMRI Studyhttps://academic.oup.com/ntr/advance-article/doi/10.1093/ntr/ntae273/7906109Vaping and Smoking Cue Reactivity in Young Adult Nonsmoking Electronic Cigarette Users: A Functional Neuroimaging Studyhttps://academic.oup.com/ntr/advance-article-abstract/doi/10.1093/ntr/ntae257/7863347Impact of Electronic Cigarettes on the Cardiovascular Systemhttps://pmc.ncbi.nlm.nih.gov/articles/PMC5634286/Naruhodo #207 - Vape e cigarro eletrônico são seguros? (2019)https://www.youtube.com/watch?v=Raa9CUrIFbsNaruhodo #85 - Por que é tão difícil parar de fumar?https://www.youtube.com/watch?v=SPkIT0ehoisNaruhodo #49 - O que causa o vício?https://www.youtube.com/watch?v=--Z_ylPXIWcNaruhodo #94 - O que é o Teorema de Bayes? (E o que horóscopo tem a ver com isso?)https://www.youtube.com/watch?v=BE5fpsfPerwNaruhodo #328 - Existem "gatilhos mentais"?https://www.youtube.com/watch?v=fxBQJlin8Z4Naruhodo #419 - Maconha faz mal? - Parte 1 de 2https://www.youtube.com/watch?v=cvLTh2bKPiQNaruhodo #420 - Maconha faz mal? - Parte 2 de 2https://www.youtube.com/watch?v=F7wVcGvpoGANaruhodo #267 - O que é dissonância cognitiva?https://www.youtube.com/watch?v=1xJwqmir5UwNaruhodo #268 - O que é dissonância cognitiva? - Parte 2 de 2https://www.youtube.com/watch?v=--OHlHmOQTM*APOIE O NARUHODO PELA PLATAFORMA ORELO!O podcast Naruhodo está no Orelo: bit.ly/naruhodo-no-oreloE é por meio dessa plataforma de apoio aos criadores de conteúdo que você ajuda o Naruhodo a se manter no ar.Você escolhe um valor de contribuição mensal e tem acesso a conteúdos exclusivos, conteúdos antecipados e vantagens especiais.Além disso, você pode ter acesso ao nosso grupo fechado no Telegram, e conversar comigo, com o Altay e com outros apoiadores.E não é só isso: toda vez que você ouvir ou fizer download de um episódio pelo Orelo, vai também estar pingando uns trocadinhos para o nosso projeto.Então, baixe agora mesmo o app Orelo no endereço Orelo.CC ou na sua loja de aplicativos e ajude a fortalecer o conhecimento científico.bit.ly/naruhodo-no-orelo

This is the 149th episode of my podcast with Mr. Paul Whittle of https://the1888letter.com/, @1888letter. For this episode, we interview English Football fan Mr. Chris Bayes, as we discuss Liverpool in the 1996/97 Cup Winners Cup.Mr. Bayes has been on the podcast on a number of occasions discussing the Liverpool FC history.   For any questions/comments, you may contact us:You may also contact me on this blog, on twitter @sp1873 and on facebook under Soccernostalgia.https://linktr.ee/sp1873 Mr. Paul Whittle, @1888letter on twitter and https://the1888letter.com/contact/https://linktr.ee/BeforeThePremierLeague You may also follow the podcast on spotify and Apple podcasts all under ‘Soccernostalgia Talk Podcast'Please leave a review, rate and subscribe if you like the podcast.Mr. Bayes' contact info:Facebook: https://www.facebook.com/chris.bayes.77 Listen on Spotify / Apple Podcasts: https://open.spotify.com/episode/58bUuVEvBZS5M5pAyj1d11?si=GP6tbPKiQ8WgtkViRayU-w&nd=1&dlsi=fe8db29a586d4834https://podcasts.apple.com/us/podcast/soccernostalgia-talk-podcast-episode-149-interview/id1601074369?i=1000678721134Youtube Link: https://www.youtube.com/watch?v=ob0-j0dAEGU Blog Link: https://soccernostalgia.blogspot.com/2024/11/soccernostalgia-talk-podcast-episode_30.htmlSupport the show

This is the 147th episode of my podcast with Mr. Paul Whittle of https://the1888letter.com/, @1888letter. For this episode, we interview English Football fan Mr. Chris Bayes, as we discuss the Roy Evans era as Liverpool FC Manager (1994-1998). Mr. Bayes has been on the podcast on a number of occasions discussing the Liverpool FC history.   For any questions/comments, you may contact us:You may also contact me on this blog, on twitter @sp1873 and on facebook under Soccernostalgia.https://linktr.ee/sp1873 Mr. Paul Whittle, @1888letter on twitter and https://the1888letter.com/contact/https://linktr.ee/BeforeThePremierLeague You may also follow the podcast on spotify and Apple podcasts all under ‘Soccernostalgia Talk Podcast'Please leave a review, rate and subscribe if you like the podcast.Mr. Bayes' contact info:Facebook: https://www.facebook.com/chris.bayes.77 Listen on Spotify / Apple Podcasts: https://open.spotify.com/episode/0J2ymDNngEWX5JbeNqzbiK?si=7LbbM8-eSw6dBlfpS024Qw&nd=1&dlsi=c9dbb012740d4a43https://podcasts.apple.com/us/podcast/soccernostalgia-talk-podcast-episode-147-interview/id1601074369?i=1000678075395Youtube Link: https://www.youtube.com/watch?v=2zZ05rtltMM Blog Link: https://soccernostalgia.blogspot.com/2024/11/soccernostalgia-talk-podcast-episode_24.htmlSupport the show

Liron Shapira, host of [Doom Debates], invited us on to discuss Popperian versus Bayesian epistemology and whether we're worried about AI doom. As one might expect knowing us, we only got about halfway through the first subject, so get yourselves ready (presumably with many drinks) for part II in a few weeks! The era of Ben and Vaden's rowdy youtube debates has begun. Vaden is jubilant, Ben is uncomfortable, and the world has never been more annoyed by Popperians. Follow Liron on twitter (@liron) and check out the Doom Debates youtube channel (https://www.youtube.com/@DoomDebates) and podcast (https://podcasts.apple.com/us/podcast/doom-debates/id1751366208). We discuss Whether we're concerned about AI doom Bayesian reasoning versus Popperian reasoning Whether it makes sense to put numbers on all your beliefs Solomonoff induction Objective vs subjective Bayesianism Prediction markets and superforecasting References Vaden's blog post on Cox's Theorem and Yudkowsky's claims of "Laws of Rationality": https://vmasrani.github.io/blog/2021/thecredenceassumption/ Disproof of probabilistic induction (including Solomonov Induction): https://arxiv.org/abs/2107.00749 EA Post Vaden Mentioned regarding predictions being uncalibrated more than 1yr out: https://forum.effectivealtruism.org/posts/hqkyaHLQhzuREcXSX/data-on-forecasting-accuracy-across-different-time-horizons#Calibrations Article by Gavin Leech and Misha Yagudin on the reliability of forecasters: https://ifp.org/can-policymakers-trust-forecasters/ Superforecaster p(doom) is ~1%: https://80000hours.org/2024/09/why-experts-and-forecasters-disagree-about-ai-risk/#:~:text=Domain%20experts%20in%20AI%20estimated,by%202100%20(around%2090%25). The existential risk persuasion tournament https://www.astralcodexten.com/p/the-extinction-tournament Some more info in Ben's article on superforecasting: https://benchugg.com/writing/superforecasting/ Slides on Content vs Probability: https://vmasrani.github.io/assets/pdf/popper_good.pdf Socials Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani, @liron Come join our discord server! DM us on twitter or send us an email to get a supersecret link Trust in the reverend Bayes and get exclusive bonus content by becoming a patreon subscriber here (https://www.patreon.com/Increments). Or give us one-time cash donations to help cover our lack of cash donations here (https://ko-fi.com/increments). Click dem like buttons on youtube (https://www.youtube.com/channel/UC_4wZzQyoW4s4ZuE4FY9DQQ) What's your credence that the second debate is as fun as the first? Tell us at incrementspodcast@gmail.com Special Guest: Liron Shapira.

AskWho just attended a “lecture” by AI Grifter Tania Duarte Slide The “TESCREAL” Bungle  by Ozy Brennan AskWho Casts AI podcast

Send us a textThis week, we're debunking the myth that "anything can happen." In today's episode, we'll explore how adopting this mindset can increase uncertainty and cognitive load—especially in high-risk environments—and how it might set us up for failure. Instead of believing that "anything can happen," we'll focus on reducing uncertainty by deepening our understanding of human behavior and utilizing practical tools like game theory, probability, and Bayes' theorem.Join us as we dive into why strategic thinking, modeled through games, is essential for real-life decision-making. We'll discuss how you can leverage both the knowns and unknowns in human interactions to predict behavior more effectively, minimize ambiguity, and ultimately make better, more informed decisions. Whether you're involved in law enforcement training, making everyday choices, or viewing human behavior as a strategic game, this episode is packed with insights to help you think sharper and be better prepared for whatever comes your way.Thank you so much for tuning in! We hope you enjoy the episode. Don't forget to check out our Patreon channel for additional content and subscriber-only episodes. If you enjoy the podcast, please consider leaving us a review and, more importantly, sharing it with a friend.Thank you for your time, and remember: Training Changes Behavior!Support the showWebsite: https://thehumanbehaviorpodcast.buzzsprout.com/shareFacebook: https://www.facebook.com/TheHumanBehaviorPodcastInstagram: https://www.instagram.com/thehumanbehaviorpodcast/ Patreon: https://www.patreon.com/ArcadiaCognerati More about Greg and Brian: https://arcadiacognerati.com/arcadia-cognerati-leadership-team/

GPT-o1 demonstrates the Blindsight thesis is likely wrong. Peter Watts on Blindsight Andrew Cutler on origins of consciousness part 1 and part 2 Thou Art Godshatter

Steven wanted to share an interesting idea from an article that draws a neat parallel between content moderation and information security. The post discussed here is Como is Infosec.

Welcome back to another exciting episode of The Yours, Mine, Away! Podcast! This week, we're joined by AFC Wimbledon Goalkeeper Coach, Ashley Bayes for an in-depth chat about his journey, career highlights, and the big names he's helped along the way.Make sure you tune in for this insightful conversation, and if you haven't yet, be sure to catch our latest Goalie Wars video on YouTube!Big shout out to our sponsors!Uperform: https://shop.u-perform.co.uk/74xd6 (DISCOUNT LINK!)Mito Red Light: https://mitoredlight.com/?afmc=YourMito5Forged Irish Stout: https://forgedirishstout.com/ Hosted on Acast. See acast.com/privacy for more information.

Everything Is Predictable: How Bayes' Remarkable Theorem Explains the World is a book about an 18th century mathematical rule for working out probability, which shapes many aspects of our modern world. Written by science journalist Tom Chivers, the book has made it onto the shortlist for the Royal Society Trivedi Science Book Prize. In the lead up to the winner's announcement, New Scientist books editor Alison Flood meets all six of the shortlisted authors.In this conversation, Tom explores the life of Thomas Bayes, the man behind the theorem, and how he had no clue his discovery would have such sweeping implications for humanity. He explains the theorem's many uses, both in practical settings like disease diagnosis, as well as its ability to explain rational thought and the human brain. And he digs into some of the controversy and surprising conflict that has surrounded Bayes' theorem over the years.The winner of the Royal Society Trivedi Science Book Prize will be announced on the 24th October. You can view all of the shortlisted entries here:https://royalsociety.org/medals-and-prizes/science-book-prize/ To read about subjects like this and much more, visit https://www.newscientist.com/ Hosted on Acast. See acast.com/privacy for more information.

Can we achieve our true potential? based on – Interview Day At Thiel Capital also mentioned: Meetups Everywhere 2024 Are You Jesus or Hitler

Brian Bailey Show 9-23-24 David Garrard, Kevin Monroe, Kevin Miller, Andrew Bayes, Jeff Kerr by Pirate Radio

A surprising update for two previously maple-pilled Yanks  

This week we review the season three episode Shadow Dancing.Joe gives us fun vampire facts, Mike almost deploys Bayes' Theorem, and Sarah reads from the Babylon 5 Visitor's Guide that she just made up.Spoiler-free discussion: 0:00:00 - 1:04:01Spoiler Zone: 1:04:01 - 1:07:30Next Episode and other Shenanigans: 1:07:30Music from this episode:"Surf Punk Rock" By absentrealities is licensed under CC-BY 3.0"Please Define The Error" By Delta Centauri is licensed under CC-BY 3.0"The Haunted McMansion" By Megabit Melodies is licensed under CC-BY 3.0

PRL 9 - 4-24 Ken Watlington. Holton Ahlers, Patrick Mason, Andrew Bayes by Pirate Radio

Een nieuwe #nerdland podcast! Met deze maand: Starliner! Glimwormhacking! Via Appia! De Homo Floriensis! Maanslinger! AI-RickRolling! Derailleurs! En veel meer... Shownotes: https://podcast.nerdland.be/nerdland-maandoverzicht-september-2024/ Gepresenteerd door Lieven Scheire, met Els Aerts, Hetty Helsmoortel, Peter Berx, Jonas Geirnaert en Jeroen Baert. Montage en mixing door Els Aerts en Jens Paeyeneers. (00:00:00) Intro (00:01:52) Boeing Starliner Saga (00:17:30) Spin lokt glimwormen door glimwormlijken te hacken (00:24:27) Wetenschappers op het spoor van het stuk brein waar creativiteit ontstaat (00:29:02) Nadia Drake vindt tekening Arecibo message terug (00:34:29) Mieren amputeren (00:40:39) Nieuw bewijs van Homo Floresiensis (00:54:20) Red Bull Basement wedstrijd voor nerds (00:56:41) Is de AI bubbel aan het barsten? (01:04:05) Llama 3.1 van Meta is gratis te downloaden (01:07:05) Trailer Megalopolis (01:08:45) LLM deelt random telefoonnummers uit en begint mensen te Rickrollen (01:11:12) GPT 4o antwoordt in stem gebruiker (01:14:11) Robottaxis komen samen op een parkeerterrein om naar elkaar te toeteren (01:17:38) SILICON VALLEY NEWS (01:18:31) Europese testraket explodeert (01:20:25) Blue Origin testraket explodeert (01:21:24) SpaceX Polaris Dawn: first tourist space walk en vlucht over de polen (01:28:46) Tweede Neuralink implantaat (01:32:41) China lanceert eigen Starlink (01:39:09) Nieuwe behandeling tegen Tinnitus (01:44:22) Regel van Bayes eens deftig uitleggen (01:52:39) China werkt aan magnetische maanslinger (01:57:26) Versnellingen hacken (02:00:36) Via Appia erkend als werelderfgoed (02:06:58) Er komt een grote straatlamp op de maan (02:11:16) RECALLS (02:11:20) Pikachu (02:13:17) 22 september MathFest www.platformwiskunde.be (02:13:54) RoboCup Junior dit jaar! www.redrobotegem.be (02:14:29) Bacteriofaag studie (02:15:13) 12 september IgNobel prijzen (02:15:40) wikiwiskwis.be (02:17:27) PROMO (02:17:29) Live podcast 26 april in Arenberg (02:18:06) Hetty op tour met missie hettyhelsmoortel.be (02:19:28) Laatste AI shows lievenscheire.be (02:19:48) Nerdland voor Kleine Nerds: 27 december in Lotto Arena: www.nerdland.be (02:20:51) AI boek verkrijgbaar in Engels! (02:21:07) AI lezingen Jeroen jeroen-baert.be (02:21:30) Code Rood van Toon is nog steeds te koop (02:21:46) Sponsor Cegeka

O 45 Graus está de férias; por isso, não há episódios novos. É uma boa altura para re-publicar alguns dos melhores episódios das últimas temporadas (os mais ouvidos e que mais feedback tiveram dos ouvintes). Esta 1ª parte da conversa com Desidério Murcho é um episódio já com quase 4 anos, mas é ainda um dos que os ouvintes mais me falam. E com boa razão: foi dos episódios do 45 Graus que mais me marcaram e inspirou alguns conteúdos dos workshops de Pensamento Crítico. A quem não teve oportunidade de ouvir na altura, espero que gostem — e não deixem de ouvir também a 2ª parte desta conversa. Até breve. ________________________________________________________ Inscreva-se aqui nos workshops de Pensamento Crítico, módulo "Desinformação e Números que Enganam: em Lisboa, Porto e Online __________________________________________ Desidério Murcho (1965) estudou Filosofia na Universidade de Lisboa e depois no King's College de Londres. É professor na Universidade Federal de Ouro Preto desde 2007. Autor de Filosofia em Directo (2011), um êxito editorial com mais de 21 mil exemplares vendidos, Sete Ideias Filosóficas que Toda a Gente Deveria Conhecer (2011), Pensar Outra Vez (2006), O Lugar da Lógica na Filosofia (2003) e Essencialismo Naturalizado (2002). Coautor dos livros Janelas para a Filosofia (2014), 50 Lições de Filosofia (2012-2013), entre outros, e organizador dos livros A Ética da Crença (2010), Viver para Quê? (2009) e Enciclopédia de Termos Lógico-Filosóficos (2006), Desidério Murcho participa habitualmente em congressos e conferências internacionais. ________________________________________________________ -> Apoie este projecto e faça parte da comunidade de mecenas do 45 Graus em: 45grauspodcast.com ________________________________________________________ Índice da conversa: (0:00) Introdução (1:44) Porque é importante todos sabermos de lógica? Livro do convidado: Lógica Elementar (10:08) A História da Lógica ao longo dos séculos: Lógica dedutiva aristotélica, Lógica dos estoicos, Matematização da lógica a partir do sec XIX  (17:27) O que é a Validade de um raciocínio (18:50) A Revolução Científica e a vitória do raciocínio indutivo sobre o dedutivo. David Hume. O Problema da Indução | Robin George Collingwood | Enciclopédia de Diderot | O debate na Filosofia entre Racionalismo vs Empirismo |  David Hume | Idealismo Hegeliano (30:33) Diferença entre raciocínio dedutivo e indutivo. | A desorganização inerente à linguagem e a dependência do contexto. A incerteza subjacente à indução (39:33) O Teorema de Bayes: por que nos é útil para fazer previsões e compreender o mundo (48:41) Limites da dedução -- e por que não há uma lógica universal? | Thomas Kuhn ________________________________________________________ Esta conversa foi editada por: Martim Cunha Rêgo

【欢迎订阅】每天早上5:30，准时更新。【阅读原文】标题：Mike Lynch was Britain's first software billionaireHe was celebrating his freedom when his yacht sank in a freak storm正文：Bayes's theorem, an 18th-century formula, holds that with the right understanding of probabilities, most outcomes are predictable. But sometimes freak events occur. In the early hours of August 19th, a superyacht owned by the wife of Mike Lynch, a British tech entrepreneur who only months ago was cleared in a vast American fraud case, was struck by a waterspout, a form of tornado, off the north coast of Sicily, and capsized. On August 22nd it was confirmed that Mr Lynch was among five bodies recovered from the sunken yacht; rescue teams continued to search for a missing woman. It was a tragic end to an extraordinary story.知识点：theorem n. /ˈθɪərəm/ a rule or principle, especially in mathematics, that can be proved to be true（尤指数学）定理获取外刊的完整原文以及精讲笔记，请关注微信公众号「早安英文」，回复“外刊”即可。更多有意思的英语干货等着你！【节目介绍】《早安英文-每日外刊精读》，带你精读最新外刊，了解国际最热事件：分析语法结构，拆解长难句，最接地气的翻译，还有重点词汇讲解。所有选题均来自于《经济学人》《纽约时报》《华尔街日报》《华盛顿邮报》《大西洋月刊》《科学杂志》《国家地理》等国际一线外刊。【适合谁听】1、关注时事热点新闻，想要学习最新最潮流英文表达的英文学习者2、任何想通过地道英文提高听、说、读、写能力的英文学习者3、想快速掌握表达，有出国学习和旅游计划的英语爱好者4、参加各类英语考试的应试者（如大学英语四六级、托福雅思、考研等）【你将获得】1、超过1000篇外刊精读课程，拓展丰富语言表达和文化背景2、逐词、逐句精确讲解，系统掌握英语词汇、听力、阅读和语法3、每期内附学习笔记，包含全文注释、长难句解析、疑难语法点等，帮助扫除阅读障碍。

Clara Grima nos ha explicado cómo se puede resolver un juicio gracias a las matemáticas con el teorema de Bayes, que nos enseña a calcular probabilidades, dependiendo de sucesos que ya sabemos que han ocurrido. Lo ha hecho con el caso del juicio de OJ Simpson. 

Ralston College Humanities MA Dr John Vervaeke is a cognitive scientist and philosopher who explores the intersections of Neoplatonism, cognitive science, and the meaning crisis, focusing on wisdom practices, relevance realization, and personal transformation. Ralston College presents a lecture titled “Levels of Intelligibility, Levels of the Self: Realizing the Dialectic,” delivered by Dr John Vervaeke, an award-winning associate professor of cognitive science at the University of Toronto and creator of the acclaimed 50-episode “Awakening from the Meaning Crisis” series. In this lecture, Dr Vervaeke identifies our cultural moment as one of profound disconnection and resulting meaninglessness. Drawing on his own cutting-edge research as a cognitive scientist and philosopher, Vervaeke presents a way out of the meaning crisis through what he terms “third-wave Neoplatonism.” He reveals how this Neoplatonic framework, drawn in part from Plato's conception of the tripartite human soul, corresponds to the modern understanding of human cognition and, ultimately, to the levels of reality itself. He argues that a synoptic integration across these levels is not only possible but imperative.   — 00:00 Levels of Intelligibility: Integrating Neoplatonism and Cognitive Science 12:50 Stage One: Neoplatonic Psycho-ontology and the Path to Spirituality 41:02 Aristotelian Science: Knowing as Conformity and Transformation 46:36 Stoic Tradition: Agency, Identity, and the Flow of Nature 01:00:10 Stage Two: Cognitive Science and the Integration of Self and Reality 01:04:45 The Frame Problem and Relevance Realization  01:08:45 Relevance Realization and the Power of Human Cognition 01:20:15 Transjective Reality: Affordances and Participatory Fittedness 01:23:55 The Role of Relevance Realization: Self-Organizing Processes 01:31:30 Predictive Processing and Adaptivity 01:44:35 Critiquing Kant: The Case for Participatory Realism 01:53:35 Stage Three: Neoplatonism and the Meaning Crisis  02:00:15 Q&A Session 02:01:45 Q: What is the Ecology of Practices for Cultivating Wisdom? 02:11:50 Q: How Has the Cultural Curriculum Evolved Over Time? 02:26:30 Q: Does the World Have Infinite Intelligibility? 02:33:50 Q: Most Meaningful Visual Art? 02:34:15 Q: Social Media's Impact on Mental Health and Information? 02:39:45 Q: What is Transjective Reality? 02:46:35 Q: How Can Education Address the Meaning Crisis? 02:51:50 Q: Advice for Building a College Community? 02:55:30 Closing Remarks   — Authors, Ideas, and Works Mentioned in this Episode:    Antisthenes Aristotle Brett Anderson Byung-Chul Han Charles Darwin Daniel Dennett D. C. Schindler Friedrich Nietzsche Galileo Galilei Gottfried Wilhelm Leibniz Heraclitus Henry Corbin Immanuel Kant Iris Murdoch Isaac Newton Igor Grossmann Johannes Kepler John Locke John Searle John Spencer Karl Friston Karl Marx Mark Miller  Maurice Merleau-Ponty Nelson Goodman Paul Ricoeur Pierre Hadot Plato Pythagoras Rainer Maria Rilke René Descartes Sigmund Freud W. Norris Clarke anagoge (ἀναγωγή) Distributed cognition eidos (εἶδος) eros (ἔρως) Evan Thompson's deep continuity hypothesis Generative grammar logos (λόγος) Sensorimotor loop Stoicism thymos (θυμός) Bayes' theorem Wason Selection Task The Enigma of Reason by Hugo Mercier and Dan Sperber The Ennead by Plotinus Explorations in Metaphysics by W. Norris Clarke Religion and Nothingness by Keiji Nishitani The Eternal Law: Ancient Greek Philosophy, Modern Physics, and Ultimate Reality by John Spencer   — Additional Resources  John Vervaeke https://www.youtube.com/@johnvervaeke  Dr Stephen Blackwood  Ralston College (including newsletter) Support a New Beginning  — Thank you for listening!

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: (Approximately) Deterministic Natural Latents, published by johnswentworth on July 21, 2024 on LessWrong. Background: Natural Latents: The Math, Natural Latents: The Concepts, Why Care About Natural Latents?, the prototypical semantics use-case. This post does not assume that you've read all of those, or even any of them. Suppose I roll a biased die 1000 times, and then roll the same biased die another 1000 times. Then... Mediation: The first 1000 rolls are approximately independent of the second 1000 given the bias (to reasonable precision). Redundancy: I can estimate the die's bias (to reasonable precision) with high confidence from either the first or second 1000 rolls. The die's bias is therefore a natural latent, which means it has various nice properties. Minimality: The bias is the smallest summary of all the information about the first 1000 rolls relevant to the second 1000 (and vice-versa). Maximality: The bias is the largest piece of information which can be calculated from the first 1000 rolls and also can separately be calculated from the second 1000 rolls. Any other variable which satisfies the above properties must tell us (approximately) the same information about the die rolls as the bias. Furthermore, the bias is a(n approximate) deterministic natural latent: the die's bias (to reasonable precision) is approximately determined by[1] the first 1000 die rolls, and also approximately determined by the second 1000 die rolls. That implies one more nice property: Uniqueness: The bias is the unique-up-to(-approximate)-isomorphism latent which has the above properties, making it a natural Schelling point for communication between agents. We've proven all that before, mostly in Natural Latents: The Math (including the addendum added six months after the rest of the post). But it turns out that the math is a lot shorter and simpler, and easily yields better bounds, if we're willing to assume (approximate) determinism up-front. That does lose us some theoretical tools (notably the resampling construction), but it gives a cleaner foundation for our expected typical use cases (like e.g. semantics). The goal of this post is to walk through that math. Background Tool: Determinism in Diagrams We're going to use diagrammatic proofs, specifically using Bayes nets. But it's non-obvious how to express (approximate) determinism using Bayes nets, or what rules diagrams follow when determinism is involved, so we'll walk through that first. This diagram says that Y is (approximately) determined by X: Intuitively, the literal interpretation of the diagram is: X mediates between Y and Y, i.e. Y itself tells me nothing more about Y once I already know X. That only makes sense if X tells me everything there is to know about Y, i.e. Y is determined by X. In the approximate case, we express the approximation error of the diagram as a KL-divergence, same as usual: ϵDKL(P[X=x,Y=y,Y=y']||P[X=x]P[Y=y|X=x]P[Y=y'|X=x]) If you get confused later about what it means to have two copies of the same variable in a diagram, go back to that line; that's the definition of the approximation error of the diagram. (One way to view that definition: there's actually two variables Y and Y', but P says that Y and Y' always have the same value.) That approximation error simplifies: DKL(P[X=x,Y=y,Y=y']||P[X=x]P[Y=y|X=x]P[Y=y'|X=x]) =DKL(P[X=x,Y=y]I[y=y']||P[X=x]P[Y=y|X=x]P[Y=y'|X=x]) =x,y,y'P[X=x,Y=y]I[y=y'](log(P[X=x,Y=y]I[y=y'])log(P[X=x]P[Y=y|X=x]P[Y=y'|X=x])) =x,yP[X=x,Y=y](log(P[X=x,Y=y])log(P[X=x]P[Y=y|X=x]P[Y=y|X=x])) =x,yP[X=x,Y=y]log(P[Y=y|X=x]) =H(Y|X) So the diagram says Y is determined by X, and the approximation error of the diagram is the entropy H of Y given X - i.e. the number of bits required on average to specify Y once one already knows X. Very intuitive! The Dangly Bit Lemma Intuitiv...

✍︎: The Curious Worldview Newsletter - the ultimate compliment to the podcast...Other episode of the podcast that suit this episode...Brian Klaas – Fluke & RandomnessRuss Roberts – EconTalkLuca Dellanna – Ergodicity All The Way DownScott Patterson – Chaos KingsNassim Taleb & Incerto PodcastFollow me on Instagram – @ryanfhoggEverything Is Predictable – Tom ChiversTom Chivers is a prolific science writer whose written for Buzzfeed, The Telegraph, Unherd, published books, written for loads of other publications as well and now writes for Semafor's daily flagship email (something I read everyday)… but here Tom is today to discuss his book about Bayes called… EVERYTHING IS PREDICTABLE: How Bayes' Remarkable Theorem Explains the World and, the lead is not buried in this case, it is a book about Bayes Throerom which to put it simply… is an equation to calculate probability.Now, my Talebian listeners will recognise a contradiction to our worldview in the title here… everything is predictable? how often has Taleb's quotes, how can we predict a future of infinite possibilities based off a finite experience of the past appeared on this podcast? We get into Chivers differences with that Talebian worldview, but as well, there is top to bottom what is Bayes theorem, why does it matter, the role of this theorem at the foundation of all of these LLM's and therefore much of AI. a neat little anecdote of Chivers family member, Sir John Maynard Keynes and plenty more as well!00:00 – Who Is Tom Chivers01:34 – Great Great Uncle John Maynard Keynes08:44 – What's The Point Of Bayes?19:14 – What Is Bayes Theorem?39:34 – Disagreeing With Nassim Taleb 52:24 – Counterintuitive Aspects Of Bayes56:28 – Bayes & LLM's & AI1:15:12 – Serendipity In Tom's Life

Sick of hearing us shouting about Bayesianism? Well today you're in luck, because this time, someone shouts at us about Bayesianism! Richard Meadows, finance journalist, author, and Ben's secretive podcast paramour, takes us to task. Are we being unfair to the Bayesians? Is Bayesian rationality optimal in theory, and the rest of us are just coping with an uncertain world? Is this why the Bayesian rationalists have so much cultural influence (and money, and fame, and media attention, and ...), and we, ahem, uhhh, don't? Check out Rich's website (https://thedeepdish.org/start), his book Optionality: How to Survive and Thrive in a Volatile World (https://www.amazon.ca/Optionality-Survive-Thrive-Volatile-World/dp/0473545500), and his podcast (https://doyouevenlit.podbean.com/). We discuss The pros of the rationality and EA communities Whether Bayesian epistemology contributes to open-mindedness The fact that evidence doesn't speak for itself The fact that the world doesn't come bundled as discrete chunks of evidence Whether Bayesian epistemology would be "optimal" for Laplace's demon The difference between truth and certainty Vaden's tone issues and why he gets animated about this subject. References Scott's original piece: In continued defense of non-frequentist probabilities (https://www.astralcodexten.com/p/in-continued-defense-of-non-frequentist) Scott Alexander's post about rootclaim (https://www.astralcodexten.com/p/practically-a-book-review-rootclaim/comments) Our previous episode on Scott's piece: #69 - Contra Scott Alexander on Probability (https://www.incrementspodcast.com/69) Rootclaim (https://www.rootclaim.com/) Ben's blogpost You need a theory for that theory (https://benchugg.com/writing/you-need-a-theory/) Cox's theorem (https://en.wikipedia.org/wiki/Cox%27s_theorem) Aumann's agreement theorem (https://en.wikipedia.org/wiki/Aumann%27s_agreement_theorem) Vaden's blogposts mentioned in the episode: Critical Rationalism and Bayesian Epistemology (https://vmasrani.github.io/blog/2020/vaden_second_response/) Proving Too Much (https://vmasrani.github.io/blog/2021/proving_too_much/) Socials Follow us on Twitter at @IncrementsPod, @BennyChugg, @VadenMasrani Follow Rich at @MeadowsRichard Come join our discord server! DM us on twitter or send us an email to get a supersecret link Help us calibrate our credences and get exclusive bonus content by becoming a patreon subscriber here (https://www.patreon.com/Increments). Or give us one-time cash donations to help cover our lack of cash donations here (https://ko-fi.com/increments). Click dem like buttons on youtube (https://www.youtube.com/channel/UC_4wZzQyoW4s4ZuE4FY9DQQ) What's your favorite theory that is neither true nor useful? Tell us over at incrementspodcast@gmail.com. Special Guest: Richard Meadows.

Brandon comes back to explain how wind works. Steven and Brandon are not the two you want if you want to quickly get to the point so this went on for a good while. It's an awesome conversation and Patrons … Continue reading →

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: Doomsday Argument and the False Dilemma of Anthropic Reasoning, published by Ape in the coat on July 5, 2024 on LessWrong. Doomsday Inference Can we use probability theory to estimate how many people there will be throughout the whole human history? Sure. We can build a probability model, that takes into account birth rates, possible existential hazards, ways to mitigate them and multiple other factors. Such models tend not to be very precise, so we would have pretty large confidence intervals but, we would still have some estimate. Hmm... this sounds like a lot of work for not much of a result. Can't we just use the incredible psychic powers of anthropics to circumvent all that, and get a very confident estimate just from the fact that we exist? Consider this: Suppose that there are two indistinguishable possibilities: a short human history, in which there are only 100 billion people and a long human history, in whichthere are 100 trillion people. You happen to be born among the 6th 10-billion group of people. What should be your credence that the history is short? As short and long history are a priori indistinguishable and mutually exclusive: P(Short)=P(Long)=1/2 Assuming that you are a random person among all the people destined to be born: P(6|Short)=1/10 P(6|Long)=1/10000 According to the Law of Total Probability: P(6)=P(6|Short)P(Short)+P(6|Long)P(Long)=0.05005 Therefore by Bayes' Theorem: P(Short|6)=P(6|Short)P(Short)/P(6)>0.999 We should be extremely confident that humanity will have a short history, just by the fact that we exist right now. This strong update in favor of short history solely due to the knowledge of your birth rank is known as the Doomsday Inference. I remember encountering it for the first time. I immediately felt that it can't be right. Back in the day I didn't have the right lexicon to explain why cognition engines can't produce knowledge this way. I wasn't familiar with the concept of noticing my own confusion. But I've already accustomed myself with several sophisms, and even practiced constructing some myself. So I noticed the familiar feeling of "trickery" that signaled that one of the assumptions is wrong. I think it took me a couple of minutes to find it. I recommend for everyone to try to do it themselves right now. It's not a difficult problem to begin with, and should be especially easy if you've read and understood my sequence on Sleeping Beauty problem. . . . . . . . . . Did you do it? . . . . . . . . . Well, regardless, there will be more time for it. First, let's discuss the fact that both major anthropic theories SSA and SIA accept the doomsday inference, because they are crazy and wrong and we live in an extremely embarrassing timeline. Biting the Doomsday Bullet Consider this simple and totally non-anthropic probability theory problem: Suppose there are two undistinguishable bags with numbered pieces of paper. The first bag has 10 pieces of paper and the second has 10000. You were given a random piece of paper from one of the bags and it happens to have number 6. What should be your credence that you've just picked a piece of paper from the first bag? The solution is totally analogous to the Doomsday Inference above: P(First)=P(Second)=1/2 P(6|First)=1/10 P(6|Second)=1/10000 P(6)=P(6|First)P(First)+P(6|Second)P(Second)=0.05005 P(First|6)=P(6|First)P(First)/P(6)=0.05/0.05005>0.999 But here there is no controversy. Nothing appears to be out of order. This is the experiment you can conduct and see for yourself that indeed, the absolute majority of cases where you get the piece of paper with number 6 happen when the paper was picked from the first bag. And so if we accept this logic here, we should also accept the Doomsday Inference, shouldn't we? Unless you want to defy Bayes' theorem itself! Maybe the ability to predict the ...

On today's episode, Kyle Grieve and Clay Finck continue their conversation on Investing: The Last Liberal Art by Robert Hagstrom. We discuss details on why using the right explanation for a business is so important to a good investment thesis, simple ways to improve your reading to get more out of the books and content that you consume, how to use simple mathematical concepts to improve your decision making in real-time, how to understand better System I and System II thinking and how it directly applies to investing, some of the latest mental models Kyle has learned from interviewing recent guests, and a whole lot more! IN THIS EPISODE YOU'LL LEARN: 00:00 - Intro 03:34 - How to use the proper explanations in your analysis to determine the right comparable best. 06:18 - Why Tesla is so misunderstood. 10:33 - Why the economics of Dino Polska make it an invalid comparison to other grocers. 12:02 - The power of narratives in investing and how we can guard ourselves from getting overly optimistic. 17:43 - How to optimize reading for learning. 40:18 - How to use Bayes theorem to tip odds in your favour and change your position sizing. 45:45 - Why value and prices become disconnected, and how human psychology plays into this. 50:20 - Why intuition (system I thinking) is so difficult to rely on in the stock market. 01:09:22 - How to make thinking in mental models a habit. 01:14:59 - Some of the latest mental models Kyle has learned from interviewing some of his latest guests. And so much more! Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join the exclusive TIP Mastermind Community to engage in meaningful stock investing discussions with Stig, Clay, Kyle, and the other community members. Buy Investing: The Last Liberal Art here. Buy The Great Mental Models here. Learn more about Mental Models here. Buy Poor Charlie's Almanck here. Buy More Than You Know here Follow Clay on Twitter and LinkedIn. Follow Kyle on Twitter and LinkedIn Check out all the books mentioned and discussed in our podcast episodes here. Enjoy ad-free episodes when you subscribe to our Premium Feed. NEW TO THE SHOW? Follow our official social media accounts: X (Twitter) | LinkedIn | Instagram | Facebook | TikTok. Check out our We Study Billionaires Starter Packs. Browse through all our episodes (complete with transcripts) here. Try our tool for picking stock winners and managing our portfolios: TIP Finance Tool. Enjoy exclusive perks from our favorite Apps and Services. Stay up-to-date on financial markets and investing strategies through our daily newsletter, We Study Markets. Learn how to better start, manage, and grow your business with the best business podcasts. SPONSORS Support our free podcast by supporting our sponsors: River Toyota Sun Life The Bitcoin Way Meyka Sound Advisory Industrious Range Rover iFlex Stretch Studios Briggs & Riley Public American Express USPS Shopify HELP US OUT! Help us reach new listeners by leaving us a rating and review on Apple Podcasts! It takes less than 30 seconds, and really helps our show grow, which allows us to bring on even better guests for you all! Thank you – we really appreciate it! Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

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: 35 Interactive Learning Modules Relevant to EAs / Effective Altruism (that are all free), published by spencerg on June 24, 2024 on The Effective Altruism Forum. Hi all! For quite a number of years now at Clearer Thinking we've been developing free, interactive, online learning modules on a wide variety of topics. I wanted to create a list of which of these tools are most relevant to EAs and to Effective Altruism itself, in case you find them useful (for yourself, or for sharing with others). Here's the list, organized by topic: 1. Calibration, prediction and knowledge practice Calibrate Your Judgment - this program contains thousands of question sets to help you become adept at making well-calibrated judgments. It also tracks your progress over time so you can see how you improve! Predict Psychological Correlations - test how accurate your understanding of psychology is by practicing and improving your ability to make predictions. Retrocaster - take the challenge to identify the correct global trends on a variety of topics - from Africa's future population to the evolution of CO2 emissions in the US. Biosafety Quiz - uncover the history of pandemics, test your biosafety knowledge, and learn essential steps to safeguard humanity's future. Long-Term Future Quiz - get a glimpse into the opportunities that may await humanity if we can avoid disasters such as nuclear war and extreme climate change. Invite your imagination to take flight with 11 multiple-choice questions. Artificial Intelligence Quiz - test your knowledge of artificial intelligence and some of the risks it poses. The Common Misconceptions Test - Separate fact from B.S. in this fun quiz that asks you to identify the misconceptions among 30 common beliefs. World's Biggest Problems Quiz - test your knowledge of some of the world's most pressing problems: global health, animal welfare, and existential risks to humanity. Political Bias Test - learn to spot your political biases and test your policy knowledge Charity Effectiveness - see if you can guess which social interventions had a positive effect, a negative effect, or no effect, based on a short description. Guess Which Experiments Replicate - Can you guess which of these high-profile experiments were legit? Improve Your Frequency Predictions - a quick quiz to test your ability to estimate the frequency of events and compare your scores to others'. 2. Sharpening Your Thinking Nuanced Thinking Techniques - Learn to recognize 3 common binary thinking traps and learn the nuanced thinking techniques you can use to combat them. The Question of Evidence - there is more to interpreting evidence than you might think. Learn to improve your predictions by understanding evidence on a deeper level using Bayes' rule. Can You Detect Weak Arguments? - Find out how well you can spot misleading rhetoric and recognize your own bias using real-world examples Faulty Reasoning Quiz - learn about five types of faulty arguments and take a quiz to see how well you can spot them Rhetorical Fallacies - train yourself to detect common reasoning errors that often go unnoticed. The Belief Challenger - our beliefs determine our behaviors and how we interact with others. Use this program to refine your beliefs and form more accurate views. The Planning Fallacy - ever notice that projects usually take longer than people predict? Understand the science behind this phenomenon and become a more reliable planner. Mental Traps - scientists have discovered a slew of systematic errors in human thought. Learn about a few of the mind's mistakes in this brief introduction. 3. Communication Productive Disagreements - learn techniques to have constructive arguments Become A Great Listener - this tool teaches the skill of Active Listening, a strategy commonly used by therapists, helpline volunteers,...

Salmon Wars Executive Producer and Host Cody McLaughlin is joined by David Bayes, a halibut charter boat captain our of Homer, Alaska and one of the men behind the wildly successful ‘STOP Alaskan Trawler Bycatch' Facebook Group that is a leading voice on the effort to reign in trawler bycatch. David, a small business owner and advocate for sustainable fishing practices, discusses the issue of trawl bycatch in Alaska and its impact on the state's fisheries. He explains how trawl bycatch, particularly of halibut and salmon, has led to significant cutbacks in the sport fishing industry and threatens the overall health of the ecosystem. David highlights the economic disparity between the trawl fleet, which generates billions of dollars in revenue but pays minimal taxes to the state, and other fishing sectors. He also emphasizes the indiscriminate nature of trawl fishing and the staggering amount of bycatch that is wasted each year. The conversation focuses on the impact of trawl fishing on salmon populations in Alaska and the need for stricter regulations. The main themes include the controversy surrounding chum salmon bycatch, the influence of the trawl fleet on fisheries management, the fear of speaking out against trawl fishing, the spread of misinformation by astroturf organizations, and potential policy solutions to mitigate the problem. Takeaways Trawl bycatch, particularly of halibut and salmon, has led to significant cutbacks in the sport fishing industry in Alaska. The trawl fleet generates billions of dollars in revenue but pays minimal taxes to the state, resulting in an economic disparity between different fishing sectors. Trawl fishing is indiscriminate and results in a staggering amount of bycatch that is wasted each year. The current management and regulations of trawl fishing prioritize economic gain over the health of the ecosystem and the sustainability of fish populations. Trawl fishing has a significant impact on salmon populations in Alaska, particularly through chum salmon bycatch. The trawl fleet has a strong influence on fisheries management, leading to loose regulations and conflicts of interest. There is a fear among fishermen and affiliated businesses of speaking out against trawl fishing due to potential repercussions. Astroturf organizations funded by the trawl industry spread misinformation and slander against those advocating for stricter regulations. Policy solutions to address the issue include setting stricter bycatch limits, increasing observer coverage, and banning bottom trawling. Learn more about Trout Stream Studios: https://www.troutstreamstudios.com  Get to know your host on Instagram: https://www.instagram.com/mclaugh1985/  Follow the host on Twitter: https://twitter.com/home  Follow Trout Stream Studios on LinkedIn and get special bonus content, more trailers, and additional shows: https://www.linkedin.com/company/trout-stream-studios  Follow Trout Stream Studios on Facebook and get special bonus content, more trailers, and additional shows: https://www.facebook.com/troutstreamstudios  Follow The Show On TikTok: https://www.tiktok.com/@troutstreamstudios?_t=8nONxhNYrP8&_r=1 Find Trout Stream Studios On YouTube For Exclusive Video Content: https://www.youtube.com/channel/UCijfUNphYKTMOU12giVt7lw Learn more about STOP Alaskan Trawler Bycatch: https://www.facebook.com/groups/181111123119023/  Learn more about your ad choices. Visit megaphone.fm/adchoices

In this episode, Xavier Bonilla has a dialogue with Tom Chivers about Bayesian probability and the impact Bayesian priors have on ourselves. They define Bayesian priors, Thomas Bayes, subjective aspects of Bayes theorem, and the problematic elements of statistical figures such as Galton, Pearson, and Fisher. They talk about the replication crisis, p-hacking, where priors come from, AI, Friston's free energy principle, and Bayesian priors in our world today. Tom Chivers is a science writer. He does freelance science writing and also writes for Semafor.com's daily Flagship email. Before joining Semafor, he was a science editor at UnHerd, science writer for BuzzFeed UK, and features writer for the Telegraph. He is the author of several books including the most recent, Everything Is Predictable: How Bayesian Statistics Explain Our World. Website: https://tomchivers.com/ Get full access to Converging Dialogues at convergingdialogues.substack.com/subscribe

Everything Is Predictable: How Bayesian Statistics Explain Our World by Tom Chivers https://amzn.to/3wxZAKu A captivating and user-friendly tour of Bayes's theorem and its global impact on modern life from the acclaimed science writer and author of The Rationalist's Guide to the Galaxy. At its simplest, Bayes's theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes's theorem is a description of almost everything. But who was the man who lent his name to this theorem? How did an 18th-century Presbyterian minister and amateur mathematician uncover a theorem that would affect fields as diverse as medicine, law, and artificial intelligence? Fusing biography, razor-sharp science writing, and intellectual history, Everything Is Predictable is an entertaining tour of Bayes's theorem and its impact on modern life, showing how a single compelling idea can have far reaching consequences.

At its simplest, Bayes's theorem describes the probability of an event, based on prior knowledge of conditions that might be related to the event. But in Everything Is Predictable, Tom Chivers lays out how it affects every aspect of our lives. He explains why highly accurate screening tests can lead to false positives and how a failure to account for it in court has put innocent people in jail. A cornerstone of rational thought, many argue that Bayes's theorem is a description of almost everything. But who was the man who lent his name to this theorem? How did an 18th-century Presbyterian minister and amateur mathematician uncover a theorem that would affect fields as diverse as medicine, law, and artificial intelligence? Fusing biography and intellectual history, Everything Is Predictable is an entertaining tour of Bayes's theorem and its impact on modern life, showing how a single compelling idea can have far reaching consequences. Tom Chivers is an author and the award-winning science writer for Semafor. Previously he was the science editor at UnHerd.com and BuzzFeed UK. His writing has appeared in The Times (London), The Guardian, New Scientist, Wired, CNN, and more. He was awarded the Royal Statistical Society's “Statistical Excellence in Journalism” awards in 2018 and 2020, and was declared the science writer of the year by the Association of British Science Writers in 2021. His books include The Rationalist's Guide to the Galaxy: Superintelligent AI and the Geeks Who Are Trying to Save Humanity's Future, and How to Read Numbers: A Guide to Stats in the News (and Knowing When to Trust Them). His new book is Everything Is Predictable: How Bayesian Statistics Explain Our World. Shermer and Chivers discuss: Thomas Bayes, his equation, and the problem it solves • Bayesian decision theory vs. statistical decision theory • Popperian falsification vs. Bayesian estimation • Sagan's ECREE principle • Bayesian epistemology and family resemblance • paradox of the heap • Reality as controlled hallucination • human irrationality • superforecasting • mystical experiences and religious truths • Replication Crisis in science • Statistical Detection Theory and Signal Detection Theory • Medical diagnosis problem and why most people get it wrong.

SummaryTom Chivers discusses his book 'Everything is Predictable: How Bayesian Statistics Explain Our World' and the applications of Bayesian statistics in various fields. He explains how Bayesian reasoning can be used to make predictions and evaluate the likelihood of hypotheses. Chivers also touches on the intersection of AI and ethics, particularly in relation to AI-generated art. The conversation explores the history of Bayes' theorem and its role in science, law, and medicine. Overall, the discussion highlights the power and implications of Bayesian statistics in understanding and navigating the world. The conversation explores the role of AI in prediction and the importance of Bayesian thinking. It discusses the progress of AI in image classification and the challenges it still faces, such as accurately depicting fine details like hands. The conversation also delves into the topic of predictions going wrong, particularly in the context of conspiracy theories. It highlights the Bayesian nature of human beliefs and the influence of prior probabilities on updating beliefs with new evidence. The conversation concludes with a discussion on the relevance of Bayesian statistics in various fields and the need for beliefs to have probabilities and predictions attached to them. Takeaways Bayesian statistics can be used to make predictions and evaluate the likelihood of hypotheses. Bayes' theorem has applications in various fields, including science, law, and medicine. The intersection of AI and ethics raises complex questions about AI-generated art and the predictability of human behavior. Understanding Bayesian reasoning can enhance decision-making and critical thinking skills. AI has made significant progress in image classification, but still faces challenges in accurately depicting fine details. Predictions can go wrong due to the influence of prior beliefs and the interpretation of new evidence. Beliefs should have probabilities and predictions attached to them, allowing for updates with new information. Bayesian thinking is crucial in various fields, including AI, pharmaceuticals, and decision-making. The importance of defining predictions and probabilities when engaging in debates and discussions.

Você é livre pra fazer suas escolhas? Ou será que todas já estão determinadas? Você de fato escolheu ouvir esse cast ou será que toda a sua história de vida, junto com a história do universo, te levaram a isso? Um debate filosófico sobre o que significa viver em um mundo determinista, as repercussões teóricas e práticas disso.         Patronato do SciCast: Patreon SciCast Padrim SciCast Nos ajude via Pix também, chave: contato@scicast.com.br Sua pequena contribuição ajuda o Portal Deviante a continuar divulgando Ciência! Contatos: contato@scicast.com.br https://twitter.com/scicastpodcast https://www.facebook.com/scicastpodcast https://instagram.com/scicastpodcast Fale conosco! E não esqueça de deixar o seu comentário na postagem desse episódio! Expediente: Produção Geral: Tarik Fernandes e André Trapani Equipe de Gravação: Tarik Fernandes, André Trapani, Roberto Spinelli, Felipe Novaes e Anna Rita Erthal Citação ABNT: Scicast #589: Determinismo. Locução: Tarik Fernandes, André Trapani, Roberto Spinelli, Felipe Novaes, Anna Rita Erthal. [S.l.] Portal Deviante, 26/04/2024. Podcast. Disponível em: https://www.deviante.com.br/podcasts/scicast-589 Arte: Jânio Referências e Indicações   Sugestões de literatura: LAPLACE, Pierre-Simon. Ensaio filosófico sobre as probabilidades. Rio de Janeiro: Editora Contraponto, 2010. SEARLE, John. Neurobiologia e Liberdade. Unifesp, 2008. DENNETT, Daniel. Brainstorms. Unifesp, 2006.   Sugestões de filmes: The Good Place, S03E07: O pior uso possível do livre-arbítrio.   Sugestões de vídeos: https://www.youtube.com/watch?v=aYzFH8xqhns&t=1s    Sugestões de links: Scicast #108: Isaac Newton: https://www.deviante.com.br/podcasts/scicast/108-isaac-newton/  Scicast #152: Física Quântica: https://www.deviante.com.br/podcasts/scicast/scicast-152-fisica-quantica/  Scicast #165: Física Quântica 2: https://www.deviante.com.br/podcasts/scicast/scicast-165-fisica-quantica-2/  Scicast #377: Teorema de Bayes: https://www.deviante.com.br/podcasts/scicast-377/  SciCast #315: Psicologia: https://www.deviante.com.br/podcasts/scicast-315/  SciCast #537: Desigualdades de Bell: https://www.deviante.com.br/podcasts/scicast-537/ SciCast #477: Emaranhamento Quântico: https://www.deviante.com.br/podcasts/scicast-477/See omnystudio.com/listener for privacy information.

Summary: The episode discusses the 10,000 year dilemma, which is a thought experiment on how to deal with nuclear waste in the future. Today's episode is hosted by guest host David Gibson, who is the founder of the Ray Kitty Creation Workshop. (Find out more about the Ray Kitty Creation Workshop by clicking here). Gabriel and Autumn are out this week, but will be returning in short order with 3 separate interviews with authors of some fantastic popular science and math books including: The Gravity of Math: How Geometry Rules the Universe by Dr. Shing-Tung Yau and Steve Nadis. This book is all about the history of our understanding of gravity from the theories of Isaac Newton to Albert Einstein and beyond, including gravitational waves, black holes, as well as some of the current uncertainties regarding a precise definition of mass. On sale now! EVERYTHING IS PREDICTABLE: How Bayesian Statistics Explain Our World by Tom Chivers. Published by Simon and Schuster. This book explains the importance of Baye's Theorem in helping us to understand why highly accurate screening tests can lead to false positives, a phenomenon we saw during the Covid-19 pandemic; How a failure to account for Bayes' Theorem has put innocent people in jail; How military strategists using the theorem can predict where an enemy will strike next, and how Baye's Theorem is helping us to understang machine learning processes - a critical skillset to have in the 21st century. Available 05/07/2024 A CITY ON MARS: Can we settle space, should we settle space, and have we really thought this through? by authors Dr. Kelly and Zach Weinersmith. Zach Weinersmith is the artist and creator of the famous cartoon strip Saturday Morning Breaking Cereal! We've got a lot of great episodes coming up! Stay tuned.

Saar Wilf is an ex-Israeli entrepreneur. Since 2016, he's been developing a new form of reasoning, meant to transcend normal human bias. His method - called Rootclaim - uses Bayesian reasoning, a branch of math that explains the right way to weigh evidence. This isn't exactly new. Everyone supports Bayesian reasoning. The statisticians support it, I support it, Nate Silver wrote a whole book supporting it. But the joke goes that you do Bayesian reasoning by doing normal reasoning while muttering “Bayes, Bayes, Bayes” under your breath. Nobody - not the statisticians, not Nate Silver, certainly not me - tries to do full Bayesian reasoning on fuzzy real-world problems. They'd be too hard to model. You'd make some philosophical mistake converting the situation into numbers, then end up much worse off than if you'd tried normal human intuition. Rootclaim spent years working on this problem, until he was satisfied his method could avoid these kinds of pitfalls. Then they started posting analyses of different open problems to their site, rootclaim.com. Here are three:

Plastics and heart disease, MINT trial letters-to-the-editor and Bayes theorem, and Brugada syndrome are the topics John Mandrola, MD, discusses in this week's podcast. This podcast is intended for healthcare professionals only. To read a partial transcript or to comment, visit: https://www.medscape.com/twic I. Plastics and Heart Disease Plastic Particles in Carotid Plaques Linked to CV Events https://www.medscape.com/viewarticle/plastic-particles-carotid-plaques-linked-cv-events-2024a10004ge Plastics and ASCVD Study https://www.nejm.org/doi/full/10.1056/NEJMoa2309822 Review https://www.nejm.org/doi/full/10.1056/NEJMra2300476 Editorial https://www.nejm.org/doi/full/10.1056/NEJMe2400683 II. MINT trial LTE and Bayes Theorem In MI With Anemia, Results May Favor Liberal Transfusion: MINT https://www.medscape.com/viewarticle/998376 The MINT Study https://www.nejm.org/doi/full/10.1056/NEJMoa2307983 Letter-to-the-Editor https://www.nejm.org/doi/full/10.1056/NEJMc2400982 Likelihood Ratio https://www.cebm.ox.ac.uk/resources/ebm-tools/likelihood-ratios III. Brugada Syndrome The EHJ paper: https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehae133/7623123 You may also like: The Bob Harrington Show with the Stephen and Suzanne Weiss Dean of Weill Cornell Medicine, Robert A. Harrington, MD. https://www.medscape.com/author/bob-harrington Questions or feedback, please contact news@medscape.net