Podcasts about graphs

Born in the 18th century when Leonhard Euler solved the puzzle of the seven bridges of Königsberg, graph theory has become a foundational tool in mathematics. It studies relationships through nodes (vertices) and the links (edges) that connect them, transforming the complexity of systems — from friendship networks to airline routes — into elegant abstractions that reveal underlying structure and interaction. Maria Chudnovsky from Princeton University is a leading mathematician in the field. In this episode of The Joy of Why, Chudnovsky talks with co-host Janna Levin about how she got into graph theory, solved the decades-old perfect graph problem, and used it to plan her wedding seating chart. Chudnovsky also reflects on her appearance in commercials as a “superstar mathematician,” and how her background primed her for a discipline that transcends language, culture and time.

The Unseen World supercut. How big is the universe? What's at the edge? Why does light have a speed limit? Discover our full back catalogue of hundreds of videos on YouTube: ⁠https://www.youtube.com/@astrumspace⁠For early access videos, bonus content, and to support the channel, join us on Patreon: ⁠https://astrumspace.info/4ayJJuZ⁠

AI models today have a 50% chance of successfully completing a task that would take an expert human one hour. Seven months ago, that number was roughly 30 minutes — and seven months before that, 15 minutes.These are substantial, multi-step tasks requiring sustained focus: building web applications, conducting machine learning research, or solving complex programming challenges.Today's guest, Beth Barnes, is CEO of METR (Model Evaluation & Threat Research) — the leading organisation measuring these capabilities.These highlights are from episode #217 of The 80,000 Hours Podcast: Beth Barnes on the most important graph in AI right now — and the 7-month rule that governs its progress, and include:Can we see AI scheming in the chain of thought? (00:00:34)We have to test model honesty even before they're used inside AI companies (00:05:48)It's essential to thoroughly test relevant real-world tasks (00:10:13)Recursively self-improving AI might even be here in two years — which is alarming (00:16:09)Do we need external auditors doing AI safety tests, not just the companies themselves? (00:21:55)A case against safety-focused people working at frontier AI companies (00:29:30)Open-weighting models is often good, and Beth has changed her attitude about it (00:34:57)These aren't necessarily the most important or even most entertaining parts of the interview — so if you enjoy this, we strongly recommend checking out the full episode!And if you're finding these highlights episodes valuable, please let us know by emailing podcast@80000hours.org.Highlights put together by Ben Cordell, Milo McGuire, and Dominic Armstrong

The era of making AI smarter just by making it bigger is ending. But that doesn't mean progress is slowing down — far from it. AI models continue to get much more powerful, just using very different methods, and those underlying technical changes force a big rethink of what coming years will look like.Toby Ord — Oxford philosopher and bestselling author of The Precipice — has been tracking these shifts and mapping out the implications both for governments and our lives.Links to learn more, video, highlights, and full transcript: https://80k.info/to25As he explains, until recently anyone can access the best AI in the world “for less than the price of a can of Coke.” But unfortunately, that's over.What changed? AI companies first made models smarter by throwing a million times as much computing power at them during training, to make them better at predicting the next word. But with high quality data drying up, that approach petered out in 2024.So they pivoted to something radically different: instead of training smarter models, they're giving existing models dramatically more time to think — leading to the rise in “reasoning models” that are at the frontier today.The results are impressive but this extra computing time comes at a cost: OpenAI's o3 reasoning model achieved stunning results on a famous AI test by writing an Encyclopedia Britannica's worth of reasoning to solve individual problems at a cost of over $1,000 per question.This isn't just technical trivia: if this improvement method sticks, it will change much about how the AI revolution plays out, starting with the fact that we can expect the rich and powerful to get access to the best AI models well before the rest of us.Toby and host Rob discuss the implications of all that, plus the return of reinforcement learning (and resulting increase in deception), and Toby's commitment to clarifying the misleading graphs coming out of AI companies — to separate the snake oil and fads from the reality of what's likely a "transformative moment in human history."Recorded on May 23, 2025.Chapters:Cold open (00:00:00)Toby Ord is back — for a 4th time! (00:01:20)Everything has changed (and changed again) since 2020 (00:01:37)Is x-risk up or down? (00:07:47)The new scaling era: compute at inference (00:09:12)Inference scaling means less concentration (00:31:21)Will rich people get access to AGI first? Will the rest of us even know? (00:35:11)The new regime makes 'compute governance' harder (00:41:08)How 'IDA' might let AI blast past human level — or not (00:50:14)Reinforcement learning brings back 'reward hacking' agents (01:04:56)Will we get warning shots? Will they even help? (01:14:41)The scaling paradox (01:22:09)Misleading charts from AI companies (01:30:55)Policy debates should dream much bigger (01:43:04)Scientific moratoriums have worked before (01:56:04)Might AI 'go rogue' early on? (02:13:16)Lamps are regulated much more than AI (02:20:55)Companies made a strategic error shooting down SB 1047 (02:29:57)Companies should build in emergency brakes for their AI (02:35:49)Toby's bottom lines (02:44:32)Tell us what you thought! https://forms.gle/enUSk8HXiCrqSA9J8Video editing: Simon MonsourAudio engineering: Ben Cordell, Milo McGuire, Simon Monsour, and Dominic ArmstrongMusic: Ben CordellCamera operator: Jeremy ChevillotteTranscriptions and web: Katy Moore

Explore God's purpose in trials: growing faith, not seeking shortcuts like wealth or false spiritual paths. Learn to surrender unmet desires and resist temptation. This message, rooted in James 1, guides you to find true freedom and fulfillment in Jesus alone, embracing His process for a life transformed.   Pastor: Jordan Hansen Series: James: Faith That Works (2) Title: Shortcuts Date: 2025.06.21+22   CHAPTERS: 00:00 - Teaser 00:34 - Series 01:04 - Sermon (1) 01:43 - Thunderbirds 02:11 - Sermon (2) 04:58 - Question 08:42 - Point 1a 16:52 - Crown of Life 17:36 - Point 1b 28:08 - Point 2 30:10 - Point 3a 32:51 - Graph 33:59 - Point 3b 38:42 - Big Idea 39:40 - Closing   SERVICE TIMES:

Today on this edition of the Math Lab Shorts. This is going to be talking about the Polar Equations using for software development.Recorded on 6/14/2025

In this podcast, Nikolaos Vasiloglou from @RelationalAI team discusses how knowledge graph based applications are leveraging Generative AI technologies and how Graph RAG techniques can be used to enhance data analytics and insights. Read a transcript of this interview: https://bit.ly/43IYWGN Subscribe to the Software Architects' Newsletter for your monthly guide to the essential news and experience from industry peers on emerging patterns and technologies: https://www.infoq.com/software-architects-newsletter Upcoming Events: InfoQ Dev Summit Boston (June 9-10, 2025) Actionable insights on today's critical dev priorities. devsummit.infoq.com/conference/boston2025 InfoQ Dev Summit Munich (October 15-16, 2025) Essential insights on critical software development priorities. https://devsummit.infoq.com/conference/munich2025 QCon San Francisco 2025 (November 17-21, 2025) Get practical inspiration and best practices on emerging software trends directly from senior software developers at early adopter companies. https://qconsf.com/ QCon AI New York 2025 (December 16-17, 2025) https://ai.qconferences.com/ The InfoQ Podcasts: Weekly inspiration to drive innovation and build great teams from senior software leaders. Listen to all our podcasts and read interview transcripts: - The InfoQ Podcast https://www.infoq.com/podcasts/ - Engineering Culture Podcast by InfoQ https://www.infoq.com/podcasts/#engineering_culture - Generally AI: https://www.infoq.com/generally-ai-podcast/ Follow InfoQ: - Mastodon: https://techhub.social/@infoq - Twitter: twitter.com/InfoQ - LinkedIn: www.linkedin.com/company/infoq - Facebook: bit.ly/2jmlyG8 - Instagram: @infoqdotcom - Youtube: www.youtube.com/infoq - Bluesky: https://bsky.app/profile/infoq.com Write for InfoQ: Learn and share the changes and innovations in professional software development. - Join a community of experts. - Increase your visibility. - Grow your career. https://www.infoq.com/write-for-infoq

Episode: 2467 Graph Theory and the Königsberg Bridge Problem.  Today, the bridges of Königsberg.

Send us a text*Causal Inference From Human Behavior, Reproducibility Crisis & The Power of Causal Graphs*Is Jonathan Heidt right that social media causes the mental health crisis in young people?If so, how can we be sure?Can other disciplines learn something from the reproducibility crisis in Psychology, and what is multiverse analysis?Join us for a conversation on causal inference from human behavior, the reproducibility crisis in sciences, and the power of causal graphs!------------------------------------------------------------------------------------------------------Audio version available on YouTube: https://youtu.be/YQetmI-y5gMRecorded on May 16, 2025, in Leipzig, Germany.------------------------------------------------------------------------------------------------------*About The Guest*Julia Rohrer, PhD, is a researcher and personality psychologist at the University of Leipzig. She's interested in the effects of birth order, age patterns in personality, human well-being, and causal inference. Her works have been published in top journals, including Nature Human Behavior. She has been an active advocate for increased research transparency, and she continues this mission as a senior editor of Psychological Science. Julia frequently gives talks about good practices in science and causal inference. You can read Julia's blog at https://www.the100.ci/*Links*Papers- Rohrer, J. (2024) "Causal inference for psychologists who think that causal inference is not for them" (https://compass.onlinelibrary.wiley.com/doi/10.1111/spc3.12948)- Bailey, D., ..., Rohrer, J. et al (2024) "Causal inference on human behaviour" (https://www.nature.com/articles/s41562-024-01939-z.epdf)- Rohrer, J. et al (2024) "The Effects of Satisfaction with Different Domains of Life on GenInspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifySupport the showCausal Bandits PodcastCausal AI || Causal Machine Learning || Causal Inference & DiscoveryWeb: https://causalbanditspodcast.comConnect on LinkedIn: https://www.linkedin.com/in/aleksandermolak/Join Causal Python Weekly: https://causalpython.io The Causal Book: https://amzn.to/3QhsRz4

Around 1 month ago, I wrote a similar Forum post on the Easterlin Paradox. I decided to take it down because: 1) after useful comments, the method looked a little half-baked; 2) I got in touch with two academics – Profs. Caspar Kaiser and Andrew Oswald – and we are now working on a paper together using a related method. That blog post actually came to the opposite conclusion, but, as mentioned, I don't think the method was fully thought through. I'm a little more confident about this work. It essentially summarises my Undergraduate dissertation. You can read a full version here. I'm hoping to publish this somewhere, over the Summer. So all feedback is welcome. TLDR Life satisfaction (LS) appears flat over time, despite massive economic growth — the “Easterlin Paradox.” Some argue that happiness is rising, but we're reporting it more conservatively — [...] ---Outline:(00:57) TLDR(02:11) 1. Background: A Happiness Paradox(04:02) 2. What is Rescaling?(06:23) 3. My Approach: Life Events would look smaller on stretched out rulers(08:10) 4. Results: Effects Are Shrinking(10:46) 5. How much might we be underestimating life satisfaction?(12:42) 6. Implications--- First published: May 26th, 2025 Source: https://forum.effectivealtruism.org/posts/wSySeNZ6C7hfDfBSx/rescaling-and-the-easterlin-paradox-2-0 --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

AI models today have a 50% chance of successfully completing a task that would take an expert human one hour. Seven months ago, that number was roughly 30 minutes — and seven months before that, 15 minutes. (See graph.)These are substantial, multi-step tasks requiring sustained focus: building web applications, conducting machine learning research, or solving complex programming challenges.Today's guest, Beth Barnes, is CEO of METR (Model Evaluation & Threat Research) — the leading organisation measuring these capabilities.Links to learn more, video, highlights, and full transcript: https://80k.info/bbBeth's team has been timing how long it takes skilled humans to complete projects of varying length, then seeing how AI models perform on the same work. The resulting paper “Measuring AI ability to complete long tasks” made waves by revealing that the planning horizon of AI models was doubling roughly every seven months. It's regarded by many as the most useful AI forecasting work in years.Beth has found models can already do “meaningful work” improving themselves, and she wouldn't be surprised if AI models were able to autonomously self-improve as little as two years from now — in fact, “It seems hard to rule out even shorter [timelines]. Is there 1% chance of this happening in six, nine months? Yeah, that seems pretty plausible.”Beth adds:The sense I really want to dispel is, “But the experts must be on top of this. The experts would be telling us if it really was time to freak out.” The experts are not on top of this. Inasmuch as there are experts, they are saying that this is a concerning risk. … And to the extent that I am an expert, I am an expert telling you you should freak out.Chapters:Cold open (00:00:00)Who is Beth Barnes? (00:01:19)Can we see AI scheming in the chain of thought? (00:01:52)The chain of thought is essential for safety checking (00:08:58)Alignment faking in large language models (00:12:24)We have to test model honesty even before they're used inside AI companies (00:16:48)We have to test models when unruly and unconstrained (00:25:57)Each 7 months models can do tasks twice as long (00:30:40)METR's research finds AIs are solid at AI research already (00:49:33)AI may turn out to be strong at novel and creative research (00:55:53)When can we expect an algorithmic 'intelligence explosion'? (00:59:11)Recursively self-improving AI might even be here in two years — which is alarming (01:05:02)Could evaluations backfire by increasing AI hype and racing? (01:11:36)Governments first ignore new risks, but can overreact once they arrive (01:26:38)Do we need external auditors doing AI safety tests, not just the companies themselves? (01:35:10)A case against safety-focused people working at frontier AI companies (01:48:44)The new, more dire situation has forced changes to METR's strategy (02:02:29)AI companies are being locally reasonable, but globally reckless (02:10:31)Overrated: Interpretability research (02:15:11)Underrated: Developing more narrow AIs (02:17:01)Underrated: Helping humans judge confusing model outputs (02:23:36)Overrated: Major AI companies' contributions to safety research (02:25:52)Could we have a science of translating AI models' nonhuman language or neuralese? (02:29:24)Could we ban using AI to enhance AI, or is that just naive? (02:31:47)Open-weighting models is often good, and Beth has changed her attitude to it (02:37:52)What we can learn about AGI from the nuclear arms race (02:42:25)Infosec is so bad that no models are truly closed-weight models (02:57:24)AI is more like bioweapons because it undermines the leading power (03:02:02)What METR can do best that others can't (03:12:09)What METR isn't doing that other people have to step up and do (03:27:07)What research METR plans to do next (03:32:09)This episode was originally recorded on February 17, 2025.Video editing: Luke Monsour and Simon MonsourAudio engineering: Ben Cordell, Milo McGuire, Simon Monsour, and Dominic ArmstrongMusic: Ben CordellTranscriptions and web: Katy Moore

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Wenn du als Online-Marketer die digitale Sichtbarkeit deines Unternehmens auf ein neues Level heben willst, dann solltest du dir diese Podcast-Folge nicht entgehen lassen! Mario Jung (OMT GmbH) und Benny Windolph (HECHT INS GEFECHT) nehmen dich mit in die Welt des Google Knowledge Graph und zeigen dir, warum er für deine Marke unverzichtbar ist. Sie erklären, wie sich der Knowledge Graph von klassischen Suchergebnissen unterscheidet und welche Vorteile du als Unternehmer daraus ziehen kannst. Außerdem bekommst du praxisnahe Tipps, wie du aktiv daran arbeiten kannst, im Knowledge Graph sichtbar zu werden – inklusive der Rolle von strukturierten Daten (Schema Markup), Wikipedia und anderen relevanten Quellen. Doch Achtung: Wer hier Fehler macht, kann sich selbst schaden! Die Experten decken die häufigsten Fallstricke auf und zeigen dir, wie du veraltete oder falsche Informationen korrigieren kannst. Und natürlich werfen sie einen Blick in die Zukunft: Welche Rolle wird Künstliche Intelligenz (KI) spielen? Welche neuen Google-Produkte und Features sind für dich relevant? Abgerundet wird das Ganze mit echten Erfolgsbeispielen und wertvollen Tools, die dir helfen, deinen Platz im Knowledge Graph zu sichern. Diese Episode ist ein Must-Listen für alle, die ihr SEO-Game auf das nächste Level bringen und bei Google ganz oben mitspielen wollen!

How to build artificial intelligence systems that understand cause and effect, moving beyond simple correlations? As we all know, correlation is not causation. "Spurious correlations" can show, for example, how rising ice cream sales might statistically link to more drownings, not because one causes the other, but due to an unobserved common cause like warm weather. Our guest, Utkarshani Jaimini, a researcher from the University of South Carolina's Artificial Intelligence Institute, tries to tackle this problem by using knowledge graphs that incorporate domain expertise.  Knowledge graphs (structured representations of information) are combined with neural networks in the field of neurosymbolic AI to represent and reason about complex relationships. This involves creating causal ontologies, incorporating the "weight" or strength of causal relationships and hyperrelations. This field has many practical applications such as for AI explainability, healthcare and autonomous driving. Follow our guest Utkarshani Jaimini's Webpage Linkedin Papers in focus CausalLP: Learning causal relations with weighted knowledge graph link prediction, 2024 HyperCausalLP: Causal Link Prediction using Hyper-Relational Knowledge Graph, 2024  

Well nerds, buckle up for this one. My buddy Ryan Burge has returned with his latest graphs about religion and the 2024 election, and let me tell you - it was zesty. We started talking about minor league baseball, chicken raising, and somehow ended up dissecting why 83% of white evangelicals voted for Trump (spoiler: it's not shocking). Ryan breaks down the real story of the 2024 election - how non-white evangelicals are now 50/50, why mainline Protestants aren't actually that liberal, and the fascinating shifts happening in the Catholic vote. We dive into the data that shows education and church attendance create some pretty stark political divides, and why Democrats might want to rethink their approach to people of faith. But this is us, so we also talked about LeBron's hair transplants, whether 100 men could take down a silverback gorilla, why online gambling is destroying America, and Ryan's ongoing campaign to get academics to eat at steakhouses instead of Sweet Green. Plus, Ryan explains why Mark Driscoll might be the godfather of the manosphere, and we debate whether Joe Scarborough and Mika have the worst work schedule in television. Oh, and we somehow got into a deep discussion about Mayor Pete's beard and why Democrats need to learn how to talk about their faith without sounding like they're apologizing for it. Because apparently that's where our brains go. Want the full conversation? This is just a taste of what we covered in over two hours of completely unhinged discussion. If you're a member of either Graphs About Religion (Ryan's substack) or Process This (mine), you get access to the entire unedited conversation, plus invitations to join us live for future streams where things get even more zesty - and yes, I'm using that word in the Whitehead sense, not the Gen Z sense.   Previous Visits from Ryan Burge Distrust & Denominations Trust, Religion, & a Functioning Democracy What it's like to close a church The Future of Christian Education & Ministry in Charts The Sky is Falling & the Charts are Popping! Graphs about Religion & Politics w/ Spicy Banter a Year in Religion (in Graphs) Evangelical Jews, Educated Church-Goers, & other bits of dizzying data 5 Religion Graphs w/ a side of Hot Takes Myths about Religion & Politics Ryan P. Burge is an assistant professor of political science at Eastern Illinois University. Author of numerous journal articles, he is the co-founder of and a frequent contributor to Religion in Public, a forum for scholars of religion and politics to make their work accessible to a general audience. Burge is a pastor in the American Baptist Church. Upcoming Online Class:⁠⁠⁠⁠ Rediscovering the Spirit: Hand-Raisers, Han, & the Holy Ghost⁠⁠⁠⁠ is an open-online course exploring the dynamic, often overlooked third person of the Trinity. Based on Grace Ji-Sun Kim's groundbreaking work on the Holy Spirit this class takes participants on a journey through biblical foundations, historical developments, diverse cultural perspectives, and practical applications of Spirit theology. ⁠⁠⁠⁠As always, this class is donation-based, including 0. To get class info and sign up, head over here. ⁠⁠⁠⁠ _____________________ ⁠⁠⁠⁠⁠⁠Hang with 40+ Scholars & Podcasts and 600 people at Theology Beer Camp 2025 (Oct. 16-18) in St. Paul, MN. ⁠⁠⁠⁠⁠⁠ This podcast is a ⁠⁠⁠⁠⁠⁠Homebrewed Christianity⁠⁠⁠⁠⁠⁠ production. Follow ⁠⁠⁠⁠⁠⁠the Homebrewed Christianity⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠Theology Nerd Throwdown⁠⁠⁠⁠⁠⁠, & ⁠⁠⁠⁠⁠⁠The Rise of Bonhoeffer⁠⁠⁠⁠⁠⁠ podcasts for more theological goodness for your earbuds. Join over 80,000 other people by joining our⁠⁠⁠⁠⁠⁠ Substack - Process This!⁠⁠⁠⁠⁠⁠ Get instant access to over 45 classes at ⁠⁠⁠⁠⁠⁠www.TheologyClass.com⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠Follow the podcast, drop a review⁠⁠⁠⁠⁠⁠, send ⁠⁠⁠⁠⁠⁠feedback/questions⁠⁠⁠⁠⁠⁠ or become a ⁠⁠⁠⁠⁠⁠member of the HBC Community⁠⁠⁠⁠⁠⁠. Learn more about your ad choices. Visit megaphone.fm/adchoices

In this special edition of the Washington AI Network Podcast, recorded live at NVIDIA 2025 GTC conference, host Tammy Haddad takes listeners inside the future of AI innovation with startups. NVIDIA's Startup Guru, Howard Wright, shares how the Inception program supports over 27,000 startups worldwide, unlocking capital, customers, and compute to fuel AI breakthroughs. Fay Arjomandi, CEO of mimik, introduces her edge-first, privacy-focused approach to agent-based AI systems. ArangoDB's Corey Sommers explains why graph databases are the foundation of intelligent, responsive generative AI platforms. And nTop's Alec Guay and Todd McDevitt demonstrate how their GPU-powered design tools are slashing engineering cycles across aerospace, energy, and manufacturing. From defense to design, this episode showcases the real-world power of AI startups—and how the NVIDIA ecosystem helps them scale.

On this week's episode, Kyle recaps his playoff weekend in Indianapolis — from attending Games 3 and 4 of Pacers/Cavs to exploring a massive 200-table card show. He shares game-day impressions, autograph stories, and some key card pickups along the way.

Send us a textGet the vidIQ plugin for FREE: https://vidiq.ink/3yvoc7rJoin Discord: https://www.vidiq.com/discordWant a 1 on 1 coach? https://vidiq.ink/theboost1on1Check out the video version here: https://youtu.be/0HPucaCMwrQAudience engagement metrics on YouTube aren't always what they seem, and retention graphs can be misleading if viewed in isolation. We explore why "good" retention varies drastically based on content length, traffic sources, and viewer behavior across different platforms.• TikTok has reportedly surpassed Twitch to become the second most streamed platform after YouTube• Retention graphs look different depending on video length, with shorts typically exceeding 100% while long-form content rarely does• High-view videos often have lower retention percentages than creators expect• Search traffic typically has shorter view duration than browse or suggested traffic• Breaking down retention by traffic source and subscriber status reveals more useful insights than aggregate data• YouTube doesn't currently track "hover behavior" when viewers preview but don't click• Platform differences significantly impact engagement behaviors (TV vs. mobile vs. desktop)• Mr. Beast has set unrealistic retention expectations for many creators• Viewer disclaimers and overexplaining opinions have become increasingly common in contentIf you enjoyed this episode, please leave us a five-star review and join us next time when we'll be sharing more about ourselves as creators.

Graph Therapeutics combines AI-driven perturbation modeling with multi-omics data to develop targeted therapies for patients with complex immune-mediated diseases who currently lack effective treatment options.

This show has been flagged as Explicit by the host. Research Tools Harvard Referencing - https://en.wikipedia.org/wiki/Parenthetical_referencing#Author%E2%80%93date_(Harvard_referencing) Google Notebook LM - https://notebooklm.google/ Google Scholar - https://scholar.google.co.uk/ Connected Papers - https://www.connectedpapers.com/ Zotero - https://www.zotero.org/ Databases SQL Databases - https://en.wikipedia.org/wiki/Relational_database NoSQL Databases - https://en.wikipedia.org/wiki/NoSQL Graph Databases - https://en.wikipedia.org/wiki/Graph_database Misc Borland Graphics Interface - https://en.wikipedia.org/wiki/Borland_Graphics_Interface Hough Transform - https://en.wikipedia.org/wiki/Hough_transform Joplin - https://joplinapp.org/ Provide feedback on this episode.

Or on the types of prioritization, their strengths, pitfalls, and how EA should balance them The cause prioritization landscape in EA is changing. Prominent groups have shut down, others have been founded, and everyone is trying to figure out how to prepare for AI. This is the first in a series of posts examining the state of cause prioritization and proposing strategies for moving forward. Executive Summary Performing prioritization work has been one of the main tasks, and arguably achievements, of EA. We highlight three types of prioritization: Cause Prioritization, Within-Cause (Intervention) Prioritization, and Cross-Cause (Intervention) Prioritization. We ask how much of EA prioritization work falls in each of these categories: Our estimates suggest that, for the organizations we investigated, the current split is 89% within-cause work, 2% cross-cause, and 9% cause prioritization. We then explore strengths and potential pitfalls of each level: Cause [...] ---Outline:(00:37) Executive Summary(03:09) Introduction: Why prioritize? Have we got it right?(05:18) The types of prioritization(06:54) A snapshot of EA(16:45) The Types of Prioritization Evaluated(16:57) Cause Prioritization(20:56) Within-Cause Prioritization(25:12) Cross-Cause Prioritization(30:07) Summary Table(30:53) What factors should push us towards one or another?(37:27) Possible Next Steps(39:44) Conclusion(40:58) Acknowledgements(41:01) en-US-AvaMultilingualNeural__ Modern geometric logo design with text RETHINK PRIORITIES(41:55) Appendix: Strengths and Pitfalls of Each Type(42:07) Within-Cause Prioritization Strengths(42:12) Decision-Making Support(42:37) Comparability of Outputs(44:18) Disciplinarity Advantages(45:45) Responsiveness to Evidence(46:48) Movement Building(48:06) Within-Cause Prioritization Weaknesses and Potential Pitfalls(48:12) Responsiveness to Evidence(50:54) Decision-Making Support(52:45) Cross-Cause Prioritization Strengths:(53:06) Decision-Making Support(54:49) Responsiveness to Evidence(56:08) Movement Building(56:22) Comparability of Outputs(56:45) Decision-Making Support(57:14) Cross-Cause Prioritization Weaknesses and Potential Pitfalls(57:20) Comparability of Outputs(58:01) Disciplinarity Advantages(58:41) Movement Building(59:09) Decision-Making Support(01:00:27) Cause Prioritization Strengths(01:00:32) Decision-Making Support(01:02:01) Responsiveness to Evidence(01:02:52) Movement Building(01:03:28) Cause Prioritization Weaknesses and Potential Pitfalls(01:04:28) Decision-Making Support(01:06:08) Responsiveness to EvidenceThe original text contained 23 footnotes which were omitted from this narration. --- First published: April 16th, 2025 Source: https://forum.effectivealtruism.org/posts/ZPdZv8sHuYndD8xhJ/doing-prioritization-better-2 --- Narrated by TYPE III AUDIO. ---Images from the article:

Are you looking for some projects where you can practice your Python skills? Would you like to experiment with building a generative AI app or an automated knowledge graph sentiment analysis tool? This week on the show, we speak with Raymond Camden about his journey into Python, his work in developer relations, and the Python projects featured on his blog.

Die Preise für Container sind für viele schwer greifbar, doch sie sind ein entscheidender Wirtschaftsfaktor. Ein Container kann Tausende Dollar kosten – und beeinflusst direkt, was wir im Alltag zahlen. Bo und Marcus nehmen das Phänomen unter die Lupe.**********In dieser Folge:00:02:03 - Vom Holzfass zu Hightech –Eine Stahlbox erobert die Welt00:09:45 - Auf der ganzen Welt - Wie der Container-Index explodieren kann00:15:21 - Deutschland - Wie gehts den Containern hier?00:19:40 - Fazit / Wahres für Bares**********An dieser Folge waren beteiligt: Gesprächspartner: Gordon Wilmsmeier, Logistikexperte an der Kühne Logistics University, Hamburg Gesprächspartner: Andreas Atrott, Container-Start-Up-Unternehmer Hosts: Marcus Wolf und Bo Hyun Kim Recherche und Faktencheck: Merle Körbele und Andreas Schöllig Produktion: Marcell Christmann Redaktion: Anne Göbel**********Die Quellen zur Folge:Bernhofen, David M.; El-Sahli, Zaki; Kneller, Richard (2014): Estimating the effects of the container revolution on world trade. George Washington University. Statista Research Department. (2024). Containertransportmenge in der weltweiten Seeschifffahrt von 2018 bis 2024 [Graph]. In Statista. Zugriff am 14. April 2025Gerson, A. (2023): Stranding of the Mega-Ship Ever Given in the Suez Canal: Causes, Consequences, and Lessons to Be Learned. In: Lutmar, C.; Rubinovitz, Z. (Hrsg.): The Suez Canal: Past Lessons and Future Challenges. Palgrave Studies in Maritime Politics and Security. Palgrave Macmillan. Allianz SE (2021): The Suez Canal Ship Is Not the Only Thing Clogging Global Trade**********Weitere Beiträge zum Thema:Finanzmärkte: Das schwierige Verhältnis zur DemokratieKryptowährung: Wie Bitcoin durch Rechenpower entstehen Tupper, Amway und Co.: Die vielen Leben des Netzwerkmarketings**********Habt ihr auch manchmal einen WTF-Moment, wenn es um Wirtschaft und Finanzen geht? Wir freuen uns über eure Themenvorschläge und Feedback an whatthewirtschaft@deutschlandfunknova.de.**********Den Artikel zum Stück findet ihr hier.**********Ihr könnt uns auch auf diesen Kanälen folgen: TikTok und Instagram .

About Potholer: I am a former science journalist and geologist 00:00 Introduction and Debate Setup00:37 Debate Topics Overview02:46 Discussion on Graphs and Data04:17 Debate on Climate Change Evidence05:36 Proxy Data and Temperature Records08:42 Disputing the 'Spike of Doom'14:42 Modern Temperature Trends25:13 Statistical Robustness and Data Interpretation30:02 Debating Statistical Robustness31:24 Holocene Climate Optimum and Ancient Civilizations32:36 Medieval Warm Period vs. Holocene Climate Optimum33:08 Disputing Study References35:48 The Spike of Doom Debate45:41 CO2 Levels and Ice Ages54:47 Urban Heat Island Effect59:26 Urban vs. Rural Temperature Trends01:00:33 Critique of Movie's Temperature Graphs01:06:34 Debate on Urban Heat Island (UHI) Effect01:13:14 Discussion on Extreme Weather01:17:11 Cosmic Rays and Climate Variability01:24:03 Motivations and Funding in Climate Science01:30:50 Final Thoughts and Closing RemarksInfo-rich NoTricksZone post: “Unmasking Marcott's “Uptick”: https://notrickszone.com/2018/12/13/a-fabricated-uptick-marcotts-2013-hockey-stick-graph-debunked-by-marcotts-own-2011-ph-d-thesis/Potholer's channel: https://www.youtube.com/@potholer54========AI summaries of all of my podcasts: https://tomn.substack.com/p/podcast-summariesMy Linktree: https://linktr.ee/tomanelson1

How do you uncover misinformation and financial fraud hidden in plain sight across thousands of digital platforms during a global election cycle? In this episode, I spoke with Jim Webber, Chief Scientist at Neo4j, to explore how graph database technology is being used to expose coordinated disinformation campaigns, empower AI systems, and help enterprises manage the complexity of modern data. At the heart of our conversation is the story of the ElectionGraph Project, where Syracuse University used Neo4j's graph technology to investigate political ad spend on Meta platforms. What they discovered was not just political messaging, but sophisticated scams disguised as legitimate campaigns. These efforts, targeting civically engaged users, used merchandise giveaways as a front to harvest credit card details and enroll victims in recurring billing traps. Traditional analytics would have struggled to trace these relationships, but graph databases allowed researchers to map and understand the deeper connections between thousands of entities. We also unpack how graph technology goes far beyond fraud detection. Jim explains why graph databases are now foundational for businesses building AI systems, particularly those using Retrieval-Augmented Generation (RAG) to reduce hallucinations and improve decision making. Whether it's helping enterprises respond to customer needs or enabling AI agents to take action in real time, graphs provide the structure and context needed for reliable outcomes. Jim also shares the backstory behind Klarna's data transformation, where the company embraced knowledge graphs at the core of its operations and replaced major systems, including parts of Salesforce. It's a striking example of what becomes possible when a business commits to connected data as a strategic asset. From misinformation to intelligent automation, this episode dives into the real-world value of graph technology in 2025. Are you thinking critically about how your data infrastructure supports your AI ambitions?

GraphBI: Expanding Analytics to All Data Through the Combination of GenAI, Graph, & Visual Analytics // MLOps Podcast #310 with Paco Nathan, Principal DevRel Engineer at Senzing & Weidong Yang, CEO of Kineviz.Join the Community: https://go.mlops.community/YTJoinIn Get the newsletter: https://go.mlops.community/YTNewsletter // AbstractExisting BI and big data solutions depend largely on structured data, which makes up only about 20% of all available information, leaving the vast majority untapped. In this talk, we introduce GraphBI, which aims to address this challenge by combining GenAI, graph technology, and visual analytics to unlock the full potential of enterprise data.Recent technologies like RAG (Retrieval-Augmented Generation) and GraphRAG leverage GenAI for tasks such as summarization and Q&A, but they often function as black boxes, making verification challenging. In contrast, GraphBI uses GenAI for data pre-processing—converting unstructured data into a graph-based format—enabling a transparent, step-by-step analytics process that ensures reliability.We will walk through the GraphBI workflow, exploring best practices and challenges in each step of the process: managing both structured and unstructured data, data pre-processing with GenAI, iterative analytics using a BI-focused graph grammar, and final insight presentation. This approach uniquely surfaces business insights by effectively incorporating all types of data.// BioPaco NathanPaco Nathan is a "player/coach" who excels in data science, machine learning, and natural language, with 40 years of industry experience. He leads DevRel for the Entity Resolved Knowledge Graph practice area at Senzing.com and advises Argilla.io, Kurve.ai, KungFu.ai, and DataSpartan.co.uk, and is lead committer for the pytextrank​ and kglab​ open source projects. Formerly: Director of Learning Group at O'Reilly Media; and Director of Community Evangelism at Databricks.Weidong YangWeidong Yang, Ph.D., is the founder and CEO of Kineviz, a San Francisco-based company that develops interactive visual analytics based solutions to address complex big data problems. His expertise spans Physics, Computer Science and Performing Art, with significant contributions to the semiconductor industry and quantum dot research at UC, Berkeley and Silicon Valley. Yang also leads Kinetech Arts, a 501(c) non-profit blending dance, science, and technology. An eloquent public speaker and performer, he holds 11 US patents, including the groundbreaking Diffraction-based Overlay technology, vital for sub-10-nm semiconductor production.// Related LinksWebsite: https://www.kineviz.com/Blog: https://medium.com/kinevizWebsite: https://derwen.ai/pacohttps://huggingface.co/pacoidhttps://github.com/ceterihttps://neo4j.com/developer-blog/entity-resolved-knowledge-graphs/~~~~~~~~ ✌️Connect With Us ✌️ ~~~~~~~Catch all episodes, blogs, newsletters, and more: https://go.mlops.community/TYExploreJoin our slack community [https://go.mlops.community/slack]Follow us on X/Twitter [@mlopscommunity](https://x.com/mlopscommunity) or [LinkedIn](https://go.mlops.community/linkedin)] Sign up for the next meetup: [https://go.mlops.community/register]MLOps Swag/Merch: [https://shop.mlops.community/]Connect with Demetrios on LinkedIn: /dpbrinkmConnect with Weidong on LinkedIn: /yangweidong/Connect with Paco on LinkedIn: /ceteri/

People immersed in chaos try to solve for what it all adds up to. Visit thisamericanlife.org/lifepartners to sign up for our premium subscription.Prologue: A scientist who is used to organizing data starts tracking scientific meetings that seem to exist only on paper—meetings that might decide the fate of years of research. The NIH website shows one reality; the empty conference rooms tell another story. She graphs the chaos. (9 minutes)Act One: American doctors returning from Gaza compare notes and start to see a pattern. (28 minutes)Act Two: A woman watches her partner get taken in handcuffs with no explanation. Days later, she spots him in the most unexpected place. The coordinates of her life suddenly don't make sense as she navigates the bewildering map of the US immigration system. (23 minutes)Transcripts are available at thisamericanlife.orgThis American Life privacy policy.Learn more about sponsor message choices.

The host of CNN's "Searching for Spain" shares why Americans should try to live life like the Spaniards do. A rare record collector reunites a woman with a Voice-o-Graph she recorded 70 years ago. How this record-setting rodent is saving lives with his sense of smell. From deception to acceptance, a female magician's decades-long journey into the world's most prestigious magic club. Plus, scientists may have found the first signs of life on a planet outside our solar system. Learn more about your ad choices. Visit podcastchoices.com/adchoices

The host of CNN's "Searching for Spain" shares why Americans should try to live life like the Spaniards do. A rare record collector reunites a woman with a Voice-o-Graph she recorded 70 years ago. How this record-setting rodent is saving lives with his sense of smell. From deception to acceptance, a female magician's decades-long journey into the world's most prestigious magic club. Plus, scientists may have found the first signs of life on a planet outside our solar system. Learn more about your ad choices. Visit podcastchoices.com/adchoices

This is a link post. Summary: The NAO will increase our sequencing significantly over the next few months, funded by a $3M grant from Open Philanthropy. This will allow us to scale our early-warning system to where we could flag many engineered pathogens early enough to mitigate their worst impacts, and also generate large amounts of data to develop, tune, and evaluate our detection systems. One of the biological threats the NAO is most concerned with is a 'stealth' pathogen, such as a virus with the profile of a faster-spreading HIV. This could cause a devastating pandemic, and early detection would be critical to mitigate the worst impacts. If such a pathogen were to spread, however, we wouldn't be able to monitor it with traditional approaches because we wouldn't know what to look for. Instead, we have invested in metagenomic sequencing for pathogen-agnostic detection. This doesn't require deciding what [...] --- First published: April 2nd, 2025 Source: https://forum.effectivealtruism.org/posts/AJ8bd2sz8tF7cxJff/scaling-our-pilot-early-warning-system Linkpost URL:https://naobservatory.org/blog/scaling-our-early-warning-system/ --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

[Cross-posted from my Substack here] If you spend time with people trying to change the world, you'll come to an interesting conundrum: Various advocacy groups reference previous successful social movements as to why their chosen strategy is the most important one. Yet, these groups often follow wildly different strategies from each other to achieve social change. So, which one of them is right? The answer is all of them and none of them. This is because many people use research and historical movements to justify their pre-existing beliefs about how social change happens. Simply, you can find a case study to fit most plausible theories of how social change happens. For example, the groups might say: Repeated nonviolent disruption is the key to social change, citing the Freedom Riders from the civil rights Movement or Act Up! from the gay rights movement. Technological progress is what drives improvements [...] The original text contained 1 footnote which was omitted from this narration. --- First published: April 24th, 2025 Source: https://forum.effectivealtruism.org/posts/kACcdhLDdWb9ZPG9L/why-you-can-justify-almost-anything-using-historical-social --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

Juan Sequeda and Jesus Barrasa are among the top experts on graphs in the world. In this episode, we chat about the definitions of semantics, ontologies, and the differences between RDF and property graphs, etc. We also talk about how AI is giving graphs a new surge of interest.

Welcome back to another episode of School Counseling Simplified! All April long, I'm sitting down with amazing guest experts to bring you insight, encouragement, and practical tools for your school counseling practice. Today's guest is the incredible Patti Hoelzle from Rooted Well, and we're talking all about something many counselors shy away from… data. But don't worry—Patti breaks it down in a way that's simple, empowering, and exciting! Patti Hoelzle is the owner of Rooted WELL and a National Board Certified School Counselor with a passion for building proactive, equitable systems of student support. She trains and consults on mindfulness in schools, trauma-informed practices, tiered interventions, and PBIS, working with educators and families nationwide. A sought-after speaker, Patti has presented at local and national conferences and teaches as an adjunct professor in a school counseling graduate program. Previously, she led social-emotional learning and MTSS efforts in a school district and has spent 18 years dedicated to being a professional school counselor. Recognized as Washington's 2021 School Counselor Advocate of the Year, Patti is dedicated to ensuring every student gets the whole-child support they deserve. Why Data Matters in School Counseling School counselors are in a unique position—we have to do the job, prove our impact, and often justify our position for the following school year. The good news? Data can do all three. Using data allows you to: Advocate for your role and time Communicate impact to stakeholders, families, and administration Support budget decisions and staffing Build confidence in your work Time Tracking as a Starting Point Patti recommends starting with one of the simplest tools: a time tracker. She's created an Excel spreadsheet workbook that allows counselors to track: Time spent on individual students Tasks completed throughout the day Graphs and charts that automatically populate from your entries This is perfect for sharing with admin, staying accountable, and noticing patterns in how your time is spent. You can find this resource in Patti's Teachers Pay Teachers store (linked in the show notes below). Using Google Tools for Easy Data Collection Another strategy Patti loves: Google Forms + the Google Suite. These tools are powerful for: Progress monitoring Sending surveys to students, teachers, and caregivers Collecting ongoing data during small groups Tracking changes in student behavior or academic progress And bonus—sending forms to caregivers via email often leads to higher participation rates than paper handouts. Advice for New Counselors Start small. Patti suggests: Begin with tracking your time, since it's something you're already doing Add in pre/post assessments once you're in the groove Use tools that already exist—no need to reinvent the wheel A Mindset Shift: The Slow Cooker Analogy “Our work is like a slow cooker, not a microwave.” Counselors often wish for a quick fix, but real change takes time. Don't be discouraged if you don't see growth right away. If your data isn't showing growth: Don't take it personally—there are many factors at play Use it as a learning opportunity Be willing to adapt and try new approaches Track student growth over time, especially with Tier 2 or Tier 3 students This conversation was such a great reminder that data doesn't have to be intimidating—it can actually empower us to better serve our students and advocate for ourselves. You can connect with Patti and find her time tracker and other amazing resources linked below in the show notes. Thanks for listening, and I'll see you next week on School Counseling Simplified!  Resources mentioned: Join my school counselor membership IMPACT here! If you are enjoying School Counseling Simplified please follow and leave us a review on Apple Podcasts! Connect with Rachel: TpT Store Blog Instagram Facebook Page Facebook Group Pinterest  Youtube Connect with Patti: rootedwellcoaching.com TpT Store TikTok Instagram More About School Counseling Simplified: School Counseling Simplified is a podcast offering easy to implement strategies for busy school counselors. The host, Rachel Davis from Bright Futures Counseling, shares tips and tricks she has learned from her years of experience as a school counselor both in the US and at an international school in Costa Rica. You can listen to School Counseling Simplified on Apple Podcasts, Spotify, Google Podcasts, and more!  

Patrick Cuba, Snowflake Architect, explores the fundamental connections between Data Modeling, Data Vault, and Knowledge Graphs—revealing how these approaches all center on the same core elements: business entities, their relationships, and their historical states. Patrick unpacks why, despite the AI revolution, human expertise remains irreplaceable for accountability and real business value. If you're wrestling with cognitive overload in the face of data explosion or wondering how different modeling disciplines can complement each other, this episode delivers the practical insights you need.

Patrick Cuba, Snowflake Architect, explores the fundamental connections between Data Modeling, Data Vault, and Knowledge Graphs—revealing how these approaches all center on the same core elements: business entities, their relationships, and their historical states. Patrick unpacks why, despite the AI revolution, human expertise remains irreplaceable for accountability and real business value. If you're wrestling with cognitive overload in the face of data explosion or wondering how different modeling disciplines can complement each other, this episode delivers the practical insights you need.

Contextual memory in AI is a major challenge because current models struggle to retain and recall relevant information over time. While humans can build long-term semantic relationships, AI systems often rely on fixed context windows, leading to loss of important past interactions. Zep is a startup that's developing a memory layer for AI agents using The post Knowledge Graphs as Agentic Memory with Daniel Chalef appeared first on Software Engineering Daily.

In this episode, Vance Crowe shares a talk delivered at the American Farm Bureau Fusion Conference, focusing on the rapid integration of technology in agriculture and society. Vance delves into the concept of 'up the graph,' explaining how ideas and technologies spread and become commonplace. Drawing from his experience at Monsanto, he discusses the importance of engaging with emerging technologies early to leverage their potential before they become mainstream. He also highlight the role of AI in transforming policy analysis, communication, and legislative drafting, emphasizing its inevitable ubiquity in the near future.Additionally, Vance explores the potential of Bitcoin and the Lightning Network in revolutionizing financial transactions for farmers, particularly in reducing transaction fees and enabling direct-to-consumer sales. He introduce the concept of value for value in podcasting and other creative industries, and discuss the emerging decentralized social media platform, Nostr, which offers an alternative to traditional platforms by allowing users to retain their audience across different services. Throughout the talk, Vance encourages listeners to engage with these technologies through experimentation and play, to better understand and harness their capabilities.Legacy Interviews - A service that records individuals and couples telling their life stories so that future generations can know their family history. https://www.legacyinterviews.com/experienceRiver.com - Invest in Bitcoin with Confidence https://river.com/signup?r=OAB5SKTP

It's time to check in on the state of religion and Christianity. We've gathered key data-backed trends shaping this decade, including the one denomination that's growing, the strongest force in American religion, and the most common words in new church names. Let's dive in.   ============================= Table of Contents: ============================= 0:00 - Intro 1:30 - Trend #1: Church Names 9:40 - Trend #2: The One Denomination That's Growing 16:07 - Trend #3: Young Men Are Now As Religious As Young Women 27:19 - Trend #4: The Strongest Force In American Religion   IMPORTANT LINKS - Ryan Burge: https://www.drburge.com/ - Ryan Burge | Twitter/X: https://twitter.com/ryanburge - Graphs about Religion: https://www.graphsaboutreligion.com/ - What's In a Name? Trends in Non-Denominational Church Branding: https://bit.ly/4iJfQL9 - The Assemblies of God: A Denomination That May Be Growing: https://bit.ly/43JmYD1 - Are Young Women Leaving Religion Faster than Young Men?: https://bit.ly/4iLkk3N - Non-Denominationalism Is the Strongest Force in American Religion: https://bit.ly/41Zvj47 - The American Religious Landscape: Facts, Trends, and the Future: https://amzn.to/3XMZ1a2   THE 167 NEWSLETTER

In this episode, I am joined by political scientist Ryan Burge for an engaging conversation about his fascinating data on religious decline and the rise of the 'Nones' and non-denominational Christianity. We discuss the implications of denominational decline, growing distrust in institutional religion, and the explosive growth of non-denominational churches. This episode features in-depth analysis, intriguing graphs, lively discussions, and insights from prominent social philosophers.   *** If you want access to the entire 2-hour conversation and invites to join us live in the future, all you have to do is become a member of either (or both) of our SubStacks — Graphs on Religion & Process This. *** Ryan P. Burge is an assistant professor of political science at Eastern Illinois University. Authorof numerous journal articles, he is the co-founder of and a frequent contributor to Religion in Public, a forum for scholars of religion and politics to make their work accessible to a general audience. Burge is a pastor in the American Baptist Church. Previous Visits from Ryan Burge Trust, Religion, & a Functioning Democracy What it's like to close a church The Future of Christian Education & Ministry in Charts The Sky is Falling & the Charts are Popping! Graphs about Religion & Politics w/ Spicy Banter a Year in Religion (in Graphs) Evangelical Jews, Educated Church-Goers, & other bits of dizzying data 5 Religion Graphs w/ a side of Hot Takes Myths about Religion & Politics Theology Beer Camp | St. Paul, MN | October 16-18, 2025 3 Days of Craft Nerdiness with 50+ Theologians & God-Pods and 600 new friends. A Five-Week Online Lenten Class w/ John Dominic Crossan Join us for a transformative 5-week Lenten journey on "Paul the Pharisee: Faith and Politics in a Divided World."This course examines the Apostle Paul as a Pharisee deeply engaged with the turbulent political and religious landscape of his time. Through the lens of his letters and historical context, we will explore Paul's understanding of Jesus' Life-Vision, his interpretation of the Execution-and-Resurrection, and their implications for nonviolence and faithful resistance against empire. Each week, we will delve into a specific aspect of Paul's theology and legacy, reflecting on its relevance for our own age of autocracy and political turmoil. . For details and to sign-up for any donation, including 0, head over here. _____________________ Hang with 40+ Scholars & Podcasts and 600 people at Theology Beer Camp 2025 (Oct. 16-18) in St. Paul, MN. This podcast is a Homebrewed Christianity production. Follow the Homebrewed Christianity, Theology Nerd Throwdown, & The Rise of Bonhoeffer podcasts for more theological goodness for your earbuds. Join over 80,000 other people by joining our Substack - Process This! Get instant access to over 45 classes at www.TheologyClass.com Follow the podcast, drop a review, send feedback/questions or become a member of the HBC Community. Learn more about your ad choices. Visit megaphone.fm/adchoices