Podcasts about nobel laureates

The former President of Myanmar seems to have disappeared inside the country's prison system. Now her son has an impassioned plea, demanding 'proof' of life. Kim Aris, the son of detained Myanmar State Counsellor Aung San Suu Kyi, has not heard from his mother since 2023. Kim contests the international media's narrative that his mother betrayed the Rohingya so she could keep the military junta on side.Recently in Australia, he has launched a global fitness and solidarity campaign called the 81 for 81 challenge. It's part of the growing international demand for Myanmar to provide 'proof of life' that the Nobel Peace Prize laureate is still alive.Guest Kim Aris, son of Aung San Suu KyiGet in touch:We'd love to hear from you! Email us at global.roaming@abc.net.auFind all the episodes of Global Roaming now via the ABC Listen App or wherever you get your podcasts. 

Download Porter Here: https://app.adjust.com/21bhdnwtGuest Suggestion Form: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://forms.gle/bnaeY3FpoFU9ZjA47⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Disclaimer: This video is intended solely for educational purposes and opinions shared by the guest are his personal views. We do not intent to defame or harm any person/ brand/ product/ country/ profession mentioned in the video. Our goal is to provide information to help audience make informed choices. The media used in this video are solely for informational purposes and belongs to their respective owners.(00:00) - Intro(02:55) - Why Are Only the Rich Getting Richer in India?(08:51) - Middle-Class Indians' Salary Range(13:27) - Should We Replace Humans Because of AI?(18:30) - India: 6th Largest Economy but Still Poor(25:33) - What Is an RCT?(29:37) - What Is Economics?(32:14) - Understanding the Indian Economy Using a Pressure Cooker(39:56) - How Are Guava, Anemia & Economics Related?(43:35) - What Is the Poverty Trap Curve?(50:43) - Why Does He Think Giving Freebies to Poor People Is Good?(59:19) - Why Don't Many Rich People Give to Charity?(1:02:15) - Why Do People Say Freebie Politics Is Ruining the Country?(1:07:57) - Why Does He Think Tax Havens Should Be Banned?(1:17:37) - Is a Closed Economy Good for Growth?(1:19:27) - Why Is India Poorer Than Japan Despite Almost the Same GDP?(1:22:56) - Why Did He Write the Paper "Marry for What"?(1:25:48) - Is Universal Basic Income the Future?(1:29:09) - Why Is There Inequality Even in Jails?(1:30:59) - Why Doesn't He Take GDP Seriously?(1:34:39) - BTS(1:35:23) - OutroIn today's episode, we sit down with Abhijit Banerjee, Nobel Laureate & Author, Economist & Co-Founder - JPAL to break down everything Indians get wrong about poverty, inequality, and the future of work.He also explains his Kenya experiment where a 2-year lumpsum beat 12 years of monthly transfers, the 17-year West Bengal study that showed one free cow made women 40% richer, the 140-study metaanalysis proving freebies make people work MORE not less, and why even a Nobel Laureate calls his own success "mostly luck."A complete masterclass on how the economy actually works from the man who built the world's most rigorous method for studying it.Subscribe for more such conversations.⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠About Raj ShamaniRaj Shamani is an Entrepreneur at heart that explains his expertise in Business Content Creation & Public Speaking. He has delivered 200+ speeches in 26+ countries. Besides that, Raj is also an Angel Investor interested in crazy minds who are creating a sensation in the Fintech, FMCG, & passion economy space.To Know More,Follow Raj Shamani On ⤵︎Instagram @RajShamani ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/rajshamani/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter @RajShamani ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/rajshamani⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook @ShamaniRaj ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/shamaniraj⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn - Raj Shamani ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.linkedin.com/in/rajshamani/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠About Figuring OutFiguring Out Podcast is a Candid Conversations University where Raj Shamani brings raw conversations with the Top 1% in India.

Pete Townsend is joined by Eric Ries, author of the New York Times bestseller The Lean Startup and founder of the Long-Term Stock Exchange, for a conversation about the invisible structural forces that corrupt even the most mission-driven companies, and what founders can do about it before it's too late.Eric's new book, Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great, is out now. Get it here: https://www.amazon.com/Incorruptible-Good-Companies-Great-Stay/dp/B0FWZZBPZBEric spent 15 years teaching a generation how to build fast and learn faster. Incorruptible asks the harder question: how do you protect what you built from the forces that will eventually try to take it from you?In this special double-length episode, he walks through the concept of financial gravity, the structural tools that the world's most durable companies have used for over a century, and why good intentions are never enough.Topics covered:– Why corporate corruption is a structural failure, not an ethical one– What financial gravity is and why it's invisible until it's too late– The Anthropic Long-Term Benefit Trust and what it was designed to protect against– How Novo Nordisk built a structure 100 years ago that protected $500 billion in shareholder value– Why Silicon Valley Bank's mission statement was worthless– The one two-page filing most founders never makeCHAPTERS00:00 The More Golden the Goose00:23 Welcome Eric Ries01:06 The Founder's Wake05:08 What Did The Lean Startup Miss?08:09 What is Financial Gravity?12:50 The Right Architecture13:11 Anthropic and the Long-Term Benefit Trust14:59 The Novo Nordisk Story18:18 Are You Smarter Than a Nobel Laureate?19:28 The Vatican Panel20:46 The Public Benefit Corporation22:41 Is LTSE Incorruptible?23:39 The Guardian of the Company's SoulConnect with Eric:X: https://x.com/ericriesLinkedIn: https://www.linkedin.com/in/eries/Incorruptible (book): https://incorruptible.coInstagram: https://www.instagram.com/ericriesactual/Newsletter: https://news.theleanstartup.com/YouTube: https://www.youtube.com/@theericriesshowPodcast: https://www.ericriesshow.co Buy on Amazon: https://www.amazon.com/Incorruptible-Good-Companies-Great-Stay/dp/B0FWZZBPZBConnect with Pete:X: @PeteTownsendNVLinkedIn: https://www.linkedin.com/in/petetownsendnv/Norio Ventures: https://norioventures.comMoneyNeverSleeps: https://moneyneversleeps.ie#incorruptible #leanstartup #founders #startups

The African continent consists of 54 countries. This conversation among African theater practitioners and scholars, necessarily diverse by expertise, engages a range of questions to understand better the term theater(s), the evolution of theaters among African countries, and this contemporary moment in Africa's theaters. Who is making theater today in Africa—who's writing, who's producing, who attends? What kinds of theaters are being created? What prevalent concerns are being written, produced, and/or published in 21st -century African theaters? What are the challenges of producing theater on the continent? In what ways do theaters play a role in the lives of contemporary Africans? Panel Members Hope Azeda, Playwright and Director, Mashirika Performing Arts; Festival Curator, Ubumuntu Arts Festival Judith G. Miller, Professor of French Literature, Thought and Culture, NYU Wole  Soyinka, Wole Soyinka, Arts Professor of Theater, NYUAD; Nobel Laureate in Literature (1986) Opening Remarks Abhishek Majumdar, Program Head, Theater; Arts Professor of Theater, NYUAD Moderated by Robert Vorlicky, Associate Professor of Drama, Tisch School of the Arts, NYU; Former Visiting Professor of Theater, NYUAD

This conversation among African playwrights and translators focuses on the challenges when translating dramatic texts by African writers into English or French. What is lost (and/or gained) when translating a text's original language into another language? Why is translation important (or not) in 21st-century global culture? What are the geopolitical, linguistic, and ethical issues raised by translating African works from their original languages into English or French? Panel Members Hope Azeda, Playwright and Director, Mashirika Performing Arts; Festival Curator, Ubumuntu Arts Festival Judith G. Miller, Professor of French Literature, Thought and Culture, NYU Wole  Soyinka, Wole Soyinka, Arts Professor of Theater, NYUAD; Nobel Laureate in Literature (1986) Moderated by Robert Vorlicky, Associate Professor of Drama, Tisch School of the Arts, NYU; Former Visiting Professor of Theater, NYUAD

Although women still hold only about 21% of ambassadorial posts worldwide, recent years have seen notable progress. This panel brings together senior officials, leading practitioners, and international scholars to examine women's leadership in diplomacy, foreign affairs, and multilateral organizations. Drawing on AGDA's Women in Diplomacy Index and LSE/IDEAS's Strengthening the Representation of Women in Diplomacy Report, the discussion will explore persistent gender disparities, variations across countries and regions, and the impact of structural reforms. Panelists will also share professional experiences and policy solutions to advance women's leadership and shape a more accessible and representative global diplomatic landscape. Speakers Karen Smith, Professor of International Relations, London School of Economics and Political Science Nouf Al Hamly, Advanced Sciences and Technology Advisor, UAE Ministry of Foreign Affairs Sara Chehab, Acting Graduate Programmes Director & Senior Research Fellow, Anwar Gargash Diplomatic Academy Moderated by Henriette Mueller, Assistant Professor of Gender, Governance and Society, NYUAD Casted by Ouided Bouchamaoui, Nobel Laureate (2015) and Director of the Art & Humanities Institute for Peace, NYUAD

Nobel Laureate Abhijit Banerjee revisits the central ideas of his seminal work Poor Economics, co-authored with Esther Duflo, fifteen years after its publication. In this talk, Professor Banerjee reflects on what we've learned about poverty alleviation from a decade and a half of field experiments, policy interventions, and global upheavals. From the evolution of evidence-based development policy to the impact of new crises such as COVID-19 and climate change, this session will provide a thought-provoking look at the shifting landscape of poverty research—and what the future may hold. Speaker Abhijit V. Banerjee, Ford Foundation International Professor of Economics, MIT; Co‑Founder & Director, Abdul Latif Jameel Poverty Action Lab (J‑PAL); Nobel Laureate in Economic Sciences (2019) In conversation with Tishani Doshi, Visiting Associate Professor of Practice, Literature and Creative Writing, NYUAD

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/african-american-studies

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/history

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/biography

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/american-studies

We know who Martin Luther King Jr. became, but who was he at the beginning of his life? How did his youth inform his outlook and activism? Before Martin Luther King, Jr. was a civil rights leader, a Nobel Laureate, and a global hero, he was an emotional boy, a middling high school student devoted to fashion, dancing, and dating. Lerone A. Martin, Faculty Director of the Martin Luther King Institute at Stanford University, traces these roots to develop a fuller understanding of the influential preacher's emotional life, his youthful confusion about his future and career direction, his teenage missteps, and his inspiration to fight for justice. Revelatory, humanizing, and compassionate, Young King: The Making of Martin Luther King Jr. (Amistad, 2026) unearths MLK's days as “Little Mike,” the ever-eager middle child and a precocious prankster; his early experiences of segregation and the summers he spent on a Connecticut tobacco farm, his first trip outside the Jim Crow South; his transformative time at Morehouse, playing basketball, hosting parties, studying sociology, and joining the Ministers' Union; and his winding path to seminary, his spiritual devotion, and his relationship with Coretta, his wife-to-be. As America undergoes another era of turmoil and change, this powerful biography—and this discussion—provides a vital roadmap for how greatness comes to light, and how history shapes a leader. You can find Lerone Martin, and the Martin Luther King, Jr. Research and Education Institute on Facebook and Instagram. Subscribe, like, follow, and rate Additions to the Archive with Sullivan Summer on Instagram, Substack, and wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The Nobel Peace Prize Committee has urged the Iranian authorities to release the jailed human rights campaigner, Narges Mohammadi, to her dedicated medical team. Her health has deteriorated sharply and she has been moved to a prison hospital. We speak to her brother, Hamidreza Mohammadi. Also in the programme: Ukraine says it has struck two oil tankers off Russia's Black Sea coast, as it continues its campaign against the energy exports that fund Moscow's war effort; a manufacturer of the United States' most widely used abortion pill has asked the Supreme Court to allow postal deliveries of the medication, a day after a lower court halted them; and Chinese-Icelandic singer, Laufey, on making jazz cool again!(Photo: Narges Mohammad. Credit: Getty Images)

Richard Thaler, Nobel Laureate and Professor at the University of Chicago, and Benjamin Robinson, Founder and CEO of Grinding the Mocks, join the Wharton Moneyball team to analyze how cognitive biases, flawed valuation frameworks, and emerging data models shape NFL draft strategies and impact team decision-making. Hosted on Acast. See acast.com/privacy for more information.

Career Principles with Nobel Laureate Dr. Robert ShillerSterling Professor Emeritus of EconomicsYale UniversityAbout this masterclassMental models for expanding your thinkingAdvice for young graduatesUniversities of the futureCareers in academicsNobel Laureate Robert J. Shiller is Sterling Professor of Economics, Department of Economics and Cowles Foundation for Research in Economics, Yale University, and Professor of Finance and Fellow at the International Center for Finance, Yale School of Management.

Paul Simon set the standard for a New American Songbook. Reviewing these selections one is struck by the elegance of his melodies - on a par with that other Paul from Liverpool, but with a lyrical sophistication to rival America's Nobel Laureate poet, Bob Dylan. “America”, as performed here by David Bowie, presents a barren landscape, - mirroring the mundane with the spiritual - to rival the literary prowess of a Hemingway; and the classically inspired “American Tune,” as interpreted by the wizard of New Orleans, Allen Toussaint, quietly goes to the heart of our nation's ambivalence. I can't contain my tears whenever I hear it. Simon and Garfunkel were known as a unified entity. It took awhile for Paul to extricate himself from his childhood performing partner, Artie. Garfunkel, with his singular, choir-boy voice, needed Simon to provide the words for his divine instrument.  But Simon didn't need Garfunkel, and if Artie's acting ambitions hadn't interfered with Paul's musical ones, Simon might never have had the confidence to go it alone. Lucky for us it turned out the way it did. Because, since going solo, Simon has amassed a body of work that defines America's last half century. Ray Charles: Still Crazy After All These YearsDavid Bowie: AmericaJustin Townes Earle: GracelandThem: Richard CoryWailin' Jennys: Loves me Like a RockEverything but the Girl: The Only Living Boy in New YorkAnnie Lennox: Something So RightThe Blue Airplanes: The Boy in the BubbleBlossom Dearie: 59th St. Bridge Song Allen Toussaint: American Tune 

In a new book, Harvard professor Namwali Serpell makes the case that we have been reading one of the most celebrated writers in American history all wrong. ‘On Morrison' is a deep dive into the Nobel Laureate's complete body of work — her 11 novels, plays, and criticism. Serpell has been teaching Morrison for nearly two decades, and she says no matter how many times she returns to the work, she still finds something new. Jazz historian Kevin Whitehead reviews two new biographies of composers and pianists born 40 years apart.To manage podcast ad preferences, review the links below:See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

After a rough stretch, investment firm AQR is on a 5-year hot streak thanks to a new AI infused investing strategy and strong tax-friendly returns, beloved by financial advisors. Last year was a banner year for many hedge funds and quant shops, and Greenwich, CT-based Applied Quantitative Research—better known as AQR—was no exception. Its assets under management have ballooned to $187 billion, increasing $73 billion in 2025. All three of its billionaire founders saw their net worths double. Cliff Asness, AQR's PhD-holding chief investment officer and largest individual shareholder with an estimated 30% stake, is now worth $6.3 billion, making him the 664th richest in the world. Cofounders John Liew and David Kabiller each saw their net worths jump to over $2 billion. The three founders—who started AQR in 1998 after working together at Goldman Sachs Asset Management—are all heavily invested in AQR's funds, tying their own fortunes to the firm's performance.  Last year AQR's core multi-strategy Apex fund, which has $6.7 billion in assets, returned 19.4%, while its Delphi long-short fund (also $6.7 billion in assets) returned 16.7%, according to a person familiar with the matter who asked for anonymity to share private information. On average over the last five years the two funds have each returned 16.6% on an annualized basis, the person added. (For comparison, the S&P 500 returned 14.4% annualized over that same time period). Among the firm's more than two dozen open-ended mutual funds, AQR's Equity Market Neutral Fund, with $3.2 billion in assets and around 2,000 positions, held both long and short, gained 26.5% in 2025. Over the last 5-years it has averaged 19.6% annually versus around 8% for most funds in its category. If AQR maintains last year's growth trajectory it will soon eclipse its previous all-time high of $226 billion in assets (in 2018), which would cap an impressive comeback for the firm, which managed less than $100 billion as recently as four years ago amid underperformance and customer outflows.  AQR's turnaround has coincided with its full-throated embrace of AI and deliberate expansion of machine-learning techniques across research and trading. As a factor-based investor, AQR traditionally sought to use value investing metrics like price-to-book or return on equity to determine which equities in the market are over or undervalued. It then relied on human input to assign weights to the various factors they use to drive stock selection. Now, machine learning is helping do that—detecting complex interactions between factors, recalibrating their weights in real time, mining huge datasets for predictive signals. On the research side, natural language processing (think ChatGPT or Claude) is helping analysts comb through reams of data to improve their models.  AQR, whose founders Asness and Liew were schooled under the University of Chicago's efficient market Nobel Laureate economist Eugene Fama, was late to the AI party compared to peers like Renaissance Technologies and D.E. Shaw. AQR hired its first head of machine learning in 2018, and that person lasted just seven months in the job. But his replacement, Brian Kelly, a Yale finance professor, has made a big splash. In December 2021, Kelly co-published a 141-page academic paper, The Virtue of Complexity in Return Prediction, which concluded that more sophisticated machine learning models outperformed simpler models in forecasting stock returns and constructing investment portfolios. Several academics wrote their own papers in response that disputed Kelly's findings saying that the research relied on an overly narrow dataset. AQR has defended the paper and continues to stand by its findings.  More recently, Asness himself has taken up the mantle of AI evangelizer-in-chief. He remarked that AQR has “surrendered more to the machine” and that AI was coming for his own job. Despite all the talk, AQR insiders insist AI has not extinguished human input. “ML and AI are definitely paying dividends in our process, but they're evolutionary, not revolutionary, to what we do,” says a person at the company. To wit, the revolutionary stuff appears to be happening in the less sexy distribution side of the business, where AQR is meeting rising demand from financial advisors seeking tax-friendly funds for their wealthy clients. This category of investor—rather than AQR's traditional institutional client base like pension funds and endowments—is now its largest source of inflows. The CEO of Affiliated Managers Group, which owns a minority stake in AQR, said during last month's earnings call that AQR's advisory client base is “driving significant organic growth,” and that its own full-year net inflows of $51 billion were “primarily driven by AQR.”  Read the full story on Forbes: By John Hyatt https://www.forbes.com/sites/johnhyatt/2026/03/16/how-3-billionaire-investors-used-ai-to-double-their-fortunes-in-a-year/ Learn more about your ad choices. Visit megaphone.fm/adchoices

In a new book, Harvard professor Namwali Serpell makes the case that we have been reading one of the most celebrated writers in American history all wrong. ‘On Morrison' is a deep dive into the Nobel Laureate's complete body of work — her 11 novels, plays, and criticism. Serpell has been teaching Morrison for nearly two decades, and she says no matter how many times she returns to the work, she still finds something new. Jazz historian Kevin Whitehead reviews two new biographies of composers and pianists born 40 years apart.See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

Toni Morrison, Nobel Laureate and one of our most beloved writers, has inspired generations of readers. But her artistic genius is often overshadowed by her monumental public persona, perhaps because, as Namwali Serpell puts it, “she is our only truly canonical black female writer—and her work is highly complex.” In On Morrison (Hogarth, 2026), Serpell brings her unique experience as both an award-winning writer and a professor who teaches a course on Morrison to illuminate her masterful experiments with literary form. This is Morrison as you've never encountered her before, a journey through her oeuvre—her fiction and criticism, as well as her lesser-known dramatic works and poetry—with contextual guidance and original close readings. At once accessible and uncompromisingly rigorous, On Morrison is a primer not only on how to read one of the most significant American authors of all time but also on how to read great works of literature in general. This dialogue on the page between two black women artist-readers is stylish, edifying, and thrilling in its scope and intelligence. Namwali Serpell was born in Lusaka and lives in New York. Her debut novel, The Old Drift, won an Anisfield-Wolf Book Award, the Arthur C. Clarke Award for Science Fiction, and the Los Angeles Times's Art Seidenbaum Award for First Fiction. Her second novel, The Furrows, was a finalist for National Book Critics Circle Award for Fiction and was selected as one of The New York Times Ten Best Books of the Year. Her book of essays, Stranger Faces, was a finalist for a National Book Critics Circle Award for Criticism. She is a recipient of the Windham-Campbell Prize for Fiction, the Caine Prize for African Writing, and a Rona Jaffe Foundation Award. She is a professor of English at Harvard University. Derek Adams is Associate Professor of African American literature at Ithaca College and is currently teaching an upper-level seminar on Toni Morrison titled Across the Decades that challenges the origins of an assumed mythic status generally applied to her. Recommended Books: Maya Binyam, Hangmen Akwaeke Emezi, Freshwater Chris Holmes is Chair of Literatures in English and Professor at Ithaca College. He writes criticism on contemporary global literatures. His book, Kazuo Ishiguro Against World Literature, is published with Bloomsbury Publishing. He is the co-director of The New Voices Festival, a celebration of work in poetry, prose, and playwriting by up-and-coming young writers. Learn more about your ad choices. Visit megaphone.fm/adchoices

Toni Morrison, Nobel Laureate and one of our most beloved writers, has inspired generations of readers. But her artistic genius is often overshadowed by her monumental public persona, perhaps because, as Namwali Serpell puts it, “she is our only truly canonical black female writer—and her work is highly complex.” In On Morrison (Hogarth, 2026), Serpell brings her unique experience as both an award-winning writer and a professor who teaches a course on Morrison to illuminate her masterful experiments with literary form. This is Morrison as you've never encountered her before, a journey through her oeuvre—her fiction and criticism, as well as her lesser-known dramatic works and poetry—with contextual guidance and original close readings. At once accessible and uncompromisingly rigorous, On Morrison is a primer not only on how to read one of the most significant American authors of all time but also on how to read great works of literature in general. This dialogue on the page between two black women artist-readers is stylish, edifying, and thrilling in its scope and intelligence. Namwali Serpell was born in Lusaka and lives in New York. Her debut novel, The Old Drift, won an Anisfield-Wolf Book Award, the Arthur C. Clarke Award for Science Fiction, and the Los Angeles Times's Art Seidenbaum Award for First Fiction. Her second novel, The Furrows, was a finalist for National Book Critics Circle Award for Fiction and was selected as one of The New York Times Ten Best Books of the Year. Her book of essays, Stranger Faces, was a finalist for a National Book Critics Circle Award for Criticism. She is a recipient of the Windham-Campbell Prize for Fiction, the Caine Prize for African Writing, and a Rona Jaffe Foundation Award. She is a professor of English at Harvard University. Derek Adams is Associate Professor of African American literature at Ithaca College and is currently teaching an upper-level seminar on Toni Morrison titled Across the Decades that challenges the origins of an assumed mythic status generally applied to her. Recommended Books: Maya Binyam, Hangmen Akwaeke Emezi, Freshwater Chris Holmes is Chair of Literatures in English and Professor at Ithaca College. He writes criticism on contemporary global literatures. His book, Kazuo Ishiguro Against World Literature, is published with Bloomsbury Publishing. He is the co-director of The New Voices Festival, a celebration of work in poetry, prose, and playwriting by up-and-coming young writers. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Toni Morrison, Nobel Laureate and one of our most beloved writers, has inspired generations of readers. But her artistic genius is often overshadowed by her monumental public persona, perhaps because, as Namwali Serpell puts it, “she is our only truly canonical black female writer—and her work is highly complex.” In On Morrison (Hogarth, 2026), Serpell brings her unique experience as both an award-winning writer and a professor who teaches a course on Morrison to illuminate her masterful experiments with literary form. This is Morrison as you've never encountered her before, a journey through her oeuvre—her fiction and criticism, as well as her lesser-known dramatic works and poetry—with contextual guidance and original close readings. At once accessible and uncompromisingly rigorous, On Morrison is a primer not only on how to read one of the most significant American authors of all time but also on how to read great works of literature in general. This dialogue on the page between two black women artist-readers is stylish, edifying, and thrilling in its scope and intelligence. Namwali Serpell was born in Lusaka and lives in New York. Her debut novel, The Old Drift, won an Anisfield-Wolf Book Award, the Arthur C. Clarke Award for Science Fiction, and the Los Angeles Times's Art Seidenbaum Award for First Fiction. Her second novel, The Furrows, was a finalist for National Book Critics Circle Award for Fiction and was selected as one of The New York Times Ten Best Books of the Year. Her book of essays, Stranger Faces, was a finalist for a National Book Critics Circle Award for Criticism. She is a recipient of the Windham-Campbell Prize for Fiction, the Caine Prize for African Writing, and a Rona Jaffe Foundation Award. She is a professor of English at Harvard University. Derek Adams is Associate Professor of African American literature at Ithaca College and is currently teaching an upper-level seminar on Toni Morrison titled Across the Decades that challenges the origins of an assumed mythic status generally applied to her. Recommended Books: Maya Binyam, Hangmen Akwaeke Emezi, Freshwater Chris Holmes is Chair of Literatures in English and Professor at Ithaca College. He writes criticism on contemporary global literatures. His book, Kazuo Ishiguro Against World Literature, is published with Bloomsbury Publishing. He is the co-director of The New Voices Festival, a celebration of work in poetry, prose, and playwriting by up-and-coming young writers. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/literary-studies

Toni Morrison, Nobel Laureate and one of our most beloved writers, has inspired generations of readers. But her artistic genius is often overshadowed by her monumental public persona, perhaps because, as Namwali Serpell puts it, “she is our only truly canonical black female writer—and her work is highly complex.” In On Morrison (Hogarth, 2026), Serpell brings her unique experience as both an award-winning writer and a professor who teaches a course on Morrison to illuminate her masterful experiments with literary form. This is Morrison as you've never encountered her before, a journey through her oeuvre—her fiction and criticism, as well as her lesser-known dramatic works and poetry—with contextual guidance and original close readings. At once accessible and uncompromisingly rigorous, On Morrison is a primer not only on how to read one of the most significant American authors of all time but also on how to read great works of literature in general. This dialogue on the page between two black women artist-readers is stylish, edifying, and thrilling in its scope and intelligence. Namwali Serpell was born in Lusaka and lives in New York. Her debut novel, The Old Drift, won an Anisfield-Wolf Book Award, the Arthur C. Clarke Award for Science Fiction, and the Los Angeles Times's Art Seidenbaum Award for First Fiction. Her second novel, The Furrows, was a finalist for National Book Critics Circle Award for Fiction and was selected as one of The New York Times Ten Best Books of the Year. Her book of essays, Stranger Faces, was a finalist for a National Book Critics Circle Award for Criticism. She is a recipient of the Windham-Campbell Prize for Fiction, the Caine Prize for African Writing, and a Rona Jaffe Foundation Award. She is a professor of English at Harvard University. Derek Adams is Associate Professor of African American literature at Ithaca College and is currently teaching an upper-level seminar on Toni Morrison titled Across the Decades that challenges the origins of an assumed mythic status generally applied to her. Recommended Books: Maya Binyam, Hangmen Akwaeke Emezi, Freshwater Chris Holmes is Chair of Literatures in English and Professor at Ithaca College. He writes criticism on contemporary global literatures. His book, Kazuo Ishiguro Against World Literature, is published with Bloomsbury Publishing. He is the co-director of The New Voices Festival, a celebration of work in poetry, prose, and playwriting by up-and-coming young writers. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/literature

"Could your daily habits be the hidden cause of memory loss and cognitive decline?" Emerging Alzheimer's research suggests that Nitric Oxide acts as a master signaling molecule for brain health, yet common products like antiseptic mouthwash and fluoride may be inhibiting its production. In this episode, I am joined by molecular medicine expert Dr. Nathan S. Bryan to explore the vascular roots of dementia and why some researchers now refer to Alzheimer's as "Type 3 Diabetes." We dive into the surprising link between chronic antacid use and brain health, while offering simple lifestyle changes—from nasal breathing to dietary shifts—to help you boost Nitric Oxide naturally and protect your cognitive longevity. Furthermore, we discuss how common products like antiseptic mouthwash and fluoride may actually inhibit your natural production. We also dive into the surprising link between chronic antacid use and a higher risk of Alzheimer's disease. Fortunately, simple lifestyle changes can help restore these vital levels. For example, nasal breathing and specific dietary shifts can significantly boost your Nitric Oxide naturally. Although these ideas may challenge your current beliefs, being curious is the first step toward prevention. Join us as we investigate the root causes of chronic disease and the science of longevity. Our Guest: Dr. Nathan S. Bryan Dr. Nathan S. Bryan is an international leader in molecular medicine and the "billion-dollar scientist" behind the nitric oxide revolution. With over 25 years in the field and 100+ peer-reviewed articles, he was recruited to the University of Texas by a Nobel Laureate to decode the biochemistry of human longevity. As an entrepreneur and inventor with dozens of patents, Dr. Bryan has moved beyond the lab to build clinical-stage therapies for heart disease, Alzheimer's, and chronic wounds. Today, he serves as the CEO of Bryan Therapeutics, where he continues to bridge the gap between complex biochemistry and life-changing consumer products. Episode Chapters & Timestamps 00:00 – The "What If" Challenge: Introduction to the Nitric Oxide revolution. 02:15 – Meet the Expert: Dr. Nathan Bryan's journey from Texas to the Nobel connection. 05:40 – The Molecule of Life: What is Nitric Oxide and why does it matter? 09:25 – Vascular Roots: Why Alzheimer's is now being called "Type 3 Diabetes." 13:10 – The Failure of Current Drugs: Why targeting amyloid plaques hasn't worked. 17:45 – The Root Cause: How loss of blood flow leads to cognitive decline. 21:30 – Association vs. Causation: Challenging the medical industry's profit model. 26:40 – The Mouthwash Connection: How daily habits are killing your Nitric Oxide. 30:15 – Fluoride & Antacids: Hidden neurotoxins in your medicine cabinet. 34:50 – Fueling the Brain: The sugar toxin and the power of high-protein diets. 38:10 – The Fasting Miracle: Using 18-hour fasts to reset your metabolic health. 42:00 – Nasal Breathing & Sunlight: Simple, free ways to boost brain blood flow. 46:30 – Biology vs. Genetics: Why your genes are not your destiny. 48:45 – Take Action: Where to find Dr. Bryan's research and resources. 50:30 – Final Thoughts: Jennifer's takeaway on being a "curious skeptic." Sign Up for more Advice & Wisdom - email newsletter. ++++++++++++++++++++++++++++++++++++++++ Please help us keep our show going by supporting our sponsors. Thank you. ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Feeling overwhelmed? HelpTexts can be your pocket therapist. Going through a tough time? HelpTexts offers confidential support delivered straight to your phone via text message. Whether you're dealing with grief, caregiving stress, or just need a mental health boost, their expert-guided texts provide personalized tips and advice. Sign up for a year of support and get: Daily or twice-weekly texts tailored to your situation Actionable strategies to cope and move forward Support for those who care about you (optional) HelpTexts makes getting help easy and convenient. ++++++++++++++++++++++++++++++++++++++++ Make Your Brain Span Match Your LifeSpan Relevate from NeuroReserve I've been focusing a lot on taking care of my brain health, & I've found this supplement called RELEVATE to be incredibly helpful. It provides me with 17 nutrients that support brain function & help keep me sharp. Since you're someone I care about, I wanted to share this discovery with you. You can order it with my code: FM15 & get 15% OFF your order. With Relevate nutritional supplement, you get science-backed nutrition to help protect your brain power today and for years to come. You deserve a brain span that lasts as long as your lifespan. ++++++++++++++++++++++++++++++++++++++++ Join Fading Memories On Social Media! If you've enjoyed this episode, please share this podcast with other caregivers! You'll find us on social media at the following links. Instagram Twitter LinkedIn  Facebook Contact Jen at hello@fadingmemoriespodcast.com or Visit us at www.FadingMemoriesPodcast.com

Nobel laureate Paul Krugman, a City University of New York professor, reacts to a federal judge's ruling that blocks a federal investigation of Fed Chair Powell. Krugman says President Trump and US Attorney for the District of Columbia Jeanine Pirro are "harassing" Powell. Krugman says the independence of the Fed is on the line.See omnystudio.com/listener for privacy information.

Most small business owners are waiting for universities to produce the employees they need. The smart ones stopped waiting years ago — and started building their own training programs.In this episode, Chris Cooper looks at a quiet trend reshaping how companies find, develop, and keep talent: the rise of the company college. Rolex opened a tuition-free watchmaking school in Dallas, complete with a monthly stipend and a final exam in Geneva. Google built a certificate program now recognized by over 150 employers. And just this week, MasterClass launched MasterClass Executive — a 12-week, AI-powered business school built with the University of Chicago and OpenAI, taught by Ray Dalio, Mark Cuban, and Nobel Laureates.These aren't vanity projects. They're strategic solutions to a real problem: universities aren't producing job-ready graduates fast enough, and the companies that can't afford to wait are building their own pipelines.Chris shares how he did exactly this at Two-Brain Business, and breaks down a four-phase blueprint any company can follow — regardless of size or budget. You'll learn why 15-minute daily lessons outperform full-day orientations, why gamification isn't just for millennials, and why your credential matters as much as your curriculum.Your Golden Hour task this week: define one role, list 10 skills, write one 15-minute lesson. That's Module One of your Company College.Next episode: how to layer a mentorship and coaching program on top of your training — turning trained employees into future leaders.Business is good.Connect with Chris Cooper:Website - https://businessisgood.com/

At age 10, Omar Yaghi walked into a school library in Amman, Jordan, and opened a book that changed his life. He saw molecular drawings — complex structures he didn't yet understand, but which immediately captivated him. "I thought I discovered something that nobody had ever seen before," Yaghi recalls. Yaghi, now a professor of chemistry at UC Berkeley, shared this story during a recent Brilliance of Berkeley lecture to illustrate how a life defined by scarcity can be transformed through the pursuit of science. Growing up in a family of 10 children, Yaghi lived in a single room that lacked electricity and running water. The family shared their living quarters with cattle, separated from the animals only by sacks of feed. Education was the family's singular priority; his parents spent everything they earned to keep their children in school to ensure they had a path toward a different future.In 2025, Yaghi was awarded the Nobel Prize in Chemistry for the development of metal-organic frameworks, or MOFs — porous materials that act like "molecular sponges" capable of capturing carbon dioxide from the air and harvesting water from desert humidity.In this Berkeley Talks episode, Yaghi describes how his childhood as a refugee and his early days as an immigrant in the U.S. shaped his relentless work ethic. He recounts the "failure" of a yearlong graduate school experiment that actually resulted in his first major discovery: a ball-shaped molecule that paved the way for his career. Today, his research on reticular chemistry continues to push toward real-world solutions to the climate crisis.For Yaghi, science is not only about discovery, but about transforming access to life's most basic resource. “My dream,” he says, is “for everyone to have water independence — where your water is yours, independent of everything else.”This lecture, which took place on Jan. 23, was part of LNS 110: Brilliance of Berkeley, a course featuring distinguished researchers working on the world's most pressing issues.Listen to the episode and read the transcript on UC Berkeley News (news.berkeley.edu/podcasts/berkeley-talks).Music by HoliznaCC0.Photo by Brittany Hosea-Small for UC Berkeley. Hosted on Acast. See acast.com/privacy for more information.

In his first interview since being elected as Moderator Designate the Rev Richard Kerr talks to Audrey about the PCI safeguarding scandal and the next steps for the church.Agreement is Owen McCafferty's dramatisation of the final four days of talks which led to the Good Friday Agreement. It starred among others Dan Gordon as John Hume and Ruairi Conaghan as David Trimble. Dan and Ruairi chat to Audrey about playing the Nobel Laureates and Brian Rowan gives us the inside story of the human personalities striving for peace.This week we marked the 4th anniversary of Vladimir Putin's invasion of Ukraine. Audrey talks to local poet Angela Graham about her new collection which was inspired by photos from the war in Ukraine.

Editor's note: CuspAI raised a $100m Series A in September and is rumored to have reached a unicorn valuation. They have all-star advisors from Geoff Hinton to Yann Lecun and team of deep domain experts to tackle this next frontier in AI applications.In this episode, Max Welling traces the thread connecting quantum gravity, equivariant neural networks, diffusion models, and climate-focused materials discovery (yes, there is one!!!).We begin with a provocative framing: experiments as computation. Welling describes the idea of a “physics processing unit”—a world in which digital models and physical experiments work together, with nature itself acting as a kind of processor. It's a grounded but ambitious vision of AI for science: not replacing chemists, but accelerating them.Along the way, we discuss:* Why symmetry and equivariance matter in deep learning* The tradeoff between scale and inductive bias* The deep mathematical links between diffusion models and stochastic thermodynamics* Why materials—not software—may be the real bottleneck for AI and the energy transition* What it actually takes to build an AI-driven materials platformMax reflects on moving from curiosity-driven theoretical physics (including work with Gerard ‘t Hooft) toward impact-driven research in climate and energy. The result is a conversation about convergence: physics and machine learning, digital models and laboratory experiments, long-term ambition and incremental progress.Full Video EpisodeTimestamps* 00:00:00 – The Physics Processing Unit (PPU): Nature as the Ultimate Computer* Max introduces the idea of a Physics Processing Unit — using real-world experiments as computation.* 00:00:44 – From Quantum Gravity to AI for Materials* Brandon frames Max's career arc: VAE pioneer → equivariant GNNs → materials startup founder.* 00:01:34 – Curiosity vs Impact: How His Motivation Evolved* Max explains the shift from pure theoretical curiosity to climate-driven impact.* 00:02:43 – Why CaspAI Exists: Technology as Climate Strategy* Politics struggles; technology scales. Why materials innovation became the focus.* 00:03:39 – The Thread: Physics → Symmetry → Machine Learning* How gauge symmetry, group theory, and relativity informed equivariant neural networks.* 00:06:52 – AI for Science Is Exploding (Not Emerging)* The funding surge and why AI-for-Science feels like a new industrial era.* 00:07:53 – Why Now? The Two Catalysts Behind AI for Science* Protein folding, ML force fields, and the tipping point moment.* 00:10:12 – How Engineers Can Enter AI for Science* Practical pathways: curriculum, workshops, cross-disciplinary training.* 00:11:28 – Why Materials Matter More Than Software* The argument that everything—LLMs included—rests on materials innovation.* 00:13:02 – Materials as a Search Engine* The vision: automated exploration of chemical space like querying Google.* 01:14:48 – Inside CuspAI: The Platform Architecture* Generative models + multi-scale digital twin + experiment loop.* 00:21:17 – Automating Chemistry: Human-in-the-Loop First* Start manual → modular tools → agents → increasing autonomy.* 00:25:04 – Moonshots vs Incremental Wins* Balancing lighthouse materials with paid partnerships.* 00:26:22 – Why Breakthroughs Will Still Require Humans* Automation is vertical-specific and iterative.* 00:29:01 – What Is Equivariance (In Plain English)?* Symmetry in neural networks explained with the bottle example.* 00:30:01 – Why Not Just Use Data Augmentation?* The optimization trade-off between inductive bias and data scale.* 00:31:55 – Generative AI Meets Stochastic Thermodynamics* His upcoming book and the unification of diffusion models and physics.* 00:33:44 – When the Book Drops (ICLR?)TranscriptMax: I want to think of it as what I would call a physics processing unit, like a PPU, right? Which is you have digital processing units and then you have physics processing units. So it's basically nature doing computations for you. It's the fastest computer known, as possible even. It's a bit hard to program because you have to do all these experiments. Those are quite bulky, it's like a very large thing you have to do. But in a way it is a computation and that's the way I want to see it. You can do computations in a data center and then you can ask nature to do some computations. Your interface with nature is a bit more complicated. But then these things will have to seamlessly work together to get to a new material that you're interested in.[01:00:44:14 - 01:01:34:08]Brandon: Yeah, it's a pleasure to have Max Woehling as a guest today. Max has done so much over his career that I've been so excited about. If you're in the deep learning community, you probably know Max for his work on variational autocoders, which has literally stood the test of prime or officially stood the test of prime. If you are a scientist, you probably know him for his like, binary work on graph neural networks on equivariance. And if you're a material science, you probably know him about his new startup, CASPAI. Max has a long history doing lots of cool problems. You started in quantum gravity, which is I think very different than all of these other things you worked on. The first question for AI engineers and for scientists, what is the thread in how you think about problems? What is the thread in the type of things which excite you? And how do you decide what is the next big thing you want to work on?[01:01:34:08 - 01:02:41:13]Max: So it has actually evolved a lot. In my young days, let's breathe, I would just follow what I would find super interesting. I have kind of this sensor. I think many people have, but maybe not really sort of use very much, which is like, you get this feeling about getting very excited about some problem. Like it could be, what's inside of a black hole or what's at the boundary of the universe or what are quantum mechanics actually all about. And so I follow that basically throughout my career. But I have to say that as you get older, this changes a little bit in the sense that there's a new dimension coming to it and there's this impact. Going in two-dimensional quantum gravity, you pretty much guaranteed there's going to be no impact on what you do relative, maybe a few papers, but not in this world, this energy scale. As I get closer to retirement, which is fortunately still 10 years away or so, I do want to kind of make a positive impact in the world. And I got pretty worried about climate change.[01:02:43:15 - 01:03:19:11]Max: I think politics seems to have a hard time solving it, especially these days. And so I thought better work on it from the technology side. And that's why we started CaspAI. But there's also a lot of really interesting science problems in material science. And so it's kind of combining both the impact you can make with it as well as the interesting science. So it's sort of these two dimensions, like working on things which you feel there's like, well, there's something very deep going on here. And on the other hand, trying to build tools that can actually make a real impact in the world.[01:03:19:11 - 01:03:39:23]RJ: So the thread that when I look back, look at the different things that you worked out, some of them seem pretty connected, like the physics to equivariance and, yeah, and, uh, gravitational networks, maybe. And that seems to be somewhat related to Casp. Do you have a thread through there?[01:03:39:23 - 01:06:52:16]Max: Yeah. So physics is the thread. So having done, you know, spent a lot of time in theoretical physics, I think there is first very fundamental and exciting questions, like things that haven't actually been figured out in quantum gravity. So that is really the frontier. There's also a lot of mathematical tools that you can use, right? In, for instance, in particle physics, but also in general relativity, sort of symmetry space to play an enormously important role. And this goes all the way to gauge symmetries as well. And so applying these kinds of symmetries to, uh, machine learning was actually, you know, I thought of it as a very deep and interesting mathematical problem. I did this with Taco Cohen and Taco was the main driver behind this, went all the way from just simple, like rotational symmetries all the way to gauge symmetries on spheres and stuff like that. So, and, uh, Maurice Weiler, who's also here, um, when he was a PhD student, he was a very good student with me, you know, he wrote an entire book, which I can really recommend about the role of symmetries in AI and machine learning. So I find this a very deep and interesting problem. So more recently, so I've taken a sort of different path, which is the relationship between diffusion models and that field called stochastic thermodynamics. This is basically the thermodynamics, which is a theory of equilibrium. So but then formulated for out of equilibrium systems. And it turns out that the mathematics that we use for diffusion models, but even for reinforcement learning for Schrodinger bridges for MCMC sampling has the same mathematics as this theoretical, this physical theory of non-equilibrium systems. And that got me very excited. And actually, uh, when I taught a course in, um, Mauschenberg, uh, it is South Africa, close to Cape Town at the African Institute for Mathematical Sciences Ames. And I turned that into a book site. Two years later, the book was finished. I've sent it to the publisher. And this is about the deep relationship between free energy, diffusion models, basically generative AI and stochastic thermodynamics. So it's always some kind of, I don't know, I find physics very deep. I also think a lot about quantum mechanics and it's, it's, it's a completely weird theory that actually nobody really understands. And there's a very interesting story, which is maybe good to tell to connect sort of my PZ back to where I'm now. So I did my PZ with a Nobel Laureate, Gerard the toft. He says the most brilliant man I've ever met. He was never wrong about anything as long as I've seen him. And now he says quantum mechanics is wrong and he has a new theory of quantum mechanics. Nobody understands what he's saying, even though what he's writing down is not mathematically very complex, but he's trying to address this understandability, let's say of quantum mechanics head on. And I find it very courageous and I'm completely fascinated by it. So I'm also trying to think about, okay, can I actually understand quantum mechanics in a more mundane way? So that, you know, without all the weird multiverses and collapses and stuff like that. So the physics is always been the threat and I'm trying to apply the physics to the machine learning to build better algorithms.[01:06:52:16 - 01:07:05:15]Brandon: You are still very involved in understanding and understanding physics and the worlds. Yeah. And just like applications to machine learning or introducing no formalisms. That's really cool.[01:07:05:15 - 01:07:18:02]Max: Yes, I would say I'm not contributing much to physics, but I'm contributing to the interface between physics and science. And that's called AI for science or science or AI is kind of a super, it's actually a new discipline that's emerging.[01:07:18:02 - 01:07:18:19]Speaker 5: Yeah.[01:07:18:19 - 01:07:45:14]Max: And it's not just emerging, it's exploding, I would say. That's the better term because I know you go from investments into like in the hundreds of millions now in the billions. So there's now actually a startup by Jeff Bezos that is at 6.2 billion sheep round. Right. Insane. I guess it's the largest startup ever, I think. And that's in this field, AI for science. It tells you something that we are creating a new bubble here.[01:07:46:15 - 01:07:53:28]Brandon: So why do you think it is? What has changed that has motivated people to start working on AI for science type problems?[01:07:53:28 - 01:08:49:17]Max: So there's two reasons actually. One is that people have been applying sort of the new tools from AI to the sciences, which is quite natural. And there's of course, I think there's two big examples, protein folding is a big one. And the other one is machine learning forest fields or something called machine learning inter-atomic potentials. Both of them have been actually very successful. Both also had something to do with symmetries, which is a little cool. And sort of people in the AI sciences saw an opportunity to apply the tools that they had developed beyond advertised placement, right, or multimedia applications into something that could actually make a very positive impact in society like health, drug development, materials for the energy transition, carbon capture. These are all really cool, impactful applications.[01:08:50:19 - 01:09:42:14]Max: Despite that, the science and the kind of the is also very interesting. I would say the fact that these sort of these two fields are coming together and that we're now at the point that we can actually model these things effectively and move the needle on some of these sort of science sort of methodologies is also a very unique moment, I would say. People recognize that, okay, now we're at the cusp of something new, where it results whether the company is called after. We're at the cusp of something new. And of course that always creates a lot of energy. It's like, okay, there's something, it's like sort of virgin field. It's like nobody's green field. Nobody's been there. I can rush in and I can sort of start harvesting there, right? And I think that's also what's causing a lot of sort of enthusiasm in the fields.[01:09:42:14 - 01:10:12:18]RJ: If you're an AI engineer, basically if the people that listen to this podcast will be in the field, then you maybe don't have a strong science background. How does, but are excited. Most I would say most AI practitioners, BM engineers or scientists would consider themselves scientists and they have some background, a little bit of physics, a little bit of industry college, maybe even graduate school that have been working or are starting out. How does somebody who is not a scientist on a day-to-day basis, how do they get involved?[01:10:12:18 - 01:10:14:28]Max: Well, they can read my book once it's out.[01:10:16:07 - 01:11:05:24]Max: This is basically saying that there is more, we should create curricula that are on this interface. So I'm not sure there is, also we already have some universities actual courses you can take, maybe online courses you can take. These workshops where we are now are actually very good as well. And we should probably have more tutorials before the workshop starts. Actually we've, I've kind of proposed this at some point. It's like maybe first have an hour of a tutorial so that people can get new into the field. There's a lot out there. Most of it is of course inaccessible, but I would say we will create much more books and other contents that is more accessible, including this podcast I would say. So I think it will come. And these days you can watch videos and things. There's a huge amount of content you can go and see.[01:11:05:24 - 01:11:28:28]Brandon: So maybe a follow-up to that. How do people learn and get involved? But why should they get involved? I mean, we have a lot of people who are of our audience will be interested in AI engineering, but they may be looking for bigger impacts in the world. What opportunities does AI for science provide them to make an impact to change the world? That working in this the world of pure bits would not.[01:11:28:28 - 01:11:40:06]Max: So my view is that underlying almost everything is immaterial. So we are focusing a lot on LLMs now, which is kind of the software layer.[01:11:41:06 - 01:11:56:05]Max: I would say if you think very hard, underlying everything is immaterial. So underlying an LLM is a GPU, and underlying a GPU is a wafer on which we will have to deposit materials. Do we want to wait a little bit?[01:12:02:25 - 01:12:11:06]Max: Underlying everything is immaterial. So I was saying, you know, there's the LLM underlying the LLM is a GPU on which it runs. In order to make that GPU,[01:12:12:08 - 01:12:43:20]Max: you have to put materials down on a wafer and sort of shine on it with sort of EUV light in order to etch kind of the structures in. But that's now an actual material problem, because more or less we've reached the limits of scaling things down. And now we are trying to improve further by new materials. So that's a fundamental materials problem. We need to get through the energy transition fast if we don't want to kind of mess up this world. And so there is, for instance, batteries. That's a complete materials problem. There's fuel cells.[01:12:44:23 - 01:13:01:16]Max: There is solar panels. So that they can now make solar panels with new perovskite layers on top of the silicon layers that can capture, you know, theoretically up to 50% of the light, where now we're at, I don't know, maybe 22 or something. So these are huge changes all by material innovation.[01:13:02:21 - 01:13:47:15]Max: And yeah, I think wherever you go, you know, I can probably dig deep enough and then tell you, well, actually, the very foundation of what you're doing is a material problem. And so I think it's just very nice to work on this very, very foundation. And also because I think this is maybe also something that's happening now is we can start to search through this material space. This has never been the case, right? It's like scientists, the normal way of working is you read papers and then you come up with no hypothesis. You do an experiment and you learn, et cetera. So that's a very slow process. Now we can treat this as a search engine. Like we search the internet, we now search the space of all possible molecules, not just the ones that people have made or that they're in the universe, but all of them.[01:13:48:21 - 01:14:42:01]Max: And we can make this kind of fully automated. That's the hope, right? We can just type, it becomes a tool where you type what you want and something starts spinning and some experiments get going. And then, you know, outcome list of materials and then you look at it and say, maybe not. And then you refine your query a little bit. And you kind of do research with this search engine where a huge amount of computation and experimentation is happening, you know, somewhere far away in some lab or some data center or something like this. I find this a very, very promising view of how we can sort of build a much better sort of materials layer underneath almost everything. And also more sustainable materials. Our plastics are polluting the planet. If you come up with a plastic that kind of destroys itself, you know, after, I don't a few weeks, right? And actually becomes a fertilizer. These are things that are not impossible at all. These things can be done, right? And we should do it.[01:14:42:01 - 01:14:47:23]RJ: Can you tell us a little bit just generally about CUSBI and then I have a ton of questions.[01:14:47:23 - 01:14:48:15]Speaker 5: Yeah.[01:14:48:15 - 01:17:49:10]Max: So CUSBI started about 20 months ago and it was because I was worried about I'm still worried about climate change. And so I realized that in order to get, you know, to stay within two degrees, let's say, we would not only have to reduce our emissions to zero by 2050, but then, you know, another half century or even a century of removing carbon dioxide from the atmosphere, not by reducing your emissions, but actually removing it at a rate that's about half the rate that we now emit it. And that is a unsolved problem. But if we don't solve it, two degrees is not going to happen, right? It's going to be much more. And I don't think people quite understand how bad that can be, like four degrees, like very bad. So this technology needs to be developed. And so this was my and my co-founder, Chet Edwards, motivation to start this startup. And also because, you know, we saw the technology was ready, which is also very good. So if you're, you know, the time is right to do it. And yeah, so we now in the meanwhile, we've grown to about 40 people. We've kind of collected 130 million investment into the company, which is for a European company is quite a lot. I would say it's interesting that right after that, you know, other startups got even more. So that's kind of tells you how fast this is growing. But yeah, we are we are now at the we've built the platform, of course, but it's for a series of material classes and it needs to be constantly expanded to new material classes. And it can be more automated because, you know, we know putting LLMs in as the whole thing gets more and more automated. And now we're moving to sort of high throughput experimentation. So connecting the actual platform, which is computational, to the experiments so that you can get also get fast feedback from experiments. And I kind of think of experiments as something you do at the end, although that's what we've been doing so far. I want to think of it as what I would call a sort of a physics processing unit, like a PPU, right, which is you have digital processing units and then you have physics processing units. So it's basically nature doing computations for you. It's the fastest computer known as possible, even. It's a bit hard to program because you have to do all these experiments. Those are quite, quite bulky. It's like a very large thing you have to do. But in a way, it is a computation. And that's the way I want to see it. So I want to you can do computations in a data center and then you can ask nature to do some computations. Your interface with nature is a bit more complicated. But then these things will have to seamlessly work together to get to a new material that you're interested in. And that's the vision we have. We don't say super intelligence because I don't quite know what it means and I don't want to oversell it. But I do want to automate this process and give a very powerful tool in the hands of the chemists and the material scientists.[01:17:49:10 - 01:18:01:02]Brandon: That actually brings up a question I wanted to ask you. First of all, can you talk about your platform to like whatever degree, like explain kind of how it works and like what you your thought processes was in developing it?[01:18:01:02 - 01:20:47:22]Max: Yeah, I think it's been surprisingly, it's not rocket science, I would say. It's not rocket science in the sense of the design and basically the design that, you know, I wrote down at the very beginning. It's still more or less the design, although you add things like I wasn't thinking very much about multi-scale models and as the common are rated that actually multi-scale is very important. And the beginning, I wasn't thinking very much about self-driving labs. But now I think, you know, we are now at the stage we should be adding that. And so there is sort of bits and details that we're adding. But more or less, it's what you see in the slide decks here as well, which is there is a generative component that you have to train to generate candidates. And then there is a digital twin, multi-scale, multi-fidelity digital twin, which you walk through the steps of the ladder, you know, they do the cheap things first, you weed out everything that's obviously unuseful, and then you go to more and more expensive things later. And so you narrow things down to a small number. Those go into an experiment, you know, do the experiment, get feedback, etc. Now, things that also have been more recently added is sort of more agentic sort of parts. You know, we have agents that search the literature and come up with, you know, actually the chemical literature and come up with, you know, chemical suggestions for doing experiments. We have agents which sort of autonomously orchestrate all of the computations and the experiments that need to be done. You know, they're in various stages of maturity and they can be continuously improved, I would say. And so that's basically I don't think that part. There's rocket science, but, you know, the design of that thing is not like surprising. What is it's surprising hard to actually build it. Right. So that's that's the thing that is where the moat is in the data that you can get your hands on and the and actually building the platform. And I would say there's two people in particular I want to call out, which is Felix Hunker, who is actually, you know, building the scientific part of the platform and Sandra de Maria, who is building the sort of the skate that is kind of this the MLOps part of the platform. Yeah. And so and recently we also added sort of Aaron Walsh to our team, who is a very accomplished scientist from Imperial College. We're very happy about that. He's going to be a chief science officer. And we also have a partnerships team that sort of seeks out all the customers because I think this is one thing I find very important. In print, it's so complex to do to actually bring a material to the real world that you must do this, you know, in collaboration with sort of the domain experts, which are the companies typically. So we always we only start to invest in the direction if we find a good industrial partner to go on that journey with us.[01:20:47:22 - 01:20:55:12]Brandon: Makes a lot of sense. Over the evolution of the platform, did you find that you that human intervention, human,[01:20:56:18 - 01:21:17:01]Brandon: I guess you could start out with a pure, you could imagine two directions when you start up making everything purely automatic, automated, agentic, so on. And then later on, you like find that you need to have more human input and feedback different steps. Or maybe did you start out with having human feedback? You have lots of steps and then like kind of, yeah, figure out ways to remove, you know,[01:21:17:01 - 01:22:39:18]Max: that is the second one. So you build tools for you. So it's much more modular than you think. But it's like, we need these tools for this application. We need these tools. So you build all these tools, and then you go through a workflow actually in the beginning just manually. So you put them in a first this tool, then run this to them or this with sithery. So you put them in a workflow and then you figure out, oh, actually, you know, this this porous material that we are trying to make actually collapses if you shake it a bit. Okay, then you add a new tool that says test for stability. Right. Yeah. And so there's more and more tools. And then you build the agent, which could be a Bayesian optimizer, or it could be an actual other them, you know, maybe trained to be a good chemist that will then start to use all these tools in the right way in the right order. Yeah. Right. But in the beginning, it's like you as a chemist are putting the workflow together. And then you think about, okay, how am I going to automate this? Right. For one very easy question you can ask yourself is, you know, every time somebody who is not a super expert in DFT, yeah, and he wants to do a calculation has to go to somebody who knows DFT. And so could you start to automate that away, which is like, okay, make it so user friendly, so that you actually do the right DFT for the right problem and for the right length of time, and you can actually assess whether it's a good outcome, etc. So you start to automate smaller small pieces and bigger pieces, etc. And in the end, the whole thing is automated.[01:22:39:18 - 01:22:53:25]Brandon: So your philosophy is you want to provide a set of specific tools that make it so that the scientists making decisions are better informed and less so trying to create an automated process.[01:22:53:25 - 01:23:22:01]Max: I think it's this is sort of the same where you're saying because, yes, we want to automate, yeah, but we don't see something very soon where the chemists and the domain expert is out of the loop. Yeah, but it but it's a retreat, right? It's like, okay, so first, you need an expert to tell you precisely how to set the parameters of the DFT calculation. Okay, maybe we can take that out. We can maybe automate that, right? And so increasingly, more of these things are going to be removed.[01:23:22:01 - 01:23:22:19]Speaker 5: Yeah.[01:23:22:19 - 01:24:33:25]Max: In the end, the vision is it will be a search engine where you where somebody, a chemist will type things and we'll get candidates, but the chemist will still decide what is a good material and what is not a good material out of that list, right? And so the vision of a completely dark lab, where you can close the door and you just say, just, you know, find something interesting and then it will it will just figure out what's interesting and we'll figure out, you know, it's like, oh, I found this new material to blah, blah, blah, blah, right? That's not the vision I have. He's not for, you know, a long time. So for me, it's really empowering the domain experts that are sitting in the companies and in universities to be much faster in developing their materials. And I should say, it's also good to be a little humble at times, because it is very complicated, you know, to bring it to make it and to bring it into the real world. And there are people that are doing this for the entire lives. Yeah. Right. And it's like, I wonder if they scratch their head and say, well, you know, how are you going to completely automate that away, like in the next five years? I don't think that's going to happen at all.[01:24:35:01 - 01:24:39:24]Max: Yeah. So to me, it's an increasingly powerful tool in the hands of the chemists.[01:24:39:24 - 01:25:04:02]RJ: I have a question. You've talked before about getting people interested based on having, you know, sort of a big breakthrough in materials, incremental change. I'm curious what you think about the platform you have now in are sort of stepping towards and how are you chasing the big change or is this like incremental or is there they're not mutually exclusive, obviously, but what do you think about that?[01:25:04:02 - 01:26:04:27]Max: We follow a mixed strategy. So we are definitely going after a big material. Again, we do this with a partner. I'm not going to disclose precisely what it is, but we have our own kind of long term goal. You could call it lighthouse or, you know, sort of moonshot or whatever, but it is going to be a really impactful material that we want to develop as a proof point that it can be done and that it will make it into the into the real world and that AI was essential in actually making it happen. At the same time, we also are quite happy to work with companies that have more modest goals. Like I would say one is a very deep partnership where you go on a journey with a company and that's a long term commitment together. And the other one is like somebody says, I knew I need a force field. Can you help me train this force field and then maybe analyze this particular problem for me? And I'll pay you a bunch of money for that. And then maybe after that we'll see. And that's fine too. Right. But we prefer, you know, the deep partnerships where we can really change something for the good.[01:26:04:27 - 01:26:22:02]RJ: Yeah. And do you feel like from a platform standpoint you're ready for that or what are the things that and again, not asking you to disclose proprietary secret sauce, but what are the things generally speaking that need to happen from where we are to where to get those big breakthroughs?[01:26:22:02 - 01:28:40:01]Max: What I find interesting about this field is that every time you build something, it's actually immediately useful. Right. And so unlike quantum computing, which or nuclear fusion, so you work for 20, 30, 40 years and nothing, nothing, nothing, nothing. And then it has to happen. Right. And when it happens, it's huge. So it's quite different here because every time you introduce, so you go to a customer and you say, so what do you need? Right. So we work, let's say, on a problem like a water filtration. We want to remove PFAS from water. Right. So we do this with a company, Camira. So they are a deep partner for us. Right. So we on a journey together. I think that the breakthrough will happen with a lot of human in the loop because there is the chemists who have a whole lot more knowledge of their field and it's us who will help them with training, having a new message. And in that kind of interface, these interactions, something beautiful will happen and that will have to happen first before this field will really take off, I think. And so in the sense that it's not a bubble, let's put it that way. So that's people see that as actual real what's happening. So in the beginning, it will be very, you know, with a lot of humans in the loop, I would say, and I would I would hope we will have this new sort of breakthrough material before, you know, everything is completely automated because that will take a while. And also it is very vertical specific. So it's like completely automating something for problem A, you know, you can probably achieve it, but then you'll sort of have to start over again for problem B because, you know, your experimental setup looks very different in the machines that you characterize your materials look very different. Even the models in your platform will have to be retrained and fine tuned to the new class. So every time, you know, you have a lot of learnings to transfer, but also, you know, the problems are actually different. And so, yes, I would want that breakthrough material before it's completely automated, which I think is kind of a long term vision. And I would say every time you move to something new, you'll have to start retraining and humans will have to come in again and say, okay, so what does this problem look like? And now sort of, you know, point the the machine again, you know, in the new direction and then and then use it again.[01:28:40:01 - 01:28:47:17]RJ: For the non-scientists among us, me included a bit of a scientist. There's a lot of terminology. You mentioned DFT,[01:28:49:00 - 01:29:01:11]RJ: you equivariance we've talked about. Can you sort of explain in engineering terms or the level of sophistication and engineering? Well, how what is equivariance?[01:29:01:11 - 01:29:55:01]Max: So equivariance is the infusion of symmetry in neural networks. So if I build a neural network, let's say that needs to recognize this bottle, right, and then I rotate the bottle, it will then actually have to completely start again because it has no idea that the rotated bottle. Well, actually, the input that represents a rotated bottle is actually rotated bottle. It just doesn't understand that. Right. If you build equivariance in basically once you've trained it in one orientation, it will understand it in any other orientation. So that means you need a lot less data to train these models. And these are constraints on the weights of the model. So so basically you have to constrain the way such data to understand it. And you can build it in, you can hard code it in. And yeah, this the symmetry groups can be, you know, translations, rotations, but also permutations. I can graph neural network, their permutations and then physics, of course, as many more of these groups.[01:29:55:01 - 01:30:01:08]RJ: To pray devil's advocate, why not just use data augmentation by your bottle is in all the different orientations?[01:30:01:08 - 01:30:58:23]Max: As an option, it's just not exact. It's like, why would you go through the work of doing all that? Where you would really need an infinite number of augmentations to get it completely right. Where you can also hard code it in. Now, I have to say sometimes actually data augmentation works even better than hard coding the equivariance in. And this is something to do with the fact that if you constrain the optimization, the weights before the optimization starts, the optimization surface or objective becomes more complicated. And so it's harder to find good minima. So there is also a complicated interplay, I think, between the optimization process and these constraints you put in your network. And so, yeah, you'll hear kind of contradicting claims in this field. Like some people and for certain applications, it works just better than not doing it. And sometimes you hear other people, if you have a lot of data and you can do data augmentation, then actually it's easier to optimize them and it actually works better than putting the equivariance in.[01:30:58:23 - 01:31:07:16]Brandon: Do you think there's kind of a bitter lesson for mathematically founded models and strategies for doing deep learning?[01:31:07:16 - 01:31:46:06]Max: Yeah, ultimately it's a trade-off between data and inductive bias. So if your inductive bias is not perfectly correct, you have to be careful because you put a ceiling to what you can do. But if you know the symmetry is there, it's hard to imagine there isn't a way to actually leverage it. But yeah, so there is a bitter lesson. And one of the bitter lessons is you should always make sure your architecture is scale, unless you have a tiny data set, in which case it doesn't matter. But if you, you know, the same bitter lessons or lessons that you can draw in LLM space are eventually going to be true in this space as well, I think.[01:31:47:10 - 01:31:55:01]RJ: Can you talk a little bit about your upcoming book and tell the listeners, like, what's exciting about it? Yeah, I should read it.[01:31:55:01 - 01:33:42:20]Max: So this book is about, it's called Generative AI and Stochastic Thermodynamics. It basically lays bare the fact that the mathematics that goes into both generative AI, which is the technology to generate images and videos, and this field of non-equilibrium statistical mechanics, which are systems of molecules that are just moving around and relaxing to the ground state, or that you can control to have certain, you know, be in a certain state, the mathematics of these two is actually identical. And so that's fascinating. And in fact, what's interesting is that Jeff Hinton and Radford Neal already wrote down the variational free energy for machine learning a long time ago. And there's also Carl Friston's work on free energy principle and active entrance. But now we've related it to this very new field in physics, which is called stochastic thermodynamics or non-equilibrium thermodynamics, which has its own very interesting theorems, like fluctuation theorems, which we don't typically talk about, but we can learn a lot from. And I think it's just it can sort of now start to cross fertilize. When we see that these things are actually the same, we can, like we did for symmetries, we can now look at this new theory that's out there, developed by these very smart physicists, and say, okay, what can we take from here that will make our algorithms better? At the same time, we can use our models to now help the scientists do better science. And so it becomes a beautiful cross-fertilization between these two fields. The book is rather technical, I would say. And it takes all sorts of things that have been done as stochastic thermodynamics, and all sorts of models that have been done in the machine learning literature, and it basically equates them to each other. And I think hopefully that sense of unification will be revealing to people.[01:33:42:20 - 01:33:44:05]RJ: Wait, and when is it out?[01:33:44:05 - 01:33:56:09]Max: Well, it depends on the publisher now. But I hope in April, I'm going to give a keynote at ICLR. And it would be very nice if they have this book in my hand. But you know, it's hard to control these kind of timelines.[01:33:56:09 - 01:33:58:19]RJ: Yeah, I'm looking forward to it. Great.[01:33:58:19 - 01:33:59:25]Max: Thank you very much. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

In this bonus episode, Nobel Prize-winning economist Daron Acemoglu joins Sam to challenge some of the most common assumptions about artificial intelligence's future. Drawing on his book Power and Progress, Daron argues that technology doesn't have a fixed destiny — and that today's choices will determine whether AI boosts workers or simply accelerates automation and inequality. He makes a case for focusing on new tasks that complement human skills, rather than replacing them, and warns that current incentives push AI toward centralization and automation by default. The conversation tackles productivity myths, reliability risks, and why regulation should proactively steer AI toward social good. Read the episode transcript here. Guest bio: Daron Acemoglu is an institute professor at MIT, faculty codirector of the James M. and Cathleen D. Stone Center on Inequality and Shaping the Future of Work, and a research affiliate at MIT's newly established Blueprint Labs. He is an elected fellow of the National Academy of Sciences, American Philosophical Society, the British Academy of Sciences, the Turkish Academy of Sciences, the American Academy of Arts and Sciences, the Econometric Society, the European Economic Association, and the Society of Labor Economists. He is also a member of the Group of Thirty. He has authored six books, including Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity with Simon Johnson. His work in economics has been recognized around the world, notably with the Nobel Prize in economic sciences, along with co-laureates Johnson and James A. Robinson, in 2024. *Please take our listener survey: ⁠⁠mitsmr.com/podcastsurvey⁠⁠ It's short — we promise! — and all respondents will receive a free MIT SMR article collection, "Maximizing the Value of Generative AI." Me, Myself, and AI is a podcast produced by MIT Sloan Management Review and hosted by Sam Ransbotham. It is engineered by David Lishansky and produced by Allison Ryder. We encourage you to rate and review our show. Your comments may be used in Me, Myself, and AI materials. ME, MYSELF, AND AI® is a federally registered trademark of Massachusetts Institute of Technology. All rights reserved.

Crispr's ability to cut genetic code like scissors has just started to turn into medicines. Now, gene editing pioneer Jennifer Doudna wants to build an entire ecosystem to bring these treatments mainstream. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Nobel Laureate Paul Krugman, a City University of New York professor, says President Donald Trump's tariffs are a sales tax and are slightly contractionary. He speaks on "Bloomberg The Close."See omnystudio.com/listener for privacy information.

How did we go from digital computers to AI seemingly everywhere? Neil deGrasse Tyson, Chuck Nice, & Gary O'Reilly dive into the mechanics of thinking, how AI got its start, and what deep learning really means with cognitive and computer scientist, Nobel Laureate, and one of the architects of AI, Geoffrey Hinton. Subscribe to SiriusXM Podcasts+ to listen to new episodes of StarTalk Radio ad-free and a whole week early.Start a free trial now on Apple Podcasts or by visiting siriusxm.com/podcastsplus. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

HEALTH NEWS Bioactive polyphenolic compounds and in vitro anti-degenerative property-based pharmacological propensities of germplasms of Amaranth Magnesium lower fasting blood sugar in older adults Inactivity linked to up to 10% of type 2 diabetes complications Could Sugary Drinks Be Fueling the Rise in Teen Anxiety? Exercise-induced activation of neurons mediates improvements in endurance   Clips For Today  Increasing Attacks on Francesca Albanese Presage a New Dark Age - Chris Edges  Dr. Luc Montagnier, Nobel Laureate, final interview before being FOUND DEAD 6 days later. Jeffrey Epstein: The Autopsy Details No One Is Talking About - Lauren Mortician 

47 years ago today, Iran was declared an Islamic republic, after a year-long revolution that toppled a Shah and sent shockwaves throughout the world. And this anniversary sees the regime in its fiercest fight for survival yet. Last month, hundreds of thousands of Iranians rose up in protest, demanding change, before authorities brutally cracked down. The government itself admits to more than 3,000 deaths, but the real number could be in the tens of thousands, according to human rights groups. The violence and intimidation continue even in prison. Detained Nobel Peace Prize winner Narges Mohammadi has been viciously assaulted, according to the Nobel Committee, whose leader Jørgen Frydnes joins from Oslo.  Also on today's show: Former Danish Prime Minister Anders Fogh Rasmussen; Sara Khaki & Mohammadreza Eyni, co-directors of Oscar-nominated Iranian documentary "Cutting Through Rocks"; Scott Galloway, professor at the NYU Stern School of Business    Learn more about your ad choices. Visit podcastchoices.com/adchoices

We all love the thrill of winning - the house, the promotion, the deal. But as Nobel laureate Richard Thaler explains, some of our biggest “wins” are actually the moments we set ourselves up to lose. Thaler breaks down why we overbid, overpay, and talk ourselves into choices we regret. And he shares simple tricks to help you catch yourself before you make a mistake you can't undo.

I can't believe we're already through the first month of 2026, but here we are. This month, Ian started us off with László Krasznahorkai's: Sátántangó. The Hungarian author was last year's Nobel Laureate, so we decided that we'd better take a look at his oeuvre. Sátántangó is a bleak novel that describes the lives of the people living on an "estate". The people lie, cheat, and steal from each other, wallowing in their own problems, until Irimiás, a man they thought dead returns. The residents think that he's going to better their lives, but Irimiás is a conman. Sátántangó is a difficult text, especially only having read it once, but upon discussing the text, had more to say than we thought. We hope you enjoy our discussion! Maybe you have your own theories about what is really going on in this book?    February's book is a classic: Wuthering Heights by Charlotte Brontë. Ronnie chose this one because Emerald Fennel's new movie!

For this episode, Robin examines the fundamental differences between liberalism and progressivism and why understanding this divide is critical for 2028.Key topics include: Why Republicans fall in line while Democrats fracture over purity tests, the data showing disruptive protest tactics reduce public support by 15%, and how protest votes intended to help Gaza enabled Trump's return and Gaza's devastation. With 31 Nobel laureates warning about fascism, Yale historians fleeing to Canada, and a Democracy Index rating the U.S. at 55/100 (authoritarian territory), ideological purity has become dangerous. With democracy itself at stake, coalition building must supersede purity politics.In this episode, Robin argues that while liberals and progressives share end goals, such as universal healthcare, climate action, workers' rights, racial justice...their strategic disagreements determine electoral outcomes. Compromise isn't betrayal; it's how democracy functions.Keywords: liberal vs progressive, democratic party divide, why democrats lose elections, electoral strategy 2028, progressive purity politics, coalition building, capitalism vs socialism, free speech vs cancel culture, identity politics, incrementalism vs revolution, protest tactics effectiveness, political compromise, Gaza protest votes, Republican electoral strategy, swing state politics, moderate vs progressive, political pragmatism, deplatforming debate, working class voters, political podcast, 2028 election analysis, authoritarianism warning, voting strategy, ideological purity critiqueSources: Pew Research (2021), Ruy Teixeira/The Liberal Patriot, Matthew Yglesias/The Atlantic, Ezra Klein/NYT, Democracy Index 2025, 31 Nobel Laureates fascism letterBecome a supporter of this podcast: https://www.spreaker.com/podcast/we-saw-the-devil-crime-political-analysis--4433638/support.Website: http://www.wesawthedevil.comPatreon: http://www.patreon.com/wesawthedevilDiscord: https://discord.gg/X2qYXdB4Twitter: http://www.twitter.com/WeSawtheDevilInstagram: http://www.instagram.com/wesawthedevilpodcast.

Nobel Laureate Dr. Omar Yaghi joins The Take after winning the 2025 Nobel Prize in Chemistry for developing metal-organic frameworks (MOFs), materials that can capture carbon and store hydrogen. Born to a Palestinian refugee family in Amman, Yaghi tells the story of how hardship shaped his imagination, from getting fresh water only once a week to inventing systems that pull water from desert air. In this episode: Dr. Omar Yaghi, Nobel Laureate in Chemistry, Professor at University of California, Berkeley and Atoco Founder Episode credits: This episode was produced by Chloe K. Li and Melanie Marich with Phillip Lanos, Spencer Cline, Tamara Khandaker, Kylene Kiang, Sarí el-Khalili and our host, Malika Bilal. It was edited by Noor Wazwaz and Sarí el-Khalili. The Take production team is Marcos Bartolomé, Sonia Bhagat, Spencer Cline, Sarí el-Khalili, Tamara Khandaker, Kylene Kiang, Phillip Lanos, Chloe K. Li, Melanie Marich, and Noor Wazwaz. Our host is Malika Bilal. Our engagement producers are Adam Abou-Gad and Vienna Maglio. Andrew Greiner is lead of audience engagement. Our sound designer is Alex Roldan. Our video editors are Hisham Abu Salah and Mohannad al-Melhem. Alexandra Locke is The Take’s executive producer. Ney Alvarez is Al Jazeera’s head of audio. Connect with us: @AJEPodcasts on X, Instagram, Facebook, and YouTube

It took longer than expected to get all of the details from Thursday’s big meeting between Maria Corina Machado and President Trump. First we heard the Nobel Laureate “presented” Trump with her medal, but it wasn’t until later in the evening we learned that not only had Trump happily accepted it, there is an incredible photo that documents the moment. Trump’s face is priceless and so is the reaction on X from the Nobel Committee.See omnystudio.com/listener for privacy information.

It took longer than expected to get all of the details from Thursday’s big meeting between Maria Corina Machado and President Trump. First we heard the Nobel Laureate “presented” Trump with her medal, but it wasn’t until later in the evening we learned that not only had Trump happily accepted it, there is an incredible photo that documents the moment. Trump’s face is priceless and so is the reaction on X from the Nobel Committee.See omnystudio.com/listener for privacy information.

It took longer than expected to get all of the details from Thursday’s big meeting between Maria Corina Machado and President Trump. First we heard the Nobel Laureate “presented” Trump with her medal, but it wasn’t until later in the evening we learned that not only had Trump happily accepted it, there is an incredible photo that documents the moment. Trump’s face is priceless and so is the reaction on X from the Nobel Committee.See omnystudio.com/listener for privacy information.

It took longer than expected to get all of the details from Thursday’s big meeting between Maria Corina Machado and President Trump. First we heard the Nobel Laureate “presented” Trump with her medal, but it wasn’t until later in the evening we learned that not only had Trump happily accepted it, there is an incredible photo that documents the moment. Trump’s face is priceless and so is the reaction on X from the Nobel Committee.See omnystudio.com/listener for privacy information.

If you appreciate my work and would like to support it: https://subscribestar.com/the-saad-truth https://patreon.com/GadSaad https://paypal.me/GadSaad To subscribe to my exclusive content on X, please visit my bio at https://x.com/GadSaad _______________________________________ This clip was posted on January 13, 2026 on my YouTube channel as THE SAAD TRUTH_1980: https://youtu.be/tYRL7TiMBiM _______________________________________ Please visit my website gadsaad.com, and sign up for alerts. If you appreciate my content, click on the "Support My Work" button. I count on my fans to support my efforts. You can donate via Patreon, PayPal, and/or SubscribeStar. _______________________________________ Dr. Gad Saad is a professor, evolutionary behavioral scientist, and author who pioneered the use of evolutionary psychology in marketing and consumer behavior. In addition to his scientific work, Dr. Saad is a leading public intellectual who often writes and speaks about idea pathogens that are destroying logic, science, reason, and common sense.  _______________________________________

In this extraordinary episode of Gateways to Awakening, Yasmeen sits down with evolutionary astrologer and Vastu gemstone master Tashi Powers, whose decades of experience reading charts for luminaries, from the Rolling Stones to Brad Pitt to Nobel Laureates, have made her one of the most respected astrologers in the world. Together, Yasmeen and Tashi explore the hidden architecture of reality through Vastu, gemstone astrology, and evolutionary astrology—revealing how our homes, bodies, and birth charts are encoded with cosmic intelligence.“Your home is a living organism. When you align your space with your planetary blueprint, the universe begins to conspire with you—fast.” — Tashi Powers“These remedies aren't symbolic. They're vibrational technologies that have been working for 10,000 years.” - Tashi Powers Tashi explains how to personalize Vastu using your birth chart, how gemstones communicate with planetary frequencies, and why your home is a living organism that can either harmonize or distort your destiny. She shares astonishing stories about space clearing, planetary remedies, and the Deva realm, and breaks down how colors, deities, sacred geometry, and gemstones can transform your relationships, career, creativity, and emotional harmony.This episode also dives into:- How Vastu aligns your home with your planetary blueprint- Why gemstones work—and how to use them for love, money, empowerment, and protection- How the days of the week correspond to planetary energies- What evolutionary astrology reveals about your karma, purpose, and soul path- The power of the moon, Venus gates, and the sacred geometry of the cosmos- How to work with natural law, intuition, and the seed cycle of the zodiac- The importance of the galactic center and why some souls come in with a “galactic mission”Yasmeen and Tashi also announce the relaunch of their personalized Vastu app, Vastu Feng Shui, which turns an ancient $500-$2,000 consultation into a modern, intuitive tool for anyone to use—complete with personalized remedies for love, health, prosperity, and emotional harmony.This is a mystical, grounded, highly practical conversation for anyone ready to understand their space, their chart, and their energy in a completely new way.Learn more at:VastuFengShuiHarmony.comEnlighteningTimes.comInstagram: @tashiastrodikini @yasmeenturayhi @vastushaktifengshuiTune in to Gateways to Awakening for more conversations with leading thinkers, creators, and spiritual pioneers shaping the future of consciousness. For more from me: follow my writing on Substack (substack.com/@therealyasmeent), find me on Instagram @TheRealYasmeenT, or visit InnerKnowingSchool.com.

A loss in Jason's family, RIP Rob Reiner -- the latest on the investigation into his and his wife, Michelle's death, myTalk Loves Local: MSP, and Alexis shares details about the Nobel Laureate dinner See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

James sits down with astrophysicist Brian Keating for a candid, useful tour through three hot zones: how to think about AI (and where it actually helps), what's broken in higher ed and admissions right now, and why outsourcing your mood to politics is a losing strategy. You'll hear first-hand stories (from UC San Diego classrooms to New York City politics), specific ways James and Brian really use AI daily, and a simple framework for protecting your attention and happiness—even when everything feels polarized. What You'll Learn: How universities can leverage AI-guided curiosity to revolutionize learning, according to James Altucher's vision for "Altucher University." Why mastering communication skills—writing, speaking, negotiating—is crucial for career success, and why these skills are often neglected in traditional education. Firsthand insights into how Brian Keating and James Altucher use AI daily for research, problem-solving, and creativity, along with practical examples from their personal and professional lives. The economic and philosophical debates around AI's actual impact on industries, jobs, and the broader GDP, including its use in coding, media, and even farming. The limitations of AI and large language models in science and creative work, and why critical thinking and prompt engineering remain essential—even as technology evolves. Timestamped Chapters: 00:00 "AI Clarifies Venezuela Questions" 05:59 Venezuela News Omission 07:45 Frustrating Academia Raise Policy 11:54 Collaboration and Engagement Terms 14:23 "Ideas Overload Dilutes Impact" 19:11 Economic Efficiency Benefits All 19:49 Automation's Effect on Jobs 23:43 "Decentralized AI Competition" 27:09 "AI's Rapid Growth" 31:39 Copyright Limits Creativity 33:17 AI Book Recommendations 38:38 "AI Won't Replace Writers" 41:01 "Dumb Takes by Geniuses" 44:39 Content Overload Shift 47:47 Self-Publishing Outperforms Traditional 49:05 Dying Publishing Model 54:21 "Nobel Laureates' Impact Explained" 57:49 "Epstein, Trump, Wishcasting" 59:37 "Thrills Free on Pluto TV" Additional resources:

Here is the GoFundMe link for Pearl that I mention in this episode: https://gofund.me/2aa4d537e Most people don't get enough sleep — and even a small deficit can take a big toll. Just 15 extra minutes a night can boost your health, focus, and mood more than you'd expect. This episode begins with a surprising look at how too little sleep quietly undermines your life — and how a little more can make all the difference. https://www.sleep.com/sleep-health/15-minutes-extra-sleep Simple beats complicated — in business, communication, and life. Yet most of us instinctively make things harder than they need to be. Marketing entrepreneur and educator Ben Guttmann, who's helped clients from the NFL to Nobel Laureates, reveals why simplicity is the ultimate superpower and how to harness it in your ideas, writing, and daily decisions. He's the author of Simply Put: Why Clear Messages Win—and How to Design Them (https://amzn.to/3udtVwz). You probably have pockets in nearly everything you wear — and yet, they're only about 500 years old. Where did they come from? Why are women's pockets so small? And what do they say about how people have lived through history? Hannah Carlson, a historian of clothing and author of POCKETS: An Intimate History of How We Keep Things Close (https://amzn.to/3SUzmef), reveals the surprisingly political, personal, and practical story of the humble pocket. Finally, anger isn't always destructive — used wisely, it can be one of your greatest motivators. Research shows that channeling anger toward a meaningful goal can actually help you focus and achieve more. I'll explain how to tap into the power of anger — without letting it take over. https://www.nbcnews.com/health/feeling-angry-may-help-people-achieve-goals-study-finds-rcna123611 PLEASE SUPPORT OUR SPONSORS! AG1: Head to ⁠⁠⁠https://DrinkAG1.com/SYSK ⁠⁠⁠ to get a FREE Welcome Kit with an AG1 Flavor Sampler and a bottle of Vitamin D3 plus K2, when you first subscribe!  AURA FRAMES: For a limited time, visit https://AuraFrames.com and get $45 off Aura's best-selling Carver Mat frames -named #1 by Wirecutter -by using promo code SOMETHING at checkout INDEED: Get a $75 sponsored job credit to get your jobs more visibility at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://Indeed.com/SOMETHING⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ right now! QUINCE: Give and get timeless holiday staples that last this season with Quince.  Go to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://Quince.com/sysk⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for free shipping on your order and 365 day returns! DELL: It's time for Black Friday at Dell Technologies. Save big on PCs like the Dell 16 Plus featuring Intel® Core™ Ultra processors. Shop now at: ⁠ https://Dell.com/deals ⁠ NOTION: ⁠⁠Notion brings all your notes, docs, and projects into one connected space that just works . It's seamless, flexible, powerful, and actually fun to use! Try Notion, now with Notion Agent, at: ⁠https://notion.com/something⁠ PLANET VISIONARIES: In partnership with Rolex's Perpetual Planet Initiative, this… is Planet Visionaries. Listen or watch on Apple, Spotify, YouTube, or wherever you get your podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

From hiding, Venezuelan opposition leader Maria Corina Machado reacts to her Nobel Peace Prize, announced Friday, and tells NPR's Ayesha Rascoe why she dedicated the prize in part to President Trump.Learn more about sponsor message choices: podcastchoices.com/adchoicesNPR Privacy Policy