Podcasts about economists

We've been conditioned to believe that saying less is safer. But playing it safe costs trust, influence, stronger negotiations, and deeper relationships because the line between “too much” and meaningful connection is further out than we think. In the latest episode of Habits & Hustle, I'm joined by author Leslie John to break down the exact tipping point where leader vulnerability backfires, why holding your cards close in negotiation weakens your leverage, and how pushing slightly past your comfort zone builds real authority. Leslie John is the James E. Burke Professor of Business Administration at Harvard Business School and author of Revealing: The Underrated Power of Oversharing. Her award-winning research appears in top academic journals and media including The New York Times, The Wall Street Journal, and The Economist. What's Discussed (04:00) Why oversharing feels risky but builds stronger relationships and influence (06:31) The difference between emotional dumping and strategic vulnerability (18:23) Disclosure flexibility and knowing when to reveal versus hold back (20:55) Why long term relationships erode when partners stop sharing (27:15) How strategic transparency increases trust and customer retention (28:50) The most common negotiation mistake: leading with concealment (34:03) Leader vulnerability and the tipping point where credibility drops (41:01) Authenticity versus impulse and why emotional intelligence matters Thank you to our sponsors: Rho Nutrition: Try Rho Nutrition today and experience the difference of Liposomal Technology. Use code JEN20 for 20% OFF everything at https://rhonutrition.com/discount/jen20. Prolon: Get 30% off sitewide plus a $40 bonus gift when you subscribe to their 5-Day Program! Just visit https://prolonlife.com/JENNIFERCOHEN and use code JENNIFERCOHEN to claim your discount and your bonus gift. Therasage: Head over to therasage.com and use code Be Bold for 15% off  Air Doctor: Go to airdoctorpro.com and use promo code HUSTLE40 for up to $300 off and a 3-year warranty on air purifiers. Magic Mind: Head over to www.magicmind.com/jen and use code Jen at checkout. Momentous: Shop this link and use code Jen for 20% off  Manna Vitality: Visit mannavitality.com and use code JENNIFER20 for 20% off your order  Amp fit is the perfect balance of tech and training, designed for people who do it all and still want to feel strong doing it. Check it out at joinamp.com/jen  Find more from Jen:  Website: https://jennifercohen.com Instagram: @therealjencohen Books: https://jennifercohen.com/books Speaking: https://jennifercohen.com/speaking-engagement Find more from Leslie John: Website: https://lesliekjohn.com Instagram: @proflesliejohn Youtube: @ProfLeslieJohn X: @ProfLeslieJohn

Merriam-Webster's Word of the Day for February 24, 2026 is: umpteen • UMP-teen • adjective Umpteen is an informal adjective meaning "very many" or "indefinitely numerous." // The artist has painted the same subject umpteen times, yet each piece has its own unique quality. See the entry > Examples: "The life of a showgirl often includes umpteen costume changes, elaborate props and copious amounts of hairspray." – The Economist, 4 Oct. 2025 Did you know? There may not be a gazillion ways in English to refer to a large, indefinite number, but there are definitely more than a soupçon. Many of these, such as zillion, bazillion, kazillion, jillion, and bajillion, start with -illion (as in million) and add a satisfying consonant or syllable in front for some extra oomph. The adjective umpteen does the same for -teen, with the oomph provided by the ump in umpty. Umpty, an adjective meaning "such and such" (as in "umpty percent" or "umpty-four") arose, like umpteen, in the latter half of the 1800s. We only occasionally use umpty these days, but you're bound to hear or read umpteen and umpteenth ("latest or last in an indefinitely numerous series") any number of times.

This Day in Legal History: Order 9066On this day in legal history, enforcement of Executive Order 9066 began in earnest following its signing by Franklin D. Roosevelt earlier in February 1942. The order authorized the military to designate exclusion zones and remove individuals deemed security risks from certain areas of the country. In practice, it led to the forced relocation and incarceration of more than 110,000 Japanese Americans, most of whom were U.S. citizens. Families were removed from their homes, businesses were lost, and entire communities were dismantled. The government justified the policy as a matter of national security during World War II. Critics argued it was rooted in racial prejudice rather than military necessity.The constitutionality of the policy reached the Supreme Court in Korematsu v. United States. Fred Korematsu, a U.S. citizen, had refused to comply with the exclusion order and was convicted. In a 6–3 decision, the Court upheld his conviction, accepting the government's claim that the exclusion was justified by wartime necessity. The majority deferred heavily to the executive branch, emphasizing the perceived threat on the West Coast. In dissent, several justices warned that the decision validated racial discrimination under the guise of military urgency.Decades later, the ruling came to be widely regarded as a grave error. In 1988, Congress passed the Civil Liberties Act, formally apologizing and providing reparations to surviving internees. In 2018, the Supreme Court explicitly stated that Korematsu was wrongly decided, rejecting its reasoning even though it was not formally overturned in the technical sense. The episode remains a cautionary example of how constitutional protections can erode in times of crisis.The U.S. Supreme Court is set to hear two cases concerning the scope of the Helms-Burton Act, a 1996 law that allows American companies to sue over property confiscated by Cuba after the 1959 revolution. One case involves ExxonMobil's effort to recover more than $1 billion for oil and gas assets seized by Cuba in 1960. Exxon sued a Cuban state-owned company in 2019, alleging it continues to profit from the confiscated property. A lower court ruled that the Cuban entities could claim foreign sovereign immunity, which generally protects foreign governments from being sued in U.S. courts. Exxon has asked the Supreme Court to reverse that decision.The second case involves four cruise operators—Carnival, Royal Caribbean, Norwegian Cruise Line, and MSC Cruises—accused of unlawfully benefiting from docks in Havana that were originally built and operated by a U.S. company before being seized by Cuba. The docks were used between 2016 and 2019, after travel restrictions were eased under President Obama. A trial judge initially ruled against the cruise lines and awarded more than $100 million in damages, but an appeals court later dismissed the case, finding that the original concession had expired before the cruise lines used the property. The Supreme Court's decisions could clarify how broadly Congress intended the Helms-Burton Act to apply and whether claimants face significant legal barriers when seeking compensation.US Supreme Court to hear Exxon bid for compensation from Cuba | ReutersU.S. Customs and Border Protection announced that it will stop collecting tariffs imposed under the International Emergency Economic Powers Act (IEEPA) beginning just after midnight on Tuesday. The decision comes several days after the U.S. Supreme Court ruled that those tariffs were unlawful. The agency said it would deactivate the tariff codes tied to President Donald Trump's IEEPA-related orders but did not explain why collections continued for days after the ruling. It also did not address whether importers who paid the duties would receive refunds.The suspension of the IEEPA tariffs coincides with the implementation of a new 15% global tariff introduced under a different statutory authority. Customs clarified that the halt applies only to the IEEPA-based tariffs and does not affect other trade measures, including those enacted under Section 232 for national security reasons or Section 301 for unfair trade practices. Economists have estimated that the now-invalidated IEEPA tariffs generated more than $175 billion in revenue and were bringing in over $500 million per day. As a result, the ruling potentially exposes the government to significant refund claims from importers.US to stop collecting tariffs deemed illegal by Supreme Court on Tuesday | ReutersJPMorgan Chase informed President Donald Trump and his hospitality company in February 2021 that it was closing their bank accounts, according to newly released documents tied to Trump's $5 billion lawsuit against the bank and its CEO, Jamie Dimon. The letters were sent about a month after the January 6, 2021, attack on the U.S. Capitol. At the time, several businesses and organizations distanced themselves from Trump, including law firms and the PGA of America.In its February 19, 2021 letters, JPMorgan did not provide a detailed explanation for ending the relationship. The bank stated generally that it may determine a client's interests are no longer served by continuing with J.P. Morgan Private Bank. JPMorgan has previously argued that Trump's lawsuit lacks merit. Trump's legal team, however, claims the letters amount to an admission that the bank intentionally “de-banked” him and his businesses, allegedly causing major financial harm.Trump contends that JPMorgan violated its own policies and unfairly targeted him for political reasons. The newly disclosed letters were submitted as part of the bank's effort to transfer the case from federal court in Miami to New York, where JPMorgan argues the dispute is more closely connected.JPMorgan says it closed Trump's bank accounts a month after Jan. 6 attack | ReutersA federal judge in Florida declined to overturn a $243 million jury verdict against Tesla stemming from a fatal 2019 crash involving the company's Autopilot system. The court found that the evidence presented at trial sufficiently supported the jury's conclusion that Autopilot played a role in the collision, which killed 22-year-old Naibel Benavides Leon in Key Largo. The jury determined that both the driver and Tesla shared responsibility for the crash.Jurors originally awarded $59 million to Benavides' parents and $70 million to her boyfriend, Dillon Angulo, who was injured in the incident. After accounting for comparative fault, the compensatory damages were reduced to about $42.6 million, with the driver found 67% responsible and Tesla 33% responsible. The jury also imposed $200 million in punitive damages against the company.Tesla asked the court to set aside the verdict or grant a new trial, arguing that the damages were excessive and that its conduct did not meet Florida's legal threshold for punitive damages. The company also contended that state law limits punitive damages to three times the compensatory award. The judge rejected these arguments, stating that Tesla was largely repeating points already considered and dismissed during trial.At trial, plaintiffs argued that Autopilot was defective because it could be activated on roads it was not designed for and did not adequately ensure driver attention. They also claimed Tesla overstated the system's capabilities. The driver admitted he had looked away from the road moments before the crash.Tesla Can't Escape $243M Autopilot Crash Verdict - Law360 This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.minimumcomp.com/subscribe

John Maytham speaks to Eckardt Naumann, economist and associate at the Trade Law Centre (TRALAC), for analysis on the legal implications of the Supreme Court ruling, the economic consequences of escalating tariffs, and what this means for global trading partners — including South Africa — at a time of heightened geopolitical tension. Presenter John Maytham is an actor and author-turned-talk radio veteran and seasoned journalist. His show serves a round-up of local and international news coupled with the latest in business, sport, traffic and weather. The host’s eclectic interests mean the program often surprises the audience with intriguing book reviews and inspiring interviews profiling artists. A daily highlight is Rapid Fire, just after 5:30pm. CapeTalk fans call in, to stump the presenter with their general knowledge questions. Another firm favourite is the humorous Thursday crossing with award-winning journalist Rebecca Davis, called “Plan B”. Thank you for listening to a podcast from Afternoon Drive with John Maytham Listen live on Primedia+ weekdays from 15:00 and 18:00 (SA Time) to Afternoon Drive with John Maytham broadcast on CapeTalk https://buff.ly/NnFM3Nk For more from the show go to https://buff.ly/BSFy4Cn or find all the catch-up podcasts here https://buff.ly/n8nWt4x Subscribe to the CapeTalk Daily and Weekly Newsletters https://buff.ly/sbvVZD5 Follow us on social media: CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/CapeTalk CapeTalk on YouTube: https://www.youtube.com/@CapeTalk567 See omnystudio.com/listener for privacy information.

Host Piya Chattopadhyay speaks with Slate justice reporter Mark Joseph Stern and The Economist's Canada correspondent Rob Russo break down the U.S. Supreme Court's ruling on Donald Trump's emergency tariffsDefence and security expert Andrea Charron and international affairs historian Susan Colbourn explore Canada's changing military strategyFormer Olympians Clara Hughes and Beckie Scott size up Canada's performance at the Milano-Cortina Winter GamesDr. Brian Goldman discusses treatments for our ailing emergency roomsWriter Matt Alt and international relations expert Shaoyu Yuan reflect on Pokémon's legacy and how it became a source of cultural soft powerDiscover more at https://www.cbc.ca/sunday

Send a textThis episode the guys sit down With Dr. Leah Payne to talk all things Christian Music -- the good, the bad, and the confusing!Leah Payne is an award-winning historian and Professor of American Religious History at Portland Seminary. She holds a Ph.D. from Vanderbilt University and her research explores the intersection of religion, politics, and popular culture. Payne is author of God Gave Rock & Roll to You: a History of Contemporary Christian Music (Oxford University Press, 2024), the 2024 Christianity Today book of the year for History and Biography, and co-host of Rock That Doesn't Roll, a Public Radio Exchange (PRX) podcast about Christian rock and its listeners. She also hosts Spirit & Power, an Axis Mundi Media podcast about politics and Pentecostal and charismatic Christians, and is co-creator of Weird Religion, a religion and pop culture podcast. Her writing and research has appeared in outlets such as The Washington Post, BBC Radio, NBC News, Religion News Service, Harper's Magazine, The Economist, and Christianity Today.www.drleahpayne.comGod Gave Rock and Roll To You: A History of Contemporary Christian Music. 

For decades, economists, armed with elegant models, powerful data, and firm conclusions about how markets should work, have claimed to be practitioners of a hard science. Yet in an era of financialization, political backlash, and rising skepticism of any “expert” consensus, many Americans are wondering whether the profession has grown too insular, too ideological, or simply too detached from reality.Luigi Zingales, professor at the University of Chicago's Booth School of Business and director of the Stigler Center, joins Oren Cass to discuss what's gone wrong. They explore the hierarchy of and conformity within the field, the temptation to defend models because of the conclusions they produce, and the gap between theoretical assumptions and real-world outcomes. The conversation closes with a look at whether a younger generation of economists is prepared to rethink the orthodoxy, and what it would take for economics to regain both its rigor and its relevance.

Welcome back to Truth, Lies & Work, the podcast where behavioural science meets workplace culture. This week we're diving into how AI is actually landing in the workplace — and what that means for managers, employees and the future of work. Our guest is Andrew Palmer, host of Boss Class from The Economist and author of the Bartleby management column. In Season 3 of Boss Class, Andrew goes hands-on with AI — not just talking about it, but living with it, testing it and asking the questions leaders need to answer as the technology transforms jobs and organisations. This episode isn't about hype. It's about what AI is actually good at today, what it's still terrible at, and how leaders should think about deploying it in ways that help people — not replace them.

Patricia and Christian talk to economist and author Dr Phil Armstrong about the least useful pieces of economic commentary from the last 12 months.   In this episode: "Sure, the government *can* create money… (but it shouldn't)" "It's okay for the government to 'borrow'… if it's investing" "The national debt is a time bomb!" "Government 'borrowing' is okay… when interest rates are low"   More to follow in part 2   Full conversation here: https://www.patreon.com/posts/150931987?pr=true   Please help sustain this podcast!  Patrons get early access to all episodes and patron-only episodes: https://www.patreon.com/MMTpodcast   ******************************** STOP PRESS!!  JOIN PATRICIA AND MMT CO-FOUNDER PROFESSOR BILL MITCHELL AT THE LAUNCH OF A NEW DEDICATED MODERN MONETARY THEORY THINK TANK - MMTUK POLICY RESEARCH GROUP!  7pm on Wednesday 25 February at Friends Meeting House, London Click here to register as an attendee: https://actionnetwork.org/events/mmtuk-launch-event/ MMTUK will be publishing its Job Guarantee policy on 25th February - read a short intro here: https://mmtuk.org/job-guarantee  ********************************   Relevant to this episode: Join Patricia and Phil (and many more) at Scotland's Festival of Economics (Edinburgh and online) 19th - 21st March 2026: https://www.scoteconfest.org/#learnmore Join the new MMT UK discord server to connect with others looking to promote MMT and ecological economics in the UK!: https://discord.gg/S3UbxFe4FR "The self-financing state: An institutional analysis of government expenditure, revenue collection and debt issuance operations in the United Kingdom" (Berkeley et al, 2022): https://www.ucl.ac.uk/bartlett/sites/bartlett/files/the_self-financing_state_an_institutional_analysis_of_government_expenditure_revenue_collection_and_debt_issuance_operations_in_the_united_kingdom.pdf For more on the (Liz) Trussageddon, listen to Episode 147 - Dirk Ehnts: Do Markets Control Our Politics?: https://www.patreon.com/posts/episode-147-dirk-72906421 "How to Fight Back Against the False Idea that the Government is at the Mercy of Financial Markets" by Sheridan Kates: https://thealternative.org.uk/dailyalternative/2025/3/10/scotonomics-monetary-autonomy "There is no need to issue public debt" by Bill Mitchell: https://billmitchell.org/blog/?p=31715 Episode 148 - Pavlina Tcherneva: Why The Job Guarantee Is Core To Modern Monetary Theory: https://www.patreon.com/posts/episode-148-why-73211346 Quick read: Pavlina Tcherneva's Job Guarantee FAQ page: https://pavlina-tcherneva.net/job-guarantee-faq/ Episode 30 - Steven Hail: Understanding Government Bonds (Part 1) :https://www.patreon.com/posts/29621245 Episode 31 - Steven Hail: Understanding Government Bonds (Part 2):  https://www.patreon.com/posts/29829500 "Federal Debt and Modern Money" by Steven Hail & David Joy: https://www.global-isp.org/wp-content/uploads/PN-121.pdf "Is exchange rate depreciation inflationary?" by Bill Mitchell: https://billmitchell.org/blog/?p=32922     Podcast Description In this compelling first part of their annual Fauxbel Prize discussion, Patricia Pino and Christian Reilly are joined by economist Dr Phil Armstrong to dissect the most deceptive economic talking points of 2026. What emerges is a masterclass in identifying the subtle linguistic tricks that maintain public misunderstanding about how government finance actually works. The conversation begins with Christian's astute observation about the phrase 'the government *can* create money' - a seemingly innocent statement that actually perpetuates dangerous misconceptions. As the panel explores, there's a world of difference between saying the government 'can' create money versus acknowledging that it 'does' create money with every pound it spends. This distinction matters because it allows economists and pundits to maintain outdated frameworks whilst appearing to acknowledge MMT insights. Dr Armstrong brings his characteristic clarity to explaining the consolidated view of government and central bank operations, illustrating why all government spending necessarily involves money creation. Using vivid analogies - from goldfish that must swim in water to the government's unique relationship with the Bank of England - he demonstrates why currency-issuing governments are fundamentally different from currency users like households or businesses. The discussion then tackles the politically damaging notion that governments should only 'borrow to invest'. Patricia explains why this framing misunderstands the true function of deficits whilst inadvertently supporting neoliberal arguments for privatisation. The panel reveals how this seemingly progressive talking point actually reinforces the household analogy and hands ammunition to fiscal conservatives. In his analysis of the 'public debt time bomb' narrative, Phil turns conventional wisdom on its head by pointing out that if foreign debt holdings were truly a source of power, then Britain - as the second-largest holder of US Treasury securities - would presumably have a decisive degree of control over America's economic destiny. Throughout, the conversation illuminates core MMT principles: the operational reality of government spending, the true nature of government bonds as private sector savings, and why exchange rate concerns, whilst legitimate, shouldn't drive us back to defunct fiscal rules. The panel's analysis reveals how even well-intentioned progressive economists can inadvertently perpetuate harmful misconceptions about monetary sovereignty.   =========== Key Topics with Timestamps [02:15] Introduction to the Fauxbel Prize concept[05:30] "Government can create money" vs "does create money"[12:45] The consolidated view of government and central bank[18:20] Why all government spending is money creation[25:10] "Borrowing to invest" - the progressive own goal[35:45] Historical context: Keynes and bifurcating budgets[42:30] The "Tap" system vs bond auctions[48:15] "Public debt = time bomb" narrative analysis[55:40] Exchange rate concerns and industrial policy   ========= Guest Bio Dr Phil Armstrong - Economist and author of "Can Heterodox Economics Make a Difference?". Researcher with expertise in monetary operations and MMT analysis. Key Takeaways Language matters: The difference between "can" and "does" in describing government money creation shapes public understanding All government spending creates new money: Currency-issuing governments cannot spend previously collected money - every expenditure creates new money The "government borrowing to Invest" narrative is counterproductive: This framing reinforces household analogies and supports privatisation arguments A government "debt" clock is a national SAVINGS clock: Government debt represents private sector savings, not a burden Exchange rate policy needs strategy: Arbitrary fiscal rules won't address structural economic vulnerabilities   ===============   All our episodes in chronological order: https://www.patreon.com/posts/43111643   All our patron-only episodes: https://www.patreon.com/posts/57542767   Scotland's Festival of Economics (Edinburgh and online)  19th - 21st March 2026: https://www.scoteconfest.org/#learnmore   JOIN PATRICIA'S MMT ACTIVIST NETWORK (MMT UK): https://actionnetwork.org/forms/activist-registration-form   Join the MMT UK Discord server to connect with others looking to promote MMT and ecological economics in the UK!: https://discord.gg/S3UbxFe4FR   MMT: THE MOVIE! "Finding The Money", a documentary by Maren Poitras featuring Stephanie Kelton is now available worldwide to rent or buy: https://findingthemoney.vhx.tv/products/finding-the-money Updates on worldwide screenings of "Finding The Money" can be found here: https://findingmoneyfilm.com/where-to-watch/ To arrange a screening of "Finding The Money", apply here: https://findingmoneyfilm.com/host-a-screening/   STUDY THE ECONOMICS OF SUSTAINABILITY! Details of Modern Money Lab's online graduate, postgraduate and standalone courses in economics are here: https://modernmoneylab.org.au/     For an intro to MMT: Our first three episodes: https://www.patreon.com/posts/41742417 Episode 126 - Dirk Ehnts: How Banks Create Money: https://www.patreon.com/posts/62603318   Quick MMT reads: Warren's Mosler's MMT white paper: http://moslereconomics.com/mmt-white-paper/ Steven Hail's quick MMT explainer: https://theconversation.com/explainer-what-is-modern-monetary-theory-72095 Quick explanation of government debt and deficit: "Some Numbers Are Big. Let Me Help You Get Over It": https://christreilly.com/2020/02/17/some-numbers-are-big-let-me-help-you-get-over-it/     For a short, non-technical, free ebook explaining MMT, download Warren Mosler's "7 Deadly Innocent Frauds Of Economic Policy" here: http://moslereconomics.com/wp-content/powerpoints/7DIF.pdf     Episodes on monetary operations:  Episode 20 - Warren Mosler: The MMT Money Story (part 1): https://www.patreon.com/posts/28004824 Episode 126 - Dirk Ehnts: How Banks Create Money: https://www.patreon.com/posts/62603318 Episode 13 - Steven Hail: Everything You Always Wanted To Know About Banking, But Were Afraid To Ask: https://www.patreon.com/posts/41790887 Episode 43 - Sam Levey: Understanding Endogenous Money: https://www.patreon.com/posts/35073683  Episode 84 - Andrew Berkeley, Richard Tye & Neil Wilson: An Accounting Model Of The UK Exchequer (Part 1): https://www.patreon.com/posts/46352183 Episode 86 - Andrew Berkeley, Richard Tye & Neil Wilson: An Accounting Model Of The UK Exchequer (Part 2): https://www.patreon.com/posts/46865929    For more on Quantitative Easing: Episode 59 - Warren Mosler: What Do Central Banks Do?: https://www.patreon.com/posts/39070023 Episode 143 - Paul Sheard: What Is Quantitative Easing?: https://www.patreon.com/posts/71589989?pr=true    Episodes on inflation: Episode 7: Steven Hail: Inflation, Price Shocks and Other Misunderstandings: https://www.patreon.com/posts/41780508 Episode 65 - Phil Armstrong: Understanding Inflation: https://www.patreon.com/posts/40672678 Episode 104 - John T Harvey: Inflation, Stagflation & Healing The Nation: https://www.patreon.com/posts/52207835 Episode 123 - Warren Mosler: Understanding The Price Level And Inflation: https://www.patreon.com/posts/59856379 Episode 128 - L. Randall Wray & Yeva Nersisyan: What's Causing Accelerating Inflation? Pandemic Or Policy Response?: https://www.patreon.com/posts/63776558   Our Job Guarantee episodes:  Episode 4 - Fadhel Kaboub: What is the Job Guarantee?: https://www.patreon.com/posts/41742701 Episode 47 - Pavlina Tcherneva: Building Resilience - The Case For A Job Guarantee: https://www.patreon.com/posts/36034543 Episode 148 - Pavlina Tcherneva: Why The Job Guarantee Is Core To Modern Monetary Theory: https://www.patreon.com/posts/episode-148-why-73211346 Quick read: Pavlina Tcherneva's Job Guarantee FAQ page: https://pavlina-tcherneva.net/job-guarantee-faq/   More on government bonds (and "vigilantes"): Episode 30 - Steven Hail: Understanding Government Bonds (Part 1):https://www.patreon.com/posts/29621245 Episode 31 - Steven Hail: Understanding Government Bonds (Part 2): https://www.patreon.com/posts/29829500 Episode 143 - Paul Sheard: What Is Quantitative Easing?: https://www.patreon.com/posts/71589989?pr=true Episode 147 - Dirk Ehnts: Do Markets Control Our Politics?: https://www.patreon.com/posts/episode-147-dirk-72906421 Episode 144 - Warren Mosler: The Natural Rate Of Interest Is Zero: https://www.patreon.com/posts/71966513 Episode 145 - John T Harvey: What Determines Currency Prices?: https://www.patreon.com/posts/72283811?pr=true   More on bank runs banking regulation:  Episode 162 - Warren Mosler: Anatomy Of A Bank Run: https://www.patreon.com/posts/80157783?pr=true Episode 163 - L. Randall Wray: Breaking Banks - The Fed's Magical Monetarist Thinking Strikes Again: https://www.patreon.com/posts/80479169?pr=true Episode 165 - Robert Hockett: Sparking An Industrial Renewal By Building Banks Better: https://www.patreon.com/posts/81084983?pr=true MMT founder Warren Mosler's Proposals for the Treasury, the Federal Reserve, the FDIC, and the Banking System: https://neweconomicperspectives.org/2010/02/warren-moslers-proposals-for-treasury.html     MMT Events And Courses: More information about Professor Bill Mitchell's MMTed project (free public online courses in MMT) here: http://www.mmted.org/ Details of Modern Money Lab's online graduate and postgraduate courses in MMT and real-world economics are here: https://modernmoneylab.org.au/     Order the Gower Initiative's "Modern Monetary Theory - Key Insights, Leading Thinkers": https://www.e-elgar.com/shop/gbp/modern-monetary-theory-9781802208085.html   MMT Academic Resources compiled by The Gower Initiative for Modern Money Studies: https://www.zotero.org/groups/2251544/mmt_academic_resources_-_compiled_by_the_gower_initiative_for_modern_money_studies   MMT scholarship compiled by New Economic Perspectives: http://neweconomicperspectives.org/mmt-scholarship     A list of MMT-informed campaigns and organisations worldwide: https://www.patreon.com/posts/47900757     We are working towards full transcripts, but in the meantime, closed captions for all episodes are available on our YouTube channel: https://www.youtube.com/channel/UCEp_nGVTuMfBun2wiG-c0Ew/videos     Show notes: https://www.patreon.com/posts/151023856

Today I have the immense pleasure of talking with Carissa Véliz, an associate professor at the University of Oxford, about her new book, Prophecy: Prediction, Power, and the Fight for the Future—from Ancient Oracles to AI.  Linking this work to her previous book, Privacy is Power: Why and How You Should Take Back Control of Your Data, Véliz writes: “ surveillance and prediction are digital technology's original sins.”In our wide-ranging discussion, we talk about how both massive and intrusive invasions of privacy at all levels of society and false claims to be able to predict the future erode democracy, are corrosive to ethics, and undermine people's ability to think for themselves.  Instead, we are conditioned to trust an unregulated band of “effective altruists” who claim to know better than we what kinds of lives we should prefer and the choices we should make.  Véliz argues instead that we should embrace the uncertain to build resilience, to prepare for contingency but not be determined by what we cannot see, and to foster curiosity and imagination.Carissa Véliz is an Associate Professor in Philosophy at the Institute for Ethics in AI, and a Fellow at Hertford College at the University of Oxford. She is the recipient of the 2021 Herbert A. Simon Award for Outstanding Research in Computing and Philosophy. She is a member of UNESCO's Women 4 Ethical AI. She advises companies and policymakers around the world on privacy and the ethics of AI. She is a board member of the Proton Foundation, along with Sir Tim Berners-Lee and Proton's CEO Andy Yen. She is the author of the highly-acclaimed Privacy Is Power (an Economist book of the year, 2020) and the editor of the Oxford Handbook of Digital Ethics. Her new book Prophecy was described as “The most important book you will read for years” by Roger McNamee, the tech investor and best selling author.

In September 2016, Islam Karimov–the first president of a post-Soviet Uzbekistan–died, at age 78. His death ended an oppressive dictatorship that had governed the Central Asian country for decades, which led to corruption, environmental damage, and political repression. Karimov was replaced with Shavkat Mirziyoyev, who instituted a tentative program of reforms. These years are the subject of Joanna Lillis's book, Silk Mirage: Through the Looking Glass in Uzbekistan (Bloomsbury, 2025). Lillis tells the stories of both the Karimov and Mirziryoyev regimes, based on many conversations with activists, journalists, and other opposition leaders in the country. Joanna Lillis is a Kazakhstan-based journalist and author writing about Central Asia who has lived and worked in the region since 2001, in Uzbekistan (2001-2005) and Kazakhstan (since 2005). Her reporting has featured in outlets including The Economist, the Guardian, the Independent, the Eurasianet website and Foreign Policy and POLITICO magazines. Prior to moving to Central Asia, she lived in Russia and worked for BBC Monitoring, the BBC World Service's global media tracking service. She is also the author of Dark Shadows: Inside the Secret World of Kazakhstan (Bloomsbury: 2019). You can find more reviews, excerpts, interviews, and essays at The Asian Review of Books, including its review of Silk Mirage. Follow on Twitter at @BookReviewsAsia. Nicholas Gordon is an editor for a global magazine, and a reviewer for the Asian Review of Books. He can be found on Twitter at@nickrigordon. 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

Welcome to The Chrisman Commentary, your go-to daily mortgage news podcast, where industry insights meet expert analysis. Hosted by Robbie Chrisman, this podcast delivers the latest updates on mortgage rates, capital markets, and the forces shaping the housing finance landscape. Whether you're a seasoned professional or just looking to stay informed, you'll get clear, concise breakdowns of market trends and economic shifts that impact the mortgage world.In today's episode, we look at some of the Fed's suggested changes to bank capital requirements. Plus, Robbie sits down with economist Elliot Eisenberg for a discussion on trends seen across economic data and how high the bar has become for the Fed to justify easing if headline resilience persists. And we close by looking at the diverging path of monetary policy in the coming months.Today's podcast is brought to you by Optimal Blue, the only end-to-end capital markets platform built to power performance, precision, and profitability, helping lenders of all sizes operate more efficiently, manage risk more effectively, and maximize results.

How AI Agents are Disrupting the AdTech Landscape Semantic content classification driven by AI agents is currently transforming digital advertising and B2B content monetization as we know it. When leveraged the right way, marketers can classify B2B content into actionable signals and find the most relevant content across the open web. This shift toward AI-native advertising allows for a more sophisticated approach to targeting that moves beyond traditional cookies. So, how can brands strategically implement these tools to generate impactful results, and what does the rise of autonomous agents mean for the future of your digital marketing strategy? That's why we're talking to Brendan Norman (Co-Founder and CEO, Classify), who shares his expertise and experience on how AI agents are disrupting the AdTech landscape. During our conversation, Brendan discussed the evolution of digital advertising and the critical integration of AI and cloud-based tools to automate manual tasks and improve campaign optimization. He also elaborated on the massive shift from human-centric to agent-centric traffic, predicting that agent traffic will surpass human traffic within 18-24 months. Brendan also explained why he believes that the future belongs to marketers who can blend audience and contextual signals to monetize human and agent attention. He highlighted how new AI-native tools are democratizing advanced ad tech, significantly reducing costs and improving efficiency for large and small advertisers. https://youtu.be/yVobWZTmwco Topics discussed in episode: [03:01] Beyond Keywords: How semantic understanding allows advertisers to target the nuance of a page (like “snow removal” vs. just “winter”) rather than broad categories.  [06:46] Optimizing for AI Agents: Why “Generative Engine Optimization” (GEO) complements traditional SEO, and how brands must prepare for agents retrieving information instead of humans.  [12:34] The Shift in Web Traffic: The prediction that agent traffic will surpass human traffic on the web in the next 6 to 24 months.  [15:50] The Power of Context + Audience: Why the best advertising strategy combines who the user is (audience) with what they are consuming in the moment (context).  [20:47] Democratizing Ad Tech: How AI agents and new frameworks will allow smaller brands with smaller budgets to access sophisticated programmatic advertising tools.  [26:54] High-Fidelity Curation at Scale: How AI reduces the cost of processing massive data sets, making real-time optimization and curation accessible and sustainable.  [33:44] The “Middleman Tax”: A look at the inefficiency of current ad tech where only 35 cents of every dollar reaches the publisher, and how AI can fix this.  Companies and links mentioned: Brendan Norman on LinkedIn  Classify  Bluefish AI Agentic Advertising Org  IAB Tech Lab Transcript Brendan Norman – Classify, Christian Klepp Brendan Norman – Classify  00:00 I think overall, jobs will change. I think that people will have to spend a lot less time doing a lot of the manual, rote tasks that they’re doing today. You know, kind of in parallel with what we’re seeing in terms of vibe coding and people’s ability to build product really quickly, design new web pages really quickly, like get ship things out quickly. I think a lot of the infrastructure layer tools, or just call them like, like, chatGPT style, cloud based tools, LLMs (Large Language Models), we’ll see a lot deeper integration into existing advertising product. And what that does is it helps democratize the whole ecosystem. So I think it frees up people’s time, you know, to not have to do a lot of the basic administrative, you know, reporting, manual, campaign, optimization type stuff, and it will help service a lot better insights. Ultimately, I think the industry grows, and I think it scales even faster and cautiously, optimistically. I think that we, we will have back to building on the curation piece, and, you know, the advertiser, outcomes piece, publisher monetization piece, user experience piece, I think that all those things will increase. Christian Klepp  01:07 When done the right way and leveraging the right approach and technology, you can classify B2B content into actionable insights and find the most similar content across the open web. So how can this be done the right way, and what role do B2B Marketers play? Welcome to this episode of the B2B Marketers in the Mission podcast, and I’m your host, Christian Klepp. Today, I’ll be talking to Brendan Norman about this. He’s the Co-Founder and CEO of Classify, a software that organizes the world’s digital content, making a privacy, safe, searchable and monetizable. Tune in to find out more about what this B2B Marketers Mission is, and off we go. I’m gonna say Mr. Brendan Norman, welcome to the show. Brendan Norman – Classify  01:49 Thanks for having me, Christian. Christian Klepp  01:51 Great to have you on. I’m really looking for this conversation because, man, like you know, in our previous discussion, besides talking about snow and bad weather, we did have, we did have we did have some interesting discussions around, I’m going to say, AI machine learning, and how that all has some kind of like strong correlation to content. So let’s just dive in. I’m going to start with the first question here. So you’re on a mission to help publishers increase monetization potential and advertisers target the most relevant, curated inventory. So for this conversation, I’m going to focus on the following topic, and we can unpack it from there. So how B2B brands can optimize their own content. And you know, let’s be honest. Brendan, who the heck doesn’t want to do that, right? So your company classify, if I remember correctly. It’s a software that organizes the world’s digital content, making it privacy, safe, searchable and monetizable. So here’s the two-pronged question I’m happy to repeat. So first one is, walk us through how your software does that and B, how does this approach benefit? B2B companies looking to optimize their own content? Brendan Norman – Classify  03:01 Historically, how a lot of content gets categorized, classified, organized, it’s fairly unsophisticated, and it’s been fairly unsophisticated for a long time, just because, you know, the technology is difficult to do, and we haven’t really had the foundational ability to understand it in a way like a human understands it until fairly recently, and do it at Deep scale. So good analogy for this question is like, if you were having a we were having a conversation just a minute ago about the snow, you know, happening in Canada, and how cold it was and how much snow you got, and, you know, also around the fact that, like you had to shovel your driveway, you have a snow blower you were putting the snow. There’s a lot of different nuance to that conversation. I as a human, and most humans, are able to interpret all of that nuance and kind of positively negatively, understand that there’s a snow blower involved in that snow blower was used to remove the snow historically that conversation, you know, if it was just a blob of text, or if it were a web page, the the basic technology to understand it would have reduced it down to a category like snow or maybe winter, and that’s it, and that’s all the targeting that would have happened to that page. So our conversation, you know, gets transcribed. It gets put on a blog, or it gets put on a news site. The only thing that a machine could understand about it was, you know, snow and then potentially a keyword, tagged snow blower. And that’s all so we took a very different one. One of the reasons why you know that that makes it challenging for advertisers and also for publishers. If you’re the publisher of that content, you’re not able to help advertisers really understand the nuance to like, what are we talking about here? Because maybe an advertiser wants to sell snow blowers for that specific site. Maybe they’re looking to sell ski and since we were talking about removing snow from a driveway, probably not the best application to go sell skis on. What is helpful is to deeply understand all the nuance to like we were talking about a driveway. We were talking about removing snow from that driveway. So we invented, you know, a much better, more sophisticated way to scrape content, classify it according to all of the different, you know, nuances semantic understanding much more like a human would, and then embed all of those different, you know, semantic understandings into, you know, this, this, this file, and then we organize that in a way that makes it searchable and kind of understands all the relationships very quickly. And what that does is it helps advertisers, like if you know, I’m Honda selling snow blowers, which they make, arguably the best snow blower in the market, if they’re looking to reach people that are talking about snow removal from the driveway, they can very quickly see the list of all the different URLs across the internet, and they can build, you know, a deal ID, or they can build a targeting, contextual targeting segment to specifically pinpoint those very specific web pages. And that’s kind of how the technology works, and then also, also why it’s relevant to advertisers. Christian Klepp  06:21 Thanks so much for sharing that Brendan that definitely helps us give, you know, some perspective into, like, what your software does. And you know, just, I’m asking you this from, from somebody who probably has learned to write one or two lines of code, and that’s as far as my dev skills go. But like, how, how is your software different from like GEO (Generative Engine Optimization), or is there some kind of overlap? Brendan Norman – Classify  06:46 It’s fairly complementary. I mean, the problem that GEO, you know, is trying to solve, and we’ve got good friends, advisors, you know, like at Blue Fish AI and like, a really cool company, Andre, I worked with him at live rail. He was the co-founder back then, before we got acquired by Facebook, you know. And I think that the problem that they’re trying to solve is going back to that it was just stay on Honda snowblowers. They’re trying to help Honda understand how they’re represented inside of, inside of an LLM or inside of a chat bot. And what they also do is they help these companies restructure their pages for, you know, better representation inside of the other end of like a chatGPT or a cloud answer. So it is kind of SEO (Search Engine Optimization), but for the generative world where we sit on is kind of on a different side of that. It’s very complimentary, though, and we’re deeply understanding content at scale, and that’s helping, you know, the advertiser understand where to position their ad. We’re also just, you know, very quickly, moving into this new space of, traditionally, advertising technology is focused on a human going to a web page, reading that content, reading the article, watching a video, you know, whatever that content looks like, and then helping the right advertisers show up in a contextually relevant way, so that the human will click on that ad, and they’ll go to another web page, they’ll buy the thing, whatever somebody wants to sell. A very recent development, so back up a year or so, you know, chatGPT Claude when they’re out and their agents and their bots are scraping like going out to the web and they’re retrieving information. They’re doing it to train their models to make their models better at answering questions. But now, you know, fast forward to today. They’re actually spending more time just going to content and then using that content to answer a specific question. So like, what’s the best recipe for, you know, creating soft shell craps. It’ll query a couple different web pages. It’ll find that, it’ll retrieve that information and bring it back that that is not being monetized today. And there’s a really interesting thing that we’re, you know, we’re starting to work on, which is monetizing the attention of an agent. And, you know, it’s, there’s a lot to figure out, but it’s kind of like the early days of a web browser, and like early days of search, when humans would go, you know, to a search engine, they would pop in some keywords, or, like, right out of search, and then, you know, Google would look at their entire index of the web, which was an algorithm that was weighted based on the number of different contextual relevancy plus the number of connections between web pages. So a web page that I might have published in geocities.com that nobody else would link to, Christian Klepp  09:50 wow, GeoCities like… Brendan Norman – Classify  09:54 Throwing way back remember the days of like writing like HTML and you know, creating that, you know, looping in some type of image because nobody else had linked to that, like personalized page that you built, it would never get shown up. And, you know, the top 20 or 30 or probably even couple 1000, or maybe even 100,000 search results. So their algorithm was about contextual relevancy, plus the number of links that other pages that had to your page. And then they started to include advertising in that. So early days of ads in search were literally anything, you know, it’s any advertiser that wanted to advertise to you, and they were just kind of choosing the highest price, trying to figure out, you know, how do we make money? And then it evolved into much more contextually relevant ads and sponsored post or sponsored advertisements. So now you know, if you’re searching for, like, what’s the best, you know, LLM or chat bot, you’re probably going to see a sponsored ad from, you know, Claude and Perplexity and chatGPT. Now you’re also going to see the search results underneath those. What’s changing about that kind of rapidly is how we’re influencing because humans are spending less time going there and doing that, and also within Google, Gemini is also surfacing some AI summary quickly and kind of superseding that, creating a chatGPT experience inside of Google, which is a brilliant way to do it also. But a lot of human interaction with the web now is humans going to chatGPT going to cloud asking questions and kind of treating it like we used to treat search back in the day. So influencing that, influencing that agent, going out to the web and sitting in between. That is another really interesting way that you can help an advertiser tell that story, not necessarily to a human but to the agent who’s retrieving the information and then bringing it back to the human, Christian Klepp  11:56 Right, right, right? And if we’re talking about content, it’s, you know, doing it in such a way that the content shows up in the AI search. Brendan Norman – Classify  12:04 Exactly. Christian Klepp  12:05 Because everybody, everybody’s got those now, right, like Google or Bing, or whatever, they’ve got the, they’ve got the AI summary at the at the very top of the page, right when you, when you, when you key in something. Brendan Norman – Classify  12:17 Yeah. Christian Klepp  12:18 Okay, fantastic. I’m gonna move us on to the next question about because we’re on the topic of optimizing content. So what are some of the key pitfalls that like B2B Marketers and their content teams? What should they be mindful of, and what should they be doing instead? Brendan Norman – Classify  12:34 That would be actually a better question for some of the GEO companies and something like more SEO focused companies about how to specifically optimize like your content. It’s a great question. I haven’t spent as much time, you know, deeply thinking through that. And the problem that we’re trying to solve is more of, you know, at scale, what is the semantic understanding of like, how somebody has built their page and or construct the video, as opposed to advising them on what they should do? You know, to think about it in a way that’s either more engaging. I would pivot that question more to the Geo and SEO focused folks, yeah, but super high level. I mean realizing that now web has two primary users of traffic. There’s humans who are bouncing or reading a, you know, web page or watching a video. But there’s also agents. And now the scale is like, changing very, very quickly. So you know, in the next year, two years, everybody will have lots of agents, kind of doing things on the back end for them. And, you know, we believe that, you know, in the next what, 6,12,18,24 months, Agent traffic will surpass human traffic on the web. So realizing that there’s these kind of two layers that one, humans see a web page and nice pretty pictures, and, you know, they see the layout great, but also having a web page that’s optimized in HTML, markdown, JSON, in ways that agents consume that, and then also knowing the different types of agents. So the cool thing that we’re building right now, in addition to this content graph of all the content, which is effectively like a understanding all the context between the content. It’s a mouthful, an agent graph that helps to inform this is an agent coming to my site. So in a lot of ways, it’s very similar to the folks who over the last decade or so, have built these identity graphs or audience graphs, and they know that like you, Christian versus me, Brendan, they’ve got some profiling on us. They understand our search history, our retargeting, our purchase intent, a lot of things that they’re appending to like you as a specific profile or an IP address. The rapid evolution of all this is mapping out the land. Landscape of different agents, where they come from, and then the personalization of these agents, and basically applying a lot of the similar logic that we’ve used for identity graphs and for audience graphs towards agents to help understand, how do you modify the content on the back end that humans never see, so that when they’re retrieving information, interacting with the content they’re doing it, you’re presenting in a really thoughtful way that drives like the answers and the results that you want to Christian Klepp  15:33 right, right? No, absolutely, absolutely. And in our previous conversation, you talked a little bit about contextual versus audience targeting. So and I mean, I’ve asked you this back then, but do you think one is better than the other, or do you think that they can work together? Brendan Norman – Classify  15:50 They should absolutely work together. Christian Klepp  15:52 And why? Brendan Norman – Classify  15:54 The reason, the reason is, you know, knowing who you are is a very important piece to the puzzle. Like, and if you even take a step back, like, what’s the whole point of advertising? Like, the whole point of advertising is storytelling, so that a brand or a service or a company can help market their brand service to the right person they’re trying to sell them something. The cool thing about the internet is we all now have this, you know, basic shared awareness that, like, there are certain things that are paid for on the internet, certain types of content that are gated. I might buy a subscription to The Economist, you know, I pay Claude a certain amount of money, a lot to be able to use it, you know, a lot and chatGPT, and then a lot of the web is free. Facebook is free, Tiktok is free, Instagram is free, LinkedIn is free. But the economics, it’s very expensive to run these businesses, so they have to, you know, support it through advertising. Ideally, you know, there’s a couple of ways to think about it, and there’s one camp of people on the internet who think that advertising is a necessary evil or a last resort, you know, we just cram it in there and make some money. There’s another camper of folks who actually think that it can be additive to the experience. And one of the reasons why, you know, it’s kind of a meme, and you always hear people talking about, you know, I didn’t need this thing, but I saw an ad for it on Instagram, and just had to buy it because it was really cool. The reason why that exists is that their advertising is phenomenal, and the targeting and optimization is phenomenal. And why it’s phenomenal on the back end is it knows a lot about you know me, who I am, what I’m interested in, based on my history, what I’ve been engaging with, where I’m spending time, you know, what I’m looking at, but it also knows specifically when I’m looking at that thing, you know, it might have a framework of saying, Brendan, really, you know, likes these types of skis, you know, he’s interested in, You know, a couple other, couple other interesting products, but the best time to serve each one of those products might be different, and it’s different depending on what I’m looking at, what I’m thinking about in that exact moment. And to kind of align these, these different graphs, graphs of intent, contextual understanding, and then audience, you know, the best time to serve me an ad for a new pair of skis is when I’m reading an article about skiing or something about the mountains. You know, it’s not necessarily when I’m reading about the Warriors, because I’m not really thinking about skiing when I’m reading about basketball. So to your point, the most effective ads are when you’re combining those two sets. It’s great for the advertiser, because I’m much more likely to click on it and go check out the skis. It’s also giving me a better experience, because it feels more native to the overall content that I’m reading. And that’s why it’s so important. It shouldn’t be an afterthought or a necessary evil or a last resort. It should be something that is intentionally thought about the entire design, because it can, it can actually be a cool experience. Christian Klepp  19:06 Absolutely, absolutely. I mean, you know, you’re talking to somebody that started his career in the in the advertising industry, so, yeah, I’ve heard that one before, and what you’ve been describing in the past couple of minutes sounds to me a little bit like time of day marketing too, right? Because you’re you know, are you the had a guest on, like, a year ago who talked about this? Right? Is, is Brendan, the same guy at eight in the morning and one one in the afternoon and seven in the evening? Right? There’s different different times of the day, different mindset, different motivation, different reason for being on your device or looking at, looking at specific type of content, right? But it is interesting, right? And it’s interesting and sometimes a little bit scary, how, um, how quickly the algorithm picks, picks this stuff up, right? Like, for example, last year, I was researching a lot on Japan, because we went there, right? Family trip and whatnot. And. And that’s what I kept seeing on Instagram, right? Like, because I was looking up specific temples and whatnot and and today I got another push. Like, would you like to invest in a temple that’s an on island in the Sea of Japan, right? Brendan Norman – Classify  20:12 Like, sorry, did you invest? Christian Klepp  20:17 No, I did not. But it was just, it was just funny that I got that ad right, like, it’s, like, Okay, interesting, but like, it’s so like it not, was not on my radar at all, right, Brendan Norman – Classify  20:29 Yeah, Christian Klepp  20:29 Okay, great. From your experience, and you talked a little bit about it now in the past couple of minutes, but like, from your experience, how can leveraging AI agents improve efficiency and save marketing leaders time? Brendan Norman – Classify  20:47 Ooh, there’s a couple different ways to think about that. So you know, part of it is this new agentic framework for how existing tools, you know, advertising and marketing tools, will communicate with each other today. You know, it’s fairly complex. You know, if I wanted to go build a contextual targeting segment to help one of our brands that we work with find the right contextual or inventory to target contextually, I would have to work with them. We build a targeting segment. We would upload that into our one of our SSPs, we would build a deal ID, you know, they would connect it back. And there’s a lot of different pieces that happen along the way. And each one of those pieces you have to go to, you know, a UI, I’ve got to go to a dashboard, I’ve got to push that thing in. Some of it happens through an API, but a lot of it happens like going to a whole bunch of different web pages to make sure this stuff all works. So stuff all works. What’s cool about agents? And I’ll unpack this, and then I’ll go to the more of the consumer focus side too. But what’s really cool about agents using, you know, things like the ACP framework from the Agentic Advertising Org., the ARTF (Agentic Real Time Framework) from IAB Tech Lab is they’re kind of built on some of the existing frameworks that allow humans to use natural language to communicate between these different systems. So there’s still the back end pipes of API pushing data or pulling data from one system to another. But on top of that is more of an agentic framework that allows, you know, a human just to use some prompting, like in chatGPT, to make a request, you know, that talks to a back end system. So that’s one part of the agentic framework for like, you know, how to think about this through the lens of advertising and marketing. And then the other side is, you know, more of the consumer focused. There are so many interesting and very quickly growing tools you know, that you can start to plug in, into Cloud, into Cloud code, and to building things that just rapidly accelerate development of different products and your ability to analyze data quickly. I think in the next, you know, 6 to 12 months, we’re going to have a totally different landscape for how people are buying like trading media also, you know, one more final thought about all of this is that a lot of the sophisticated tooling and pipes that we have are only accessible towards the largest advertisers today. And I think that you’ll pretty quickly see a democratization of the ability for anybody to just buy programmatic ads, whether you’ve got a $20 a month budget or a $20 million a month budget. Now, the ability to similar types of tools to access the right content across the web will start to be available towards a lot more folks outside of the existing, you know, kind of ad tech ecosystem. Christian Klepp  23:55 And I might be stating the obvious when I say this here, but that’s a good thing, isn’t it, because, I mean, I, again, I came out of this industry, and I know that, like, you know, if you wanted to advertise in the New York Times, for example, right? Like, how expensive that would be, or, or anything that was print, right? And then they migrated all that to digital, and then it still wasn’t, it still wasn’t affordable. It was, it was cheaper than print, but still not like, exactly like, you know, yeah, I wonder, wonder if they’ll be worth the investment or not. And then now you have this, this push towards the democratization of all of this through AI and machine learning and, and I do think that you know, for all the the scare mongering that you know people are doing now with, with, oh, you know, all this stuff around AI, I do think that that part certainly will be advantageous to to B2B companies and to marketing in general. Brendan Norman – Classify  24:49 Great. I mean, yeah, optimistically, I think I’m excited about the entire landscape changing because it does a couple things. It allows for much more contextually relevant ads. I know right now there’s only, let’s call it to the magnitude of like, 1000s, 10s of 1000s, maybe hundreds of 1000s, of campaigns and or brands that are able to use these pipes to reach the largest publishers. And all of a sudden you expand that out. You know, I think between meta and Google, they each have somewhere between 15 to 20 million unique advertisers on their platforms, and what that means is, you get really hyper specific ads. And it also means that, like, I might get a local ad for my hometown here for some restaurant that’s launching a promotion that I might only get here, and I might only get to your point, maybe not in the morning, but I’ll get in the evening. There’s a lot of different data sets around my identity, you know, the psychographic profile, contextual understanding of what I’m reading at that exact moment. And what it does a lot of things. It helps smaller brands get more traction, get more visibility. It also just helps improve the publisher experience, and like publishers, make more money. And then the user who’s consuming that content, reading the web page, watching a video, also has just a better experience. And then the other layer of that will continue to just go on, this narrative of agentic, tension, but the agents who are reading that content, watching that video for an end user. On the other side, are also able to interact with advertising content that’s very contextually relevant to the content that they’re consuming again, and it’s good for the storytelling of the advertiser and good for monetization of that publisher too. Christian Klepp  26:38 Absolutely, absolutely. Okay. So how can high fidelity curation? This is the next question, right? How can high fidelity curation make B2B companies more sustainable? And if you can just provide an example, Brendan Norman – Classify  26:54 Curations like, it’s such an interesting term, but you know, effectively, it’s just, it’s helping to use the word and the definition, the definition in the word, curate the right inventory to run an ad campaign on, and curate the right inventory and audiences. So it’s a really important part of the business. I think it involves a couple things. It involves front end targeting, of knowing who’s the back to that question, who’s the audience, and then what’s the right content, and then it also involves a lot of ongoing optimization. And I’ll say that there are some some interesting companies that that are really good at curation, who are building out the right automatic tools to think about more real time optimization, and it’s something that the really big social media companies do very well, like they’re constantly looking at lots and lots of signals when they’re running a campaign, and they’re looking at inventory and stitching together based on the signals that they’re acquiring around. Why certain campaigns do well, to your point, you know, when we’re testing that, selling that pair of skis to Christian, we’re testing a lot of things. We’re testing what he’s reading, you know, we’re testing maybe time of day. We’re testing, you know, where he is. There’s a lot of different elements on the back end that they will ingest and understand and then refeed into that targeting and optimization algorithm. And I think that that is one of the cool things that AI to use, like the air quotes, AI will help enable the processing of a lot of this data to just be a lot faster, be a lot more cost effective, and a lot of these systems that you know previously have been not accessible to the ad tech ecosystem, just because we we operate at such a crazy scale of 10s, hundreds of billions of requests and impressions and transactions that happen every single day. It’s very cost expensive if you’re processing all of that data and all these different signals, with the advancement of how the model cost is getting a lot less expensive, very quickly, not just from an LLM perspective, but then the foundational layers and the infrastructure layers, like we’re doing contextual intelligence as an infrastructure layer. There are inference layers that all kind of sit underneath the LLM and help inform an LLM understanding of that content. As those costs start to decrease, you’ll start to see a lot better performance from curation, just because, you know, it’s not as cost prohibitive, and we’ll be able to find that balance in terms of economics. Christian Klepp  29:45 Yeah, yeah, you hit the nail on the head there. Because, you know, I was just writing this down. You said faster, more cost effective and in my head, and you said it, it’s like, and at scale, like, you can scale this stuff faster, like, when I when I think back, like, years ago, when we, when we launched an ad campaign, and, you know, just the amount of effort, like, for the print and then the cost into, you know, the media placements and all of that and and just alone for like, one city, just just the amount of investment that was involved in all of that, right? Just think, thinking about that. It’s like, gosh, and then now you can scale all of that, like, even faster, because it’s because it’s digital, right? So it’s just such an incredible evolution. Like, I’m getting just as excited as you are man, I’m like, for this next question. Brendan, I’m not sure if you’re the type that likes to do this, but I need you to look into the crystal ball for a second here, right? Because we’re looking at, like, stuff that is, you know, the events that are yet to come, if I’m gonna that, make it sound a little bit suspenseful, but, um, the future of digital advertising, like, how do you think that could become less fragmented and more optimized with everything that we’ve talked about in this conversation. Brendan Norman – Classify  31:04 Yeah, I caution against, like, having any, any specific predictions, and more of, like, a framework for, I mean, for me, at least, yeah, more of a framework for how I think overall, jobs will change. I think that people will have to spend a lot less time doing a lot of the manual, rote tasks that they’re doing today. And, you know, kind of in parallel with what we’re seeing in terms of vibe coding and people’s ability to build product really quickly, design new web pages really quickly. Like, get ship things out quickly. I think a lot of the the infrastructure layer tools, or just call them like, you know, the like, chatGPT style, cloud-based tools, LLMs, we’ll see a lot deeper integration into existing advertising product. And what that does is it helps democratize the whole ecosystem. So I think it frees up people’s time to not have to do a lot of the basic administrative, reporting, manual, campaign, optimization type stuff, and it will help service a lot better insights. Ultimately, I think the industry grows, and I think it scales even faster. And, you know, cautiously, optimistically, I think that we, we will have back to building on the curation piece, and, you know, the advertiser, outcomes piece, publisher, monetization piece, user experience piece, I think that all those things will increase, and I I’m hopeful that with the integration of just better technology, embedding AI into a lot of these systems, it’s going to help steer us towards having better experiences across any type of Publisher content. I think that the advertisers will see better outcomes. I think that the people that are in this industry will get to think more creatively about how they’re, you know, building better creative storytelling, better reaching the right people with those stories. And my hope is that it just continues to expedite and grow the overall industry. Brendan Norman – Classify  33:17 That will be my hope as well. All right, get up on your soapbox here for a little bit. What is a status quo in your area of expertise? So anything that we’ve talked about now in this conversation, what’s the status quo that you passionately disagree with and why? Oh, you must have a ton. Brendan Norman – Classify  33:44 I definitely do. I mean, you know, Christian Klepp  33:48 just name one, just one, Brendan Norman – Classify  33:50 Like in any industry, you know, there’s always, there’s always the early adopters, you know, there’s always the kind of like the middle stack, you know, there’s always, like, the laggards. There’s definitely, you know, a smaller, but growing quickly, minority of folks who are really leaning into, you know, I’ll just call it AI, and then the agentic web, and there’s a lot of discussion right now in ad tech around like, what that means? I’m still hearing that. There’s a lot of skeptics who are kind of making fun of it, or, you know, trash talking about different protocols. Fine, like those are the folks that are absolutely going to get left behind. And I think a lot of those folks on the soapbox in the next 6 to 12 months will look back at, you know what they said, and we’ll all kind of say that didn’t age well, and you were not building this stuff. You weren’t fingers on keyboard or hands on keyboard. Vibe marketing, vibe targeting, building stuff like shipping new product and testing and iterating. What I what I don’t think, is that the really big platforms are just able to be super nimble and adapt to a lot of these new frameworks quickly, totally like the pipes will continue to stay there. I think that there will be startups that are more nimble, that can build and ship things, you know, proof of concepts, prototypes, get things out, learn from them, fail, iterate, and then start to scale meaningful businesses without having to rely on a lot of the existing infrastructure that exists today. Do I think the trade desk is, you know, going anywhere? No, do I think that they will, like, continue to be a valuable piece in this ecosystem, absolutely. And I think that they will ship things. I think that they’ll enable the industry like to build on top of of the pipes that they’ve already built. And at the same time, I think a lot of that rapid advancement will come from startups who are kind of proving that, like they don’t necessarily need the existing pipes and channels to be able to at the end of the day, you know, this whole ecosystem is about helping an advertiser surface their ad against the right content for a human or for an agent. And there have been a lot of folks kind of sitting in the middle for that space for a long time. One of my favorite stats, soapboxy stats, is that if an advertiser puts $1 in to the open web with a programmatic web, 35 cents comes out to a publisher, so 65 cents is being taken by some combination of middlemen, you know, who are collecting a margin for, you know, different services, also some version of fraud. There’s a lot of things that happen in between that and what I’m again, cautiously optimistic about, you know, like the big picture, AI, of facilitating, is the ability to reduce that margin so that, you know, advertiser puts $1 in. A lot more of that dollar comes out towards the publisher, I think big social media, you know, it’s around 70 cents comes out. So they take, you know, somewhere between 25 to 30 cents, which is kind of the value exchange of providing the services, all the targeting, all the technology that goes into supporting that, you know, as a more fair exchange. So I think what a lot of the folks on more of the startup on more of like the front end of the frontier tech in the space we’re excited about is getting to reduce a lot of that inefficiency and a lot of that margin in the middle, and helping more of that dollar show up towards the publisher where it should. Christian Klepp  37:34 Boom and there you have it. Man Brendan, this has been awesome conversation, so thanks again for your time, please. Quick intro to yourself and how folks out there can get in touch with you. Brendan Norman – Classify  37:45 Yeah. Brendan Norman, CEO co-founder at Classify, please. You know, hit me up on LinkedIn or shoot me an email. Check out our website, which is, you know, www.tryclassify.com. I’m happy to connect. You know, if you have questions about advertising from a publisher side, from an advertiser side. Love to chat about it. Christian Klepp  38:06 Sounds good. Sounds good once again. Brendan, thanks for your time. Take care, stay safe and talk to you soon. Brendan Norman – Classify  38:13 Cool. Thanks, Christian. Christian Klepp  38:14 All right. Bye for now.

In September 2016, Islam Karimov–the first president of a post-Soviet Uzbekistan–died, at age 78. His death ended an oppressive dictatorship that had governed the Central Asian country for decades, which led to corruption, environmental damage, and political repression. Karimov was replaced with Shavkat Mirziyoyev, who instituted a tentative program of reforms. These years are the subject of Joanna Lillis's book, Silk Mirage: Through the Looking Glass in Uzbekistan (Bloomsbury, 2025). Lillis tells the stories of both the Karimov and Mirziryoyev regimes, based on many conversations with activists, journalists, and other opposition leaders in the country. Joanna Lillis is a Kazakhstan-based journalist and author writing about Central Asia who has lived and worked in the region since 2001, in Uzbekistan (2001-2005) and Kazakhstan (since 2005). Her reporting has featured in outlets including The Economist, the Guardian, the Independent, the Eurasianet website and Foreign Policy and POLITICO magazines. Prior to moving to Central Asia, she lived in Russia and worked for BBC Monitoring, the BBC World Service's global media tracking service. She is also the author of Dark Shadows: Inside the Secret World of Kazakhstan (Bloomsbury: 2019). You can find more reviews, excerpts, interviews, and essays at The Asian Review of Books, including its review of Silk Mirage. Follow on Twitter at @BookReviewsAsia. Nicholas Gordon is an editor for a global magazine, and a reviewer for the Asian Review of Books. He can be found on Twitter at@nickrigordon. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/political-science

Economist science correspondent Matt Kaplan discusses his new book, “I Told You So!,” and the scientists who were ridiculed, sidelined or punished for advancing ideas that later proved correct.

Welcome to another episode of TBCY.Today, we are joined by Bronwyn Williams — Futurist, Economist, Trend Analyst at Flux Trends, and Author.In this engaging conversation with host Ashutosh Garg, Bronwyn explores the science and art behind “futurenomics,” examines the real impact of AI on the modern workforce, and shares powerful lessons from organizations that failed to adapt.The tension between short-term wins and long-term consequencesHow AI is reshaping value, labor, and societyWhy Africa holds unique opportunities that many futurists overlookThe importance of agency and rejecting a deterministic view of the future

Trump's “Board of Peace” emerged from last year's ceasefire negotiations to govern Gaza after the war. But since then, the board has evolved into a motley group of countries that are willing to pay a billion dollars to join a body that has Donald Trump as its chairman for life. They also have mostly stopped talking about Gaza.Guest: Gregg Carlstom, Middle East Correspondent at The Economist. Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen.Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther. Hosted on Acast. See acast.com/privacy for more information.

Trump's “Board of Peace” emerged from last year's ceasefire negotiations to govern Gaza after the war. But since then, the board has evolved into a motley group of countries that are willing to pay a billion dollars to join a body that has Donald Trump as its chairman for life. They also have mostly stopped talking about Gaza.Guest: Gregg Carlstom, Middle East Correspondent at The Economist. Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen.Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther. Hosted on Acast. See acast.com/privacy for more information.

Trump's “Board of Peace” emerged from last year's ceasefire negotiations to govern Gaza after the war. But since then, the board has evolved into a motley group of countries that are willing to pay a billion dollars to join a body that has Donald Trump as its chairman for life. They also have mostly stopped talking about Gaza.Guest: Gregg Carlstom, Middle East Correspondent at The Economist. Want more What Next? Subscribe to Slate Plus to access ad-free listening to the whole What Next family and across all your favorite Slate podcasts. Subscribe today on Apple Podcasts by clicking “Try Free” at the top of our show page. Sign up now at slate.com/whatnextplus to get access wherever you listen.Podcast production by Elena Schwartz, Paige Osburn, Anna Phillips, Madeline Ducharme, and Rob Gunther. Hosted on Acast. See acast.com/privacy for more information.

After years of trade skepticism, India appears to be back in the deal-making business—signing new agreements, reviving stalled talks, and announcing ambitious frameworks with key bilateral partners. A few weeks ago, the European Union and India announced a mega-trade deal that was more than two decades in the works. And just days after this news broke, the White House announced that the United States had also reached an understanding with India on trade, an issue which had sapped relations between the two erstwhile partners over the past year.To help make sense of what's changed—and what hasn't—Milan is joined on this show this week by Mark Linscott. Mark is a nonresident senior fellow on India at the Atlantic Council and a Senior Advisor with The Asia Group. He previously served as the assistant US trade representative for South and Central Asian Affairs from 2016 to 2018. He has more than 30 years of experience working on trade and economic issues at the Commerce Department and USTR. It is my pleasure to welcome him to the show for the very first time.Milan and Mark discuss India's new external trade posture, the geopolitics and economics of the EU-India FTA, and the timing and substance of India's trade deal with the United States. Plus, the two discuss India's relative positioning vis-à-vis other Asian competitors and the possible roadblocks in the way of a larger U.S.-India accord.Episode notes:Ravi Dutta Mishra, “How India's US deal tariff advantage over Bangladesh vanished overnight,” Indian Express, February 10, 2026.Arvind Subramanian, “India may be about to become one of the world's most open economies,” The Economist, February 5, 2026.Michael Kugelman and Mark Linscott, “What to know about the US-India trade deal,” Atlantic Council “Dispatches” blog, February 2, 2026. “Can the U.S. Salvage Its Relationship with India? (with Lisa Curtis),” Grand Tamasha, February 4, 2026.Michael Kugelman and Mark Linscott, “The India–EU trade deal is worth watching, but not overhyping,” Atlantic Council “Dispatches” blog, January 27, 2026. 

Ярослав Макітра, політолог, експерт дослідницької компанії Соціополіс, на Radio NV про перемовини в Женеві, заяву Зеленського про підготовку до зустрічі з Путіним, розбіжності всередині української делегації, про які пише The Economist, а також про позицію представників США. Ведуча – Юлія Петрова

What is the impact of land reform on economic development? What are the implications of property law when a financial crisis hits? This episode offers a comprehensive look at how land has shaped socio-economic landscapes.Mike Bird is the Wall Street editor at The Economist and the author of the new book, The Land Trap: A New History of the World's Oldest Asset.Greg and Mike discuss the historical and contemporary importance of real estate as an asset class, its undervaluation in modern investment strategies, and its critical role in the financial systems. Their conversation explores the distinction between land and other assets, and how mortgage-backed securities have revolutionized real estate finance. Mike lays out the history of land financing from colonial North America to present-day reforms, touching on the influence of key historical figures and economic theories. *unSILOed Podcast is produced by University FM.*Episode Quotes:How land reform fueled economic growth41:29: These sort of moments of expropriation are really focused on land quite tightly. They do not spread over into sort of general expropriation attitudes. They can have seemingly really positive impacts. So lots of people credit land reform in Japan in particular with sort of establishing the basis of a democratic society, of massively accelerating the education boost in Japan. If you are a tenant farmer and you are given land yourself, you are able to actually invest in it. And you want to make the most of it because it is no longer the landlord taking it from you. The surplus you create is your own. Most of those people used the extra money they made to massively accelerate the education of their children. This generation of people in Japan becomes a more educated one, which fuels the economic development that happens, you know, 1950s, 1960s, 1970s. So the spillover effect from land reform is really quite large.ETF vs home ownership psychology50:15: I would say, I think half the answer here is behavioral and slightly irrational and social, and half of the answer is deeply rational and makes sense to any student of finance. The side that is irrational is home and land ownership has a reputation and a status that other asset ownership does not have. You have people who say they do not want to form a family until they can own a home. That is a fairly common sentiment in large parts of the world. Nobody says, I have got to own $300,000 in my S and P 500 ETF, or I am not starting a family. It is not a common thing. There is a sense of status security, middle class belonging that comes through owning a home, which makes it very unusual. And I think this digs into a deep historical thing about freedom from feudalism, from living under a landlord, from living, in sort of someone else's pocket.Why housing isn't diversified54:52: Obviously what you cannot buy unless you are buying an extremely well diversified REIT, for example, you cannot buy a US house, right? It has to be somewhere. You are plugging into the opportunities and rewards or punishment of a local economy, and so on, I am not enormously surprised at that. I think the thing that is unique in the US relative to the rest of the world is just how well you can do and have done historically investing in listed equities, investing in risk assets and getting the compounded returns relative to home ownership, which I think is massively to America's credit. This is not true in other large portions of the rest of the world.Show Links:Recommended Resources:Samuel AdamsHernando de SotoZamindarHenry GeorgeProgress and PovertyGeorgismLeasehold EstateDuke of WestminsterWolf LadejinskyCase–Shiller IndexGuest Profile:MikeBird.coProfile on The EconomistLinkedIn ProfileSocial Profile on XSocial Profile on BlueSkyGuest Work:The Land Trap: A New History of the World's Oldest Asset Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In this episode of WealthVest: The Weekly Bull& Bear, Drew and Tim interviewed Aditya Bhave, Senior US Economist at Bank of America. They discussed the drivers of the economy in 2026, including fiscal stimulus, monetary policy and AI. WealthVest – based in Bozeman, MT– is a financial services marketing and distribution firm specializing in fixed and fixed index annuities from many high-quality insurance companies. WealthVest provides the tools, resources, practice management support, and products that financial professionals need to provide their clients a predictable retirement that has their best interest in mind.Hosts: Drew Dokken, Tim PierottiAlbum Artwork: Matt LueckShow Editing and Production: Matt LueckDisclosure: The information covered and posted represents the views and opinions of the hosts and does not necessarily represent the views or opinions of WealthVest. The mere appearance of Content on the Site does not constitute an endorsement by WealthVest. The Content has been made available for informational and educational purposes only. WealthVest does not make any representation or warranties with respect to the accuracy, applicability, fitness, or completeness of the Content.WealthVest does not warrant the performance, effectiveness or applicability of any sites listed or linked to in any Content. The content is not intended to be a substitute for professional investing advice. Always seek the advice of your financial advisor or other qualified financial service provider with any questions you may have regarding your investment planning. Investment and investing involves risk, including possible loss of principal. Hosted on Acast. See acast.com/privacy for more information.

Nate Miles joins Jeremy Keil to discuss how the Allspring retirement research reveals trends of concern among retirees and the options they have to address them. Mike and Susan did what many couples do. They saved diligently. They crossed the $1 million mark before retirement. They felt prepared. But when it came time to make actual retirement decisions—when to claim Social Security, how to withdraw from their accounts, how to manage taxes—they realized something uncomfortable: They had spent decades saving… but very little time learning how to retire. This example speaks directly to what this year's Allspring Retirement Study uncovered. As Nate Miles shared on the “Retire Today” podcast, this wasn't a small or struggling population. Participants were 50+ with at least $200,000 in investable assets. A third of retirees surveyed had $1 million or more. Yet only six out of ten retirees said they feel financially secure. That gap between assets and confidence tells us something important: retirement success isn't just about how much you've accumulated. It's about how well you transition into distribution. The Social Security Mistake One of the most striking findings involved Social Security. Nate explained: “One third of our respondents claimed Social Security at 62 years old… because they believed the value or the benefit of waiting was not worth it. Yet they underestimated the value of waiting by 50%.” Many respondents assumed the benefit grew at 4% per year when delayed. In reality, for most people, it grows closer to 8% annually between full retirement age and 70. That misunderstanding alone can permanently reduce lifetime income. In the MAKE step of the 5 Step Retirement Master Plan, Social Security is foundational. For many retirees, it represents 30–40% of their guaranteed income. Optimizing that decision isn't optional—it's essential. And yet, education around it is surprisingly thin. As Nate pointed out, there are “560-something permutations” of Social Security claiming strategies. It's ubiquitous, but complicated. And too often, people default to the earliest date simply because it feels tangible. The Tax Blind Spot The second major theme of the study? Taxes. Only about 20% of retirees reported using a tax-efficient withdrawal strategy. Think about that. After decades of saving in multiple account types—traditional IRAs, Roth IRAs, brokerage accounts—most retirees are simply withdrawing from wherever feels convenient. Nate put it plainly: “Taxes matter for everyone, not just the high net worth crowd.” In the KEEP step of retirement planning, how you withdraw can meaningfully impact how long your money lasts. Choosing between Roth and traditional dollars. Managing capital gains. Coordinating withdrawals with Social Security timing. These aren't abstract academic exercises. They are practical levers that affect real income. Yet as Nate observed, most people spent 40 years having taxes withheld automatically from paychecks. They paid taxes—but they never actively managed them. Retirement flips that script completely. Now you must choose. The Psychological Shift No One Talks About Nate shared that many retirees are comfortable spending above their retirement number—until their account dips below it. The moment it falls beneath that original balance, panic sets in. Even if the plan accounts for drawdown. Even if it's sustainable. Even if it's expected. That's what I call the “accumulation paradox.” Economists assume you'll build your assets and gradually spend them down toward zero. Real people assume the number should stay intact forever. But retirement isn't about preserving a scoreboard. It's about funding a life. This is where the SPEND step meets the INVEST step. You saved to use the money. And yes, at some point, your balance may begin to decline. That's not failure. That's function. Advice Still Matters One of Nate's most memorable lines was this: “Monte Carlo gets 10,000 cracks at retirement. You and I get one.” We don't get multiple trial runs. We get one real-life retirement. That's why quality advice matters. The study suggests people with pensions are more likely to use annuities. People with advice are more likely to use tax strategies. And people who understand their income sources are more confident. Retirement is no longer just accumulation. It's design. And design requires intention. If you're within five years of retirement—or already there—ask yourself: Have I optimized my Social Security? Am I intentionally managing taxes? Do I have a clear income floor? Am I emotionally prepared to draw down assets? Because as this year's research shows, even million-dollar portfolios can feel uncertain without a plan. Retirement isn't about guessing well. It's about designing well. Don't forget to leave a rating for the “Retire Today” podcast if you've been enjoying these episodes! Subscribe to Retire Today to get new episodes every Wednesday. Apple Podcasts: https://podcasts.apple.com/us/podcast/retire-today/id1488769337  Spotify Podcasts: https://bit.ly/RetireTodaySpotify About the Author: Jeremy Keil, CFP®, CFA is a retirement financial advisor with Keil Financial Partners, author of Retire Today: Create Your Retirement Income Plan in 5 Simple Steps, and host of the Retirement Today blog and podcast, as well as the Mr. Retirement YouTube channel. Jeremy is a contributor to Kiplinger and is frequently cited in publications like the Wall Street Journal and New York Times. Additional Links: Buy Jeremy's book – Retire Today: Create Your Retirement Master Plan in 5 Simple Steps Allspring 2026 Retirement Study: By Default or By Design? Nate Miles, Allspring Global Investments Connect With Jeremy Keil: Keil Financial Partners LinkedIn: Jeremy Keil Facebook: Jeremy Keil LinkedIn: Keil Financial Partners YouTube: Mr. Retirement Book an Intro Call with Jeremy's Team Media Disclosures: Disclosures This media is provided for informational and educational purposes only and does not consider the investment objectives, financial situation, or particular needs of any consumer. Nothing in this program should be construed as investment, legal, or tax advice, nor as a recommendation to buy, sell, or hold any security or to adopt any investment strategy. The views and opinions expressed are those of the host and any guest, current as of the date of recording, and may change without notice as market, political or economic conditions evolve. All investments involve risk, including the possible loss of principal. Past performance is no guarantee of future results. Legal & Tax Disclosure Consumers should consult their own qualified attorney, CPA, or other professional advisor regarding their specific legal and tax situations. Advisor Disclosures Alongside, LLC, doing business as Keil Financial Partners, is an SEC-registered investment adviser. Registration does not imply a certain level of skill or expertise. Advisory services are delivered through the Alongside, LLC platform. Keil Financial Partners is independent, not owned or operated by Alongside, LLC. Additional information about Alongside, LLC – including its services, fees and any material conflicts of interest – can be found at https://adviserinfo.sec.gov/firm/summary/333587 or by requesting Form ADV Part 2A. The content of this media should not be reproduced or redistributed without the firm’s written consent. Any trademarks or service marks mentioned belong to their respective owners and are used for identification purposes only. Additional Important Disclosures

The Russian army invading Ukraine today is very different to the one which started the conflict. How are things going for Putin's military – and how can Ukraine and Europe push back against them? Shashank Joshi, defence editor at The Economist, joins Gavin Esler to discuss.  www.patreon.com/bunkercast  Follow us on BlueSky: https://bsky.app/profile/bunkerpod.bsky.social  • Advertisers! Want to reach smart, engaged, influential people with money to spend? (Yes, they do exist). Some 3.5 MILLION people download and watch our podcasts every month – and they love our shows. Why not get YOUR brand in front of our influential listeners with podcast advertising? Contact ads@podmasters.co.uk to find out more Written and presented by Gavin Esler. Audio editor: Simon Williams. Managing editor: Jacob Jarvis. Design by James Parrett. Music by Kenny Dickinson. Group Editor: Andrew Harrison. THE BUNKER is a Podmasters Production. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Stephen Grootes speaks to Sifiso Skenjana, Economist and Managing Director at ESG Analytics, about South Africa’s latest unemployment figures, which show the official rate has dropped but remains deeply entrenched in crisis levels. Recent data highlights both areas of improvement and persistent challenges in the labour market, with high levels of joblessness among youth and structural unemployment continuing to burden the economy. In other interviews, Siyabonga Madlala, Chairman of the South African Farmers Development Association, talks about the sweeping regulatory reforms that hand the embattled sugar industry greater control over how it manages imports and stabilises the domestic market. The Money Show is a podcast hosted by well-known journalist and radio presenter, Stephen Grootes. He explores the latest economic trends, business developments, investment opportunities, and personal finance strategies. Each episode features engaging conversations with top newsmakers, industry experts, financial advisors, entrepreneurs, and politicians, offering you thought-provoking insights to navigate the ever-changing financial landscape.    Thank you for listening to a podcast from The Money Show Listen live Primedia+ weekdays from 18:00 and 20:00 (SA Time) to The Money Show with Stephen Grootes broadcast on 702 https://buff.ly/gk3y0Kj and CapeTalk https://buff.ly/NnFM3Nk For more from the show, go to https://buff.ly/7QpH0jY or find all the catch-up podcasts here https://buff.ly/PlhvUVe Subscribe to The Money Show Daily Newsletter and the Weekly Business Wrap here https://buff.ly/v5mfetc The Money Show is brought to you by Absa     Follow us on social media   702 on Facebook: https://www.facebook.com/TalkRadio702 702 on TikTok: https://www.tiktok.com/@talkradio702 702 on Instagram: https://www.instagram.com/talkradio702/ 702 on X: https://x.com/CapeTalk 702 on YouTube: https://www.youtube.com/@radio702   CapeTalk on Facebook: https://www.facebook.com/CapeTalk CapeTalk on TikTok: https://www.tiktok.com/@capetalk CapeTalk on Instagram: https://www.instagram.com/ CapeTalk on X: https://x.com/Radio702 See omnystudio.com/listener for privacy information.

Low milk prices are a grim reality for dairy producers in the near term, with growing trade and federal action serving as remedies to get farmers through tough times, NMPF economists said in a Dairy Defined Podcast.“There really is no quick fix to get back into balance,” said Will Loux, Senior Vice President for Global Economic Affairs and the head of the joint economics team for NMPF and the U.S. Dairy Export Council. “I do think there are real ways that, from the Whole Milk to Healthy Kids Act, to the National Milk Exports and Trade program, to opportunities to beef up Dairy Revenue Protection, to making sure folks are utilizing that program or Dairy Margin Coverage. There are ways to help, I think, mitigate the pain that we see dairy farmers feeling today from a policy perspective.” Loux is joined in the podcast by Stephen Cain, Vice President for Economic Policy and Market Analysis.

Guest host Robin Gill talks to David Williams, Economist with the B.C. Business Council Learn more about your ad choices. Visit megaphone.fm/adchoices

This Topic Tuesday News Bulletin 5 shares African News, Political News, Economic Business News and Celebrity News. You will hear snippets of voices from Tik Tokers on the state of world order African getting on board with A.I. and future forecast for our hoods. Hear Malcolm X, TikTokers on China's business model, TikTokers on Burkina Faso work, Tik Tokers on Capitalist System, and hear from Marketers, Economist, Historians, News Reporters, and hear how the Americans are in the Debt Trap. Hear the Celebrity status being trapped in another Slave Model System and the failed Music Marketing Social Media. 

Our data journalists trawled through the vast email archive of Jeffrey Epstein, a dead sex offender. It is a revealing look at how and with whom he communicated. As interest grows in banning young people's use of social media, we argue there are better ways to mitigate harms. And a blindfolded introduction to “blouge”, a new, more climate-resilient wine variety.Guests and host:Rosie Blau, host of “The Intelligence”Dan Rosenheck, data editorTom Wainwright, media editorTom Standage, deputy editor of The EconomistTopics covered: The Epstein filesSocial-media bans“Blouge” wineGet a world of insights by subscribing to Economist Podcasts+. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account. Hosted on Acast. See acast.com/privacy for more information.

Our data journalists trawled through the vast email archive of Jeffrey Epstein, a dead sex offender. It is a revealing look at how and with whom he communicated. As interest grows in banning young people's use of social media, we argue there are better ways to mitigate harms. And a blindfolded introduction to “blouge”, a new, more climate-resilient wine variety.Guests and host:Rosie Blau, host of “The Intelligence”Dan Rosenheck, data editorTom Wainwright, media editorTom Standage, deputy editor of The EconomistTopics covered: The Epstein filesSocial-media bans“Blouge” wineGet a world of insights by subscribing to Economist Podcasts+. For more information about how to access Economist Podcasts+, please visit our FAQs page or watch our video explaining how to link your account. Hosted on Acast. See acast.com/privacy for more information.

China's antitrust regime has evolved rapidly over the past decade. What role does economic analysis play in the actual enforcement? Anora Wang and Kathleen Hu speak with Dr. Vanessa Zhang of Compass Lexecon about the growing role of economic analysis in Chinese competition law, drawing on her experience advising China's antitrust authority and serving as a testifying expert in high-stakes cases. The conversation explores how economic evidence is developed, evaluated, and increasingly relied upon in China's evolving antitrust regime. With special guest: Vanessa Zhang, Executive Vice President, Compass Lexecon Related Links: The Complex Geopolitics of Digital Regulation: The Three Body Problem Hosted by: Anora Wang, Arnold & Porter and Kathleen Hu, Cornerstone Research

Our guest this week is writer, journalist, cultural historian and broadcaster Matthew Sweet. Alongside Mark Gatiss, Matthew co-writes the detective series Bookish for U&Alibi, and is the author of works including Inventing the Victorians, Shepperton Babylon: The Lost Worlds of British Cinema, as well as the novel The New Forest Murders. A familiar voice on radio, he has presented The Sound of Cinema on BBC Radio 3 and programmes for BBC Radio 4, while also writing for major publications such as The Economist, The Daily Telegraph and The Financial Times.  To join Scarred Club and get fortnightly bonus episodes, monthly newsletters, ad-free listening and access to the members forum - sign-up here - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://scarredforlife.supportingcast.fm/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Based on the hugely successful Scarred for Life books, this is a weekly exploration of the things that scared people growing up and what those things say about us today. Join Andy Bush and Dave Lawrence as each week they talk to a special guest who brings with them three terrors from their childhoods. Email us - contact@scarredforlifebooks.com Follow us on socials: Scarred For Life - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Andy Bush - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Producer - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Dane Smith⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Production Company - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Lock It In Studio Learn more about your ad choices. Visit podcastchoices.com/adchoices

The jury is still out for many analysts on the outlook for economic growth, inflation and the labor market this year.Some see lots of reasons for concern for the road ahead.Others are much more convinced 2026 is going to be a blockbuster year.Which is more likely?To find out, we have the good fortune to talk today with Dr Anna Wong, Chief U.S. Economist for Bloomberg Economics. Prior to her current role, Anna also worked at the Federal Reserve Board, the White House Council of Economics Advisers, and the U.S. Treasury.Anna and her team started the year quite bullish, seeing many of last year's headwinds turning into tailwinds in 2026.But, in light of recent developments, she's starting to turn more cautious.To find out why, watch this video.Follow Anna on Bloomberg by typing BECO + "Go"Or on X at @AnnaEconomistREGISTER FOR THOUGHTFUL MONEY'S SPRING ONLINE CONFERENCE AT THE EARLY BIRD DISCOUNT PRICE at https://www.thoughtfulmoney.com/conference#gdp #inflation #unemploymentrate _____________________________________________ Thoughtful Money LLC is a Registered Investment Advisor Promoter.We produce educational content geared for the individual investor. It's important to note that this content is NOT investment advice, individual or otherwise, nor should be construed as such.We recommend that most investors, especially if inexperienced, should consider benefiting from the direction and guidance of a qualified financial advisor registered with the U.S. Securities and Exchange Commission (SEC) or state securities regulators who can develop & implement a personalized financial plan based on a customer's unique goals, needs & risk tolerance.IMPORTANT NOTE: There are risks associated with investing in securities.Investing in stocks, bonds, exchange traded funds, mutual funds, money market funds, and other types of securities involve risk of loss. Loss of principal is possible. Some high risk investments may use leverage, which will accentuate gains & losses. Foreign investing involves special risks, including a greater volatility and political, economic and currency risks and differences in accounting methods.A security's or a firm's past investment performance is not a guarantee or predictor of future investment performance.Thoughtful Money and the Thoughtful Money logo are trademarks of Thoughtful Money LLC.Copyright © 2026 Thoughtful Money LLC. All rights reserved.

Binyamin Appelbaum, lead writer on economics and business for The New York Times editorial board and the author of The Economists' Hour (Little, Brown and Company, 2019) , talks about the use of robots and automation in farming jobs typically held by immigrants and why cutting immigration doesn't necessarily lead to more job openings.Photo caption: A worker drives in cattle to be milked at T-Bar Dairy in Porterville, California, on December 17, 2024. (Photo by David Swanson / AFP via Getty Images)  

DHS funding runs out at midnight - setting up what would be the third shutdown of President Donald Trump's second term. Economists say inflation is moving in the right direction. Newly released Epstein files trigger a shakeup at Goldman Sachs. We'll tell you what led to the El Paso International Airport shutdown - it may surprise you. Plus, why the International Olympic Committee is catching heat over its merch. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Alex Preston is an award-winning author of five novels including This Bleeding City, The Revelations, In Love and War and Winchelsea, as well as a book of non-fiction As Kingfishers Catch Fire. He writes regularly for the New York Times, the Economist and Harper's Bazaar. He reviews books for the Observer's New Review, Financial Times and Spectator. Alex is co-founder of the Corfu Literary Festival and Patron of Oxford Literary Festival. On this episode of Little Atoms he talks to Neil Denny about his latest novel A Stranger in Corfu. Hosted on Acast. See acast.com/privacy for more information.

No 3 em 1 desta sexta-feira (13), o destaque foi que o ministro do Supremo Tribunal Federal, André Mendonça, reuniu-se com a Polícia Federal para obter um panorama das investigações sobre o caso Banco Master. Como novo relator do processo, Mendonça passa a avaliar os desdobramentos do inquérito e definir os próximos passos no STF, em meio à repercussão política e jurídica envolvendo a apuração. A troca de relatoria do caso Banco Master no Supremo Tribunal Federal gerou reações distintas entre parlamentares. Com a saída de Dias Toffoli, o ministro André Mendonça passa a conduzir o processo, enquanto a oposição cobra mais transparência na divulgação das provas e acompanha os desdobramentos das investigações que também envolvem a fraude no INSS e contratos de crédito consignado. O senador Carlos Viana (Podemos-MG), presidente da CPMI do INSS, solicitou ao ministro André Mendonça, do STF, o acesso a dados sigilosos de Daniel Vorcaro, dono do Banco Master. A medida busca avançar as investigações na comissão, enquanto cresce a expectativa por um encontro entre Viana e Mendonça após o Carnaval para tratar do compartilhamento das informações. O presidente dos Estados Unidos, Donald Trump, participou de um encontro com forças especiais responsáveis pela captura de Nicolás Maduro em uma operação recente. A reunião ocorreu em Fort Bragg, na Carolina do Norte, e também contou com familiares dos militares, em meio às repercussões políticas, econômicas e geopolíticas do episódio envolvendo a Venezuela. A revista britânica The Economist apontou a situação econômica do Brasil como um importante sinal de alerta para grandes economias mundiais. A publicação criticou aspectos do modelo fiscal e previdenciário brasileiro, destacando riscos e impactos que podem servir de referência negativa no cenário internacional. A Câmara dos Deputados da Argentina aprovou a proposta que reduz a maioridade penal de 16 para 14 anos, em meio ao avanço de pautas do governo de Javier Milei. O tema ganhou força após o assassinato de um adolescente na província de Santa Fé, gerando comoção nacional e reacendendo o debate sobre o regime penal juvenil. O texto segue agora para análise do Senado argentino. Ministros do governo Lula foram orientados a não participar do desfile da escola de samba que fará homenagem ao presidente no Rio de Janeiro. A decisão ocorre em meio a questionamentos no TSE sobre possível propaganda eleitoral antecipada, enquanto Lula mantém agenda de carnaval pelo Nordeste e acompanha a repercussão política do evento. O ministro Dias Toffoli negou ter gravado a reunião reservada entre integrantes do Supremo Tribunal Federal que antecedeu sua saída da relatoria do caso Banco Master. O encontro, realizado a portas fechadas, gerou repercussão nos bastidores da Corte após a divulgação de detalhes do diálogo entre ministros e aumentou a tensão institucional em torno da investigação. Tudo isso e muito mais você acompanha no 3 em 1. Learn more about your ad choices. Visit megaphone.fm/adchoices

An extra piece for you this week. I had planned to follow up on Dr John's timely piece on oil and gas today, but it will have to wait.We need to talk about bitcoin.Since peaking at $126,000 in early October, the bitcoin price has been in freefall, and the declines have accelerated this year. Earlier in the week, it touched $60,000 - declines of over 50% from peak to trough. Today it sits at $67,000.Call it what it is. It's a bear market.Here's a 2-year chart so you can see the price action. All the gains of 2025 have been given back and we are back at 2024 levels.Bitcoin has become a software proxyMy first observation is that bitcoin's decline since October has coincided exactly with a brutal selloff in software stocks, even as hard assets - gold, silver, and other metals - have caught one heck of a bid.Just a few years ago, hard assets had no value, it seemed. Forget land, mining, the real economy. It was all about digital, software, IP, trademarks. How things have changed.This chart appeared in a WhatsApp group and I don't know who made it to give credit, but the story is clear: Bitcoin has become a software proxy and vice versa.The correlation is striking. As concerns around AI have hammered software more generally, bitcoin has followed. Hardware plays within tech have held up Maybe they're next to be hit. That remains to be seen.When the mainstream media calls the bottom - the next wave of bitcoin obituariesThe Financial Times, wrong about bitcoin since 2009, came out with its latest stupidity this week claiming that bitcoin is $69,000 overvalued. Yesterday the Daily Mail joined the Retard Gang in telling us bitcoin will go to zero.Remember: just as media frenzy often indicates the peak of a market, so does a media scrum at the bottom. All we need is a high-profile article from the Economist and the lows will be in.I get that some people don't like bitcoin, and bitcoiners can be obnoxiously vocal when the price is rising, but nocoiners can be just as bad. The amount of people trolling me about bitcoin - cc-ing me into tweets telling me how badly it's doing, slagging off Michael Saylor, sharing “going to zero” articles - has risen sharply.The more evolved and widespread these narratives, the more people repeating them, the closer we are to an end.On which note, here is a longer-term weekly chart of bitcoin. That weekly RSI is close to all-time lows. Doesn't mean this is the end. But you get these kinds of sentiment extremes at the end of cycles, not at the beginning. Join this elite readership.Where we go from hereThis is a bear market. Crypto winter is upon us once again. The trend is down.But the trend will end. It always does.Looking at the above charts, there's a lot of price memory in the $50-70,000 range. Bitcoin spent much of 2021 and 2024 here. I expect $50,000 - or just below - to hold. I give that a more than 50% probability.But it's bitcoin. So anything is possible. A typical bitcoin monster correction would see us go all the way back to the 2022 lows at ~$15,000. I don't see that as likely - especially as the preceding bull market wasn't that mammoth - maybe 10% probability.It's also possible the lows are already in, but my gut tells me this bear market has a bit longer to play out. It's not a short sharp correction like we saw in the spring of last year around the Tariff Tantrum ™, but more of a grinder. Corrections happen in price and time, and I feel this one has a few more twists to it, especially as markets generally are not quite as easy as they were a couple of months ago.My outlook at the beginning of this year was that the S&P 500 would follow the typical trajectory of the second year of a US presidency - and that points to a rocky second and third quarter with a strong final quarter. That has implications for liquidity and sentiment more generally. Bitcoin is the same technological genius creation it always was. It hasn't changed. Only perception has changed, as it always does.It has been repeatedly demonstrated that bitcoin is a volatile asset that goes to the extremities of both pessimism and optimism, that it is cyclical and that it crucifies hubris. Those cheering the bear market clearly haven't learned.Instead of celebrating, I urge the skeptical to take advantage of this bear market and use it to learn.On which note, if you're new to bitcoin, my 2014 book Bitcoin: the Future of Money? is a good place to start.Bitcoin isn't dead. It's just going through a bear market. They happen.What's the story that takes bitcoin higher, then?Remember: narrative follows price.When the price starts rising, all sorts of reasons will get attached and the story will form. Just as now with the price falling, all sorts of bearish narratives have emerged. Quantum Computing is going to end it. Jeffrey Epstein hijacked it. The core devs have fallen out. Strategy (NASDAQ.MSTR) is going bust. Whatever.It doesn't matter what the story is. That will come. Price leads.Quantum BSWhen you go to a bitcoin conference, one thing that's notable is just how intelligent, educated, informed and ambitious the participants are. There is not the proliferation of midwits that you might find on, for example, the FT payroll. The bitcoin community is super bright.Do you think those involved haven't thought about and prepared for Quantum computing and the threats it may or may not present? Of course they have.Is bitcoin more likely to be ready to deal with the quantum computing threat than say SWIFT, the BBC, the NHS, or some bank? And which is likely to cope with it better - a sector crammed full of genius computer scientists with their own capital at stake, or some institution run by a government?If you actually had a computer capable of taking down bitcoin, there are much easier, more satisfying things to take out, such as the House of Commons email server.Way more important than the actual threat of quantum computing is the perception of what that threat is, even if that perception is bogus. But, as I say, perceptions change, just as bull and bear market cycles do, and so will this narrative die except among the most ardent nocoiners.Of course I would rather bitcoin was at $150,000. But I am not worried. I won't like it if bitcoin goes to $50,000. I'll like it even less if it goes to $15,000. But we have been here before, and we'll likely be here again.We know how this story ends.A prediction for the recordHere it is: It may have to go lower first, but bitcoin will outperform precious metals over the next 18 months, and probably over the next 12.Let's mark the price: gold is $5,000. Silver is $78. Bitcoin is $67,000.By the way, I advocate owning both: gold and bitcoin. So at this point I should really plug Charlie Morris's BOLD, an ETF you can buy through your broker which owns both gold and bitcoin. Until next time,DominicBitcoin: the Future of Money? by Dominic Frisby is available at all good bookstores. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.theflyingfrisby.com/subscribe

He explains that the government sector shrinking is actually positive for the overall economy. Ford's CEO released a statement noting that EV sales have significantly underperformed expectations. NFL players are reportedly losing thousands of dollars because of California's Jock Tax. What changes does the Big Beautiful Bill bring when it comes to filing your taxes this year?

He explains that the government sector shrinking is actually positive for the overall economy. Ford's CEO released a statement noting that EV sales have significantly underperformed expectations. NFL players are reportedly losing thousands of dollars because of California's Jock Tax. What changes does the Big Beautiful Bill bring when it comes to filing your taxes this year?See omnystudio.com/listener for privacy information.

Artificial intelligence is playing an increasing role in all our daily lives – and handing over power to AI comes with many risks. From misinformation and disruption to autonomous war technology, can we handle the dangers? Gavin Esler talks to Alex Hern, AI writer at The Economist. Advertisers! Want to reach smart, engaged, influential people with money to spend? (Yes, they do exist). Some 3.5 MILLION people download and watch our podcasts every month – and they love our shows. Why not get YOUR brand in front of our influential listeners with podcast advertising? Contact ads@podmasters.co.uk to find out more. • Support us on Patreon to keep This Is Not A Drill producing thought-provoking podcasts like this. Written and presented by Gavin Esler. Produced by Robin Leeburn. Original theme music by Paul Hartnoll – https://www.orbitalofficial.com. Executive Producer Martin Bojtos. Managing Editor Jacob Jarvis. Group Editor Andrew Harrison. This Is Not A Drill is a Podmasters production. Learn more about your ad choices. Visit podcastchoices.com/adchoices

President Donald Trump praised January's jobs report after employers added 130,000 positions, calling the number “greater than expected.” But revised government data shows weaker annual job growth in 2025, and Black unemployment among men rose to 7.3%, well above the 4.3% national rate. Economists warn that limited job growth could leave workers in slower-growing sectors facing longer job searches. Subscribe to our newsletter to stay informed with the latest news from a leading Black-owned & controlled media company: https://aurn.com/newsletter Learn more about your ad choices. Visit megaphone.fm/adchoices

Artificial intelligence is moving fast, with new tools changing how people work, create and compete. Whether you're an AI doomer or AI boomer, it's hard to ignore what's coming. Economist and professor Tyler Cowen has spent years analyzing how these developments could reshape the economy and everyday life. He joins host Megan McArdle to talk through how AI could transform talent, human capital and competition — and how to make sure you don't get left behind.Subscribe to The Washington Post here.

AI isn't just coming from Silicon Valley anymore. A growing number of startups — and companies like Airbnb — are turning to Chinese open-source AI models instead of US-based APIs. Not because it's trendy. Because it's cheaper, more flexible, and often good enough. In this episode, Sophia Matveeva speaks with Alex Hern, AI correspondent at The Economist, about what's driving this shift. They break down how DeepSeek disrupted the market, why constraints fueled smarter engineering, and what founders can realistically try today if they want more AI options without more spend. Alex Hern is The Economist's AI Writer, focusing on the science and technology of artificial intelligence. Before joining the paper, he covered technology for 11 years at The Guardian, where he was the UK technology editor. In this episode, you will hear: Why relying on US AI APIs may be quietly limiting your product and your margins How Chinese open-source models let founders experiment, customize, and ship faster without runaway costs The real reason DeepSeek shocked Silicon Valley — and what it reveals about building under constraints What you can realistically try today if you want AI leverage without an AI-sized budget Free AI Mini-Workshop for Non-Technical Founders Learn how to go from idea to a tested product using AI — in under 30 minutes. Get free access here: techfornontechies.co/aiclass Follow and Review: We'd love for you to follow us if you haven't yet. Click that purple '+' in the top right corner of your Apple Podcasts app. We'd love it even more if you could drop a review or 5-star rating over on Apple Podcasts. Simply select "Ratings and Reviews" and "Write a Review" then a quick line with your favorite part of the episode. It only takes a second and it helps spread the word about the podcast. Episode Credits If you like this podcast and are thinking of creating your own, consider talking to my producer, Emerald City Productions. They helped me grow and produce the podcast you are listening to right now. Find out more at https://emeraldcitypro.com Let them know we sent you. For the full transcript, go to https://www.techfornontechies.co/blog/290-why-airbnb-switched-from-openai-to-chinese-ai-and-what-it-means-for-your-budget  

What if physics is just the universe learning? Most Theories of Everything episodes are mind‑bending for their math, physics, philosophy, or consciousness implications. This one hits all four simultaneously. Professor Vitaly Vanchurin joins me to argue the cosmos isn't just modeled by neural networks—it literally is one. Learning dynamics aren't a metaphor for physics; they are the physics. Vanchurin shows why we need a three‑way unification: quantum mechanics, general relativity, and observers. As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe TIMESTAMPS: - 00:00:00 - The Neural Network Universe - 00:05:48 - Learning Dynamics as Physics - 00:11:52 - Optimization and Variational Principles - 00:21:17 - Deriving Fundamental Field Equations - 00:28:47 - Fermions and Particle Emergence - 00:37:17 - Geometry of Learning Algorithms - 00:44:53 - Emergent Quantum Mechanics - 00:50:01 - Renormalization and Interpretability - 00:57:00 - Second Law of Learning - 01:05:10 - Subatomic Natural Selection - 01:15:40 - Consciousness and Learning Efficiency - 01:24:09 - Unifying Physics and Observers - 01:31:01 - Qualia and Hidden Variables - 01:40:24 - Free Energy Principle Integration - 01:46:04 - Epistemological Doubt and Advice LINKS MENTIONED: - Vitaly's Papers: https://inspirebeta.net/literature?sort=mostrecent&size=25&page=1&q=find%20author%20vanchurin - Vitaly's Lecture: https://youtu.be/TagDLiLb2VQ - Vitaly's Website: https://cosmos.phy.tufts.edu/~vitaly/ - Towards A Theory Of Machine Learning [Paper]: https://arxiv.org/pdf/2004.09280 - Autonomous Particles [Paper]: https://arxiv.org/pdf/2301.10077 - Emergent Field Theories From Neural Networks [Paper]: https://arxiv.org/pdf/2411.08138 - Covariant Gradient Descent [Paper]: https://arxiv.org/pdf/2504.05279 - A Quantum-Classical Duality And Emergent Spacetime [Paper]: https://arxiv.org/abs/1903.06083 - Emergent Quantumness In Neural Networks [Paper]: https://arxiv.org/abs/2012.05082 - Predictability Crisis In Inflationary Cosmology And Its Resolution [Paper]: https://arxiv.org/abs/gr-qc/9905097 - Stationary Measure In The Multiverse [Paper]: https://arxiv.org/abs/0812.0005 - The World As A Neural Network [Paper]: https://arxiv.org/pdf/2008.01540 - Self-Organized Criticality In Neural Networks [Paper]: https://arxiv.org/pdf/2107.03402v1 - One Hundred Authors Against Einstein [Book]: https://amazon.com/dp/B09PHH7KC8?tag=toe08-20 - Geocentric Cosmology: A New Look At The Measure Problem [Paper]: https://arxiv.org/abs/1006.4148 - Jacob Barandes [TOE]: https://youtu.be/gEK4-XtMwro - Yang-Hui He [TOE]: https://youtu.be/spIquD_mBFk - Eva Miranda [TOE]: https://youtu.be/6XyMepn-AZo - Felix Finster [TOE]: https://youtu.be/fXzO_KAqrh0 - Stephen Wolfram [TOE]: https://youtu.be/FkYer0xP37E - Stephen Wolfram 2 [TOE]: https://youtu.be/0YRlQQw0d-4 - Avshalom Elitzur [TOE]: https://youtu.be/pWRAaimQT1E - Ted Jacobson [TOE]: https://youtu.be/3mhctWlXyV8 - Geoffrey Hinton [TOE]: https://youtu.be/b_DUft-BdIE - Wayne Myrvold [TOE]: https://youtu.be/HIoviZe14pY - Cumrun Vafa [TOE]: https://youtu.be/kUHOoMX4Bqw - Claudia De Rham [TOE]: https://youtu.be/Ve_Mpd6dGv8 - Lee Smolin [TOE]: https://youtu.be/uOKOodQXjhc - Consciousness Iceberg [TOE]: https://youtu.be/65yjqIDghEk - Matthew Segall [TOE]: https://youtu.be/DeTm4fSXpbM - Andres Emilsson [TOE]: https://youtu.be/BBP8WZpYp0Y - Will Hahn [TOE]: https://youtu.be/3fkg0uTA3qU - David Wallace [TOE]: https://youtu.be/4MjNuJK5RzM - Karl Friston [TOE]: https://youtu.be/uk4NZorRjCo Learn more about your ad choices. Visit megaphone.fm/adchoices

Bob Goodson was the first employee at Yelp, founder of social media analytics company Quid, co-inventor of the Like button, and co-author of the new book Like: The Button That Changed the World. On Oct 1, 2025, Bob spent a day with our MBA students at the University of Kansas, and he shared so much great content that I asked him if we could put together some of the highlights as a podcast, which I've now put together in three chapters: First is Careers, second is Building Companies, and third is AI and Social Media. As a reminder, any views and perspectives expressed on the podcast are solely those of the individual, and not those of the organizations they represent. Hope you enjoy the episode. - [Transcript] Nate:  My name is Nate Meikle. You're listening to Meikles and Dimes, where every episode is dedicated to the simple, practical, and under-appreciated. Bob Goodson was the first employee at Yelp, founder of social media analytics company Quid, co-inventor of the like button, and co-author of the new book Like: The Button That Changed the World. On Oct 1, 2025, Bob spent a day with our MBA students at the University of Kansas, and he shared so much great content that I asked him if we could put together some of the highlights as a podcast, which I've now put together in three chapters: First is Careers, second is Building Companies, and third is AI and Social Media. As a reminder, any views and perspectives expressed on the podcast are solely those of the individual and not those of the organizations they represent. Hope you enjoy the episode. Let's jump into Chapter 1 on Careers. For the first question, a student asked Bob who he has become and how his experiences have shaped him as a person and leader.   Bob:  Oh, thanks, Darrell. That's a thoughtful question. It's thoughtful because it's often not asked, and it's generally not discussed. But I will say, and hopefully you'll feel like this about your work if you don't already, that you will over time, which is I'm 45 now, so I have some sort of vantage point to look back over. Like, I mean, I started working when I was about 9 or 10 years old, so I have been working for money for about 35 years. So I'm like a bit further into my career than perhaps I look. I've been starting companies and things since I was about 10. So, in terms of like my professional career, which I guess started, you know, just over 20 years ago, 20 years into that kind of work, the thing I'm most grateful for is what it's allowed me to learn and how it's evolved me as a person. And I'm also most grateful on the business front for how the businesses that I've helped create and the projects and client deployments and whatever have helped evolve the people that have worked on them. Like I genuinely feel that is the most lasting thing that anything in business does is evolve people. It's so gratifying when you have a team member that joins and three years later you see them, just their confidence has developed or their personality has developed in some way. And it's the test of the work that has evolved them as people. I mean, I actually just on Monday night, I caught up for the first time in 10 years with an intern we had 10 years ago called Max Hofer. You can look him up. He was an intern at Quid. He was from Europe, was studying in London, came to do an internship with us in San Francisco for the summer. And, he was probably like 18, 19 years old. And a few weeks ago, he launched his AI company, Parsewise, with funding from Y Combinator. And, he cites his experience at Quid as being fundamental in choosing his career path, in choosing what field he worked in and so on. So that was, yeah, that was, when you see these things happening, right, 10 years on, we caught up at an event we did in London on Monday. And it's just it's really rewarding. So I suppose, yeah, like I suppose it's it's brought me a lot of perspective, brought me a lot of inner peace, actually, you know, the and and when you're when I was in the thick of it at times, I had no sense of that whatsoever. Right. Like in tough years. And there were some - there have been some very tough years in my working career that you don't feel like it's developing you in any way. It just feels brutal. I liken starting a company, sometimes it's like someone's put you in a room with a massive monster and the monster pins you down and just bats you across the face, right, for like a while. And you're like just trying to get away from the monster and you're like, finally you get the monster off your back and then like the monster's just on you again. And it just, it's just like you get a little bit of space and freedom and then the monster's back and it's just like pummeling you. And it's just honestly some years, like for those of you, some of you are running companies now, right? And starting your own companies as well. And I suppose it's not just starting companies. There are just phases in your career and work where it's like you look back and you're like, man, that year was just like, that was brutal. You just get up and fight every day, and you just get knocked down every day. So I think, I don't wish that on anybody, but it does build resilience that then transfers into other aspects of your life.    Nate:  Next, a student made a reference to the first podcast episode I recorded with Bob and asked him if he felt like he was still working on the most important problem in his field.    Bob:  Yeah, thank you. Thanks for listening to the podcast, as this gives us… thanks for the chance to plug the podcast. So the way I met Nate is that he interviewed me for his podcast. And for those of you who haven't listened to it, it's a 30 minute interview. And he asked this question about what advice would you share with others? And we honed in on this question of like, what is the most important problem in your field? And are you working on it? Which I love as a guide to like choosing what to work on. And so we had a great conversation. I enjoyed it so much and really enjoyed meeting Nate. So we sort of said, hey, let's do more fun stuff together in the future. So that's what brought us to this conversation. And thanks to Nate for, you know, bringing us all together today. I'm always working on what I think is the most important problem in front of me. And I always will be. I can't help it. I don't have to think about it. I just can't think about anything else. So yes, I do feel like right now I'm working on the most important problem in my field. And I feel like I've been doing that for about 20 years. And it's not for everybody, I suppose. But I just think, like, let's talk about that idea a little bit. And then I'll say what I think is the most important problem in my field that I'm working on. Like, just to translate it for each of you. Systems are always evolving. The systems we live in are evolving. We all know that. People talk about the pace of change and like life's changing, technology's changing and so on. Well, it is, right? Like humans developed agriculture 5,000 years ago. That wasn't very long ago. Agriculture, right? Just the idea that you could grow crops in one area and live in that area without walking around, without moving around settlements and different living in different places. And that concept is only 5,000 years old, right? I mean, people debate exactly how old, like 7, 8,000. But anyway, it's not that long ago, considering Homo sapiens have been walking around for in one form or another for several hundred thousand years and humans in general for a couple million years. So 5,000 years is not long. Look at what's happened in 5,000 years, right? Like houses, the first settlements where you would actually just live at sleep in the same place every night is only 5,000 years old. And now we've got on a - you can access all the world's knowledge - on your phone for free through ChatGPT and ask it sophisticated questions and all right answers. Or you can get on a plane and fly all over the world. You have, you know, sophisticated digital currency systems. We have sophisticated laws. And like, we've got to be aware, I think, that we are living in a time of great change. And that has been true for 5,000 years, right? That's not new. So I think about this concept of the forefront. I imagine, human development is, you can just simply imagine it like a sphere or balloon that someone's like blowing up, right? And so every time they breathe into it, like something shifts and it just gets bigger. And so there's stuff happening on the forefront where it's occupying more space, different space, right? There's stuff in the middle that's like a bit more stable and a bit more, less prone to rapid change, right? The education system, some parts of the healthcare system, like certain professions, certain things that are like a bit more stable, but there's stuff happening all the time on the periphery, right? Like on the boundary. And that stuff is affecting every field in one way or another. And I just think if you get a chance to work on that stuff, that's a really interesting place to live and a really interesting place to work. And I feel like you can make a contribution to that, right, if you put yourself on the edge. And it's true for every field. So whatever field you're in, we had people here today, you know, in everything from, yeah, like the military to fitness to, you know, your product, product design and management and, you know, lots of different, you know, people, different backgrounds. But if you ask yourself, what is the most important thing happening in my area of work today, and then try to find some way to work on it, then I think that sort of is a nice sort of North Star and keeps things interesting. Because the sort of breakthroughs and discoveries and important contributions are actually not complicated once you put yourself in that position. They're obvious once you put yourself in that position, right? It's just that there aren't many people there hanging out in that place. If you're one of them, if you put yourself there, not everyone's there, suddenly you're kind of in a room where like lots of cool stuff can happen, but there aren't many people around to compete with you. So you're more likely to find those breakthroughs, whether it's for your company or for, you know, the people you work with or, you know, maybe it's inventions and, but it just, anyway, so I really like doing that. And in my space right now, I call it the concept of being the bridge. And this could apply to all of you too. It's a simple idea that the world's value, right, is locked up in companies, essentially. Companies create value. We can debate all the other vehicles that do it, but basically most of the world's value is tied up in companies and their processes. And that's been true for a long time. There's a new ball of power in the world, which is been created by large language models. And I think of that just like a new ball of power. So you've got a ball of value and a ball of power. And the funny thing about this new ball of power is this actually has no value. That's a funny thing to say, right? The large language models have no value. They don't. They don't have any value and they don't create value. Think about it. It's just a massive bag of words. That has no value, right? I can send you a poem now in the chat. Does that have any value? You might like it, you might not, but it's just a set of words, right? So you've got this massive bag of words that with like a trillion connections, no value whatsoever. That is different from previous tech trends like e-commerce, for example, which had inherent value because it was a new way to reach consumers. So some tech trends do have inherent value because they're new processes, but large language models don't. They're just a new technology. They're very powerful. So I call it a ball of power. but they don't have any value. So why is there a multi-trillion dollar opportunity in front of all of us right now in terms of value creation? It's being the bridge. It's how to make use of this ball of power to improve businesses. And businesses only have two ways you improve them. You save money or you grow revenue. That's it. So being the bridge, like taking this new ball of power and finding ways to save money, be more efficient, taking this new ball of power and finding ways to access new consumers, create new offerings and so on, right? Solve new problems. That is where all the value is. So while you may think that the new value, this multi-trillion dollar opportunity with AI is really for the people that work on the AI companies, sure, there's a lot of, you know, there's some money to be made there. And if you can go work for OpenAI, you probably should. Everyone should be knocking the door down. Everyone should be applying for positions because it's the most important company, you know, in our generation. But if you're not in OpenAI or Meta or Microsoft or whoever, you know, three or four companies in the US that are doing this, for everybody else, it's about being the bridge, finding ways that in your organizations, you can unlock the power of AI by bringing it into the organizations and finding ways to either save money or grow the business. And that's fascinating to me because anybody can be the bridge. You don't have to be good with large language models. You have to understand business processes and you have to be creative and willing to even think like this. And suddenly you can be on the forefront of like creating massive value at your companies because you were the, you know, you're the one that brings brings in the new tools. And I think that skill set, there are certain skills involved in being the bridge, but that skill set of being the bridge is going to be so valuable in the next 5 to 10 years. So I encourage people, and that's what I'm doing. Like, I see my role - I serve clients at Quid. I love working with clients. You know, I'm not someone that really like thrives for management and like day-to-day operations and administration of a business. I learned that about myself. And so I just spend my time serving clients. I have done for several years now. And I love just meeting clients and figuring out how they can use Quid's AI, Quid's data, and any other form of AI that we want to bring to the table to improve their businesses. And that's just what I do with my time full-time. And I'll probably be doing that for at least the next 5 or 10 years. I think the outlook for that area of work is really huge.    Nate:  Building on the podcast episode where Bob talked about working on the most important problem in his field, I asked if he could give us some more details on how he took that advice and ended up at Yelp.    Bob:  So I was in grad school in the UK studying, well, I was actually on a program for medieval literature and philosophy, but looking into like language theory. So it was not the most commercial course that one could be doing. But I was a hobbyist programmer, played around with the web when it first came up and was making, you know, various new types of websites for students. while in my free time. I didn't think of that as commercial at all. I didn't see any commercial potential in that. But I did meet the founders of PayPal that way, who would come to give a talk. And I guess they saw the potential in me as a product manager. You know, there's lots of new apps they wanted to build. This is in 2003. And so they invited me to the US to work for them. And I joined the incubator when there were just five people in it. Max Levchin was one of them, the PayPal co-founder. Yelp, Jeremy Stoppelman and Russel Simmons were in those first five people. They turned out to be the Yelp co-founders. And Yelp came out of the incubator. So we were actually prototyping 4 companies each in a different industry. There was a chat application that we called Chatango that was five years before Twitter or something, but it was a way of helping people to chat online more easily. There were, which is still around today, but didn't make it as a hit. There was an ad network called AdRoll, which ended up getting renamed and is still around today. That wasn't a huge hit, but it's still around. Then there was Slide, which is photo sharing application, photo and video sharing, which was Max's company. That was acquired by Google. And that did reasonably well. I think it was acquired for about $150 million. And then there was Yelp, which you'll probably know if you're in the US and went public on the New York Stock Exchange and now has a billion dollars in revenue. So those are the four things that we were trying to prototype, each very different, as you can see. But I suppose that's the like tactical story, right? Like the steps that took me there. But there was an idea that took me there that started this journey of working on the most, the most important problems that are happening in the time. So if I rewind, when I was studying medieval literature, I got to the point where I was studying the invention of the print press. And I'd been studying manuscript culture and seeing what happened when the print press was invented and how it changed education, politics, society. You know, when you took this technology that made it cheaper to print, to make books, books were so expensive in the Middle Ages. They were the domain of only the wealthiest people. And only 5% of people could read before the print process was invented, right? So 95% of people couldn't read anything or write anything. And that was because the books themselves were just so expensive, they had to be handwritten, right? And so when the print press made the cost of a book drop dramatically, the literacy rates in Europe shot up and it completely transformed society. So I was studying that period and at the same time, like dabbling with websites in the early internet and sort of going, oh, like there was this moment where I was like, the web is our equivalent of the print press. And it's happening right now. I'm talking like maybe 2002, or so when I had this realization. It's happening right now. It's going to change everything during our lifetimes. And I just had a fork in my life where it's like I could be a professor in medieval history, which was the path I was on professionally. I had a scholarship. There were only 5 scholarships in my year, in the whole UK. I was on a scholarship track to be a professor and study things like the emergence of the print press, or I could contribute to the print press of our era, which is the internet, and find some way to contribute, some way, right? It didn't matter to me if it was big or small, it was irrelevant. It was just be in the mix with people that are pushing the boundaries. Whatever I did, I'd take the most junior role available, no problem, but like just be in the mix with the people that are doing that. So yeah, that was the decision, right? Like, and that's what led me down to sort of leave my course, leave my scholarship. And, my salary was $40,000 when I moved to the US. All right. And that's pretty much all I earned for a while. I'd spent everything I had starting a group called Oxford Entrepreneurs. So I had absolutely no money. The last few months actually living in Oxford, I had one meal a day because I didn't have enough money to buy three meals a day. And then I packed up my stuff in a suitcase - one bag - wasn't even a suitcase, it was a rucksack and moved to the US and, you know, and landed there basically on a student visa and friends and family was just thought I was, you know, not making a good decision, right? Like, I'm not earning much money. It's with a bunch of people in a like a dorm room style incubator, right? Where the tables and chairs we pulled off the street because we didn't want to spend money on tables and chairs. And where I get to work seven days a week, 12 hours a day. And I've just walked away from a scholarship and a PhD track at Oxford to go into that. And it didn't look like a good decision. But to me, the chance to work on the forefront of what's happening in our era is just too important and too interesting to not make those decisions. So I've done that a number of times, even when it's gone against commercial interest or career interest. I haven't made the best career decisions, you know, not from a commercial standpoint, but from a like getting to work on the new stuff. Like that's what I've prioritized.    Nate:  Next, I asked Bob about his first meeting with the PayPal founders and how he made an impression on them.    Bob:  Good question, because I think... So I have a high level thought on that, like a rubric to use. And then I have the details. I'll start with the details. So I had started the entrepreneurship club at Oxford. And believe it or not, in 800 years of the University's history, there was no entrepreneurship club. And they know that because when you want to start a new society, you go to university and they go through the archive, which is kept underground in the library, and someone goes down to the library archives and they go through all these pages for 800 years and look for the society that's called that. And if there is one, they pull it out and then they have the charter and you have to continue the charter. Even if it was started 300 years ago, they pull out the charter and they're like, no, you have to modify that one. You can't start with a new charter. So anyway, it's because it's technically a part of the university, right? So they have a way of administrating it. So they went through the records and were like, there's never been a club for entrepreneurs at the university. So we started the first, I was one of the co-founders of this club. And, again, there's absolutely no pay. It was just a charity as part of the university. But I love the idea of getting students who were scientists together with students that were business minded, and kind of bringing technical and creative people together. That was the theme of the club. So we'd host drinks, events and talks and all sorts. And I love building communities, at least at that stage of my life. I loved building communities. I'd been doing it. I started several charities and clubs, you know, throughout my life. So it came quite naturally to me. But what I didn't, I mean, I kind of thought this could happen, but it really changed my life as it put me at the center of this super interesting community that we've built. And I think that when you're in a university environment, like starting clubs, running clubs, even if they're small, like, we, I ran another club that we called BEAR. It was an acronym. And it was just a weekly meetup in a pub where we talked about politics and society and stuff. And like, it didn't go anywhere. It fizzled out after a year or two, but it was really like an interesting thing to work on. So I think when you're in a university environment, even if you guys are virtual, finding ways to get together, it's so powerful. It's like, it's who you're meeting in courses like this that is so powerful. So I put myself in the middle of this community, and I was running it, I was president of it. So when these people came to speak at the business school, I was asked to bring the students along, and I was given 200 slots in the lecture theatre. So I filled them, I got 200 students along. We had 3,000 members, by the way, after like 2 years running this club. It became the biggest club at the university, and the biggest entrepreneurship student community in Europe. It got written up in The Economist actually as like, because it was so popular. But yeah, it meant that I was in the middle of it. And when the business school said, you can come to the dinner with the speakers afterwards, that was my ticket to sit down next to the founder of PayPal, you know. And so, then I sat down at dinner with him, and I had my portfolio with me, which back then I used to carry around in a little folder, like a black paper folder. And every project I'd worked on, every, because I used to do graphic design for money as a student. So I had my graphic design projects. I had my yoga publishing business and projects in there. I had printouts about the websites I'd created. So when I sat down next to him, and he's like, what do you work on? I just put this thing on the table over dinner and was like, he picked it up and he started going through it. And he was like, what's this? What's this? And I think just having my projects readily available allowed him to sort of get interested in what I was working on. Nowadays, you can have a website, right? Like I didn't have a website for a long time. Now I have one. It's at bobgoodson.com where I put my projects on there. You can check it out if you like. But I think I've always had a portfolio in one way or another. And I think carrying around the stuff that you've done in an interactive way is a really good way to connect with people. But one more thing I'll say on this concept, because it connects more broadly to like life in general, is that I think that I have this theory that in your lifetime, you get around five opportunities put in front of you that you didn't yet fully deserve, right? Someone believes in you, someone opens a door, someone's like, hey, Nate, how about you do this? Or like, we think you might be capable of this. And it doesn't happen very often, but those moments do happen. And when they happen, a massive differentiator for your life is do you notice that it's happening and do you grab it with both hands? And in that moment, do everything you can to make it work, right? Like they don't come along very often. And to me, those moments have been so precious. I knew I wouldn't get many of them. And so every time they happened, I've just been all in. I don't care what's going on in my life at that time. When the door opens, I drop everything, and I do everything I can to make it work. And you're stretched in those situations. So it's not easy, right? Like someone's given you an opportunity to do something you're not ready for, essentially. So you're literally not ready for it. Like you're not good enough, you don't know enough, you don't have the knowledge, you don't have the skills. So you only have to do the job, but you have to cultivate your own skills and develop your skills. And that's a lot of work. You know, when I landed in, I mean, working for Max was one of those opportunities where I did not, I'd not done enough to earn that opportunity when I got that opportunity. I landed with five people who had all done PayPal. They were all like incredible experts in their fields, right? Like Russ Simmons, the Yelp co-founder, had been the chief architect of PayPal. He architected PayPal, right? Like I was with very skilled technical people. I was the only Brit. They were all Americans. So I stood out culturally. Most of them couldn't understand what I was saying when I arrived. I've since changed how I speak. So you can understand me, the Americans in the room. But I just mumbled. I wasn't very articulate. So it was really hard to get my ideas across. And I had programmed as a hobbyist, but I didn't know enough to be able to program production code alongside people that had worked at PayPal. I mean, their security levels and their accuracy and everything was just off the, I was in another league, right? So there I was, I felt totally out of my depth, and I had to fight to stay in that job for a year. Like I fought every day for a year to like not get kicked out of that job and essentially out of the country. Because without their sponsorship, I couldn't have stayed in the country. I was on a student visa with them, right? And I worked seven days a week for 365 days in a row. I basically almost lived in the office. I got an apartment a few blocks from the office and I had to. No one else was working those kind of hours, but I had to do the job, and I had to learn 3 new programming languages and all this technical stuff, how to write specs, how to write product specs like I had to research the history of various websites in parts of the internet. So I'm just, I guess I'm just giving some color to like when these doors open in your career and in your life, sometimes they're relationship doors that open, right? You meet somebody who's going to change your life, and it's like, are you going to fight to make that work? And, you know, like, so not all, it's not always career events, but when they happen, I think like trusting your instinct that this is one of those moments and knowing this is one of the, you can't do this throughout your whole life. You burn out and you die young. Like you're just not sustainable. But when they happen, are you going to put the burners on and be like, I'm in. And sometimes it only takes a few weeks. Like the most it's ever taken for me is a year to walk through a door. But like, anyway, like just saying that in case anyone here has one of these moments and like maybe this will resonate with one of you, and you'll be like, that's one of the moments I need to walk through the door.    Nate:  That concludes chapter one. In chapter 2, Bob talks about building companies. First, I asked Bob if he gained much leadership experience at Yelp.    Bob:  I gained some. I suppose my first year or two in the US was in a technical role. So I didn't have anyone reporting to me. I was just working on the user interface and front end stuff. So really no leadership there. But then, there was a day when we still had five people. Jeremy started to go pitch investors for our second round because we had really good traffic growth, right? In San Francisco, we had really nice charts showing traffic growth. We'd started to get traction in New York and started to get traction in LA. So we've had the start of a nice story, right? Like this works in other cities. We've got a model we can get traffic. And Jeremy went to his first VC pitch for the second round. And the VC said, you need to show that you can monetize the traffic before you raise this round. The growth story is fine, but you also need to say, we've signed 3 customers and they're paying this much, right, monthly. So Jeremy came back from that pitch, and I remember very clearly, he sat down, kind of slumped in his chair and he's like, oh man, we're going to have to do some sales before we can raise this next round. Like we need someone on the team to go close a few new clients. And it's so funny because it's like, me and four people and everyone went like this and faced me at the same time. And I was like, why are you looking at me? Like, I'm not, I didn't know how to start selling to local businesses. And they're like, they all looked at each other and went, no, we think you're probably the best for this, Bob. And they were all engineers, like all four of them were like, background in engineering. Even the CEO was VP engineering at PayPal before he did Yelp. So basically, we were all geeks. And for some reason, they thought I would be the best choice to sell to businesses. And I didn't really have a choice in it, honestly. I didn't want to do it. They were just like, you're like, that's what needs to happen next. And you're the most suitable candidate for it. So I I just started picking up the phone and calling dentists, chiropractors, restaurants. We didn't know if Yelp would resonate with bars or restaurants or healthcare. We thought healthcare was going to be big, which is reasonably big for Yelp now, but it's not the focus. But anyway, I just started calling these random businesses with great reviews. I just started with the best reviewed businesses. And the funny thing is some of those people, my first ever calls are still friends today, right? Like my chiropractor that I called is the second person I ever called and he signed up, ended up being my chiropractor for like 15 years living in San Francisco. And now we're still in touch, and we're great friends. So it's funny, like I dreaded those first calls, but they actually turned out to be really interesting people that I met. But yeah, we didn't have a model. We didn't know what to charge for. So we started out charging for calls. We changed the business's phone number. So if you're, you had a 415 number and you're a chiropractor on Yelp, we would change your number to like a number that Yelp owned, but it went straight through to their phone. So it was a transfer, but it meant our system could track that they got the call through Yelp, right? Yeah. And then we tracked the duration of the call. We couldn't hear the call, but we tracked the duration of the call. And then we could report back to them at the end of the month. You got 10 calls from Yelp this month and we're going to charge you $50 a call or whatever. So I sold that to 5 or 10 customers and people hated it. They hated that model because they're like, they'd get a call, it'd be like a wrong number or they just wanted to ask, they're already a current customer and they're asking about parking or something, right? So then we'd get back to and be like, you got a call and we charged you 50 bucks. So like, no, I can't pay you for that. Like, that was one of my current customers. So now the reality is they were getting loads of advertising and that was really driving the growth for their business, but they didn't want to pay for the call. So then I was like, that's not working. We have to do something else. Then we paid pay for click, which was we put ads on your page and when someone clicks it, they see you. And then people hated that too, because they're like, my mum just told me she's been like clicking on the link, right? Because she's like looking at my business. And my mum probably just cost me 5 bucks because she said she clicked it 10 times. And like, can you take that off my bill? So people hated the clicks. And then one day we just brought in a head of operations, Geoff Donaker. And by this point, by the way, I had like 2 salespeople working for me that I'd hired. And so it was me and two other people. We were calling these companies, signing these contracts. And one day I just had this epiphany. I was like, we should just pay for the ads that are viewed, not the ads that are clicked. In other words, pay for impressions to the ads. So if I tell you, I've put your ad in front of 500 people when they were looking for sushi this month, right? That you don't mind paying for because there's no action involved, but you're like, whoa, it's a big number. You put me in front of 500 people. I'll pay you 200 bucks for that. No problem. Essentially impression-based advertising. And I went to our COO and I was like, I think we should try this. He was like, if you want to give it a go. And I wrote up a contract and started selling it that day. And that is that format, that model now has a billion dollars revenue running through Yelp. So basically they took that model, like I switched it to impression-based advertising. And that was what was right for local. And our metrics were amazing. We're actually able to charge a lot more than we could in the previous two models. And I built out the sales team to about 20 people. Through that process, I got hooked, basically. Like I realized I love selling during that role. I would never have walked into sales, I think, unless everyone had gone, you have to do it. And I dreaded it, but I got really hooked on it. I love the adrenaline of it. I love hunting down these deals and I love like what you can learn from customers when you're selling. You can learn what they need and you can evolve your business model. So I love that flywheel and that's kind of what I've been doing ever since. But I built out a team of 20 people, so I got to learn management, essentially by just doing it at Yelp and building out that team.    Nate:  Next, I asked Bob how he developed his theory of leadership.    Bob:  I actually developed it really early on. You know, I mentioned earlier I'd been starting things since I was about 10 years old. And what's fascinated me between the age of like 10 and maybe, you know, my early 20s, I love the idea of creating stuff with people where no one gets paid. And here's why. These are charities and nonprofits and stuff, right? But I realized really early, if I can lead and motivate in a way where people want to contribute, even though they're not getting paid, and we can create stuff together, if I can learn that aspect, like management in that sense, then if I'm one day paying people, I'm going to get like, I'm going to, we're all going to be so much more effective, essentially, right? Like the organization is going to be so much more effective. And that is a concept I still work with today. Yes, we pay everyone quite well at Quid who works at Quid, right? Like we pay at or above market rate. But I never think about that. I never, ever ask for anything or work with people in a way that I feel they need to do it because that's their job ever. I just erased that from my mindset. I've never had that in my mindset. I always work with people with like, with gratitude and and in a way where I'm like, well, I'll try and make it fun and like help them see the meaning in the work, right? Like help them understand why it's an exciting thing to work on or a, why it's right for them, how it connects to their goals and their interests and why it's, you know, fun to contribute, whether it's to a client or to an area of technology or whatever we're working on. It's like, so yeah, I haven't really, I haven't, I mean, you guys might have read books on this, but I haven't really seen that idea articulated in quite the way that I think about it. And because I didn't read it in a book, I just kind of like stumbled across it as a kid. But that's, but I learned because I practiced it for 10 years before I even ended up in the US, when I started managing teams at Yelp, I found that I was very effective as a manager and a leader because I didn't take for granted that, you know, people had to do it because it was their job. I thought of ways to make the environment fun and make the connections between the different team members fun and teach them things and have there be like a culture of success and winning and sharing in the results of the wins together. And I suppose this did play out a little bit financially in my career because, although we pay people well at Yelp, we're kind of a somewhat mature business now. But in the early days of Yelp and in the early days of Quid, I never competed on pay. You know, when you're starting a company, it's a really bad idea to try and compete on pay. You have to, I went into every hiring conversation all the way through my early days at Yelp, as well as through the early days at Quid, like probably the first nearly 10 years at Quid. And every time I interviewed people, I would say early on, this isn't going to be where you earn the most money. I'm not going to be able to pay you market rate. You're going to earn less here than you could elsewhere. However, this is what I can offer you, right? Like whether then I make a culture that's about like helping learning. Like we always had a book like quota at Quid. If you want to buy books to read in your free time, I don't care what the title is, we'll give you money to buy books. And the reality is a book's like 10 bucks or 20 bucks, right? No one spends much on books, but that was one of the perks. I put together these perks so that we were paying often like half of what you could get in the market for the same role, but you're printing like reasons to be there that aren't about the money. Now, it doesn't work for everybody, you know, that's as in every company doesn't, but that's just what played out. And that's really important in the early days. You've got to be so efficient. And then once you start bringing in the money, then you can start moving up your rates and obviously pay people market rate. But early on, you've got to find ways to be really, really, really efficient and really lean. And you can't pay people market rate in the early days. I mean, people kind of expect that going into early stage companies, but I was particularly aggressive on that front. But that was just because I suppose it was in my DNA that like, I will try and give you other reasons to work here, but it's not going to be, it's not going to be for the money.    Nate:  Next, I asked Bob how he got from Yelp to Quid and how he knew it was time to launch his own company.    Bob:  Yeah, like looking back, if I'd made sort of the smart decision from a financial standpoint and from a, you know, career standpoint, I suppose you'd say, I would have just stayed put. if you're in a rocket ship and it's growing and you've got a senior role and you get to, you've got, you've earned the license to work on whatever you want. Like Yelp wanted me to move to Phoenix and create their first remote sales team. They wanted, I was running customer success at the time and I'd set up all those systems. Like there was so much to do. Yelp was only like three or four years old at the time, and it was clearly a rocket ship. And you know, I could have learned a lot more like from Yelp in that, like I could have seen it all the way through to IPO and, setting up remote teams and hiring hundreds of people, thousands of people eventually. So I, but I made the choice to leave relatively early and start my own thing. Just coming back to this idea we talked about in the session earlier today, I I always want to work on the forefront of whatever's going on, like the most important thing happening in our time. And I felt I knew what was next. I could kind of see what was next, which was applying AI to analyze the world's text, which was clear to me by about 2008, like that was going to be as big as the internet. That's kind of how I felt about it. And I told people that, and I put that in articles, and I put it in talks that are online that you can go watch. You know, there's one on my website from 10 years ago where I'd already been in the space for five or six years. You can go watch it and see what I was saying in 2015. So fortunately, I documented this because it sounds a bit, you know, unbelievable given what's just happened with large language models and open AI. But it was clear to me where things were going around 2008. And I just wanted to work on what was next, basically. I wanted to apply neural networks and natural language processing to massive text sets like all the world's media, all the world's social media. And yeah, I suppose whenever I've seen what's going to happen next, like with social network, going to Yelp, like seeing what was going to happen with social networking, going to building Yelp, and then seeing this observation about AI and going and doing Quid, it's not, it doesn't feel like a choice to me. It's felt like, well, just what I have to do. And regardless of whether that's going to be more work, harder work, less money, et cetera, it's just how I'm wired, I guess. And I'm kind of, I see it now. Like I see what's next now. And I'll probably just keep doing this. But I was really too early or very, very early, as you can probably see, to be trying to do that at like 2008, 2009, seven or eight years before OpenAI was founded, I was just banging my head against the wall for nearly a decade with no one that would listen. So even the best companies in the world and the biggest investors in the world, again, I won't name them, But it was so hard to raise money. It was so hard to get anyone to watch it that, after a time, I actually started to think I was wrong. Like after doing it for like 10 years and it hadn't taken off, I just started to think like, I was so wrong. I spent a year or two before ChatGPT took off. I'd got to a point where I'd spent like a year or two just thinking, how could my instinct be so wrong about what was going to play out here? How could we not have unlocked the world's written information at this point? And I started to think maybe it'll never happen, you know, and like I was simply wrong, which of course you could be wrong on these things. And then, you know, ChatGPT and OpenAI like totally blew up, and it's been bigger than even I imagined. And I couldn't have told you exactly which technical breakthrough was going to result in it. Like no one knew that large language models were going to be the unlock. But I played with everything available to try and unlock that value. And as soon as large language models became promising in 2016, we were on it, like literally the month that the Google BERT paper came out, because we were like knocking on that door for many years beforehand. And we were one of the teams that were like, trying to unlock that value. That's why many of the early Quid people are very senior at OpenAI and went on to take what they learned from Quid and then apply it in an OpenAI environment, which I'm very proud of. I'm very proud of those people, and it's amazing to see what they've done.    Nate:  That concludes Chapter 2. In Chapter 3, we discuss AI and social media. The first question was about anxiety and AI.    Bob:  Maybe I'll just focus on the anxiety and the issues first of all. A lot's been said on it. I suppose what would be my headlines? I think that one big area of concern is how it changes the job market. And I think the practical thing on that is if you can learn to be the bridge, then you're putting yourself in a really valuable position, right? Because if you can bridge this technology into businesses in a way that makes change and improvements, then you are moving yourself to a skill set that's going to continue to be really valuable. So that's just a practical matter. One of the executives I work with in a major US company likes to say will doctors become redundant because of AI? And he says, no, doctors won't be redundant, but doctors that don't use AI will be redundant. And that's kind of where we are, right? It's like, we're still going to need a person, but if you refuse, if you're not using it, you're going to fall behind and like that is going to put you at risk. So I think there is some truth to that little kind of illustrative story. There will be massive numbers of jobs that are no longer necessary. And the history of technology is full of these examples. Coming back to like 5,000 years ago, think of all the times that people invented stuff that made the prior roles redundant, right? In London, before electricity was discovered and harnessed, one of the biggest areas of employment was for the people that walked the streets at night, lighting the candles and gas lights that lit London. That was a huge breakthrough, right? You could put fire in the street, you put gas in the street and you lit London. Without that, you couldn't go out at night in London and like it would have been an absolute nightmare. The city wouldn't be what it is. But that meant there were like thousands of people whose job it was to light those candles and then go round in the morning when the sun came up and blow them out. So when the light bulb was invented, can you imagine the uproar in London where all these jobs were going to be lost, thousands of jobs were going to be lost. by people that no longer are needed to put out these lights. There were riots, right? There was massive social upheaval. The light bulb threatened and wiped out those jobs. How many people in London now work lighting gas lamps and lighting candles to light the streets, right? Nobody. That was unthinkable. How could you possibly take away those jobs? You know, people actually smashed these light bulbs when the first electric light bulbs were put into streets. People just went and smashed them because they're like, we are not going to let this technology take our jobs. And I can give you 20 more examples like that throughout history, right? Like you could probably think of loads yourselves. Even the motor car, you know, so many people were employed to look after horses, right? Think of all the people that were employed in major cities around the world, looking after horses and caring for them and building the carts and everything. And suddenly you don't need horses anymore. Like that wiped out an entire industry. But what did it do? It created the automobile industry, which has been employing massive numbers of people ever since. And the same is true for, you know, like what have light bulbs done for the quality of our lives? You know, we don't look at them now and think that's an evil technology that wiped out loads of jobs. We go, thank goodness we've got light bulbs. So the nature of technology is that it wipes out roles, and it creates roles. And I just don't see AI being any different. Humans have no limit to like, seem to have no limit to the comfort they want to live with and the things that we want in our lives. And those things are still really expensive and we don't, we're nowhere near satisfied. So like, we're going to keep driving forward. We're going to go, oh, now we can do that. Great. I can use AI, I can make movies and I can, you know, I don't know, like there's just loads of stuff that people are going to want to do with AI. Like, I mean, using the internet, how much time do we spend on these damn web forms, just clicking links and buttons and stuff? Is that fun? Do we even want to do that? No. Like we're just wasting hours of our lives every week, like clicking buttons. Like if we have agents, they can do that for us. So we have, I think we're a long way from like an optimal state where work is optional and we can just do the things that humans want to do with their time. And so, but that's the journey that I see us all along, you know. So anyway, that's just my take on AI and employment, both practically, what can you do about it? Be the bridge, embrace it, learn it, jump in. And also just like in a long arc, I'm not saying in the short term, there won't be riots and there won't be lots of people out of work. And I mean, there will be. But when we look back again, like I often think about what time period are we talking about? Right? People often like, well, what will it do to jobs? Next year, like there'll certain categories that will become redundant. But are we thinking about this in a one year period or 100 year period? Like it's worth asking yourself, what timeframe am I talking about? Right? And I always try and come back to the 100 year view at a minimum when talking about technology change. If it's better for humanity in 100 years, then we should probably work on it and make it happen, right? If we didn't do that, we wouldn't have any light bulbs in our house. Still be lighting candles?    Nate:  Next was a question about social media, fragmented attention, and how it drives isolation.    Bob:  Well, it's obviously been very problematic, particularly in the last five or six years. So TikTok gained success in the United States and around the world around five or six years ago with a completely new model for how to put content in front of people. And what powered it? AI. So TikTok is really an AI company. And the first touch point that most of us had with AI was actually through TikTok. It got so good at knowing the network of all possible content and knowing if you watch this, is the next thing we should show you to keep you engaged. And they didn't care if you were friends with someone or not. Your network didn't matter. Think about Facebook. Like for those of you that were using Facebook, maybe say 2010, right? Like 15 years ago. What did social media look like? You had a profile page, you uploaded photos of yourself and photos of your friends, you linked between them. And when you logged into Facebook, you basically just browsing people's profiles and seeing what they got up to at the weekend. That was social media 15 years ago. Now imagine, now think what you do when you're on Instagram and you're swiping, right? Or you go to TikTok and you're swiping. First of all, let's move to videos, which is a lot more compelling, short videos. And most of the content has nothing to do with your friends. So there was a massive evolution in social media that happened five or six years ago, driven by TikTok. And all the other companies had to basically adopt the same approach or they would have fallen too far behind. So it forced Meta to evolve Instagram and Facebook to be more about attention. Like there's always about attention, that's the nature of media. But these like AI powered ways to keep you there, regardless of what they're showing you. And that turned out to be a bit of a nightmare because it unleashed loads of content without any sense of like what's good for the people who are watching it, right? That's not the game they're playing. They're playing attention and then they're not making decisions about what might be good for you or not. So we went through like a real dip, I think, in social media, went through a real dip and we're still kind of in it, right, trying to find ways out of it. So regulation will ultimately be the savior, which it is in any new field of tech. Regulation is necessary to keep tech to have positive impact for the people that it's meant to be serving. And that's taken a long time to successfully put in place for social media, but we are getting there. I mean, Australia just banned social media for everyone under 16. You may have seen that. Happened, I think, earlier this year. France is putting controls around it. The UK is starting to put more controls around it. So, you know, gradually countries are voters are making it a requirement to put regulation around social media use. In terms of just practical things for you all, as you think about your own social media use, I think it's very healthy to think about how long you spend on it and find ways to just make it a little harder to access, right? Like none of us feel good when we spend a lot of time on our screens. None of us feel good when we spend a lot of time on social media. It feels good at the time because it's given us those quick dopamine hits. But then afterwards, we're like, man, I spent an hour, and I just like, I lost an hour down like the Instagram wormhole. And then we don't feel good afterwards. It affects us sleep negatively. And yeah, come to the question that was, posted, can create a sense of isolation or negative feelings of self due to comparison to centrally like models and actors and all these people that are like putting out content, right? Kind of super humans. So I think just finding ways to limit it and asking yourself what's right for you and then just sticking to that. And if that means coming off it for a month or coming off it for a couple of months, then, give that a try. Personally, I don't use it much at all. I'll use it mostly because friends will share like a funny meme or something and you just still want to watch it because it's like it's sent to you by a friend. It's a way of interacting. Like my dad sends me funny stuff from the internet, and I want to watch it because it's a way of connecting with him. But then I set a timer. I like to use this timer. It's like just a little physical device. I know we've all got one on our phones, but I like to have one on my desk. And so if I'm going into something, whether it's like I'm going to do an hour on my inbox, my e-mail inbox, or I'm going to, you know, open up Instagram and just swipe for a bit, I'll just set a timer, you know, and just keep me honest, like, okay, I'm going to give myself 8 minutes. I'm not going to give myself any more time on there. So there's limited it. And then I put all these apps in a folder on the second screen of my phone. So I can't easily access them. I don't even see them because they're on the second screen of my phone in a folder called social. So to access any of the apps, I have to swipe, open the folder, and then open the app. And just moving them to a place where I can't see them has been really helpful. I only put the healthy apps on my front page of my phone.    Nate:  Next was a question about where Bob expects AI to be in 20 years and whether there are new levels to be unlocked.    Bob:  No one knows. Right? Like what happens when you take a large language model from a trillion nodes to like 5 trillion nodes? No one knows. It's, this is where the question comes in around like consciousness, for example. Will it be, will it get to a point where we have to consider this entity conscious? Fiercely debated, not obvious at all. Will it become, it's already smarter than, well, it already knows more than any human on the planet. So in terms of its knowledge access, it knows more. In terms of most capabilities, most, you know, cognitive capabilities, it's already more capable than any single human on the planet. But there are certain aspects of consciousness, well, certain cognitive functions that humans currently are capable of that AI is not currently capable of, but we might expect some of those to be eaten into as these large language models get better. And it might be that these large language models have cognitive capabilities that humans don't have and never could have, right? Like levels of strategic thinking, for example, that we just can't possibly mirror. And that's one of the things that's kind of, you know, a concern to nations and to people is that, you know, we could end up with something on the planet that is a lot smarter than any one of us or even all of us combined. So in general, when something becomes more intelligent, it seeks to dominate everything else. That is a pattern. You can see that throughout all life. Nothing's ever got smarter and not sought to dominate. And so that's concerning, especially because it's trained on everything we've ever said and done. So I don't know why that pattern would be different. So that, you know, that's interesting. And and I think in terms of, so the part of that question, which is whole new areas of capability to be unlocked, really fascinating area to look at is not so much the text now, because everything I've written is already in these models, right? So the only way they can get more information is by the fact that like, loads of social networks are creating more information and so on. It's probably pretty duplicitous at this point. That's why Elon bought Twitter, for example, because he wanted the data in Twitter, and he wants that constant access to that data. But how much smarter can they get when they've already got everything ever written? However, large language models, of course, don't just apply to text. They apply to any information, genetics, photography, film, every form of information can be harnessed by these large language models and are being harnessed. And one area that's super interesting is robotics. So the robot is going to be as nimble and as capable as the training data that goes into it. And there isn't much robotic training data yet. But companies are now collecting robotic training data. So in the coming years, robots are going to get way more capable, thanks to large language models, but only as this data gets collected. So in other words, like language is kind of reaching its limits in terms of new capabilities, but think of all the other sensor types that could feed into large language models and you can start to see all kinds of future capabilities, which is why everyone suddenly got so interested in personal transportation vehicles and personal robotics, which is why like Tesla share price is up for example, right? Because Elon's committed now to kind of moving more into robotics with Tesla as a company. And there are going to be loads of amazing robotics companies that come out over the next like 10 or 20 years.    Nate:  And that brings us to the end of this episode with Bob Goodson. Like I mentioned in the intro, there were so many great nuggets from Bob. Such great insight on managing our careers, building companies, and the evolving impact of AI and social media. In summary, try to be at the intersection of new power and real problems. Seek to inspire rather than just transact, and be thoughtful about how to use social media and AI. All simple ideas, please, take them seriously.   

Think Like an Economist’s Justin Wolfers joins us to talk about the increasingly worrying state of the U.S. economy. The Miami Herald’s Julie K. Brown stops by to discuss the Epstein files—and the critical pieces that have yet to be put together.See omnystudio.com/listener for privacy information.

Our Global Head of Macro Strategy Matthew Hornbach and Chief U.S. Economist Michael Gapen discuss the path for U.S. interest rates after the nomination of Kevin Warsh for next Fed chair.Read more insights from Morgan Stanley.----- Transcript -----Matthew Hornbach: Welcome to Thoughts on the Market. I'm Matthew Hornbach, Global Head of Macro Strategy. Michael Gapen: And I'm Michael Gapen, Morgan Stanley's Chief U.S. Economist. Matthew Hornbach: Today we'll be talking about the Federal Open Market Committee meeting that occurred last week.It's Thursday, February 5th at 8:30 am in New York.So, Mike, last week we had the first Federal Open Market Committee meeting of 2026. What were your general impressions from the meeting? And how did it compare to what you had thought going in? Michael Gapen: Well, Matt, I think that the main question for markets was how hawkish a hold or how dovish a hold would this be. As you know, it was widely expected the Fed would be on hold. The incoming data had been fairly solid. Inflation wasn't all that concerning, and most of the employment data suggested things had stabilized. So, it was clear they were going to pause. The question was would they pause or would they be on pause, right? And in our view, it was more of a dovish hold. And by that, it suggests to us, or they suggested to us, I should say, that they still have an easing bias and rates should generally move lower over time. So, that really was the key takeaway for me. Would they signal a prolonged pause and perhaps suggest that they might be done with the easing cycle? Or would they say, yes, we've stopped for now, but we still expect to cut rates later? Perhaps when inflation comes down and therefore kind of retain a dovish bias or an easing bias in the policy rate path. So, to me, that was the main takeaway. Matthew Hornbach: Of course, as we all know, there are supposed to be some personnel changes on the committee this year. And Chair Powell was asked several questions to try to get at the future of this committee and what he himself was going to do personally. What was your impression of his response and what were the takeaways from that part of the press conference? Michael Gapen: Well, clearly, he's been reluctant to, say, pre-announce what he may do when his term is chair ends in May. But his term as a governor extends into 2028. So, he has options. He could leave normally that's what happens. But he could also stay and he's never really made his intentions clear on that part. I think for maybe personal or professional reasons. But he has his own; he has his own reasons and, and that's fine. And I do think the recent subpoena by the DOJ has changed the calculus in that. At least my own view is that it makes it more likely that he stays around. It may be easier for him to act in response to that subpoena by being on staff. It's a request for additional information; he needs access to that information. I think you could construct a reasonable scenario under which, ‘Well, I have to see this through, therefore, I may stay around.' But maybe he hasn't come to that conclusion yet. And then stepping back, that just complicates the whole picture in the sense that we now know the administration has put forward Kevin Warsh as the new Fed chair. Will he be replacing the seat that Jay Powell currently sits in? Will he be replacing the seat that Stephen Myron is sitting in? So yes, we have a new name being put forward, but it's not exactly clear where that slot will be; and what the composition of the committee will look like. Matthew Hornbach: Well, you beat me to the punch on mentioning Kevin Warsh… Michael Gapen: I kind of assumed that's where you were going. Matthew Hornbach: It was going to be my next question. I'm curious as to what you think that means for Fed policy later this year, if anything. And what it might mean more medium term? Michael Gapen: Yeah. Well, first of all, congratulations to Mr. Warsh on the appointment. In terms of what we think it means for the outlook for the Fed's reaction function and interest rate policy, we doubt that there will be a material change in the Fed's reaction function. His previous public remarks don't suggest his views on interest rate policy are substantively outside the mainstream, or at least certainly the collective that's already in the FOMC. Some people would prefer not to ease. The majority of the committee still sees a couple more rate cuts ahead of them. Warsh is generally aligned with that, given his public remarks. But then also all the reserve bank presidents have been renominated. There's an ongoing Supreme Court case about the ability of the administration to fire Lisa Cook. If that is not successful, then Kevin Warsh will arrive in an FOMC where there's 16 other people who all get a say. So, the chair's primary responsibility is to build a consensus; to herd the cats, so to speak. To communicate to markets and communicate to the public. So, if Mr. Warsh wanted to deviate substantially from where the committee was, he would have to build a consensus to do that. So, we think, at least in the near term, the reaction function won't change. It'll be driven by the data, whether the labor market holds up, whether inflation, decelerates as expected. So, we don't look for material change. Now you also asked about the medium term. I do think where his views differ, at least with respect to current Fed policy is on the size of the Fed's balance sheet and its footprint in financial markets. So, he has argued over time for a much smaller balance sheet. He's called the Fed's balance sheet bloated. He has said that it creates distortions in markets, which mean interest rates could be higher than they otherwise would be. And so, I think if there is a substantive change in Fed policy going forward, it could be there on the balance sheet. But what I would just say on that is it'll likely take a lot of coordination with Treasury. It will likely take changes in rules, regulations, the supervisory landscape. Because if you want to reduce the balance sheet further without creating volatility in financial markets, you have to find a way to reduce bank demand for it. So, this will take time, it'll take study, it'll take patience. I wouldn't look for big material changes right out of the box. So Matt, what I'd like to do is, if I could flip it back to you, Warsh was certainly one of the expected candidates, right? So, his name is not a surprise. But as we knew financial markets, one day we're thinking it'd be one candidate. The next day it'd be thinking at the next it was somebody else. How did you see markets reacting to the announcement of Mr. Warsh? For the next Fed share, and then maybe put that in context of where markets were coming out of the last FOMC meeting. Matthew Hornbach: Yeah, so the markets that moved the most were not the traditional, very large macro markets like the interest rate marketplace or the foreign exchange market. The markets that moved the most were the prediction markets. These newer markets that offer investors the ability to wager on different outcomes for a whole variety of events around the world. But when it comes to the implications of a Kevin Warsh led Fed – for the bigger macro markets like interest rates and currencies, the question really comes down to how? If the Fed's balance sheet policies are going to take a while to implement, those are not going to have an immediate effect, at least not an effect that is easily seen with the human eye. But it's other types of policy change in terms of his communication policy, for example. One of the points that you raised in your recent note, Mike, was how Kevin Warsh favored less communication than perhaps some of the recent, Federal Open Market Committees had with the public. And so, if there is some kind of a retrenchment from the type of over-communication to the marketplace, from either committee members or non-voters that could create a bit more volatility in the marketplace. Of course, the Fed has been one of the central banks that does not like to surprise the markets in terms of its monetary policy making. And so, that contrasts with other central banks in the G10. For example, the Swiss National Bank tends to surprise quite a lot. The Reserve Bank of Australia tends to surprise markets. More often, certainly than the Fed does. So, to the extent that there's some change in communication strategy going forward that could lead to more volatile interest rate in currency markets. And that then could cause investors to demand more risk premium to invest in those markets. If you previously were comfortable owning a longer duration Treasury security because you felt very comfortable with the future path of Fed policy, then a Kevin Warsh led Fed – if it decides to change the communication strategy – could naturally lead investors to demand more risk premium in their investments. And that, of course, would lead to a steeper U.S. Treasury curve, all else equal. So that would be one of the main effects that I could see happen in markets as a result of some potential changes that the Fed may consider going forward. So, Mike, with that said, this was the first FOMC meeting of the year, and the next meeting arrives in March. I guess we'll just have to wait between now and then to see if the Fed is on hold for a longer period of time or whether or not the data convinced them to move as soon as the March meeting. Thanks for taking time to talk, Mike. Michael Gapen: Great speaking with you, Matt. Matthew Hornbach: And thanks for listening. If you enjoy Thoughts on the Market, please leave us a review wherever you listen and share the podcast with a friend or colleague today.