Podcasts about Reddy

At The Wire with Scott Miller Reddy's Echo Returns at Keeneland: A Racehorse Story from Trackside to the Winner's Circle A Racehorse Story Opens the Episode The episode begins with a lyrical theme about racing, memory, glory, and the spirit of the track. The introduction frames the program as a story-driven look at Reddy's Echo, a racehorse returning from a four-month layoff and making what the transcript presents as his four-year-old debut in 2009. The host explains that the goal is to learn where the horse came from, how he became a racehorse, and what his plans may be moving forward. Behind-the-Scenes Production of the Introduction A substantial early portion captures the host and production voice working through the on-camera introduction. The producer encourages the host to repeat lines, praises the improved delivery, and reassures him that the concept will work on camera. The exchange shows the program being shaped in real time, with the host refining the message that each racehorse has a unique story and that Reddy's Echo's story begins with the International Equine Network. Plans to Educate New Racing Fans The host describes a broader intention to help people understand the racing world beyond what they see during major events like the Derby. He discusses filming at Fasig-Tipton, explaining what a sales company does, talking about horses that graduate into higher-profile racing, and visiting farms during a time when young horses are visible. The purpose is to make horse racing more accessible to new fans by showing the path from farms and sales to major races. Trackside Activity and Race-Day Atmosphere The middle of the transcript contains substantial trackside background audio, much of it fragmented, hurried, or garbled by the automated transcription. Usable portions show people coordinating shots, watching movement around the track, reacting to the moment, and trying to capture useful lines or visuals. Several repeated automated loops were removed, while unresolved background audio was preserved as marked unclear material rather than rewritten into unsupported dialogue. Reddy's Echo's Race and Jockey Reaction After the race, the host interviews the jockey about Reddy's Echo's performance. The jockey says the horse ran very well, responded positively after the layoff, recovered after being pinched back, and handled the synthetic track nicely. He notes that the surface did not seem to hit the horse in the face as harshly and that Reddy's Echo appeared to travel over it well, presenting the race as a strong and encouraging return. Winner's Circle Reflections at Keeneland The closing interview takes place in the winner's circle at Keeneland with two owner or representative voices identified from the transcript as Kevin and Brian Solomon, though the exact names require verification. They describe relief after the win, especially given the pressure of being a favorite in a field with other capable horses. They reflect on the horse moving forward, the patience shown during the race, and the excitement of winning on a beautiful, packed day at Keeneland before the theme returns to close the episode.

What could happen if we were really intentional with outreach and evangelism, especially around one of the biggest world events, like the World Cup? On this episode of Student Ministry Connection, Steve talks with Heather Reddy about her own soccer experience and how that eventually led her to work with Cru and then leading their big World Cup outreach initiative called Victory Beyond the Cup.  Links referenced in this episode:  Learn more about Victory Beyond the Cup - https://victorybeyondthecup.com Connect more with Heather - heather.reddy@cru.org  Find your next speaker at The Speaker Hub - https://youthminhub.com/speakerhub  Learn more about Steve's ministry with NNYM - https://nnym.org/stevecullum  Sign up to get Steve's newsletter - https://bit.ly/cullumnewsletter  Support the ministry by giving online - https://bit.ly/cullumsupport  Contact Steve about partnerships, speaking, coaching, or consulting - https://bit.ly/cullumcontact  Follow Student Ministry Connection on Instagram - https://instagram.com/studentministryconnection  Read Steve's blog - https://stevecullum.com  Follow Steve on Twitter - https://twitter.com/stevecullum  Follow Steve on Instagram - https://instagram.com/stevecullum  Follow Steve on Facebook - https://facebook.com/stevecullum    Be sure to join us in prayer for revival every Wednesday at 11am PT, 12pm MT, 1pm CT, 2pm ET.    Looking for student ministry resources? Check out Steve's curated list of books, games, and more at https://www.amazon.com/shop/stevecullum    Note: Some of the links above are affiliate links. By clicking them, Steve may receive commission to support this ministry.    Subscribe on your favorite podcast app. Links to the more popular ones are at https://linktr.ee/studentministryconnection     If you like what you hear, be sure to like, subscribe, share, and comment! Thanks, be sure to get connected, and may God bless your ministry!    

DESCRIPTION South Carolina's primary election enters the final stretch as accusations of dark money, fake conservative groups, and misleading campaign attacks dominate the conversation. Tara Servatius breaks down allegations that establishment forces are targeting Freedom Caucus conservatives through deceptive mailers and text campaigns while interviewing State Representative Josiah Magnuson. The show also examines claims about election integrity, California voting practices, and a gubernatorial race increasingly defined by outsider-versus-insider politics. PODCAST SUMMARY With South Carolina voters heading toward a critical primary election, concerns over dark money and political deception have taken center stage. Tara Servatius discusses allegations that organizations presenting themselves as conservative groups are actually working to undermine Freedom Caucus lawmakers through misleading mailers and text messages. Representative Josiah Magnuson joins the program to respond to attacks on his voting record, arguing that claims about tax increases and legislative pay raises are false and designed to mislead voters. The discussion highlights ongoing battles between establishment Republicans and Freedom Caucus conservatives within the South Carolina legislature. The program then shifts to broader election concerns, examining voting practices in California and allegations regarding ballot harvesting, voter roll maintenance, and election integrity. Tara argues these systems create opportunities for abuse and warns of potential national implications. Later, gubernatorial candidate Rom Reddy joins the show to discuss his outsider campaign, immigration enforcement, government reform, judicial reform efforts, and proposals to eliminate dark money influence in South Carolina politics. Reddy positions himself as a business leader rather than a career politician and outlines his vision for changing how state government operates. KEY TOPICS South Carolina primary election showdown Freedom Caucus under attack Dark money influence in state politics Misleading political mailers and texts Josiah Magnuson interview Legislative pay raise controversy South Carolina tax policy debate California election integrity concerns Ballot harvesting discussion Voter roll maintenance controversies Rom Reddy gubernatorial campaign Immigration enforcement proposals Judicial reform efforts Government transparency initiatives Outsider vs. insider political battle SEO KEYWORDS South Carolina politics, Freedom Caucus, Josiah Magnuson, Rom Reddy, South Carolina governor race, dark money politics, South Carolina primary election, conservative politics, election integrity, California voting laws, ballot harvesting, Tara Servatius, South Carolina legislature, judicial reform, government transparency SOCIAL MEDIA POST

TVN Reddy, CEO of Aptean, breaks down why the entire software industry is selling "bigger is better" AI while the real goal is the opposite: people spending 80% less time in systems and more time doing the work that actually drives the business. He explains why general purpose models hand every competitor the same 95% while the deep vertical 5% drives the outsized gains, why enterprise AI is unusable past roughly a half percent error rate, and why validation agents beat the instinct to hire three people to check the AI's work. TVN also digs into the quiet security crisis of employees pasting P&Ls and proprietary recipes into public LLMs that never had training turned off, and why agents bolted onto generic models won't scale without truly vertical models underneath. Finally, he shares why the winners won't be the companies with the hottest models but the ones with the courage to re-engineer their processes, because every big technology removes old constraints only to create new ones.

Hear the Senators sit down with a candidate for the South Carolina Governor's office to get an in-depth look at who he is, why he's running for Governor, his business background, how he sees the future of South Carolina, and so much more!Hear about Rom Reddy's priorities for South Carolina, how the campaign trail and fundraising is treating him, and get an inside look at the hot republican primary race only days before the primary ends!Get your latest Statehouse update and hear firsthand the rationale behind some of the legislature's most controversial bills, including re-districting, strange pressure points from the President's office. Join Senators Sheheen and Lourie in this week's episode where they take a deeper look at upcoming legislation and lawmakers' actions in S.C.    Support the showKeep up to Date with BITBR: Twitter.com/BITBRpodcastFacebook.com/BITBRpodcasthttps://bourboninthebackroom.buzzsprout.com

The second segment of hour two on the June 3, 2026, broadcast of The Charlie James Show focused on a report from the American Parents Association detailing what they described as leftist curriculum in public school classrooms. The segment highlighted growing parental pushback against politically driven content and underscored demands for greater ideological transparency in education.

During the second segment of Hour 4 on Wednesday, June 3, 2026, The Charlie James Show opened up the WORD talk lines to gather listener feedback on high-profile Republican figures, focusing heavily on South Carolina Senator Lindsey Graham and political commentator Rom Reddy. Callers strongly debated Graham's shifting alliance with Donald Trump and his ongoing stance on foreign policy, while others reacted to Reddy's latest criticisms of the state's traditional conservative establishment.

DESCRIPTION President Donald Trump has officially endorsed Pam Evette in South Carolina's Republican gubernatorial primary, but the endorsement sparked immediate controversy. During today's show, Tara examines Trump's surprising reference to Henry McMaster Jr. as Evette's future lieutenant governor pick—a claim Evette has repeatedly declined to confirm publicly. The conversation explores allegations of political deal-making involving Governor Henry McMaster, the failed congressional redistricting effort, and whether Trump's endorsement was strategic support or a subtle warning shot. Callers weigh in on the future of South Carolina politics, concerns about establishment influence, and comparisons to political shifts seen in other states. Later, gubernatorial candidate Rom Reddy joins the program to discuss the endorsement, polling trends, government spending, and his vision for South Carolina's future. KEY TOPICS Donald Trump's endorsement of Pam Evette Henry McMaster Jr. lieutenant governor controversy South Carolina congressional redistricting battle Claims of political deal-making and establishment influence New gubernatorial polling data Caller reactions from across South Carolina Rom Reddy interview and campaign platform Concerns about the future direction of South Carolina politics SEGMENT BREAKDOWN Segment 1: Trump's Endorsement Sparks Debate Tara analyzes Trump's endorsement of Pam Evette and focuses on the portion of the statement mentioning Henry McMaster Jr. as a future lieutenant governor candidate. The discussion centers on whether Trump intentionally highlighted a politically sensitive issue for Evette's campaign. Segment 2: The McMaster Connection The show explores allegations that support from Governor Henry McMaster came with expectations regarding future political appointments. Tara argues that Trump's comments exposed an issue Evette had previously avoided addressing publicly. Segment 3: Redistricting and Political Fallout Discussion shifts to South Carolina's failed congressional redistricting effort. Tara contends that political leaders failed to support changes sought by Trump and examines how those developments may have influenced the endorsement. Segment 4: Listener Reactions Callers from across South Carolina share concerns about establishment politics, open primaries, voter engagement, and comparisons to political developments in Colorado. Several callers discuss why they believe the gubernatorial race remains highly competitive despite Trump's endorsement. Segment 5: Rom Reddy Interview Gubernatorial candidate Rom Reddy joins the program and reacts to Trump's endorsement. Reddy discusses polling, government spending, taxes, economic development, and concerns about what he describes as the creation of a long-term political dynasty in South Carolina. Segment 6: Looking Ahead The show concludes with discussion about the increasingly crowded Republican gubernatorial race, emerging polling data, and questions surrounding how much influence Trump's endorsement will ultimately have on primary voters. TOP QUOTES "Donald Trump endorsed Pam Evette in the governor's race. That's not even the interesting part." "A big added plus for Pam is that I hear Henry McMaster Junior will be running with her as the next lieutenant governor." "People don't like that sort of thing. It starts marking the old smoke-filled backroom politics." "Governor is a CEO. We need to focus on the record." "Are we tired of politicians? Are we tired of all the name-calling?" SEO KEYWORDS Trump endorsement, Pam Evette, South Carolina governor race, Henry McMaster Jr, South Carolina politics, gubernatorial primary, Rom Reddy, Alan Wilson, Ralph Norman, Nancy Mace, redistricting controversy, Republican primary, South Carolina election, Tara Show, political analysis SHORT PROMO Trump endorses Pam Evette—but one line in that endorsement may have created a bigger controversy than the endorsement itself. Tara breaks dow ...

How can a simple game like soccer become a universal language for peace and a bridge for the Gospel? In this episode, we sit down with Heather Reddy, chaplain for the US Women's National Soccer Team and a leader with Cru, to discuss the incredible unifying power of "the beautiful game."From stories of 90 minutes of peace in Colombia to the identity struggles of elite athletes, Heather shares how we can use the upcoming 2026 World Cup as a massive opportunity for connection and outreach.In this episode, you'll learn:What "Victory Beyond the Cup" is and how you can get involved.The "Mole Poblano" strategy for building community.Practical ways for churches and individuals to host World Cup watch parties.Heather's experiences ministering to the USWNT.Links & Resources: ⚽ Get your World Cup Watch Party Kit: victorybeyondthecup.com 

Why is the traditional resume dying — and how can AI actually make hiring more human, not less? Vijay Reddy, CEO of Hireko.ai, shares how conversational video interfaces capture nuance and empathy that text-based AI misses, ending the resume black hole and the AI spam cycle. Join host Khudania Ajay (KAJ) as they explore the difference between text AI and video AI, how to interview 1,000 candidates overnight, and why video is the only antidote to AI-generated spam in the trust crisis. Support independent journalism at https://kajmasterclass.com=========================================*KAJ Masterclass*A video-first, live-first global conversation platform — editorially independent and depth-driven. In-depth, unscripted conversations with thinkers, leaders, entrepreneurs, authors, and experts — exploring ideas, lived experience, and real-world wisdom. Hosted by Khudania Ajay (KAJ), independent journalist.

durée : 00:05:36 - Le 13/14 - par : Frédéric Pommier - Fondatrice du podcast Bliss Stories, pour lequel elle a recueilli les confidences de centaines de femmes depuis 2018, elle sera le 30 mai à l'Olympia avec une dizaine d'entre elles pour le spectacle Bliss Show 2. Au micro de Frédéric Pommier, Clémentine Galey évoque "I Am Woman" d'Helen Reddy. Vous aimez ce podcast ? Pour écouter tous les épisodes sans limite, rendez-vous sur Radio France

Welcome to TBCY! In this insightful episode, we sit down with Reddy Mallidi, Chief AI Officer and COO at J&R Consulting, renowned for his practical expertise in implementing AI solutions across industries.Hosted by Stephen Ibaraki, this conversation explores the rise of agentic AI, practical AI adoption strategies, governance challenges, and how organizations can build trust in AI systems.Reddy Mallidi shares real-world lessons from deploying AI in enterprise environments, discusses the future of AI agents, and explains how leaders can move beyond the hype to create measurable business value.Key takeaways include:The future of agentic AI and autonomous workflowsOvercoming AI adoption challenges related to data, infrastructure, talent, and trustPractical frameworks for AI implementation and governanceReal-world use cases that demonstrate measurable business impactWhy curiosity, experimentation, and responsible AI practices matter

During the Friday, May 22, 2026, broadcast of The Tara Show, Lucy in Greenville called into WYRD (WORD) with two distinct, sharp political theories regarding the brewing South Carolina Republican primary chaos:1. Is David Pascoe Secretly a Democrat?Lucy's first question attacked David Pascoe's political identity, questioning if his recent party switch was a genuine ideological conversion or pure political opportunism.The Context: Pascoe served as a high-profile Democratic Solicitor for years and was even touted for Attorney General as a Democrat in 2022. He only officially switched to the Republican party in April 2025.The Skepticism: The caller echoed Donald Trump's blistering online attacks that labeled Pascoe a "RINO and total fraud." Lucy questioned whether Pascoe's jump to the GOP was simply a calculated calculation because Democrats have not won a statewide race in South Carolina since 2006, making a primary run on the Republican ticket his only viable path to winning the Attorney General seat.2. Is Rom Reddy a "Plant" Working Against Conservatives?Lucy's second question raised a conspiracy theory popular in Lowcountry political circles, questioning if multi-millionaire DOGE SC founder Rom Reddy is actually a political "plant" or spoiler candidate.The Context: Reddy built massive sway among South Carolina conservatives by funding the DOGE SC reform movement to gut government waste. However, he shocked the political establishment by suddenly dissolving his advocacy group to launch a Quixotic bid for Governor.The Skepticism: The caller questioned Reddy's motives, pointing out the suspicious timing of his organization giving Pascoe a "green check mark" endorsement despite Pascoe's long history as a progressive Democrat. Lucy floated the theory that Reddy's abrupt shift from a conservative reformer to a chaotic gubernatorial candidate—while backing party-switchers like Pascoe—is a deliberate play to fracture the traditional conservative vote and protect the established political machine in Columbia.

DESCRIPTION South Carolina gubernatorial candidate Ram Ready joins the show to directly respond to accusations made earlier this week by guest host Adam Morgan. Ready denies claims he's a political “plant,” blasts longtime Republican insiders, calls out alleged anti-Trump figures in the GOP, and lays out his outsider campaign message focused on taxes, spending, and government reform. The interview turns fiery as Ready defends his conservative credentials and positions himself as the businessman ready to shake up Columbia politics. PODCAST SUMMARY Republican gubernatorial candidate Ram Ready appeared on The Tara Show to push back against accusations made earlier in the week that he was acting as a political “plant” for South Carolina House Speaker Murrell Smith. Ready strongly denied the allegation, arguing it makes no logical sense for him to self-fund his campaign while allegedly working on behalf of another political figure. Throughout the interview, he criticized longtime Republican officeholders, accused Congressman Ralph Norman of previously backing Nikki Haley over Donald Trump, and framed himself as a true outsider candidate fighting establishment politics in Columbia. The conversation also touched on South Carolina's rising government spending, taxes, infrastructure, and education performance. Ready defended his past donations to Governor Henry McMaster while explaining that he supports Republican candidates over Democrats in general elections, even when he disagrees with their records. Ready also discussed his AI-powered campaign website, his policy platform, and his promise to bring private-sector accountability to state government. The interview closed with a sharp critique of political insiders, campaign operatives, and what Ready described as a lack of transparency in South Carolina politics. SEGMENT HIGHLIGHTS Ram Ready Responds to “Plant” Allegation Denies claims he is working for House Speaker Murrell Smith Says accusations are politically motivated attacks Defends self-funding campaign as proof of independence Clash Over Ralph Norman & Nikki Haley Ready accuses Norman allies of misleading voters Criticizes Norman's past support for Nikki Haley during Trump campaign Frames himself as a stronger Trump-aligned candidate Government Spending & South Carolina Politics Critiques rising state and local spending Calls South Carolina's Republican leadership ineffective Discusses taxes, roads, education, and economic performance Outsider Campaign Message Promotes himself as a citizen candidate, not a career politician Says voters are frustrated with establishment politics Promises private-sector accountability and reform AI Campaign Website & Policy Rollout Highlights detailed online policy platform Discusses use of AI tools to answer voter questions Encourages voters to read full campaign newspaper and proposals KEY QUOTES “You'd have to be pretty stupid to be a plant if you're spending your own money.” “When you vote for me, it's like throwing a grenade in the swamp.” “A bad Republican is still better than any Democrat.” “People are fed up with these career politicians and insider games.” SEO KEYWORDS Ram Ready governor campaign, South Carolina governor race, Tara Show interview, Ralph Norman criticism, South Carolina politics, Republican primary SC, Murrell Smith controversy, Nikki Haley Trump support, conservative podcast, South Carolina taxes, Columbia politics, outsider candidate, GOP primary battle, South Carolina government spending, Ram Ready interview HASHTAGS #SouthCarolina #SCPolitics #GovernorRace #RamReady #Republicans #Trump #Conservative #Politics #SouthCarolinaPolitics #GOP #Election2026 #TheTaraShow #PoliticalPodcast #AmpersandWave #BreakingNews

Explosive allegations rock the political world as gubernatorial candidate Ram Reddy fires back against accusations from allies of Ralph Norman, while conservatives warn about rising extremism, China's growing influence inside America, and GOP civil war tensions in Washington. From assassination attempt conspiracy theories to climate change backlash and Senate Republican infighting, today's episode covers the political chaos shaping 2026. PODCAST SUMMARY Today on AmperWave Daily, the hosts dive into a fiery interview with South Carolina gubernatorial candidate Ram Reddy, who forcefully rejects claims that he is a political “plant” for South Carolina House Speaker Murrell Smith. Reddy accuses supporters of Ralph Norman of spreading false attacks while portraying himself as an outsider willing to “throw a grenade into the swamp.” The conversation expands into broader political warfare, touching on accusations of anti-Trump sentiment among establishment Republicans, disputes over redistricting, campaign financing, and growing voter distrust in career politicians. Hosts discuss internal GOP battles involving Senate Republicans, including criticism aimed at John Thune and John Cornyn over their relationship with President Donald Trump and the America First movement. The episode also explores controversial rhetoric surrounding antisemitism, political extremism, and radical statements allegedly made by Democratic candidates. The hosts argue that Democrat leadership has failed to decisively condemn inflammatory behavior within its own ranks, while warning that ideological radicalization is accelerating nationwide. In another major segment, the show examines public distrust in media after polling showed many Americans questioning whether the attempted assassination of President Trump was real. Hosts blame declining trust in traditional media, AI-generated misinformation, and online conspiracy culture for America's fractured perception of reality. The discussion later pivots to China's influence in U.S. politics and economics. The hosts claim the China and the Chinese Communist Party have strategically benefited from climate change policies, energy restrictions, and left-wing activist networks in America. They also criticize establishment Democrats for alleged ties to Chinese-linked organizations and warn about long-term geopolitical consequences. Finally, the podcast tackles renewed fears surrounding pandemics, mRNA vaccine controversies, and media narratives around emerging viruses. Hosts express skepticism toward pharmaceutical companies, government censorship, and public health institutions while reflecting on the lingering fallout from the COVID era. KEY TALKING POINTS Ram Reddy denies claims he is connected to Murrell Smith Sharp attacks exchanged between allies of Reddy and Ralph Norman Debate over Republican establishment vs. America First conservatives Hosts criticize Senate Republicans including John Thune and John Cornyn Discussion about antisemitism and extremist rhetoric in modern politics Concerns over conspiracy theories surrounding the Trump assassination attempt Media trust collapse and AI misinformation fears Claims of growing Chinese influence inside American political and activist networks Criticism of climate change policy and energy infrastructure decisions Vaccine skepticism and pandemic-era censorship controversies SEO KEYWORDS Trump assassination attempt, Ram Reddy governor race, Ralph Norman controversy, South Carolina politics, China influence in America, Democrat extremism, GOP civil war, John Thune criticism, John Cornyn backlash, climate change debate, vaccine controversy, media trust collapse, America First movement, conservative podcast, AmperWave Daily HASHTAGS #Trump #SouthCarolinaPolitics #RamReddy #RalphNorman #China #AmericaFirst #Politics #ConservativeNews #Podcast #BreakingNews #MediaBias #GOP #ClimateChange #VaccineDebate #AmperWave FIRST COMMENT HASHTAGS #Trump2026 #SCPolitics #Br ...

In the second part of his interview on the Charlie James Show, gubernatorial candidate Rom Reddy outlines a platform focused on self-funded campaigning, sweeping education reform, and decentralizing infrastructure management. Reddy advocates for stricter criminal sentencing, school choice, and argues his "DOGE SC" initiative is necessary to eliminate government waste. Listen to the full episode on the Charlie James Show Podcast.

In a May 21, 2026, interview, South Carolina gubernatorial candidate Rom Reddy outlines his platform to overhaul state government by reducing 101 agencies to 35, eliminating state income tax, and cutting spending by $1,500 per citizen annually. Framing himself as an anti-establishment, self-funded outsider, Reddy proposes decentralizing infrastructure management and restructuring the executive branch to combat bureaucratic overreach. Listen to the full episode on Audacy.

During his appearance on The Charlie James Show, South Carolina gubernatorial candidate and DOGESC founder Rom Reddy detailed an anti-establishment platform focused on slashing state spending, cutting state agencies by two-thirds, and eliminating the state income tax. As a self-funded political outsider with a background in corporate restructuring, Reddy emphasized his refusal to accept campaign contributions or special interest endorsements, framing his campaign as a direct challenge to the "ruling class" and traditional political structures. Read the full interview recap at Audacy.

Reddy has built a $2.2 million dollar portfolio and is just getting started, a tale of many immigrants on their way to riches in Australia! ❤️ A Melbourne based Business Analyst working for a bank, I'm proud to call him a client of the Property Investment Accelerator.

In this episode of The Daily Lawyer's GC Series, we sit down with Dr. Vivek Mittal, the Executive Director of Legal and Corporate Affairs at Hindustan Unilever Limited (HUL). Vivek's journey is a masterclass in career agility, global leadership, and the "How" of hiring. He shares the incredible story of how a chance trip to Delhi and a sense of "FOMO" led him to register for a Company Secretary course with an 800-rupee loan - a decision that eventually led him to lead legal teams at global giants like Lupin, Dr. Reddy's, and now HUL. Key Topics Covered: 1. Career Growth: How he flipped his focus from being a Company Secretary to a General Counsel at India's leading companies 2. Global Leadership: Lessons from leading massive M&A deals in Brazil, Mexico, and Japan, and managing cross-cultural teams. 3. The "How" of Hiring: Why Vivek gives 50% or more weightage to a candidate's attitude and ethics over their technical domain skills. 4. AI & Legal Tech: Why you can't run away from LLMs and how technology will soon handle 70-80% of routine legal tasks. This episode is part of our General Counsel Series, presented in proud collaboration with Zoho Sign. About Zoho Sign Zoho Sign is a comprehensive digital e-signature solution tailored for Indian businesses. It helps organisations sign, send, manage documents, automate signature workflows, authenticate signers, and enable e-stamping — all while staying compliant with Indian law. If your business deals with a high volume of contracts and legal documentation, Zoho Sign is built to simplify and accelerate the process. Subscribe to The Daily Lawyer If you enjoy conversations with top legal leaders, in-house counsel, law firm partners, and legal entrepreneurs, subscribe to The Daily Lawyer for more such episodes. #TheDailyLawyer #VivekMittal #HindustanUnilever #HUL #GeneralCounsel #GCSeries #LegalCareer #CorporateLawyer #InHouseCounsel #LeadershipLessons #CareerTransition #HiringTips #CompanySecretary #ProfessionalGrowth #NewspaperTest #AIinLegal #LegalTech #GlobalBusiness #EthicsInBusiness #LawStudentsIndia #ZohoSign #LegalAdvice #PodcastIndia #BusinessStrategy #CorporateGovernance

Host: JR Guest: Isabella Reddy, author of That You RememberJR sits down with acclaimed author Isabella Reddy to discuss her novel That You Remember, a work of historical fiction loosely based on the Buffalo Creek Disaster — a devastating flood that struck Logan County, West Virginia on February 26, 1972, killing 125 people, mostly women and children, after a coal slurry dam owned by the Pittston Coal Company catastrophically failed.Isabella shares how she spent 10 years researching the story, including visiting the region, reviewing court depositions from the landmark Gerald Stern lawsuit against Pittston, and even going inside coal mines in Beckley, WV and Wales. The spark that drove her to write the novel? A poem recited online by a disaster survivor, whose words — "I can't remember... I can't forget" — moved her to tell the story.The Buffalo Creek Disaster: What happened, who was affected, and why it's been overlooked in mainstream historyCoal culture in southern WV: The deep bond communities have with coal mining, the role of unions (UMWA), and the economic reality of Logan CountyResearch process: Visiting Logan County, going into homes, attending memorials (from the 40th to the 54th anniversary), and using her father's personal desk diaries — he once worked for PittstonThe character of Sarah: A fictional heroine inspired by real people Isabella met — spunky, outspoken, caught between loyalty to her community and a forbidden relationship with a coal operatorCorporate accountability vs. responsibility: Pittston infamously called the disaster "an act of God" — JR and Isabella discuss what that deflection reveals about corporate ethicsThe Miracle Baby, Carrie Albright: A real survivor of the disaster, thrown to safety by his mother as she was swept away; now a successful man in New York CityConnections to global disasters: The 1966 Aberfan disaster in Wales, Erin Brockovich, and Dark WatersHow to support the book and your local library: Purchase the book and provide its ISBN to your state capital to get it placed in every county libraryAmazon and Barnes & NobleRequest it at your local bookstore or libraryPublisher: Bell Aisle Books (an imprint of Brandy Lane Publishing, Richmond, VA)Author's website: thatyouremember.com- **Instagram | Tumblr | Twitter | TikTok | Facebook | LinkedIn — @WVUncommonPlaceMerch store: onecommonplacesquarespace.comJoin the email list via the websiteRate, subscribe, and leave feedback on your favorite podcast platformWV Uncommon Place is a variety podcast covering mental health, empowerment, pop culture, and West Virginia — hosted by JR and Stacey.Episode SummaryKey Topics CoveredWhere to Find the BookConnect with WV Uncommon Place

In this episode of D Talks - The Design Podcast, host Sanjay Reddy speaks to Aanik Sirothiya, who secured AIR 17 in UCEED 2026.Aanik Sirothiya from Madhya Pradesh secured an AIR 17 in UCEED 2026. He has always been deeply interested in creativity, visual storytelling, and observing everyday problems around him. For Aanik, design is not just about aesthetics, but about creating meaningful and practical solutions that improve people's experiences.He enjoys sketching, exploring ideas, and thinking about how small changes in products or systems can make daily life easier and more comfortable. Like many design aspirants, Aanik switched from JEE preparation to UCEED during his preparation journey. It was one of his relatives who introduced him to design entrance exams, but by then, it was too late for him to apply for UCEED that year. With only one attempt remaining, he went on to secure an AIR 17 in the General Category in UCEED 2026. ________________________________________Order the book: INTRODUCTION TO DESIGN“Introduction to Design” isn't just a book; it's a helpful guide that clears up confusion, busts myths, and shows the way for new designers. With the help of beautiful and simplified diagrams and illustrations, this book makes understanding the design world even easier and more practical, empowering readers to explore their creativity with confidence. Split into four main parts, each one acts like a map, leading you through the world of design. It helps you understand what design is all about and figure out your own path within it. With easy-to-understand writing and detailed illustrations, this book goes beyond just teaching—it becomes a joyful experience, full of knowledge, and a journey of discovery and understanding yourself better.I've been designing for 15 years and if this book had come 15 years ago, I would have achieved all I did till now, in 8 years! Aaquib WaniFounder & Creative Director Aaquib Wani Design________________________________________Introduction to Design online courses for UCEED CEED NID & NIFT#NID #UCEED #CEED #NIFT #designpodcast ________________________________________Connect with Sanjay Reddy(Host)LinkedinInstagram________________________________________

And what's really happening inside India's healthcare system that nobody talks about?Dr. Guru N Reddy, Founder of Continental Hospitals, sits down with VK for one of the most honest health conversations we've ever had. Nothing is off limits.Here's what we covered - - Hospitals opening like supermarkets, doctor poaching & medical billing manipulation- Insurance companies, hospitals & patients - who's really winning?- Patented vs generic drugs - Ozempic, Mounjaro & Minoxidil explained- The REAL reasons for weight gain - it's a hormonal problem, not a willpower one- Gut-Brain Axis - how your gut and brain influence each other more than you think- Seasonal fruits, kitchen superfoods & the shocking sugar in cool drinks- Beer & the growing global epidemic of Fatty Liver- Rapid fire - AI for diagnosis, parasites in Indian guts, ENO & moreThis is not your regular health podcast. Raw, real & straight from one of India's top medical minds

A Minimally Invasive Alternative to Traditional Sinus Surgery Dr. Smith and Dr. Reddy explain what balloon sinuplasty is, how it works, what conditions it treats, and how it compares to traditional sinus surgery in this breakdown of one of ENT's most significant recent innovations. What you'll learn: What balloon sinuplasty is and how it differs from traditional sinus surgery Who makes a good candidate and what conditions it's designed to treat How effective it is and what to expect from results How it can be combined with other procedures for a more complete treatment approach Tired of dealing with sinus issues and wondering if balloon sinuplasty could be the answer? Listen to the full episode of We Nose Noses for a complete breakdown from the doctors themselves, then reach out to NJ ENT to schedule your consultation. https://www.njent.com/what-is-balloon-sinuplasty

Finding Who You Are in Who He Is

In this insightful episode of TBCY, Ashutosh Garg sits down with Srilakshmi Reddy, Founder & Director of Keystone School, KCITE, and ASquare Foundation. Discover Srilakshmi Reddy's inspiring journey from software engineer to educational innovator, and how she's transforming the learning landscape in India.Learn about the groundbreaking "Idea Loom" approach, the importance of meaningful and experiential learning, empowering teachers, integrating financial literacy and digital citizenship, and preparing students for an AI-driven world. Srilakshmi Reddy also shares her thoughts on the single most critical quality she wishes every student could have upon graduation.

What ENT Specialists Want You to Know About Sinus Infection Contagiousness Not all sinus infections are created equal. In this episode, Dr. Smith and Dr. Reddy explain the difference between viral and bacterial sinus infections, what makes one contagious and the other not, and how to protect yourself and the people around you. What you'll learn: Why sinus infections develop and what three triggers are most commonly responsible Why viral sinus infections are generally very contagious and how they spread Why bacterial sinus infections are unlikely to be passed on to others How to tell the difference between the two types based on your symptoms Dealing with recurring sinus infections? Our board-certified ENT specialists can help you get to the root cause. Schedule a consultation at NJ ENT today.   https://www.njent.com/common-question-are-sinus-infections-contagious/

Are recessions actually the best time to start your company? Aneesh Reddy, the founder of Capillary Technologies, believes that economic downturns are the ultimate filter for identifying products that have a "right to exist”,which is only earned when a product solves a deep, non-negotiable pain point for the customer. This idea has shaped Capillary's journey that led to a 4500 Crore IPO, 250 million consumers and 100,000+ stores worldwide.We explore the internal culture at Capillary that has not only retained 20% of its core team for over a decade but has also served as a launchpad for 50+ startups. Aneesh offers a contrarian view on leadership that founders should micromanage their teams for the first six months to instill the right DNA before scaling. We also discuss expansion into the US market, detailing the "Risk vs Reference" framework that defines how sales strategies must pivot when moving between continents. He shares what went wrong in Capillary's early attempt to enter the US, the lessons from that experience, and what eventually helped them succeed in the market the second time around, leading to the US now contributing over 50% of their revenue.If you are a founder building in SaaS or looking to scale from India to the world, this episode with Aneesh Reddy is for you.00:00 – Trailer01:50 – What to build that has not been commoditized05:20 – Customer-facing or fast-changing products will survive09:08 – How Capillary hit early PMF13:54 – Risk vs Reference in the US & Asia18:10 – How Capillary won the US market (after failing first)24:56 – Outbound & partnerships that work better in the US30:30 – Right to exist differs in startups vs large companies35:34 – Micromanage in startups for the first 6 months40:47 – How Vipassana changed the founder49:57 – How 1/5th of the team stayed for 10+ years55:29 – The culture that created 50+ startups58:24 – The right metrics to go IPO in India01:01:53 – The choice to build a product company01:05:24 – Pioneering acquisitions of US startups01:09:18 – Why not build a roll-up to get $200 million ARR?01:10:43- 5 major decisions behind Capillary's journey01:14:46 – Why are top SaaS stocks down?-------------India's talent has built the world's tech—now it's time to lead it.This mission goes beyond startups. It's about shifting the center of gravity in global tech to include the brilliance rising from India.What is Neon Fund?We invest in seed and early-stage founders from India and the diaspora building world-class Enterprise AI companies. We bring capital, conviction, and a community that's done it before.Subscribe for real founder stories, investor perspectives, economist breakdowns, and a behind-the-scenes look at how we're doing it all at Neon.-------------Check us out on:Website: https://neon.fund/Instagram: https://www.instagram.com/theneonshoww/LinkedIn: https://www.linkedin.com/company/beneon/Twitter: https://x.com/TheNeonShowwConnect with Siddhartha on:LinkedIn: https://www.linkedin.com/in/siddharthaahluwalia/Twitter: https://x.com/siddharthaa7-------------This video is for informational purposes only. The views expressed are those of the individuals quoted and do not constitute professional advice.Send us Fan Mail

You want to be open about your faith—but not that person. Pushy. Scripted. Weird. So you stay quiet. Meanwhile, life's already full—kids' games, long weekends, surface-level talk. What if sports evangelism didn't feel like a setup? Heather Reddy, national women's soccer chaplain with Athletes in Action, gets the tension and offers a more natural way to connect—right where you already are, without forcing the moment. To support this ministry financially, visit: https://www.oneplace.com/donate/84/29?v=20251111

90% of family wealth evaporates by the third generation. GV Keshav Reddy is building to beat those odds.In this episode of Raw Talks With VK, we sit down with Keshav Reddy — scion of the GVK Group, one of India's most iconic infrastructure conglomerates behind the  Bangalore and Mumbai Airports and the founder of Equal AI, an AI-powered assistant built to serve every Indian.Keshav opens up about growing up inside a business empire, what the third-generation curse really feels like from the inside, and why he's betting his career on building digital infrastructure for a billion people.In this episode:The real economics of how airports are built and bid for in IndiaWhy he founded Equal AI  and his goal of 1 million daily active usersHis early investments in CRED and Upstox and what he saw before others didHis personal philosophy: "Feet to the ground, eyes to the sky"How Transcendental Meditation and calendar discipline shape his decision-makingHis relationships with Nikhil Kamath, Nithin Kamath, and Kunal ShahHow Mukesh Ambani and Elon Musk inspire Whether you're building something from scratch or figuring out where to put your money — this conversation will give you boardroom perspectives and C-suite advice you won't find anywhere else.

In this episode of Bladder Cancer Matters, host and survivor Rick Bangs sits down with ImmunityBio's Chief Medical Officer, Dr. Bobby Reddy, for a fascinating, hopeful look at the future of bladder cancer treatment. They unpack how next-generation immunotherapies like ANKTIVA—paired with innovative approaches to BCG—are reshaping care for patients, especially those with limited options, while also tackling real-world challenges like ongoing BCG shortages. Dr. Reddy breaks down the science in a way that's accessible, highlighting how activating the body's own immune system could lead to longer-lasting responses and even help patients avoid more invasive treatments. Tune in to this conversation about progress and possibility.

In this episode, Sunitha Reddy, Chief Revenue Officer and Vice President of Operations, Prime Healthcare, discusses how revenue cycle strategy powers hospital turnarounds, tackles payer pressure and denials, and leverages AI to improve efficiency while supporting care access.Learn more about relentlessly raising RCM yield here: https://med-metrix.com/?utm_source=beckers&utm_medium=podcast&utm_campaign=brand

In today's Tech3 from Moneycontrol, UPI completes a decade with massive scale and now targets 1 billion users and deeper credit adoption. Swiggy sees key leadership exits and board changes. Spacetech firms rethink strategy as geopolitical tensions and war-linked controls shape satellite data access. Meanwhile, TCS reports strong deal wins but declining revenue, highlighting a shift toward AI-led, outcome-based models in IT services.

Matt Watson sits down with Mohan Reddy, serial entrepreneur and Chief Scientist at Cornerstone AI Labs, to explore how AI is fundamentally reshaping the way we think about work, skills, and human potential. Mohan shares the origin story of Skyhive—a workforce intelligence platform built to reskill and upskill people at a global scale—and how its acquisition by Cornerstone brought that mission to a larger stage.The conversation digs into why AI doesn't eliminate skills but transforms them, the distinction between tasks that can be automated versus those that require human judgment, and why "vibe coding" is both a breakthrough and a danger. Mohan also makes the case for reverse engineering as the most critical skill in an AI-driven world, and why sandbox environments will be essential for building trust in AI-assisted workflows.Whether you're a founder, engineer, or business leader trying to navigate the AI transition, this episode offers a grounded, optimistic perspective from someone who has spent decades at the intersection of human potential and machine intelligence.If you enjoyed today's episode, subscribe to the Starter Hustle podcast and leave us a review!⏱️ Episode Breakdown00:30 The Journey of Mohan Reddy and Skyhive03:34 Transition to Cornerstone AI Labs06:22 AI's Impact on Skills and Workforce09:33 The Evolution of Software Engineering12:29 The Future of Coding and AI Collaboration15:33 Upskilling in the Age of AI18:30 Curiosity and Learning in Tech21:34 Final Thoughts and AdviceLinks & ResourcesConnect with Mohan Reddy on LinkedInWhat Smart CTOs Are Doing Differently With Offshore Teams in 2025Subscribe to the Global Talent SprintFull Scale – Build your dev team quickly and affordablyIf you're trying to get your team out of the basement and into real product ownership, this episode is your playbook. Stop being a ticket factory. Build teams that think, create, and lead.Follow the show, rate it, and send this to someone who's still trying to do “real Scrum.” They need it more than you do.

Understanding Silent Sinus Syndrome and Why Early Detection Can Protect Your Vision and Health Dr. Smith and Dr. Reddy walk through a real patient case of silent sinus syndrome, a chronic sinus condition that often causes little to no symptoms yet can lead to serious complications if left untreated. Learn how it is diagnosed, why early treatment matters, and how minimally invasive in-office procedures are changing outcomes for patients. What you'll learn: What silent sinus syndrome is and how it differs from typical chronic sinusitis Why patients with this condition often have minimal or no symptoms, and what subtle signs to watch for How untreated silent sinus syndrome can affect the eye and surrounding structures over time What modern, minimally invasive treatment options are available, including in-office balloon dilation Think you might have sinus issues that have gone undiagnosed? Take our Sinus Quiz to find out if your symptoms point to something that deserves a closer look. https://www.njent.com/a-case-of-silent-sinus-syndrome/

In the early morning hours of February 26, 1972, a wall of black water tore through a narrow Appalachian hollow in Logan County—erasing communities, taking lives, and leaving behind a silence that still echoes today. The Buffalo Creek Mine Disaster wasn't just a tragedy—it was a moment that changed families, reshaped a region, and raised questions that have never fully settled. But history doesn't always capture what it felt like to live there… to lose everything… to remember. In this episode of Appalachian Shine, we sit down with Isabel Reddy, author of That You Remember, a powerful novel inspired by the people and stories of Buffalo Creek. Through fiction rooted in a real tragedy, Reddy explores the emotional aftermath of disaster—the grief, the resilience, and the burden of memory carried by those who survived. Together, we talk about the real communities that were lost, the responsibility of telling stories drawn from tragedy, and what it means for Appalachia to remember—not just what happened, but who it happened to. Because some places don't disappear…they live on in the stories we choose to tell.  #ThatYouRemember #IsabelReddy #HistoricalFiction #BooksThatMatter #AuthorInterview #BuffaloCreek #BuffaloCreekDisaster #WestVirginiaHistory #AmericanHistory #ForgottenHistory #AppalachianShine www.supportappalachia.org  

TEATIME WITH MISS LIZ SERVES: ISABEL REDDY Title That You Remember: Storytelling, Healing & The Power of Memory Tagline Sometimes remembering is the beginning of healing. Topic Storytelling, memory, healing, identity, and using creative expression to process life experiences. Description: In this heartfelt Teatime, Miss Liz welcomes Isabel Reddy, a writer whose work explores the power of memory, identity, and emotional truth. Through her book Buffalo Creek: That You Remember, Isabel invites readers into a deeply reflective space where storytelling becomes a pathway to healing. Her work captures the quiet moments, the unspoken emotions, and the stories that shape who we are—often long before we fully understand them. Isabel's voice is both gentle and powerful, offering a reminder that our memories—whether clear or fragmented—hold meaning, connection, and the possibility for transformation. honouring This Teatime is about honouring our stories, finding strength in reflection, and allowing memory to guide us toward deeper understanding.“Welcome to Teatime with Miss Liz, where I don't serve a beverage — I serve real-life changemakers. Today, I sit with Isabel Reddy, a storyteller who reminds us that memory is not just something we carry—it's something that shapes us, heals us, and connects us.”Isabel reminds us that our stories matter—even the quiet ones. When we take time to reflect and remember, we create space for healing, clarity, and connection. Isabel Reddy is an author and storyteller whose work explores memory, identity, and emotional healing. Through her writing, including Buffalo Creek: That You Remember, she invites readers to reflect on their experiences and uncover meaning within their personal stories, offering a path toward understanding and transformation. You can also find her audiobook online. #TeatimeWithMissLiz #IsabelReddy #StorytellingHealing #ThatYouRemember#TranscendEmbraceEnvision

On this episode of the Zen Frenz podcast the team recaps Reddy's 21st birthday at Indibar in Scottsdale, their trip to the Talking Stick Casino, and a conversation around the best animated movies. 

On this episode, I sit down with the CEO of Mosaik to talk about how there needs to be more of a focus on optimizing our consumers' outcomes in real estate and so much more. Our PartnersMosaik: Your sidekick for streamlining operations to empower you as an agent and run a fully transparent process that brings your buyer and seller into the transaction with you. Let mosaik.io take your business to all-new heights! Schedule a consult today!StackWrap: If you are a broker or team leader and want to consolidate your tech stack into one easy-to-use platform to maximize your agents' adoption and usage of the tools you provide, check out StackWrap now by going to www.stackwrap.comJared James Academy: If you are an agent, a broker, or a team leader who knows your agents would benefit from ongoing training with Jared James, did you know you could join Jared James Academy for as little as $99/month? Visit jaredjamestoday.com/academy to learn more about your options for individuals, teams, and brokerages. We can't wait to have you in our community!

Mistral has been on an absolute tear - with frequent successful model launches it is easy to forget that they raised the largest European AI round in history last year. We were long overdue for a Mistral episode, and we were very fortunate to work with Sophia and Howard to catch up with Pavan (Voxtral lead) and Guillaume (Chief Scientist, Co-founder) on the occasion of this week's Voxtral TTS launch:Mistral can't directly say it, but the benchmarks do imply, that this is basically an open-weights ElevenLabs-level TTS model (Technically, it is a 4B Ministral based multilingual low-latency TTS open weights model that has a 68.4% win rate vs ElevenLabs Flash v2.5). The contributions are not just in the open weights but also in open research: We also spend a decent amount of the pod talking about their architecture that combines auto-regressive generation of semantic speech tokens with flow-matching for acoustic tokens (typically only applied in the Image Generation space, as seen in the Flow Matching NeurIPS workshop from the principal authors that we reference in the pod).You can catch up on the paper here and the full episode is live on youtube!Timestamps00:00 Welcome and Guests00:22 Announcing Voxtral TTS01:41 Architecture and Codec02:53 Understanding vs Generation05:39 Flow Matching for Audio07:27 Real Time Voice Agents13:40 Efficiency and Model Strategy14:53 Voice Agents Vision17:56 Enterprise Deployment and Privacy23:39 Fine Tuning and Personalization25:22 Enterprise Voice Personalization26:09 Long-Form Speech Models26:58 Real-Time Encoder Advances27:45 Scaling Context for TTS28:53 What Makes Small Models30:37 Merging Modalities Tradeoffs33:05 Open Source Mission35:51 Lean and Formal Proofs38:40 Reasoning Transfer and Agents40:25 Next Frontiers in Training42:20 Hiring and AI for Science44:19 Forward Deployed Engineering46:22 Customer Feedback Loop48:29 Wrap Up and ThanksTranscriptswyx: Okay, welcome to Latent Space. We're here in the studio with our gues co-host Vibh u. Welcome. Thanks. Excited for this one as well as Guillaume and Pavan from Mistral. Welcome. Excited to be here.Guillaume: Thank you.swyx: Pavan, you are leading audio research at Mistral and Guillaume, you're Chief Scientist,Announcing Voxtral TTSswyxHost(00:05) Okay. (00:05) Welcome to Lean Space. (00:06) We're here in the studio with trustee co-hosts, Vibhu. (00:09) Welcome.VibhuHost(00:11) Very excited for this one.swyxHost(00:12) As well as Guillaume and Pavan from Mistral. (00:15) Welcome. (00:16) Excited to be here. (00:17) Thank you for having us.(00:18) Pavan, you are leading audio research at Mistral and Guillaume, you're a chief scientist. (00:23) What are we announcing today where we're coordinating this release with you guys?GuillaumeGuest(00:26) Yeah, so we are releasing Voxtral TTS. So it's our first audio model that generates speech. It's not our first audio model. We had a couple of releases before.(00:35) We had one in the summer that was Voxtral, our first audio model, but it was like a transcription model, ASR. Like a few months later, we released some update on top of this, supporting more languages. Also a lot of table stack features for our customers, context biasing, precision, timestamping and transcription. We also have some real-time model that can transcribe not just at the end of the level.(00:56) You don't need to fill your entire audio file, but that can also come in real-time. And here, this is a natural extension in the audio, so basically speech generation. So yeah, so we support nine languages, and this is a pretty small model, 3D model, so very fast, and also state of the art. Performed at the same level as the base model, but it's much more efficient in terms of cost, and also much, in terms of cost, it's also much cheaper, only a fraction of the cost of our competitors.(01:22) And we are also releasing the work that this model is running.swyx What's the decision factor?Guillaume It's a good question.swyxThere will be more. Yeah, Pavan, any sort of research notes to add on?Architecture and CodecPavan: But it's a novel architecture that we develop inhouse.We traded on several internal architectures and ended up with a auto aggressive flow matching architecture. And also have a new in-house neural audio codec. Which, converts this audio into all point by herds latent [00:02:00] tokens, semantic and acoustic tokens. And yeah, that's that's their new part about this model and we're pretty excited that it's, it came out with such good quality and Jim was mentioning. Yeah, it's a three B model. It's based off of the TAL model that we actually released just a few months back and insert trunk and mainly meant for like the TTS stuff, but they need text capabilities are also there. Yeah.swyx: So there's a lot to cover.I always I love any, anything to do with novel encodings and all those things because I think that's obviously I creates a lot of efficiency, but also maybe bugs that sometimes happen. You were previously a Gemini and you worked on post training for language models, and maybe a lot of people will have less experience with audio models just in general compared to pure language.What did you find that you have to revisit from scratch as you joined this trial and started doing this? At leastUnderstanding vs GenerationPavan: when it comes to, for, I think the, there are two buckets, I guess the audio understanding and audio [00:03:00] generation. The audio understanding, like the walkthrough models that Kim was mentioning that we released earlier.The walkthrough chat that we released I think July last year, and the follow up transcription only, models family that we released in January, that would be one bucket, and the generation is another bucket. I think. You can also treat them as a unified set of models, but currently the approaches are a little different between these two.To your question on how audio is fed to the model? In the understanding model, it's very similar to actually Pixar models that we also released,swyx: yes.Pavan: That'sswyx: amazing.Pavan: It was pretty, I, that was the first project I worked on after joined Misra. It was pretty, pretty nice. And Wtu was very similar in spirit.I guess So we feed audio through an audio encoder similar to images through a vision encoder, and it produces continuous embeddings and which are fed as tokens to the main transformer decoded transformer model. Yeah. On the model output is just text. So on the output side, there is nothing that needs to be done in these kinds of mode.I [00:04:00] guess the interesting part of what the generation stuff is, the output now has to produce audio and. The approach that we have is this neural audio codec, which converts audio into these latent tokens. There is a lot of existing attrition and a lot of models which are based off of this kind of approach.And we took a slightly. A different, design decisions around this. But at the end of the day, the neural audio product converts audio into a 12.5 herdz set of latents. And each latent is, has a semantic token and a set of acoustic tokens. And the idea is that you take these discrete tokens and then feed it on the input side.There's several ways to use this at each frame, but we just sum the embedding. So it's like having key different vocabularies. Combine all of them because they all correspond to one audio frame on the input side. The output side is the interesting part on the output side, the, it's not the, I don't know if it's the most popular, but one.Popular technique is to have a depth transformer [00:05:00] because you have K tokens at each time step, like with a text, you just have one token at each time step. So you just do predict the token from the vocabulary with, yeah, with just, you get probabilityswyx: This's a very straightforward text. VeryPavan: straightforward.swyx: Yeah.Pavan: But if you have K tokens, then the name thing would be to predict all of them in paddle. That doesn't work. At least that doesn't work that well because audio has more entropy. And the, one of the techniques people use is this depth transformer where you you almost have a small transformer, or it can be L-S-T-M-R in as well, but people use transformers and you predict the K tokens in auto aggressive fashion in that.So you have two auto reive things going on.Flow Matching for AudioPavan: So the thing we did differently is in, instead of having this auto aggressive K step prediction, we have a flow matching model. Instead of modeling this as a discrete token set we trained the codec to be both discrete and continuous to have this flexibility.So we did try the discrete stuff too, and which it works well, but the continuous stuff works just better. So yeah, we took this flow matching, so the, it's a flow [00:06:00] matching head, which takes the latent from the main transformer and like kind in fusion, it's denoising, but in this flow matching itself, velocity estimate.So you go from this noise t all the way to there. Audio latent, which corresponds to the 80 millisecond audio and then, which is sent through the work order to get back the 80 millisecond audio frame.swyx: Yeah. Is this the first application of flow matching in audio? Because usually I come across this in the image.Pavan: Yeah. Actually, in some sense there are models flow matching models in audio, but I think this specific combination I could be wrong. There could be somewhat. No. I haven't seen. I haven't seen much work in this, so I think it's novel and a lot of it's just a way bigger community, so they, I think they pioneer a lot of these diffusion flow matching work, and it's interesting to adopt some of the ideas there into audio and,swyx: yeah.Pavan: Yeah, I'm, personally that's the think part which is trying out about. One of more meta point is unlike text, even in vision, I think this is true, but in [00:07:00] audio step literature that there is no.Winner model, yet there is no, okay, this is the way you do things. It's it's still by, I think people are still iterating and figuring out like what's the best overall recipe. I guess the idea. Pretty sure there are models which are also completely end-to-end, like NATO audio. NATO audio, but it's still not come to a convergence point where this, the right way to think that.That also makes. A space pretty exciting to explore.Real Time Voice AgentsVibhu: What are some of the ways to look at it?Vibhu: There are ways where you can do diffusion for audio generation, but if you want like real time generation, that's a big thing with the approach I'm assuming that you took. Yeah. And also like how do you go about evaluating different axes of what you care about, yeah,Pavan: good point. I think we so you can do just flow matching diffusion for the whole audio. We didn't even go down that path because one of the main applications is voice agents and we want real time streaming, and that's the use case. That's not the only use case, but that's one of the primary use cases we want to get to.So we [00:08:00] picked the auto aggressive approach for that. And within the auto aggressive space, again, you can do chunk by chunk or you can do so we picked the. I think at least personally prefer the operations, which are the simplest, and so we try to see, can we just add audio as just another head to our regular transformer decode model because that kind of makes it easier for eventual end-to-end modeling of audio text native modeling.Yeah. And it works pretty well. So I guess we went with that and we tried a little bit, but the flow matching head itself, like we had a discreet. Diffusion kind of approach, which also works well, but the flow matching work better.swyx: I was just curious about how you also think about this overall direction of research.Do you basically, when you work with the audio team, do you set some high level parameters and then let them explore whatever, or how does it work between you guys?Guillaume: No I think the way it works is that we are the, we are prioritizing together, I think, what are the most important features because there are many things we can do [00:09:00] in audio.Yeah, I think we try to. These are like how we should do things, for instance. Ultimately what we want to do is to build this through duplex model, but we are not going to start this start there directly, I think is. Some of the project people are doing, butswyx: just to confirm, full effects means it can speak while I'm speaking or,Guillaume: yeah.Okay. Audio. Yeah. Yeah. So intimately we're going to get there, but for us it was, we decided to take it like a step by step. So we start with whatever is the most important. I think support customers, which is the transcription is the most popular use case. Then the speech generation, Soviet time, just a bit before that.And then actually to be like more, but try combining everything all together. But but yeah, we thought it was also important to like separate things and optimize each capability one by one before weswyx: measure of that together. And the super omni model. ButGuillaume: very interesting because as Par said, it's when you work on some other domains of this airline and everything, there are many areas where I think it's not as interesting.For instance. Many places, it's essentially just around data or like creating new environments on a lot of kind [00:10:00] of easy things. But things were, I think the research is maybe not as interesting. Were in audio. There are so many ways to actually build this model. So many ways to go around it. That's the sense I think is really interesting.And what we also tried for speed generation is that we tried multiple approaches. What was interesting that even though they were extremely different, they under the big know the particles but the for matching turned out to be quite more natural. So we are happy with this.swyx: Is there intuition why it maybe like flow matching is just models speech better in some natural fundamental, latent dimension?Pavan: No, I think the main thing is e even at a particular time step, there is a distribution of things.swyx: Yes.Pavan: To be predicted like the way you inflate. So you already know the word that you're speaking and Yeah. The intake space, let's say the word maps register a single token for simplicity.In most cases it does. So there is not a lot of so you just pick the word, but with within audio, even the same word could, even with your own voice, could be inflicted in so many different ways. And I think [00:11:00] any approach which like models this distribution and. And flow matching is one, one of the take.It's not the only one at all, but it's a one which works pretty reasonably well. I think that's better. So you have to pick across several different, the intuition I have is it's, there are some, several different clusters each corresponding to some specific way you would inflict, pronounce that thing.And you can't predict the mean of it because that corresponds to some blurred out speech or something like that. But you have to pick one. And then like sharpswyx: conditional inference.Pavan: Yeah, exactly.swyx: Is that all covered under disfluencies, which is I think the normal term of art. Pauses intonations. By the way, I have to thank Sophia for setting all this up, including like some of these really good notes becausePavan: Yeah.swyx: I'm less familiar with the audios for me.Pavan: No. I think dis dismisses are definitely one such Eno defenses is more likeswyx: which is arms are.Pavan: Yeah, arms. And also repeat like you like,swyx: yeah.Pavan: You do this full of words, your thinking, so you repeat the word.swyx: Okay. Whereas intonation is like a diff, it's up up [00:12:00] speak and all this.Okay.Pavan: Yeah. So I think there is a lot of like entropy. And modeling it as a distribution. And a, any technique which helps with it and the depth transformer is a conditional way of modeling this. And Transformers actually really good at it, even though that's a mini transformers. So I think that worked pretty well too for us too.It's just that the main concentration is when you have a depth transformer. If you have K tokens, you need to do K auto steps, right? Even though it's a small thing, it's K steps, which is very vacant, say heavy, but flow matching. We were able to cut it down significantly. So we are able to do the inference in quad steps or 16 steps and it works pretty well.And there are more normal techniques to bring it down even further to like, in extreme case, one step like we're not doing it yet, but it at least the framework, LEDs itself to more efficient and Yes.swyx: And the image guys have done.Pavan: Yeah.swyx: Incredible work guys. Yeah.Pavan: It now you just. Send a prompt and you get an image.swyx: Yeah. Surprisingly not enough. I think image model labs use those techniques in production. I think it's, I feel like it's a lot of research demos, but [00:13:00] nothing I can use on my phone today.Guillaume: The thing, there's a thing that would be interesting here is that since, indeed I've been so much sure that has been done in the vision community compared to radio dys, stomach, I think there are so many long infra Yeah.And there are so many things we can do to actually improve this further. So it's our first version, but we have so many ways to exist, much better and much more efficient, cost efficient, soswyx: yeah.Guillaume: So really it's not a new field at all, of course, but there are still so many things that can be done.Perfect. It'sswyx: nice. I should also mention for those who are newer to flow matching, I think the creator, this guy's name is Alex, he's done I think in Europe's maybe two Europes as ago. There was, there's a very good workshop. There's one hour on like this matching is I would recommend people look that up.That's the other thing, right?Efficiency and Model Strategyswyx: The efficiency wise, like I, I imagine like the reason is open weights the reason you pick 3.6 B backbone it you are 3.4 B you are, try to fit to some kinda hardware constraints. You kinda fits some kinda basic constraints. What are they?Guillaume: Not necessarily, I think something we care about in our model that they're efficient.So we have a [00:14:00] lot of separate model, for instance. So we have this that is very small, very efficient. We also have a small OCR model that is available. Good, highly efficient as well. And I think on a project maybe there, I think companies are going to take is to have a coverage general model that will do a bit of everything.But that is also going to be expensive. On here. What want say is if you care about this specific use case, if you can actually use this model, it just does that. It's extremely good at it. Survey, very efficient. That's why we can actually add. We do, but also OCR that are like really good at that.And that would be much more cost effective factors and the general model that will contain a lot of capabilities you don't really need. So yeah. So we're doing like general model, but also like more customized model. This,Open Weights and BenchmarksVibhu: how does it compare to other TTS models? It's, we are going follow open wave.We're just dropping it. I think it's pretty good.Pavan: Yeah, I think it's pretty good. Like it, it's definitely one of the best. For sure. It's probably I would say it's the best open source model, butVibhu: decipher themselves.swyx: Yeah.Voice Agents VisionVibhu: Why now? How does it fit into broader ral vision? How do you see voice agents?How do you see voice? I think every year I've heard, okay, you're a [00:15:00] voice. You're a voice. There's a lot of architectural stuff. There's a lot of end time that see it, your solving, but where do you see voice setting?Guillaume: We had so many customers asking for voice. That's also why we wanted to build it.What's interesting in this domain is that. In a sense, if you take something simple like transcription it doesn't seem like something that should be very hard to do for a model. It's essentially, it's pattern recognition. It's classification on this. Models are very good at classifying, right?Or nonetheless, when you talk to them it's not there yet, right? It's not, you don't talk to them the same way you talk to a person. On something, maybe people don't realize it. It's in English it's still much better than in any user language, even compared to French instance. If you talk to this million in French, when you see people talking to this they'll talk very slow.They'll articulate as much as they can. So it's not natural, right? We're not yet to this. And I think, yeah, maybe the next generation will not know this, but yeah, I think people that. But our edge will actually always keep this bias speaking very slowly when they talk to this model. Even if maybe, probably in a couple of years, maybe next year it'll not be necessary anymore.But yeah. But what's interesting is to see that yeah, even for like languages [00:16:00] like yeah, French and Spanish Germans that are not no, no resource on religion. You have a lot of audios there on still it's not as good. And I think a consequence. Because then for this, I suppose just is not as much energy, as much effort that has been put done in some other mod that for some vision or like coding.But but yeah, there's still a lot of progress to be done. I think it's just a question of doing the work and it's clear path I think to get there.Pavan: It's a little fascinating because I worked on Google Assistant I think while back at this point, but it's, I think it's, it like when you take a step back, it's fascinating.It's not that long ago. It was like four years ago or five years ago, and it's now it's completely audio in, audio out and the function calling and the whole thing happens completely end to end. And in a very natural,swyx: yeah,Pavan: natural way and still ways to go. Kim was telling, even despite all the previous, it's not like you're speaking to a person.When you talk to any of these agents, bots, or voice mode kind of situation, it's still like a gap. I think that's the great part and I feel like with even the existing [00:17:00] stack, we should be able to get to this very natural speech conversational abilities soon enough I guess.And we'll also hope. I get thatGuillaume: on this kind of the next step, right? Because when you talk to these agents, like usually people are just writing to them and sometimes they'll this very clear, for instance, you are, you want to write code, but you are, you have a very clear idea of how you want the model to implement what you in mind.But so here you are able to spend a lot of time writing. So it's not really efficient on audio is really like a natural interface that is just not there yet, but I think it's just gonna be the place.Vibhu: How's it like building, serving, inferencing, like we see a lot about, it's very easy to take LMS off the shelf, serve them.Fine tuning, deploying. I know you guys have a whole you have Ford, you have a whole stack of customizing, deploying. Is there a lag in getting that. Like distribution channel. Are you helping? There is. So like prompting, lms, you can have them be concise, verbose, all that.They're built on LM backbones, these models. How do you see all that?Enterprise Deployment and PrivacyGuillaume: Yeah, I think this is a lot of what we're doing with our own customers. Very [00:18:00] often they come to us, so it's for different reasons. I think one reason is sometimes they have this lot of privacy concerns.They have this data that it's very sensitive. They don't want data to leave. The companies, they wanted to stay. Inside the company. So we have them deploy model in-house. So either on a, either on premise or on private cloud. So they're not worried that it's given to a third party on the there some leakage.Sometimes they have this kind of many companies have this different, sensitivity of data they have like sometimes channel chat can send it to the cloud has to stay there. So then it creates some kind of heterogeneous workflows where it's annoying. You cannot send some data to the cloud.This one you can, so here, when we actually deploy the model for them, they don't have this consideration. They are like not worried that, this is going to leak. Everything is much easier. So we help them basically do this on the, so it's one of the very proposition. But but the other is very often, when customers use this off the shelf close model, but very sad is that they are not leveraging, these data that have been collecting for four years or something for decades.So much data. Sometimes it's trillions of tokens of [00:19:00] data in a very specific domain. Their domain, which is data that you'll not find in the public, on the public internet. So data on which, like close model, we actually not have access to one, which that's going to be really good. So if they're using like closed source models are basically not benefiting from all these insights.All these data they have collected three years, they can always give it into the context that in France, but is never as good as if you actually train the modern analysis. So yes, that's basically what we help them to do. We actually provide them some purchase, basically what we announced at GTC this week.So we provide them with this, it's basically like a platform with a lot of tools to actually help them process data. Trained on that. Yeah, it's actually the same thing that we're using in the science team. So it's actually very better tested infrastructure, like a lot of efficient training cut base.For a quality pre-training like a fine tuning, even doing S-F-T-I-L. So we help them do this using the same tools as what our science team is building is using. So since it's tools that we've been using for two years now, it's really better tested. It's really sophisticated.So it's the same thing. We are giving to them, giving the company the same thing [00:20:00] that what are same still using internally actually build their own ai and it makes a really big difference. I think sometimes customers. And many in general don't realize how much better the model becomes when you fine tune it on your own data.And you can have a, your model is here. You start from there. You have a cross source model, which is sort here, but if you actually fine tune it can actually really go much further than this. And then you have a very big advantage. The model is trained on your entire company knowledge, so it knows everything.You don't have to feed like 10 K tokens of contact at every query. So it's it's much easier. It's a bit, I think using a closed source model is really sad because it basically puts. You are not leveraging all this data and you are going to be using the same model as all your old competitors when you're actually using, everything you have been collected for years, which is really valuable.So yeah. So we help basically customers do this. We have a lot of solution I mean deployed for engineers that go in the company that basically look at the problem customers are facing to look at what they're struggling to do what we should do to solve it. So we help them solve them together.So it's I think our approach is a bit different, but here. [00:21:00] Some of their companies and competitors, it's, we don't just release an endpoint on sale, do some stuff on top of that, or we don't just give a checkpoint. We really look very closely with customers. We look at the issues they have, we had them solve them.We really make some tailored solution for the client are facing. Some example are also going to be, sometime we have some customers. They really wanted to have a really good model, really performance on some, like Asian languages on the, if you take some of the shelf models, they can speak it, they can write in this language, but it's not amazing.This language would be like maybe zero 1% of the mixture. So it has been included during training, but very little. So what we did here is upgrade. We trained a new model for them, but so this language was 50% of the mix, so it's much, much stronger. It knows of the dialects, it knows the, so it's yeah.So it's some example of things we can do and it's really arbitrary, custom. I think you had some of their customers, for instance, they wanted some. They wanted some 3D model that can do audio with a very good function cable. So something you wanted to put in the car in particular, they wanted this to be offline because in a car you don't necessarily have access to internet.So [00:22:00] yeah. So here we can actually build the solutions. There is no like model out of the box on this. In the internet you have this very, you have this very general model generalist, like he's strong model. But for things like this, they always want at specific solutions and on some other reasons.Sometimes they come to us is because, like they, they experiment with some closed source model. They get some prototype. They're happy with what they build. They, it works well. They're happy with the performance, and then they want to go to production and then they analyze. But it's extremely expensive.You cannot push this. It's so then they come back to us on this. They can help us build the same thing as this, but using something much cheaper on here. And here we can sometime be something 10 x cheaper by just functioning a model and it'll be better OnPrem on their old server and also much cheaper as well.So yeah,swyx: that's the drop pitch right there. Take all themoney.Vibhu: And outside of that you do, we do put open wave models so people can do this themselves. I feel like not enough people go outta their way.swyx: They're not going to, they're gonna ask them to do it as the expert. IGuillaume: think initially we didn't know, [00:23:00] we wanted completely short at the beginning of the company because, I think our study was not exactly the same as what it is today, but what we underestimated initially is the complexity of deploying this model and connecting them to everything to be sure it has access to the company knowledge on the, and it was, yeah, on, we were seeing customers struggling with this, but it was even, that was three years ago and no, things are much more complicated because now you don't just have, text on SFT on a simple instruction following.You have reasoning like your agents, you have like tools. You have a multimodal audio, so it's much more complicated than before. And even back then it was hard for customers. So they really need, have some support and this is why actually providing like always some four D position as well. The processFine Tuning and Personalizationswyx: I'm curious is there also voice fine tuning that people do?Pavan: So in this forge we also have a say unified framework. And the hope is like the er speech to text that we released earlier this year. And even the ER chart that we released last year. And I think a big people, I think there's a big, rich ecosystem [00:24:00] of people fine tuning whisper, and people want the same thing with w so it's much stronger than Whisper.And yeah, the the platform offers that kind of fine tuning yeah, which could be any kind of fine tuning. Like for instance, even sometimes people want to support new languages to this, which are tail languages, which we hope to cover. Certain natively, but if there is a language where you data and you want to frank you, I think this is a good use case.Or the other use cases, you, it's the same language, like even English but it's in a very domain specific way.swyx: Yeah. Terminology, jargon, medical stuff.Pavan: Exactly. And also there's specific acoustic conditions like there's a lot of noise or the, and. The model will do decently in most conditions, but you can always make it better.And that those are some of the use cases where you can improve it e even further. And that's one good use case for this and for text to speech. We're just releasing it so we'll have support for that soon too. I think it's similar use case.Voice Personalization Pavan: It's little different the kind of things that you want to extend a [00:25:00] text to speech model to, which could be like voice personalization, voice adaptation for enterprises.Many enterprises need very specific kind of tone, very specific kind of like personality for this kind of voice. And all of those are like good use cases for fine tuning.swyx: This one I was gonna ask you, we never talked about cloning voice clothing here. How important is it, right?Like I can clone a famous person's voice. Okay. ButPavan: the main use case would be like for enterprise personalization, like enterprises need like a lot of customization. You don't want the same. Voice for all the enterprises. Each enterprise want a customized, specialized something which is representative both their brand and also their, I guess safety considerations and the use case I think the kind of thing that you would deploy as a empathetic assistant in the context of a healthcare domain would be very different from the kind of thing that would be in a customer support bot and would be different from like more conversational aspects.I think those are the. [00:26:00] Customizations you would expect from enterprise. And that's the main use case, at least from our side.Vibhu: My, my basic example is you don't want to call to customer services and have the same exact voice. It's just, it's gonna be weird.Long-Form Speech ModelsLong-Form Speech ModelsVibhu: But also on the technical side of this, so there's like a few things in TRO that I thought were pretty interesting.He's a big fan of this paper. Oh, he said very good paper. He said this is the best SR paper he's ever read. Yeah. I've hyped up this voice paper enough. We covered it. Somewhere, but a big thing. So Whisper is known for 32nd generation a 32nd processing. You extended this to 40 minutes. There was a lot of good detail in the paper about how this was done.Even little niches of how the padding is. So it's very much needed. You need to have that padding in there, the synthetic data generation around this. I'm wondering if you can share the same about the new speech to text, right? Text to speech. So how do you. How do you generate long form, coherent?How do you generate, how do you do that? And then any gems? Is there gonna be a paper?Pavan: Yeah. Yeah. They would be a technical report. Okay. Yeah. I think I could have a lot of details.Real-Time Encoder AdvancesPavan: But me I think the [00:27:00] summary of it, actually, some of the considerations in this paper were, because we started with the wipa encoder as the starting point, and now we have in-house encoders, like the bigger time model, for instance, which we released in January.Also release a technical report for that real time model as well, which is this dual stream architecture. It's an interesting architecture. You should check it out. And there we have a causal encoder and I don't think there's any strong, multilingual causal encoder out in the community. So we thought it's a good contribution.So that's one nice encoder there. Other people want to adapt. That's a good end code. And we train it from scratch. I think her. Post stack is now mature enough that we are able to train super strong ENC codes. And some of these considerations, like spatting and stuff, is a function of the Whisper ENC code.And now that we train encoders, inhouse the design concentrations are different.Scaling Context for TTSPavan: And for the question on text to speech, I think that's also leans onto the original auto aggressive decoder backbone. I think, it says very, almost identical considerations. I think the long context in it's not even long con, [00:28:00] so the model processes audio at 12.5 herds, so one second maps to like 12.5 tokens.So I think one minute is like 7.8 tokens. You can get like up to 10 minutes in eight K context window and get half an hour and 30 K context window. So that's and 30 2K context is something that's we are very comfortable training on. We can extend it even much longer. 1 48 K. Okay. You can naturally see how it can extend to even our long generations.Yeah. We need the. Like data recipe and the whole algorithm to work coherently enough through such long context. But the techniques are some way very similar to the text, long context modeling. And the key differences, it's just doing flow matching order regressively instead of a text open prediction.swyx: Okay. I think that was most, most of the sort of voice questions that we had. ButWhat Makes a Model SmallVibhu: I have a big question on Mr. Al, Mr. Small. So what is small? How do we define [00:29:00] small? What is this? What is this? I remember the days of Misal seven B on my laptop. The snuff fitting on my laptop. I could run it on the big laptop, butGuillaume: it's just additional.Question of terminology, like here what we did, baseball is north active parameters, but it's true. Really not give it another name, but yeah, we could have called it medium, but only, I,I suppose it's a model that we released mixture of experts. It's a model that combines different model before which we were doing the same, is that we had one model, general model for Israel. Doing instruction following, were like a separate model that was Devrel trial. So qu coding specify specific to code with another model for Reason Maal.So this were separate artifacts built by different team at trial on what we're doing is basically merging all of this. It was, you had pixel trial was the first vision model. We was like a separate model on the way we do things internally is that we have one team focus on one capability, build one model.On the means mature, mature enough, we decide to merge this into the [00:30:00] matrix. But here it was the first time we basically match all of this into one. But there are some other things we did at first time to merge time, for instance, like more capabilities or function coding I think would be, are, it's going to be much, much better in this trial, small platform.But but yeah, so it's our latest model on the working is,Vibhu: and yeah, key things is it's very sparse. Six, be active pretty efficient to serve. 2 56 K context. Yeah,Merging Capabilities vs Specialistsswyx: I think what's interesting is just this general theory of developing individual capabilities in different teams and then merging them.Where is this going gonna end up?Vibhu: Like we've seen the five things put together in this. Yeah. What are the next five teams?swyx: I think actually OpenAI has gone away from the original four Oh. Vision of the Omni model. This was what they were selling. All modalities and all modalities out.But I feel like you might do it.Guillaume: I think there's some mod where it's not competitive use, for instance for audio. For audio here, if you want to do transcription, I think it makes no sense to use a model. If you just want to trans tech it, it'll be very inefficient. If you want to do audio, you probably just want to be the [00:31:00] one VR 3D model performance essentiallyswyx: the same.It's going to be incredibly cheaper. So here, that's why we wantGuillaume: to have a separate but just does this. Yeah, I think the question is just, yeah. If you are to, to your model. By speech and you asking like a very complex questions on how you do this on the, just to cascade things. Do you want to put a d in a model that has like a one key around it?It's like a, not a competitive discussion, I think unaware if you doing into the direction, but that's possible. Of course. But yeah. But I think for us, the next capabilities we want to try to integrate into these models when we are going to be yes, like marketing or no reasoning better, I think more capabilities that people don't talk too much about, but at high bottom, I think for our customers in our, on different industries, for instance, things are around like a legal computer.I design all these things that is this males out of the box are to put at that. Because people, if you don't prioritize this, there is not like too benchmark on that. Butswyx: this done how toGuillaume: make this good and this just start to do the work. Extracting some that processing it [00:32:00] expression. So yeah.But we are offering the imagine to this.swyx: I think for voice. Yeah. The key thing I think over maybe like the last year or so with VO and gr Imagine and all these things is joining voice with video, right? Which people don't understand spatial audio because like most TTS is just oh, I'm speaking to a microphone in perfect studio quality.But when you have video, like the voice moves around.Pavan: That's true. The constitution was a little different in the sense that there it's like a a standalone artifact where you get the whole thing and you consume it. But in a conversational setting, it's a, you need the extreme low latency.swyx: Yeah,Pavan: streaming would be one of the primary concentrations.swyx: You can build a giant company just doing that, right? So you don't need to do the voice, but I was just know on the theme of merging modalities, that is something I, I am like, wow. Like I didn't, everyone up till, let's say mid last year was just doing these like pipelines of okay, we'll stitch a TTS model with a voice thing and a lip sync [00:33:00] thing and what have you.Nope. Just giant model. Yeah.Open Source MissionVibhu: I have a two part question. So one is, it's still open. It seems like open source is still very core to what you guys do and I just have to plug your paper. Jan 2024. This is the one trial of experts like. Very fundamental research on how to do good.Moes paper comes out very good paper for anyone. That's just side tangent. No.swyx: This thing caused, we bring back, eight by 22 was like the nuclear bomb for open source. I think it takes Shouldn be more seven B more. Yeah. Yeah. But this is a bigger opposite than me.Yeah. Yeah I don't remember this. I remember, I don't think it was January, right? It was like new reps it was, it dropped during new reps and everyone in Europes was December of 25th, I think. Yeah. The model was did as well.Vibhu: It's just a little update probably.swyx: Yeah. No, but you have a point to make.Vibhu: No, you gotta check that. But then, I just want to hear more broadly on open source for you guys, and when you had asked earlier [00:34:00] about what's next, what are the other, side tapes working on you. You put out Lean straw. This,swyx: it's not necessarily surprise. I was like, I don't, this doesn't fit my mental model or Misra.Guillaume: Yeah. First for open source in general, I think it's really something which looks to the January of the company. I think we started it per once, is we so we have open sourcing with, since the beginning and even before this. So before this, so me and Tim were at Meta, we released LA and I think what was really nice.To see that before this, for most researchers like universities, it was impossible to work on elements. There was no alien outside. And if you look at many of the techniques that were developed after, for instance, was open source all this post-training approaches like even DPOD, like preference optimization, all of this were done by people that had access to this portal.And it'll have been impossible to do without this. So it's really making sense, move faster. So we really want to contribute to this ecosystem. I think like the deep and also like very lot of impact. All these papers that are I think in the open source community are really helping the science community as a whole to move faster.So [00:35:00] we want contribute to this ecosystem. That's why we're releasing very detailed technical reports. So ma trial and our first reason model, and ation, lot of results, things that work, things that did not work as well. Think helpful on the, yeah, so for the audio model also to share a lot of details, share of them for real time model.And the, yeah, so we really want to continue this, basically belong to this community of people who share science. I think we really don't want to be, leading in a world where the smartest model, the best models are only behind, close doors. Only accessible to a shoe companies that we, as a power to decide we can use them on it.I think it's a scary future. We don't want to live in, we really want this model to be accessible to anyone that want. Intelligence to be used unaccessible by anyone who can use it. So yeah, so that's why we are pushing this mission and source model. Yeah. So not, so yeah, no strategy. So it's open source, not the first model, so not the best on the Yeah.Lean and Formal ProofsGuillaume: LIN trial I think is also one step into this direction. So it's yeah, a bit different than what we are usually releasing. But we have a small team internally [00:36:00] working on them. Formal proofing, formal math. So I think a subject we care about in general and we were working on reasoning. I think we started too early before doing reasoning without LMD is very hard, especially when you work with formal systems because the amount of data you have is negligible.It's addressable community of people writing like formal proofs. But the reason why we like it is because I think there is if you look at what people are doing with reasoning, is there, the problems that you can use. Are usually going to be problems where you can verify the output. So for instance, all this ai ME problem where the solution is a number between 100, like a thousand.So you can verify, compare this with a reference or it's an expression. You can actually compare the output expression generic with the reference. But there are many, most of them have problem and most of the reason problem. There is no like way to easily verify the solution. If the question is show that F is continuous, cannot compare in the reference, right?If it's a probe that this is true or probes is properties, there is no way to. You cannot act, simply verify the correctness of your proof. So it's hard to apply the, there is no referable reward here. So [00:37:00] what you could provide is of course, like a judge and judge that will look at your proof. But it's very hard and it's very, you could do certain, some reward hacking happening there.So it's difficult. You could provide like a reference proof, but then there are also many ways to prove the same thing. So if the model says give negative reward because it's a different poop, maybe it was still digit proof, just different. So it's not going to work well. What's nice with lean and with formal probing is that you don't have to worry about this whatsoever.We just,swyx: they're all function is largely compiles in lean is functionally the same. Exactly.Guillaume: It's like a problem if it compiles it's correct. It's very easy. And you can apply this and then you can,swyx: it's just way too small. So no human will actually go and do it.Guillaume: Yeah, that's exactly.It's the only people can do it. It's like a very small committee of people doing a PhD on that. So it's super small. And it's sad because it's actually very useful on not just mat, but also in software verification. So for instance, software verification today. So tiny market. Very few industries work on this and we need that.It's usually going to be like companies like building airplanes, air robotics,swyx: likeGuillaume: things [00:38:00] where they absolutely want to be sure. Life depend on this, but it's very rare that people formally verify the correctness of their software. But I think one of the reasons for this is simply that it's just hard to do.swyx: Are you think of TLA plus? It's the language that some people do for software verification? No. That people use in a ference, but but yeah, it's the reason I think why people don't use it more and why this industry is not as big as could be is because it's very hard. But now with cutting edges that are there, it's going to be very different.Guillaume: We're going to see much more of this. So I think yes, industry there is going to be much larger in the future that we, these models. So yeah. Here also anticipating this a little bit, we wanted to work on that because it's proving like a math theory and like a, essentially the same tools.swyx: Yeah.Reasoning Transfer and Agentsswyx: One of my theories is that because the proofs takes so long, it's actually just a proxy for long horizon reasoning and coherence and planning. Maybe a lot of people will say okay, it's for people who like math. It's for being okay. It's like a niche math language. Who cares? But actually, and you use this as part of your data mixture for [00:39:00] post-training and reasoning, actually, it might spike everywhere else.Yeah. And I think that's un under explored or no one's like really put out a definitive paper on how this generalizes.Guillaume: Yeah, absolutely. AndPavan: I think evenGuillaume: that's what we're seeing already. For instance, you should do some reasoning on math as then the American should do reason even.Yeah. In the early stage. So we, the, there is some transfer, some sort of emergence that happens. And I think some, it's also interesting, it's not just I think the topic in general, but it's, there is a lot of connection with this on including agents because. Sometimes the model can see like a three that it has to prove it's very complex, but then it can take the initiative to say, I'm going to prove this three lr.I'm going to suggest three Rs, and I'm going to in parallel prove each R. So three of them in parallel with sub agents, but I'm also going to prove them in theory and the three tool so you can do this also. Pretty interesting. You can, even if you fail to put one of the LeMar, you can actually, maybe you succeed to put the normal lema too, so you get some possible reward here.So it's a bit less Spartan issue, just get to zero one for the entire thing. [00:40:00] So it's pretty interesting. I think we can actually,Vibhu: yeah, it's also an interesting case just for specialized models in general, right? Like the cost thing you show is pretty interesting yeah, similar score wise, you are, thirty, seventy, a hundred fifty, three hundred bucks.Smaller.swyx: I think cost is a bit unfair, right? ‘cause this one is at like inference cost. It's always there on top with their margins on top of it. But, we don't know anything else, so we gotta figure it out.Vibhu: Okay.Next Frontiers in TrainingVibhu: I did wanna actually push on that more. Not on cost, but you mentioned about, okay, it's a great way to have verifiable long context reasoning.What are other frontiers that, I'm sure you guys are working on internally, there's a lot of push of people pushing back on pre-training. Scaling, RL pushing, compute towards having more than half of your training budget. All on rl. Where are you guys seeing the frontier of research in that?Guillaume: You mean theVibhu: just in foundation model training in the next, one thing that you guys do actually is you do fundamental research from the ground up, right? So you probably have a really good look at where you can [00:41:00] forecast this out.Guillaume: Yeah. I think for us we're still working a lot on the pre-training side.I think we are very far from situational, the pre-training. I think ML four preprinting will be like big step compared to everything we have done before. So we are pretty excited about this. And I think on the other side, I think now we have more and more to think about this algorithm that will actually support this very long trajectories.I think when it was, for instance, GRPO for it doesn't really work this any bit of policy. Which was okay initially because you are solving math problem that can be solved in like a few thousand tokens. So the model can alize them pretty quickly. So when you do your update, the model is never too far off.It's never too far off. But now when you are moving towards this kind of problems where certain takes hours, like six hours to get a reward, then your model is co pick places. So you have bi new infrastructure that supports this, but also new A, so now everything we're doing internally, we're trying to. Build some infra that we actually anticipate is what we have in six months, one now, which is this extremely no scenarios on the, I think when we started Missal, part of me and [00:42:00] we wanted to, is very nice under element where people are there, they can do research, they like with a lot of resources.So it was nice. I think things changed a lot when I think when J Pity came out. I think after that I think was. This one is same again. But but yeah, but it was nice. And I think we also want to work part of this descrip beforeswyx: coming to the end.Hiring and Team Footprintswyx: We're just, obviously, I think you guys are doing incredible work.You've, they are a very impressive vision for open source and for voice. What are you hiring for? What's the what are you looking for that you are trying to join the company?Guillaume: Yeah, so we are hiring a lot of people in our sense team. We're hiring, in all our offices. So we have a, our H two is in France in Paris.We have a small team in London. We like a team in Pato as well. Co we open some offices in in SAU, in Poland. So one in Zurich. We also like some presence in New York as well on Sooner one in San Francisco. So we all bit either way also like hiring remotely. So we're going the team trying to hire like very strong people.I think we want to stay, so the team is not. Instead of fairly small team. [00:43:00] But I think we want to keep it that way. ‘Cause we we find it quite efficient. So like a small team they agile so yeah.swyx: Okay.AI for Science Partnershipsswyx: Let's focus on science and the forward deployed. We actually are strong believers in science.We started the our new science pod that focuses specifically on the air for science. What areas do you think are the most promis.Guillaume: What we're pretty excited about right now, and something we have already started doing or that we'd probably be able to share more about this in a couple of months, is that we are exploring AI for science.And there are a lot of areas where we think that you could get some extremely promising buzz. If you were to apply AI in these domains. There are a lot of long inputs. You just have to find these domains where actually AI has not been yet applied, and it's usually hard to do because the people working in those domains don't necessarily know the capability of these models.They don't know. How I would just have to pair them with Yeah, exactly. Your researcher slashing, which is actually hard to do. But this matching, we're doing it naturally with our customers. So we have some company we are very closely with. So for instance, ISM Andreesen are one of our partners, so we're doing some research with them on their other, like tons of extremely interesting problems.Columns in physics, in [00:44:00] science matter science that they're essentially the only ones to work on. ‘cause they're doing something No, no one else is doing on the, yeah. So there are many domains where AI can actually revolutionize things. Just you have to think about it on you familiar with what can do or to apply it.So yeah, it's something where more modeling with our partners, with our customers sort AI for s, but.swyx: Yeah. Okay.Forward Deployed Skillsswyx: And then for deployed what it makes a good four deployed engineer, what do they need? Where do people fail?Guillaume: I think it's usually you need people that are very familiar with the tech and not necessarily with a lot of research expertise, but that are actually pretty good at using this model that can actually like that know how to do functioning, that know how to like, start some error pipeline.And it's it's not easy. It's something that mucus. Majority of companies will not be able to do this on their own. So here I think we need people that are, that like to solve problems that are accept solving some complex, very concrete problem. It's applied science basically.And yeah, so I think it's not too different. I think from the case you need in research because it's essentially you are trying to find solutions to problems that in [00:45:00] customers have not yet. So sometimes it's easy. Sometimes you're here to do the work. You have to like create synthetic data.Find some edge case. So it can be, yeah. Depends on the problem. But but yeah, you have to, I think it also a bit of patience on the be creative. I think very similar skill is Asian,Pavan: the diversity of the work they do. It always surprises me. It's it's, it goes all the way from the kind of stuff they encounter in industries.It's just very interesting. I think.swyx: Any fun like success anecdotes.Guillaume: Yeah, it can be actually training this small model on edge that just we do one specific thing can be like training some very large model without some specific languages as well. Making models really good at some tube use, like for instance, computer ID design, these kind of things.Is that pairing with vision as well? Yeah,Pavan: and the fact detection for chips or like in, in factories identifying things like it, the. Diversity could be anything where you can deploy these foundation models. So yeah the work to make it work in that specific setting, basically whatever it takes to make it like add value in that, by the way, workflow.Vibhu: Yeah. [00:46:00] And it goes across the stack, right? Like even just pulling up the website like.swyx: It's so broad on compute. It is so broad.Vibhu: We didn't even touch on if you have a coding CLI tool. One thing you guys were actually like, I think the first tool was agents, ral agents. You had the agent builder, you can serve it via API and all that.And I'm guessing forward deploy people.Guillaume: Yeah.Vibhu: Help build that out and stuff.Customer Feedback LoopGuillaume: It is also why we are, so we're doing many things, but I think that's also part of the value proposition that sometime know customers. They're always very. Extremely careful about their data and they don't want to, they don't like, trusting so many partners, trusting one partner for code, giving the data to another third party for like audios and another one.So they don't like this here. What they really like with our approach that we can help them on anything so they don't have to send the data to so many clouds. So yeah,swyx: I think that there can be many orders of magnitude more. F Ds then research scientists and they don't need your full experience, but they're still super variable to customersGuillaume: in practice.These two teams [00:47:00] are still quite intertwine, very often. Yeah. So first of all, they're using the same tools, the same data pipeline and everything on the, it's it's very helpful for the science team to get the feedback and the solution team ‘cause they can. Look at these customers are trying to do this.This is not working. It can really be show in the next version. Yeah. But this is basically a real world eval. Yeah, it's real world eval and it's not something, for instance, if you're just working in the lab, it's just ships model. But you don't do this work of for customers. You have no idea for whether your model is good at this H case.For instance, you even in year found this, right? So yeah, there is a very gap, big gap between the public benchmarks that are very like academic. OnPavan: the rare cases are just very diverse and in the specific concept of a customer, you can fine tune and make it like first evaluate, create a solid eval, benchmark, and then measure in the context of their, the kind of audio.Like for instance, one use case is literally just, there's the word for kids and they have to just say it out. It's a very specific thing. You're just saying one word and then you have to you, you'll grade the kid whether they did it right or not. It's [00:48:00] like R for, but so there're very diverse use cases and the idea is that they, the.Applied scientist engineer will go and make it better. And then from the learnings we incorporate it into the base model itself. So it's it's just better out of the box.Vibhu: Yeah. It's a good full circle system. Like the foundation model evals are all just proxies of what you really, you're never gonna have one that says it, it doesn't make sense for there to be, a one word transcription like that.It's not something you wanna fit on. Perfect.Wrap Up and Thanksswyx: Everyone should go check out everything that Michelle has to offer and try the TTS model, which will link in the show notes. But thank you so much for coming tha thanks. Such a stretch. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.latent.space/subscribe

Sharath Reddy, Senior Vice President of Corporate R&D at Magna, joins Michael Cason, Senior Engineer at Munro, for a deep dive into the evolving world of EV development. As electrification accelerates, the conversation explores the shift from component level design to fully integrated systems level engineering and what that means for the future of vehicle innovation. They also unpack the growing role of software and ADAS in shaping next generation vehicles and how these technologies are redefining performance, safety, and vehicle identity.Munro Live is the media division of Munro & Associates, an engineering consulting firm with a design-first approach. At Munro, we specialize in costing, benchmarking, and product & manufacturing optimization, helping our clients reimagine their products and processes to achieve better business outcomes—driving down costs while increasing efficiency, performance, and quality.At the core of our work is Lean Design®, our proprietary methodology that optimizes design efficiency and consistently delivers exceptional ROI for our clients.Munro - Home of Lean Designhttps://leandesign.com/

On this episode of the South Carolina Lede for March 204, 2026, we look at the legislative week ahead with the House back in along with the Senate and more.

Our guests are Seinfeld writers, Seinfeld actors and actresses and Seinfeld crew. We also welcome well-known Seinfeld fans from all walks of life including authors, entertainers, and TV & Radio personalities. We analyze Seinfeld and breakdown the show with an honest insight. We rank every Seinfeld episode and compare Seinfeld seasons. If you are a fan of Seinfeld, television history, sitcoms, acting, comedy or entertainment, this is the place for you. Do us a solid, support the Podcast Use code THIRSTY for 10% off awesome Golf Apparel at ⁠⁠⁠⁠flopshotgolfer.com/THIRSTY⁠⁠⁠⁠ Website:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://www.seinfeldpodcast.com⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ iTunes:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://apple.co/2RGC89m⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Spotify:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://spoti.fi/3tqDVh6⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Social:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://linktr.ee/ThisThirsty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Twitter:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://twitter.com/ThisThirsty⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram:⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.instagram.com/thisthirsty/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠"This Podcast Is Making Me Thirsty" is The #1 Destination For "Seinfeld" fans. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

This episode delves into the silent struggle behind avoidant personality disorder, the crippling fear of rejection, and how treatment is finally making progress.Are you or someone you love trapped in a cycle of loneliness and fear of rejection? Recent research and real-life case studies reveal powerful new insights about avoidant personality disorder, this deeply misunderstood disorder that's likely more common than you think. Social avoidance is especially common now, as social media and remote life intensify those feelings of inferiority and rejection.In this episode, Dr. Kibby dives into what avoidant personality disorder is, how it's different from social anxiety, and how core beliefs of inferiority shape every aspect of life and relationships. She discusses how avoidant personality disorder stems from beliefs originating from unmet childhood needs, and how misguided coping mechanisms (e.g. withdrawing, self-criticism, and overthinking) perpetuate emotional pain.Dr. Kibby breaks down the latest research, including a groundbreaking 2024 clinical trial testing cognitive behavioral therapy and schema therapy for this disorder. She shares compelling case examples, illustrating how understanding and gentle, sustained therapy can help individuals slowly soften their defenses, confront their fears, and build genuine connections.If social rejection, shame, and feelings of worthlessness dominate your life or the life of someone you care about, this episode might explain why. Learn about innovative treatment strategies that target the core beliefs fueling avoidant traits and why patience and persistence are essential for lasting change.Resources:Balje, A. E., Greeven, A., Deen, M., van Giezen, A. E., Arntz, A., & Spinhoven, P. (2024). Group schema therapy versus group cognitive behavioral therapy for patients with social anxiety disorder and comorbid avoidant personality disorder: A randomized controlled trial. Journal of Anxiety Disorders, 104, 102860.Kohli, T. K., Manjula, M., Arntz, A., & Reddy, Y. J. (2026). Schema Therapy for Avoidant Personality Disorder: Working with Dysfunctional Coping Modes. Indian Journal of Psychological Medicine, 02537176261418993.

In this episode, we're diving deep into ultra-processed foods — and why cravings in your 30s, 40s, and 50s are not a character flaw. If you've ever: Felt compulsive around certain foods Wondered why you “used to have more willpower” Eaten for stress relief and felt ashamed afterward Asked yourself why your partner can stop but you can't This episode is for you. There are three major biologic reasons why cravings intensify during this season of life: 1️⃣ Engineered hyper-palatable foods Modern ultra-processed foods are scientifically designed to manipulate salt, sugar, fat, texture, and glycemic response — overriding normal satiety signals and strengthening dopamine tagging in the brain. 2️⃣ Chronic stress physiology Stress amplifies cravings for energy-dense foods. These foods temporarily shift serotonin and dopamine signaling, creating relief — but worsening the long-term cycle. 3️⃣ Perimenopause & progesterone decline As ovarian reserve shifts in your late 30s and beyond, progesterone drops. Less allopregnanolone support at the GABA receptor means higher anxiety tone — and weaker “brakes” on impulse control. This isn't about willpower. It was never a fair fight.   Citation: Episode 2 – Mechanism-Anchored Evidence Map: Ultra-Processed Foods, Reward Signaling, Stress, and Hormonal Vulnerability Ultra-Processed Food Engineering – Salt, sugar, fat, and texture are manipulated to maximize reward signaling and overconsumption. (Fazzino et al., 2019; Gearhardt et al., 2011; Hall et al., 2019) Dopamine and Reward Tagging – Dopamine marks important stimuli, reinforcing repeated behavior and “wanting” rather than pleasure. (Schultz, 2016; Berridge & Robinson, 1998) High-Glycemic Carbohydrates – Increase tryptophan availability and serotonin synthesis, influencing mood and short-term relief. (Fernstrom & Wurtman, 1972; Wurtman & Wurtman, 1989) Chronic Stress – Alters reward circuitry, increasing vulnerability to compulsive behaviors. (Piazza & Le Moal, 1998; Sinha, 2008) Progesterone, Allopregnanolone, and GABA – Hormonal neurosteroids modulate GABAergic inhibition, stress buffering, and reward sensitivity. (Paul & Purdy, 1992; Reddy, 2010; Purdy et al., 1990) Sleep and Appetite Regulation – Hormonal and neurosteroid pathways influence sleep; sleep disruption increases hunger and cravings. (Tasali et al., 2004; Purdy et al., 1990) Summary: These mechanisms explain why hyper-stimulating foods are particularly compelling during chronic stress and hormonal transitions, showing cravings are biologically reinforced rather than a matter of willpower.   Dr. Brendan McCarthy is the founder and Chief Medical Officer of Protea Medical Center in Arizona. With over two decades of experience, he's helped thousands of patients navigate hormonal imbalances using bioidentical HRT, nutrition, and root-cause medicine. He's also taught and mentored other physicians on integrative approaches to hormone therapy, weight loss, fertility, and more. If you're ready to take your health seriously, this podcast is a great place to start.  

Our podcast guest today is Dr Satya V. Reddy who is an anterior segment surgeon in Louisiana, USA and we talk about one of the most important issues that you will face in your life: how to balance building a practice with having a family (and personal) life that you can enjoy. I have struggled with this and have made many mistakes. Now we realize that the concept of "delayed gratification" may not be the best approach. We talk about the challenges and how to figure out the right recipe and balance for you and your life. I know you will find this very useful.We feature a new podcast every week on Sundays and they are uploaded to all major podcast services (click links here: Apple, Google, Spotify) for enjoying as you drive to work or exercise. The full video of the podcast is here on CataractCoach as well as on our YouTube channel. Starting now we have sponsorship opportunities available for the top podcast in all of ophthalmology. Please contact us to inquire.

Can't believe we are saying this but How Cum is now-- How Came, and How Went! In other words, after 6 seasons and countless guests and a million different topics we are finished. Today's episode is all about what got this whole thing started-- female healthcare (or the lack thereof) and we are discussing it with Tia's Dr. Shreya Reddy and comedian Lauren Hope Krass. We are talking why Dr. Reddy entered this field, Tia (a clinic specifically for female healthcare), and how Lauren's life has been changed by Tia. My life was changed IMMENSELY by this podcast and I am so so grateful to everyone who supported this journey and who came along for the ride. We may still record some new episodes -- and if we do, they will ONLY be posted on Patreon, and maybe someday it will even C*M BACK in a big way. But for now it is so long, and thank you, and I love you all very much.   Did You Love How C*m? -- RATE, REVIEW & SUBSCRIBE  You can STILL put your first O experience on our first time map it is as anonymous as you would like it to be! Follow / DM us at @HowCumPodcast @RemyKassimir Support the podcast/ get extras like this Post Coitus chat on Patreon Check out our website for merch!

“We keep iterating on an old construct—let's stop and start over. How do we want to do things differently? Let's get back to first principles.”KP ReddyEpisode Summary:In this special ElevateAEC 2025 edition of The Zweig Letter Podcast, we're sharing KP Reddy's keynote from the main stage—a straight-talk session about where innovation in AEC is actually heading. Drawing from real conversations with major owners, hands-on research, and his own experience as an engineer and investor, KP breaks down why the industry's current approach to innovation isn't cutting it—and what needs to change.He tackles the questions that matter: What do owners actually want? How can AI and agentic systems make a real difference? And what would a new master builder mindset look like today? This keynote delivers practical insights and honest challenges for AEC leaders ready to rethink how they approach business, technology, and client value.Key Takeaways:Owners Want Real Innovation, Not Lip Service: True innovation means solving problems in significantly better ways—not just adopting new technology for technology's sake. Owners are craving AEC partners who listen and deliver true value.Communication Gaps Hurt Everyone: Clients frequently feel like outsiders in the process, with their feedback often ignored. Successful firms will prioritize transparency, owner-centric approaches, and collaborative requirement gathering.Tech Is a Tool—Not the Solution: Despite years of BIM and other advancements, core challenges with cost, schedule, and quality persist. The next leap forward will come from integrating AI, agentic design, and robotics as part of service delivery—and from business models, not software alone.Business Model Reinvention Is Essential: Shifting away from headcount-driven metrics, AEC firms should explore skin-in-the-game approaches—like bonuses for outcomes, equity stakes, and public-private partnerships.Client and Product Manufacturers Must Both Change: Building-product innovators report frustration as AEC professionals and owners often resist new solutions. KP encourages the industry to break the cycle of “the way we've always done it” and fully explore prefabrication, modularity, and automation.All this and more on this episode of the Zweig Letter podcast.KP Reddy is the founder and CEO of Shadow Ventures and a recognized voice on innovation in architecture, engineering, and construction. With expertise spanning AI, robotics, and automation—plus his role as a lecturer at Georgia Tech—KP brings practical strategies that push the AEC industry forward.Links referenced in this episode:Shadow VenturesKP Reddy on LinkedIn"Creating the Intangible Enterprise" by KP ReddyZweig Group & ElevateAEC ConferenceLearn about the Zweig Letter and subscribe: https://thezweigletter.com/Connect with Randy Wilburn on LinkedInGet your FREE Subscription to the Zweig Letter Newsletter.Stay tuned for more enlightening content from the Zweig Letter podcast, and make sure to subscribe for regular updates!Other episodes you'll enjoy:Architecture with Heart - Carley ChastainFrom Specs to Stories with Cherise LakesideBridging Design and Construction with Dan CristAI Transforming AEC with KP ReddyConnect with Zweig Group:Instagram: Zweig GroupFacebook: Zweig GroupTwitter: Zweig GroupLinkedIn: Zweig GroupWebsite: Zweig Group

Ray Reddy is VP of Retail at Shopify, leading the company's retail business and championing local entrepreneurs. With a career focused on leveraging technology for commerce, he previously co-founded Ritual, a mobile commerce platform supporting local restaurants, and PushLife (acquired by Google), where he later led mobile product management for shopping and commerce. Ray is passionate about building products that simplify complexity and create new opportunities to help local entrepreneurs win. Top 3 Value Bombs 1. Retailers are entering a modern renaissance where AI and rapid innovation make entrepreneurship easier than ever. 2. Shopify POS Hub delivers near-perfect reliability by solving the long-standing pain of iPad-peripheral incompatibility. 3. Expanding delivery and payment capabilities, like Uber Direct and global Tap to Pay, helps merchants offer world-class customer experiences. Learn more about Shopify's retail solutions and the Winter '26 Edition - Shopify Winter '26 Edition Sponsors HighLevel - The ultimate all-in-one platform for entrepreneurs, marketers, coaches, and agencies. Learn more at HighLevelFire.com. Intuit QuickBooks - Transform your cash flow and your business this year. Check out QuickBooks money tools today! Learn more at QuickBooks.com/money. Terms apply. Money movement services are provided by Intuit Payments Inc., licensed as a Money Transmitter by the New York State Department of Financial Services.