Podcasts about bridges

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reference: Sri Aurobindo, Bases of Yoga, Chapter 5, Physical Consciousness — Subconscient — Sleep and Dream — Illness, pg. 102This episode is also available as a blog post at https://sriaurobindostudies.wordpress.com/2026/02/22/the-lack-of-transcription-or-bridges-of-consciousness-prevents-awareness-of-the-waking-consciousness-of-experiences-of-deep-sleep-and-other-alternative-states-of-awareness/Video presentations, interviews and podcast episodes are allavailable on the YouTube Channel https://www.youtube.com/@santoshkrinsky871More information about Sri Aurobindo can be found at www.aurobindo.net  The US editions and links to e-book editions of SriAurobindo's writings can be found at Lotus Press www.lotuspress.com#Sri Aurobindo #yoga #integral yoga #spirituality #sleep #yoga nidra #samadhi

What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

In today's connected world, burning bridges in the electrical industry can cost you far more than you realize. In this episode, The Electrical Guru dives into the real-world consequences of publicly criticizing inspectors, manufacturers, educators, and fellow electricians—especially on social media.The electrical trade is a tight-knit community where reputations travel fast, and opportunities often depend on professional relationships built over years. One emotional post or public rant can quietly damage your credibility, limit future support, and close doors you didn't even know were open.Whether you're an electrical contractor, apprentice, inspector, or industry professional, this episode delivers straight talk on why professionalism matters, how online behavior impacts your business, and what smart electricians do instead of burning bridges.If you're serious about long-term success in the electrical industry, this is a conversation you don't want to miss.Listen as Paul Abernathy, CEO and Founder of Electrical Code Academy, Inc., the leading electrical educator in the country, discusses electrical code, electrical trade, and electrical business-related topics to help electricians maximize their knowledge and industry investment.If you are looking to learn more about the National Electrical Code, for electrical exam preparation, or to better your knowledge of the NEC, then visit https://fasttraxsystem.com for all the electrical code training you will ever need by the leading electrical educator in the country with the best NEC learning program on the planet.Become a supporter of this podcast: https://www.spreaker.com/podcast/ask-paul-national-electrical-code--4971115/support.

https://paulvanderklay.me/2026/02/19/why-the-crc-golden-age-failed/ https://firstthings.com/why-im-done-with-notre-dame/ https://archive.org/details/pub_reformed-journal-1951 https://paulvanderklay.me/2026/02/17/the-new-metagelical-elites-and-christian-education/ https://paulvanderklay.me/2026/02/18/lila-rose-and-nancy-pelosi-go-to-the-same-church/ https://www.newyorker.com/culture/the-weekend-essay/losing-faith-in-atheism  @CalvinUniversity  Renaissance of Christian Thought - Marsden, Mouw, Plantinga & Wolterstorff https://youtu.be/FjqsaD1k-NM?si=WGigEMbbvABhDISa Why are Christian Reformed Churches struggling and Christian Reformed Day Schools Thriving? https://youtu.be/kLp7nCCKVGM https://paulvanderklay.me/2026/02/20/the-way-we-were-crc-voices-edition/  What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

Manny Faces joins us to explore how hip hop can be a powerful catalyst for change in various sectors, including education, health, and social justice. As an award-winning journalist and cultural strategist, Manny shares his journey of using hip hop to unlock innovation and drive progress within marginalized communities. He discusses the often-overlooked potential of hip hop to address trauma and facilitate meaningful dialogue among youth, particularly in environments where traditional communication methods may fall short. Through engaging anecdotes and insightful reflections, Manny illustrates how hip hop not only serves as an artistic expression but also as a bridge for connecting diverse experiences and fostering understanding across generations. Join us as we delve into this transformative art form that has the potential to reshape culture and ignite positive change in our society.Exploring the transformative power of hip hop, Manny Faces, an award-winning journalist and cultural strategist, joins Keith Haney on this episode of Becoming Bridge Builders to unravel how the genre can serve as a catalyst for social change. The discussion delves deep into Manny's journey, from his early days as a wannabe rapper to his evolution into a prominent voice in hip hop journalism. He shares insights from his acclaimed podcast, 'Hip Hop Can Save America,' highlighting how hip hop culture can redefine education, health, and social justice. Manny's personal anecdotes provide a rich tapestry of experiences that showcase the resilience and creativity embedded in hip hop, illustrating its potential to uplift marginalized communities. Throughout the conversation, listeners are encouraged to consider the impact of hip hop not just as a musical genre, but as a vital tool for cultural expression and communal healing, challenging the often negative perceptions surrounding it. The episode also touches on the nuances of hip hop's evolution, especially how it has been perceived across generations. Manny argues that while older generations may lament the state of contemporary rap, there exists a wealth of talent and meaningful expression still thriving within the culture. He emphasizes the importance of understanding the socio-economic contexts that shape these narratives and the role of storytelling in fostering empathy and connection among diverse audiences. By bridging the gap between hip hop enthusiasts and skeptics, Manny advocates for a more inclusive dialogue that recognizes the genre's ability to articulate the struggles and dreams of a generation. This episode serves as an invitation to engage with hip hop as a living, breathing force for good, urging listeners to explore how they can harness its power to create positive change in their own communities.In a thought-provoking dialogue, Manny Faces discusses the intersection of hip hop and social change with Keith Haney, revealing the profound ways in which rap music can influence education, mental health, and community engagement. Drawing from his extensive background in journalism and cultural strategy, Manny reflects on his personal connection to hip hop, recounting stories from his youth that shaped his understanding of the genre's significance. He argues that hip hop is not just music; it's a cultural movement that speaks to the heart of societal issues, offering a voice to those often unheard. Their conversation highlights key initiatives where hip hop has been utilized in educational settings, demonstrating its effectiveness as a medium for self-expression and personal development among youth.Listeners are treated to an engaging exploration of how hip hop can serve to address systemic issues faced by marginalized communities. Manny shares examples of programs that leverage rap to foster healing and empowerment, illustrating that hip hop can be a bridge to understanding and addressing complex social problems. As the discussion unfolds, it becomes clear...

​ ⁨@EzraKleinShow⁩  What the Epstein Files Reveal About How Elite Worlds Work | The Ezra Klein Show https://youtu.be/eBnQ6qxoMr8?si=OwnIKJbBwZd8YmNL   ⁨@TalmudforEveryone⁩  Purity according to the Pharisees & the Rabbis https://youtu.be/ejplay13HV8?si=eRPk1VyFRFCk26rc    What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

https://paulvanderklay.me/2026/02/17/the-new-metagelical-elites-and-christian-education/ https://www.realclearinvestigations.com/articles/2026/02/17/surprising_revival_gen_z_men_and_highly_educated_lead_return_to_religion_1165235.html@UCrZyTWGMdRM9_P26RKPvh3A Education on the Battlefront - Jordan Hall & Annie Crawford https://youtu.be/OQyaeO45U8U?si=gguqlUROrpidWBbi https://firstthings.com/why-im-done-with-notre-dame/ https://swierenga.com/BurnWoodenShoesOrigPaper.html  @InterestingTimesNYT  https://youtu.be/leLQuObRyaU?si=PPhxbRP7vzDF53WO ‘Trump Has Lost the Country' | Interesting Times with Ross Douthat https://www.newyorker.com/culture/the-weekend-essay/losing-faith-in-atheism https://paulvanderklay.me/2026/02/18/lila-rose-and-nancy-pelosi-go-to-the-same-church/  What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

BIG WEDNESDAY! Nanos wears his Erik Estrada shirt for some interviews to pump his own ego! Chuck Schumer comes out for Voter ID! (20 years ago), Dugan Bridges, writer and director of Blackwater Draw: The Making of Billy the Kid, Michael Letts, law enforcement expert, Barney Brenner and LD17 Senate Candidate Chris King.

Oh snap, Tom has started ANOTHER CAMPAIGN! This time they're running some first edition Warhammer 40,000: Dark Heresy, and Magill's playing a pox-marked guardsman who's really good at being average. Tune in to learn the foundational elements of Tom's campaign, and also to take a deep dive into the background of Alsamasath, one of Tom's reoccurring NPCs.Find us on Facebook!All music composed by Vince Nitro.

 @DarkHorsePod  Epstein Probably DID Survive - Bret Weinstein Explains Why | DarkHorse 313 https://youtu.be/KgmxybiObSI?si=7IZb9XHofOgvQUtF  @BishopBarron  Bishop Barron Presents | Ross Douthat - Is it Rational to Believe in God? https://youtu.be/iBz7T0oBwPw?si=EfjCOJpxZ2W9Pglq I want the TLC to Break the 4th Wall and Be with Me. Sam from New Zealand https://youtu.be/9bwhnol6U9Q?si=yPJKh5nwxMyFaXCI   @howtounderstandtheworld  How to Understand Truth https://youtu.be/OIuR6BqBC5M?si=d49KXAZsNIisqM4h  @faturechi  Iran Update https://www.youtube.com/live/rj8OfbADx2M?si=k_u0TACYcO2ywQFl  @triggerpod  Is This The End of Humanity? - Eric Weinstein https://youtu.be/g4jnK58co2Q?si=brMGaaK2EIxrkfD0  @pillarandstep  Is there evidence for Jesus? | Tom Holland & Peter J. Williams | FULL FILM https://youtu.be/RwAKlbMhF3M?si=H29N5IYwM_GjEO2T  What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

Episode 7 touches on reaction to previous episodes and columns, and has information about an upcoming 3 day seminar. Part 1 - We received a personal remembrance about our friend Peter Young from Marylene Vestergom, a former luge competitor who has provided television coverage of four Olympics. Peter helped her at the start of her broadcast career and she wrote about how "Peter's passing just days before another Winter Olympics has brought those Sarajevo memories back with such clarity." You'll hear her tribute to him.12.18 Part 2- "Bridges for Peace has truly been a great friend and supporter of both Jews and Israel over the years," wrote Bill Narvey in his email about their upcoming seminar, Israel's Battle for Truth . It's being held Feb. 25-28th and features informedand expert speakers such as Itamar Marcus, the director of Palestinian Media Watch. The sessions deal with historical and current truths, facts and realities about Israel and the existential challenges and threats Jews and Israel continue to face. To register or for more information, contact info@bfpcan.org or call 1-855-489-369721.00 Part 3- Our two latest columns in the Winnipeg Sun garnered a lot of comment and reaction. They were:Feb. 8- Ashdown Market shutdown reflects city's disarrayFeb. 15 - The reluctant acceptance of Louis Riel Day by the NDPYou'll hear a recap of those columns - including a terse email that Point Douglas Councillor Vivian Santos received about failing to address crime from homeless encampments in the East Exchange. There are underlying issues with the way legacy media fails to cover these kinds of stories accurately. EVERY EPISODE OF OUR PODCAST IS AVAILABLE AT https://actionline.ca/podcast/

Brad's Story https://youtu.be/EmCIC8W0_SY Brian's Story https://youtu.be/1qYiwIVYwkY Round One: https://youtu.be/lc-uzgZEYHk   What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Stephanie Paolini is the reason "Seacoast Stories" exists.Without her, host Troy Farkas never would have planted roots on the Seacoast.And today (finally), the owner of 3 Bridges Yoga (Portsmouth) finally makes her long-awaited debut on the 100th EPISODE OF THE PODCAST

John 3 to 5   What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

February 13, 2026 ~ Chris Renwick and Lloyd Jackson spoke with Kaelan Dorr, White House Deputy Communications Director. They discussed the Minnesota immigration drawdown and the Gordie Howe Bridge, highlighting collaboration between federal and local law enforcement. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

On this episode of Ticats Today, host Troy Durrell is joined by Hamilton Tiger-Cats receiver Shemar Bridges as he discusses what his family means to him ahead of Family Day, re-signing with the club and looking ahead to the 2026 season. The Ticats Audio Network provides Hamilton Tiger-Cats fans with the most comprehensive, entertaining and informative news and information about their favourite football team. Featuring Steve Milton, Mike Daly, Bubba O'Neil, Courtney Stephen, Simoni Lawrence, Mike Morreale, Rob Hitchcock, Mike Daly, Louie Butko, Troy Durrell, Ticats players, coaches and front office personnel, and many more. Regular shows include Ticats Today, Ticats This Week, Tiger-Cats Game Day, Tiger-Cats Pregame, Tiger-Cats At The Half, Tiger-Cats Postgame, Speaking With The Enemy, Morreale & Hitch, The Milton Report, What Happened with Simoni Lawrence, and so much more. Ticats Audio Network content can be found on the Tiger-Cats YouTube channel, Spotify, Apple Podcasts, at listen.ticats.ca and anywhere else you find podcasts. Please follow, like, leave a review wherever you find our content, and follow the Hamilton Tiger-Cats social media channels to keep up to date with all Ticats Audio Network content. Twitter: @TicatsInsta: @hamiltontigercatsTikTok: @hamiltonticatsFacebook: cfltigercatsYouTube: ticatstvchannel

​ @ClubRandomPodcast   Ana Kasparian | Club Random with Bill Maher https://youtu.be/mRaDwa7E-NY?si=vMokl1J95zB8lGDI  @NextUpHalperin  What Clinton and Epstein REALLY Reveal About Double Standards in Political Scandals https://youtu.be/giEcGUDqdgc?si=JEaebAkWmz79UdCF  @faturechi  Iran Update https://www.youtube.com/live/rj8OfbADx2M?si=a1HzdUgNlAkP1eLx  @CanonPress   “Trump Has Lost the Country” | Doug Wilson https://youtu.be/hEHw8FpoKrQ?si=Iu09yjX_8SE3BABN  What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

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From rewriting Google's search stack in the early 2000s to reviving sparse trillion-parameter models and co-designing TPUs with frontier ML research, Jeff Dean has quietly shaped nearly every layer of the modern AI stack. As Chief AI Scientist at Google and a driving force behind Gemini, Jeff has lived through multiple scaling revolutions from CPUs and sharded indices to multimodal models that reason across text, video, and code.Jeff joins us to unpack what it really means to “own the Pareto frontier,” why distillation is the engine behind every Flash model breakthrough, how energy (in picojoules) not FLOPs is becoming the true bottleneck, what it was like leading the charge to unify all of Google's AI teams, and why the next leap won't come from bigger context windows alone, but from systems that give the illusion of attending to trillions of tokens.We discuss:* Jeff's early neural net thesis in 1990: parallel training before it was cool, why he believed scaling would win decades early, and the “bigger model, more data, better results” mantra that held for 15 years* The evolution of Google Search: sharding, moving the entire index into memory in 2001, softening query semantics pre-LLMs, and why retrieval pipelines already resemble modern LLM systems* Pareto frontier strategy: why you need both frontier “Pro” models and low-latency “Flash” models, and how distillation lets smaller models surpass prior generations* Distillation deep dive: ensembles → compression → logits as soft supervision, and why you need the biggest model to make the smallest one good* Latency as a first-class objective: why 10–50x lower latency changes UX entirely, and how future reasoning workloads will demand 10,000 tokens/sec* Energy-based thinking: picojoules per bit, why moving data costs 1000x more than a multiply, batching through the lens of energy, and speculative decoding as amortization* TPU co-design: predicting ML workloads 2–6 years out, speculative hardware features, precision reduction, sparsity, and the constant feedback loop between model architecture and silicon* Sparse models and “outrageously large” networks: trillions of parameters with 1–5% activation, and why sparsity was always the right abstraction* Unified vs. specialized models: abandoning symbolic systems, why general multimodal models tend to dominate vertical silos, and when vertical fine-tuning still makes sense* Long context and the illusion of scale: beyond needle-in-a-haystack benchmarks toward systems that narrow trillions of tokens to 117 relevant documents* Personalized AI: attending to your emails, photos, and documents (with permission), and why retrieval + reasoning will unlock deeply personal assistants* Coding agents: 50 AI interns, crisp specifications as a new core skill, and how ultra-low latency will reshape human–agent collaboration* Why ideas still matter: transformers, sparsity, RL, hardware, systems — scaling wasn't blind; the pieces had to multiply togetherShow Notes:* Gemma 3 Paper* Gemma 3* Gemini 2.5 Report* Jeff Dean's “Software Engineering Advice fromBuilding Large-Scale Distributed Systems” Presentation (with Back of the Envelope Calculations)* Latency Numbers Every Programmer Should Know by Jeff Dean* The Jeff Dean Facts* Jeff Dean Google Bio* Jeff Dean on “Important AI Trends” @Stanford AI Club* Jeff Dean & Noam Shazeer — 25 years at Google (Dwarkesh)—Jeff Dean* LinkedIn: https://www.linkedin.com/in/jeff-dean-8b212555* X: https://x.com/jeffdeanGoogle* https://google.com* https://deepmind.googleFull Video EpisodeTimestamps00:00:04 — Introduction: Alessio & Swyx welcome Jeff Dean, chief AI scientist at Google, to the Latent Space podcast00:00:30 — Owning the Pareto Frontier & balancing frontier vs low-latency models00:01:31 — Frontier models vs Flash models + role of distillation00:03:52 — History of distillation and its original motivation00:05:09 — Distillation's role in modern model scaling00:07:02 — Model hierarchy (Flash, Pro, Ultra) and distillation sources00:07:46 — Flash model economics & wide deployment00:08:10 — Latency importance for complex tasks00:09:19 — Saturation of some tasks and future frontier tasks00:11:26 — On benchmarks, public vs internal00:12:53 — Example long-context benchmarks & limitations00:15:01 — Long-context goals: attending to trillions of tokens00:16:26 — Realistic use cases beyond pure language00:18:04 — Multimodal reasoning and non-text modalities00:19:05 — Importance of vision & motion modalities00:20:11 — Video understanding example (extracting structured info)00:20:47 — Search ranking analogy for LLM retrieval00:23:08 — LLM representations vs keyword search00:24:06 — Early Google search evolution & in-memory index00:26:47 — Design principles for scalable systems00:28:55 — Real-time index updates & recrawl strategies00:30:06 — Classic “Latency numbers every programmer should know”00:32:09 — Cost of memory vs compute and energy emphasis00:34:33 — TPUs & hardware trade-offs for serving models00:35:57 — TPU design decisions & co-design with ML00:38:06 — Adapting model architecture to hardware00:39:50 — Alternatives: energy-based models, speculative decoding00:42:21 — Open research directions: complex workflows, RL00:44:56 — Non-verifiable RL domains & model evaluation00:46:13 — Transition away from symbolic systems toward unified LLMs00:47:59 — Unified models vs specialized ones00:50:38 — Knowledge vs reasoning & retrieval + reasoning00:52:24 — Vertical model specialization & modules00:55:21 — Token count considerations for vertical domains00:56:09 — Low resource languages & contextual learning00:59:22 — Origins: Dean's early neural network work01:10:07 — AI for coding & human–model interaction styles01:15:52 — Importance of crisp specification for coding agents01:19:23 — Prediction: personalized models & state retrieval01:22:36 — Token-per-second targets (10k+) and reasoning throughput01:23:20 — Episode conclusion and thanksTranscriptAlessio Fanelli [00:00:04]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space. Shawn Wang [00:00:11]: Hello, hello. We're here in the studio with Jeff Dean, chief AI scientist at Google. Welcome. Thanks for having me. It's a bit surreal to have you in the studio. I've watched so many of your talks, and obviously your career has been super legendary. So, I mean, congrats. I think the first thing must be said, congrats on owning the Pareto Frontier.Jeff Dean [00:00:30]: Thank you, thank you. Pareto Frontiers are good. It's good to be out there.Shawn Wang [00:00:34]: Yeah, I mean, I think it's a combination of both. You have to own the Pareto Frontier. You have to have like frontier capability, but also efficiency, and then offer that range of models that people like to use. And, you know, some part of this was started because of your hardware work. Some part of that is your model work, and I'm sure there's lots of secret sauce that you guys have worked on cumulatively. But, like, it's really impressive to see it all come together in, like, this slittily advanced.Jeff Dean [00:01:04]: Yeah, yeah. I mean, I think, as you say, it's not just one thing. It's like a whole bunch of things up and down the stack. And, you know, all of those really combine to help make UNOS able to make highly capable large models, as well as, you know, software techniques to get those large model capabilities into much smaller, lighter weight models that are, you know, much more cost effective and lower latency, but still, you know, quite capable for their size. Yeah.Alessio Fanelli [00:01:31]: How much pressure do you have on, like, having the lower bound of the Pareto Frontier, too? I think, like, the new labs are always trying to push the top performance frontier because they need to raise more money and all of that. And you guys have billions of users. And I think initially when you worked on the CPU, you were thinking about, you know, if everybody that used Google, we use the voice model for, like, three minutes a day, they were like, you need to double your CPU number. Like, what's that discussion today at Google? Like, how do you prioritize frontier versus, like, we have to do this? How do we actually need to deploy it if we build it?Jeff Dean [00:02:03]: Yeah, I mean, I think we always want to have models that are at the frontier or pushing the frontier because I think that's where you see what capabilities now exist that didn't exist at the sort of slightly less capable last year's version or last six months ago version. At the same time, you know, we know those are going to be really useful for a bunch of use cases, but they're going to be a bit slower and a bit more expensive than people might like for a bunch of other broader models. So I think what we want to do is always have kind of a highly capable sort of affordable model that enables a whole bunch of, you know, lower latency use cases. People can use them for agentic coding much more readily and then have the high-end, you know, frontier model that is really useful for, you know, deep reasoning, you know, solving really complicated math problems, those kinds of things. And it's not that. One or the other is useful. They're both useful. So I think we'd like to do both. And also, you know, through distillation, which is a key technique for making the smaller models more capable, you know, you have to have the frontier model in order to then distill it into your smaller model. So it's not like an either or choice. You sort of need that in order to actually get a highly capable, more modest size model. Yeah.Alessio Fanelli [00:03:24]: I mean, you and Jeffrey came up with the solution in 2014.Jeff Dean [00:03:28]: Don't forget, L'Oreal Vinyls as well. Yeah, yeah.Alessio Fanelli [00:03:30]: A long time ago. But like, I'm curious how you think about the cycle of these ideas, even like, you know, sparse models and, you know, how do you reevaluate them? How do you think about in the next generation of model, what is worth revisiting? Like, yeah, they're just kind of like, you know, you worked on so many ideas that end up being influential, but like in the moment, they might not feel that way necessarily. Yeah.Jeff Dean [00:03:52]: I mean, I think distillation was originally motivated because we were seeing that we had a very large image data set at the time, you know, 300 million images that we could train on. And we were seeing that if you create specialists for different subsets of those image categories, you know, this one's going to be really good at sort of mammals, and this one's going to be really good at sort of indoor room scenes or whatever, and you can cluster those categories and train on an enriched stream of data after you do pre-training on a much broader set of images. You get much better performance. If you then treat that whole set of maybe 50 models you've trained as a large ensemble, but that's not a very practical thing to serve, right? So distillation really came about from the idea of, okay, what if we want to actually serve that and train all these independent sort of expert models and then squish it into something that actually fits in a form factor that you can actually serve? And that's, you know, not that different from what we're doing today. You know, often today we're instead of having an ensemble of 50 models. We're having a much larger scale model that we then distill into a much smaller scale model.Shawn Wang [00:05:09]: Yeah. A part of me also wonders if distillation also has a story with the RL revolution. So let me maybe try to articulate what I mean by that, which is you can, RL basically spikes models in a certain part of the distribution. And then you have to sort of, well, you can spike models, but usually sometimes... It might be lossy in other areas and it's kind of like an uneven technique, but you can probably distill it back and you can, I think that the sort of general dream is to be able to advance capabilities without regressing on anything else. And I think like that, that whole capability merging without loss, I feel like it's like, you know, some part of that should be a distillation process, but I can't quite articulate it. I haven't seen much papers about it.Jeff Dean [00:06:01]: Yeah, I mean, I tend to think of one of the key advantages of distillation is that you can have a much smaller model and you can have a very large, you know, training data set and you can get utility out of making many passes over that data set because you're now getting the logits from the much larger model in order to sort of coax the right behavior out of the smaller model that you wouldn't otherwise get with just the hard labels. And so, you know, I think that's what we've observed. Is you can get, you know, very close to your largest model performance with distillation approaches. And that seems to be, you know, a nice sweet spot for a lot of people because it enables us to kind of, for multiple Gemini generations now, we've been able to make the sort of flash version of the next generation as good or even substantially better than the previous generations pro. And I think we're going to keep trying to do that because that seems like a good trend to follow.Shawn Wang [00:07:02]: So, Dara asked, so it was the original map was Flash Pro and Ultra. Are you just sitting on Ultra and distilling from that? Is that like the mother load?Jeff Dean [00:07:12]: I mean, we have a lot of different kinds of models. Some are internal ones that are not necessarily meant to be released or served. Some are, you know, our pro scale model and we can distill from that as well into our Flash scale model. So I think, you know, it's an important set of capabilities to have and also inference time scaling. It can also be a useful thing to improve the capabilities of the model.Shawn Wang [00:07:35]: And yeah, yeah, cool. Yeah. And obviously, I think the economy of Flash is what led to the total dominance. I think the latest number is like 50 trillion tokens. I don't know. I mean, obviously, it's changing every day.Jeff Dean [00:07:46]: Yeah, yeah. But, you know, by market share, hopefully up.Shawn Wang [00:07:50]: No, I mean, there's no I mean, there's just the economics wise, like because Flash is so economical, like you can use it for everything. Like it's in Gmail now. It's in YouTube. Like it's yeah. It's in everything.Jeff Dean [00:08:02]: We're using it more in our search products of various AI mode reviews.Shawn Wang [00:08:05]: Oh, my God. Flash past the AI mode. Oh, my God. Yeah, that's yeah, I didn't even think about that.Jeff Dean [00:08:10]: I mean, I think one of the things that is quite nice about the Flash model is not only is it more affordable, it's also a lower latency. And I think latency is actually a pretty important characteristic for these models because we're going to want models to do much more complicated things that are going to involve, you know, generating many more tokens from when you ask the model to do so. So, you know, if you're going to ask the model to do something until it actually finishes what you ask it to do, because you're going to ask now, not just write me a for loop, but like write me a whole software package to do X or Y or Z. And so having low latency systems that can do that seems really important. And Flash is one direction, one way of doing that. You know, obviously our hardware platforms enable a bunch of interesting aspects of our, you know, serving stack as well, like TPUs, the interconnect between. Chips on the TPUs is actually quite, quite high performance and quite amenable to, for example, long context kind of attention operations, you know, having sparse models with lots of experts. These kinds of things really, really matter a lot in terms of how do you make them servable at scale.Alessio Fanelli [00:09:19]: Yeah. Does it feel like there's some breaking point for like the proto Flash distillation, kind of like one generation delayed? I almost think about almost like the capability as a. In certain tasks, like the pro model today is a saturated, some sort of task. So next generation, that same task will be saturated at the Flash price point. And I think for most of the things that people use models for at some point, the Flash model in two generation will be able to do basically everything. And how do you make it economical to like keep pushing the pro frontier when a lot of the population will be okay with the Flash model? I'm curious how you think about that.Jeff Dean [00:09:59]: I mean, I think that's true. If your distribution of what people are asking people, the models to do is stationary, right? But I think what often happens is as the models become more capable, people ask them to do more, right? So, I mean, I think this happens in my own usage. Like I used to try our models a year ago for some sort of coding task, and it was okay at some simpler things, but wouldn't do work very well for more complicated things. And since then, we've improved dramatically on the more complicated coding tasks. And now I'll ask it to do much more complicated things. And I think that's true, not just of coding, but of, you know, now, you know, can you analyze all the, you know, renewable energy deployments in the world and give me a report on solar panel deployment or whatever. That's a very complicated, you know, more complicated task than people would have asked a year ago. And so you are going to want more capable models to push the frontier in the absence of what people ask the models to do. And that also then gives us. Insight into, okay, where does the, where do things break down? How can we improve the model in these, these particular areas, uh, in order to sort of, um, make the next generation even better.Alessio Fanelli [00:11:11]: Yeah. Are there any benchmarks or like test sets they use internally? Because it's almost like the same benchmarks get reported every time. And it's like, all right, it's like 99 instead of 97. Like, how do you have to keep pushing the team internally to it? Or like, this is what we're building towards. Yeah.Jeff Dean [00:11:26]: I mean, I think. Benchmarks, particularly external ones that are publicly available. Have their utility, but they often kind of have a lifespan of utility where they're introduced and maybe they're quite hard for current models. You know, I, I like to think of the best kinds of benchmarks are ones where the initial scores are like 10 to 20 or 30%, maybe, but not higher. And then you can sort of work on improving that capability for, uh, whatever it is, the benchmark is trying to assess and get it up to like 80, 90%, whatever. I, I think once it hits kind of 95% or something, you get very diminishing returns from really focusing on that benchmark, cuz it's sort of, it's either the case that you've now achieved that capability, or there's also the issue of leakage in public data or very related kind of data being, being in your training data. Um, so we have a bunch of held out internal benchmarks that we really look at where we know that wasn't represented in the training data at all. There are capabilities that we want the model to have. Um, yeah. Yeah. Um, that it doesn't have now, and then we can work on, you know, assessing, you know, how do we make the model better at these kinds of things? Is it, we need different kind of data to train on that's more specialized for this particular kind of task. Do we need, um, you know, a bunch of, uh, you know, architectural improvements or some sort of, uh, model capability improvements, you know, what would help make that better?Shawn Wang [00:12:53]: Is there, is there such an example that you, uh, a benchmark inspired in architectural improvement? Like, uh, I'm just kind of. Jumping on that because you just.Jeff Dean [00:13:02]: Uh, I mean, I think some of the long context capability of the, of the Gemini models that came, I guess, first in 1.5 really were about looking at, okay, we want to have, um, you know,Shawn Wang [00:13:15]: immediately everyone jumped to like completely green charts of like, everyone had, I was like, how did everyone crack this at the same time? Right. Yeah. Yeah.Jeff Dean [00:13:23]: I mean, I think, um, and once you're set, I mean, as you say that needed single needle and a half. Hey, stack benchmark is really saturated for at least context links up to 1, 2 and K or something. Don't actually have, you know, much larger than 1, 2 and 8 K these days or two or something. We're trying to push the frontier of 1 million or 2 million context, which is good because I think there are a lot of use cases where. Yeah. You know, putting a thousand pages of text or putting, you know, multiple hour long videos and the context and then actually being able to make use of that as useful. Try to, to explore the über graduation are fairly large. But the single needle in a haystack benchmark is sort of saturated. So you really want more complicated, sort of multi-needle or more realistic, take all this content and produce this kind of answer from a long context that sort of better assesses what it is people really want to do with long context. Which is not just, you know, can you tell me the product number for this particular thing?Shawn Wang [00:14:31]: Yeah, it's retrieval. It's retrieval within machine learning. It's interesting because I think the more meta level I'm trying to operate at here is you have a benchmark. You're like, okay, I see the architectural thing I need to do in order to go fix that. But should you do it? Because sometimes that's an inductive bias, basically. It's what Jason Wei, who used to work at Google, would say. Exactly the kind of thing. Yeah, you're going to win. Short term. Longer term, I don't know if that's going to scale. You might have to undo that.Jeff Dean [00:15:01]: I mean, I like to sort of not focus on exactly what solution we're going to derive, but what capability would you want? And I think we're very convinced that, you know, long context is useful, but it's way too short today. Right? Like, I think what you would really want is, can I attend to the internet while I answer my question? Right? But that's not going to happen. I think that's going to be solved by purely scaling the existing solutions, which are quadratic. So a million tokens kind of pushes what you can do. You're not going to do that to a trillion tokens, let alone, you know, a billion tokens, let alone a trillion. But I think if you could give the illusion that you can attend to trillions of tokens, that would be amazing. You'd find all kinds of uses for that. You would have attend to the internet. You could attend to the pixels of YouTube and the sort of deeper representations that we can find. You could attend to the form for a single video, but across many videos, you know, on a personal Gemini level, you could attend to all of your personal state with your permission. So like your emails, your photos, your docs, your plane tickets you have. I think that would be really, really useful. And the question is, how do you get algorithmic improvements and system level improvements that get you to something where you actually can attend to trillions of tokens? Right. In a meaningful way. Yeah.Shawn Wang [00:16:26]: But by the way, I think I did some math and it's like, if you spoke all day, every day for eight hours a day, you only generate a maximum of like a hundred K tokens, which like very comfortably fits.Jeff Dean [00:16:38]: Right. But if you then say, okay, I want to be able to understand everything people are putting on videos.Shawn Wang [00:16:46]: Well, also, I think that the classic example is you start going beyond language into like proteins and whatever else is extremely information dense. Yeah. Yeah.Jeff Dean [00:16:55]: I mean, I think one of the things about Gemini's multimodal aspects is we've always wanted it to be multimodal from the start. And so, you know, that sometimes to people means text and images and video sort of human-like and audio, audio, human-like modalities. But I think it's also really useful to have Gemini know about non-human modalities. Yeah. Like LIDAR sensor data from. Yes. Say, Waymo vehicles or. Like robots or, you know, various kinds of health modalities, x-rays and MRIs and imaging and genomics information. And I think there's probably hundreds of modalities of data where you'd like the model to be able to at least be exposed to the fact that this is an interesting modality and has certain meaning in the world. Where even if you haven't trained on all the LIDAR data or MRI data, you could have, because maybe that's not, you know, it doesn't make sense in terms of trade-offs of. You know, what you include in your main pre-training data mix, at least including a little bit of it is actually quite useful. Yeah. Because it sort of tempts the model that this is a thing.Shawn Wang [00:18:04]: Yeah. Do you believe, I mean, since we're on this topic and something I just get to ask you all the questions I always wanted to ask, which is fantastic. Like, are there some king modalities, like modalities that supersede all the other modalities? So a simple example was Vision can, on a pixel level, encode text. And DeepSeq had this DeepSeq CR paper that did that. Vision. And Vision has also been shown to maybe incorporate audio because you can do audio spectrograms and that's, that's also like a Vision capable thing. Like, so, so maybe Vision is just the king modality and like. Yeah.Jeff Dean [00:18:36]: I mean, Vision and Motion are quite important things, right? Motion. Well, like video as opposed to static images, because I mean, there's a reason evolution has evolved eyes like 23 independent ways, because it's such a useful capability for sensing the world around you, which is really what we want these models to be. So I think the only thing that we can be able to do is interpret the things we're seeing or the things we're paying attention to and then help us in using that information to do things. Yeah.Shawn Wang [00:19:05]: I think motion, you know, I still want to shout out, I think Gemini, still the only native video understanding model that's out there. So I use it for YouTube all the time. Nice.Jeff Dean [00:19:15]: Yeah. Yeah. I mean, it's actually, I think people kind of are not necessarily aware of what the Gemini models can actually do. Yeah. Like I have an example I've used in one of my talks. It had like, it was like a YouTube highlight video of 18 memorable sports moments across the last 20 years or something. So it has like Michael Jordan hitting some jump shot at the end of the finals and, you know, some soccer goals and things like that. And you can literally just give it the video and say, can you please make me a table of what all these different events are? What when the date is when they happened? And a short description. And so you get like now an 18 row table of that information extracted from the video, which is, you know, not something most people think of as like a turn video into sequel like table.Alessio Fanelli [00:20:11]: Has there been any discussion inside of Google of like, you mentioned tending to the whole internet, right? Google, it's almost built because a human cannot tend to the whole internet and you need some sort of ranking to find what you need. Yep. That ranking is like much different for an LLM because you can expect a person to look at maybe the first five, six links in a Google search versus for an LLM. Should you expect to have 20 links that are highly relevant? Like how do you internally figure out, you know, how do we build the AI mode that is like maybe like much broader search and span versus like the more human one? Yeah.Jeff Dean [00:20:47]: I mean, I think even pre-language model based work, you know, our ranking systems would be built to start. I mean, I think even pre-language model based work, you know, our ranking systems would be built to start. With a giant number of web pages in our index, many of them are not relevant. So you identify a subset of them that are relevant with very lightweight kinds of methods. You know, you're down to like 30,000 documents or something. And then you gradually refine that to apply more and more sophisticated algorithms and more and more sophisticated sort of signals of various kinds in order to get down to ultimately what you show, which is, you know, the final 10 results or, you know, 10 results plus. Other kinds of information. And I think an LLM based system is not going to be that dissimilar, right? You're going to attend to trillions of tokens, but you're going to want to identify, you know, what are the 30,000 ish documents that are with the, you know, maybe 30 million interesting tokens. And then how do you go from that into what are the 117 documents I really should be paying attention to in order to carry out the tasks that the user has asked? And I think, you know, you can imagine systems where you have, you know, a lot of highly parallel processing to identify those initial 30,000 candidates, maybe with very lightweight kinds of models. Then you have some system that sort of helps you narrow down from 30,000 to the 117 with maybe a little bit more sophisticated model or set of models. And then maybe the final model is the thing that looks. So the 117 things that might be your most capable model. So I think it has to, it's going to be some system like that, that is really enables you to give the illusion of attending to trillions of tokens. Sort of the way Google search gives you, you know, not the illusion, but you are searching the internet, but you're finding, you know, a very small subset of things that are, that are relevant.Shawn Wang [00:22:47]: Yeah. I often tell a lot of people that are not steeped in like Google search history that, well, you know, like Bert was. Like he was like basically immediately inside of Google search and that improves results a lot, right? Like I don't, I don't have any numbers off the top of my head, but like, I'm sure you guys, that's obviously the most important numbers to Google. Yeah.Jeff Dean [00:23:08]: I mean, I think going to an LLM based representation of text and words and so on enables you to get out of the explicit hard notion of, of particular words having to be on the page, but really getting at the notion of this topic of this page or this page. Paragraph is highly relevant to this query. Yeah.Shawn Wang [00:23:28]: I don't think people understand how much LLMs have taken over all these very high traffic system, very high traffic. Yeah. Like it's Google, it's YouTube. YouTube has this like semantics ID thing where it's just like every token or every item in the vocab is a YouTube video or something that predicts the video using a code book, which is absurd to me for YouTube size.Jeff Dean [00:23:50]: And then most recently GROK also for, for XAI, which is like, yeah. I mean, I'll call out even before LLMs were used extensively in search, we put a lot of emphasis on softening the notion of what the user actually entered into the query.Shawn Wang [00:24:06]: So do you have like a history of like, what's the progression? Oh yeah.Jeff Dean [00:24:09]: I mean, I actually gave a talk in, uh, I guess, uh, web search and data mining conference in 2009, uh, where we never actually published any papers about the origins of Google search, uh, sort of, but we went through sort of four or five or six. generations, four or five or six generations of, uh, redesigning of the search and retrieval system, uh, from about 1999 through 2004 or five. And that talk is really about that evolution. And one of the things that really happened in 2001 was we were sort of working to scale the system in multiple dimensions. So one is we wanted to make our index bigger, so we could retrieve from a larger index, which always helps your quality in general. Uh, because if you don't have the page in your index, you're going to not do well. Um, and then we also needed to scale our capacity because we were, our traffic was growing quite extensively. Um, and so we had, you know, a sharded system where you have more and more shards as the index grows, you have like 30 shards. And then if you want to double the index size, you make 60 shards so that you can bound the latency by which you respond for any particular user query. Um, and then as traffic grows, you add, you add more and more replicas of each of those. And so we eventually did the math that realized that in a data center where we had say 60 shards and, um, you know, 20 copies of each shard, we now had 1200 machines, uh, with disks. And we did the math and we're like, Hey, one copy of that index would actually fit in memory across 1200 machines. So in 2001, we introduced, uh, we put our entire index in memory and what that enabled from a quality perspective was amazing. Um, and so we had more and more replicas of each of those. Before you had to be really careful about, you know, how many different terms you looked at for a query, because every one of them would involve a disk seek on every one of the 60 shards. And so you, as you make your index bigger, that becomes even more inefficient. But once you have the whole index in memory, it's totally fine to have 50 terms you throw into the query from the user's original three or four word query, because now you can add synonyms like restaurant and restaurants and cafe and, uh, you know, things like that. Uh, bistro and all these things. And you can suddenly start, uh, sort of really, uh, getting at the meaning of the word as opposed to the exact semantic form the user typed in. And that was, you know, 2001, very much pre LLM, but really it was about softening the, the strict definition of what the user typed in order to get at the meaning.Alessio Fanelli [00:26:47]: What are like principles that you use to like design the systems, especially when you have, I mean, in 2001, the internet is like. Doubling, tripling every year in size is not like, uh, you know, and I think today you kind of see that with LLMs too, where like every year the jumps in size and like capabilities are just so big. Are there just any, you know, principles that you use to like, think about this? Yeah.Jeff Dean [00:27:08]: I mean, I think, uh, you know, first, whenever you're designing a system, you want to understand what are the sort of design parameters that are going to be most important in designing that, you know? So, you know, how many queries per second do you need to handle? How big is the internet? How big is the index you need to handle? How much data do you need to keep for every document in the index? How are you going to look at it when you retrieve things? Um, what happens if traffic were to double or triple, you know, will that system work well? And I think a good design principle is you're going to want to design a system so that the most important characteristics could scale by like factors of five or 10, but probably not beyond that because often what happens is if you design a system for X. And something suddenly becomes a hundred X, that would enable a very different point in the design space that would not make sense at X. But all of a sudden at a hundred X makes total sense. So like going from a disk space index to a in memory index makes a lot of sense once you have enough traffic, because now you have enough replicas of the sort of state on disk that those machines now actually can hold, uh, you know, a full copy of the, uh, index and memory. Yeah. And that all of a sudden enabled. A completely different design that wouldn't have been practical before. Yeah. Um, so I'm, I'm a big fan of thinking through designs in your head, just kind of playing with the design space a little before you actually do a lot of writing of code. But, you know, as you said, in the early days of Google, we were growing the index, uh, quite extensively. We were growing the update rate of the index. So the update rate actually is the parameter that changed the most. Surprising. So it used to be once a month.Shawn Wang [00:28:55]: Yeah.Jeff Dean [00:28:56]: And then we went to a system that could update any particular page in like sub one minute. Okay.Shawn Wang [00:29:02]: Yeah. Because this is a competitive advantage, right?Jeff Dean [00:29:04]: Because all of a sudden news related queries, you know, if you're, if you've got last month's news index, it's not actually that useful for.Shawn Wang [00:29:11]: News is a special beast. Was there any, like you could have split it onto a separate system.Jeff Dean [00:29:15]: Well, we did. We launched a Google news product, but you also want news related queries that people type into the main index to also be sort of updated.Shawn Wang [00:29:23]: So, yeah, it's interesting. And then you have to like classify whether the page is, you have to decide which pages should be updated and what frequency. Oh yeah.Jeff Dean [00:29:30]: There's a whole like, uh, system behind the scenes that's trying to decide update rates and importance of the pages. So even if the update rate seems low, you might still want to recrawl important pages quite often because, uh, the likelihood they change might be low, but the value of having updated is high.Shawn Wang [00:29:50]: Yeah, yeah, yeah, yeah. Uh, well, you know, yeah. This, uh, you know, mention of latency and, and saving things to this reminds me of one of your classics, which I have to bring up, which is latency numbers. Every programmer should know, uh, was there a, was it just a, just a general story behind that? Did you like just write it down?Jeff Dean [00:30:06]: I mean, this has like sort of eight or 10 different kinds of metrics that are like, how long does a cache mistake? How long does branch mispredict take? How long does a reference domain memory take? How long does it take to send, you know, a packet from the U S to the Netherlands or something? Um,Shawn Wang [00:30:21]: why Netherlands, by the way, or is it, is that because of Chrome?Jeff Dean [00:30:25]: Uh, we had a data center in the Netherlands, um, so, I mean, I think this gets to the point of being able to do the back of the envelope calculations. So these are sort of the raw ingredients of those, and you can use them to say, okay, well, if I need to design a system to do image search and thumb nailing or something of the result page, you know, how, what I do that I could pre-compute the image thumbnails. I could like. Try to thumbnail them on the fly from the larger images. What would that do? How much dis bandwidth than I need? How many des seeks would I do? Um, and you can sort of actually do thought experiments in, you know, 30 seconds or a minute with the sort of, uh, basic, uh, basic numbers at your fingertips. Uh, and then as you sort of build software using higher level libraries, you kind of want to develop the same intuitions for how long does it take to, you know, look up something in this particular kind of.Shawn Wang [00:31:21]: I'll see you next time.Shawn Wang [00:31:51]: Which is a simple byte conversion. That's nothing interesting. I wonder if you have any, if you were to update your...Jeff Dean [00:31:58]: I mean, I think it's really good to think about calculations you're doing in a model, either for training or inference.Jeff Dean [00:32:09]: Often a good way to view that is how much state will you need to bring in from memory, either like on-chip SRAM or HBM from the accelerator. Attached memory or DRAM or over the network. And then how expensive is that data motion relative to the cost of, say, an actual multiply in the matrix multiply unit? And that cost is actually really, really low, right? Because it's order, depending on your precision, I think it's like sub one picodule.Shawn Wang [00:32:50]: Oh, okay. You measure it by energy. Yeah. Yeah.Jeff Dean [00:32:52]: Yeah. I mean, it's all going to be about energy and how do you make the most energy efficient system. And then moving data from the SRAM on the other side of the chip, not even off the off chip, but on the other side of the same chip can be, you know, a thousand picodules. Oh, yeah. And so all of a sudden, this is why your accelerators require batching. Because if you move, like, say, the parameter of a model from SRAM on the, on the chip into the multiplier unit, that's going to cost you a thousand picodules. So you better make use of that, that thing that you moved many, many times with. So that's where the batch dimension comes in. Because all of a sudden, you know, if you have a batch of 256 or something, that's not so bad. But if you have a batch of one, that's really not good.Shawn Wang [00:33:40]: Yeah. Yeah. Right.Jeff Dean [00:33:41]: Because then you paid a thousand picodules in order to do your one picodule multiply.Shawn Wang [00:33:46]: I have never heard an energy-based analysis of batching.Jeff Dean [00:33:50]: Yeah. I mean, that's why people batch. Yeah. Ideally, you'd like to use batch size one because the latency would be great.Shawn Wang [00:33:56]: The best latency.Jeff Dean [00:33:56]: But the energy cost and the compute cost inefficiency that you get is quite large. So, yeah.Shawn Wang [00:34:04]: Is there a similar trick like, like, like you did with, you know, putting everything in memory? Like, you know, I think obviously NVIDIA has caused a lot of waves with betting very hard on SRAM with Grok. I wonder if, like, that's something that you already saw with, with the TPUs, right? Like that, that you had to. Uh, to serve at your scale, uh, you probably sort of saw that coming. Like what, what, what hardware, uh, innovations or insights were formed because of what you're seeing there?Jeff Dean [00:34:33]: Yeah. I mean, I think, you know, TPUs have this nice, uh, sort of regular structure of 2D or 3D meshes with a bunch of chips connected. Yeah. And each one of those has HBM attached. Um, I think for serving some kinds of models, uh, you know, you, you pay a lot higher cost. Uh, and time latency, um, bringing things in from HBM than you do bringing them in from, uh, SRAM on the chip. So if you have a small enough model, you can actually do model parallelism, spread it out over lots of chips and you actually get quite good throughput improvements and latency improvements from doing that. And so you're now sort of striping your smallish scale model over say 16 or 64 chips. Uh, but as if you do that and it all fits in. In SRAM, uh, that can be a big win. So yeah, that's not a surprise, but it is a good technique.Alessio Fanelli [00:35:27]: Yeah. What about the TPU design? Like how much do you decide where the improvements have to go? So like, this is like a good example of like, is there a way to bring the thousand picojoules down to 50? Like, is it worth designing a new chip to do that? The extreme is like when people say, oh, you should burn the model on the ASIC and that's kind of like the most extreme thing. How much of it? Is it worth doing an hardware when things change so quickly? Like what was the internal discussion? Yeah.Jeff Dean [00:35:57]: I mean, we, we have a lot of interaction between say the TPU chip design architecture team and the sort of higher level modeling, uh, experts, because you really want to take advantage of being able to co-design what should future TPUs look like based on where we think the sort of ML research puck is going, uh, in some sense, because, uh, you know, as a hardware designer for ML and in particular, you're trying to design a chip starting today and that design might take two years before it even lands in a data center. And then it has to sort of be a reasonable lifetime of the chip to take you three, four or five years. So you're trying to predict two to six years out where, what ML computations will people want to run two to six years out in a very fast changing field. And so having people with interest. Interesting ML research ideas of things we think will start to work in that timeframe or will be more important in that timeframe, uh, really enables us to then get, you know, interesting hardware features put into, you know, TPU N plus two, where TPU N is what we have today.Shawn Wang [00:37:10]: Oh, the cycle time is plus two.Jeff Dean [00:37:12]: Roughly. Wow. Because, uh, I mean, sometimes you can squeeze some changes into N plus one, but, you know, bigger changes are going to require the chip. Yeah. Design be earlier in its lifetime design process. Um, so whenever we can do that, it's generally good. And sometimes you can put in speculative features that maybe won't cost you much chip area, but if it works out, it would make something, you know, 10 times as fast. And if it doesn't work out, well, you burned a little bit of tiny amount of your chip area on that thing, but it's not that big a deal. Uh, sometimes it's a very big change and we want to be pretty sure this is going to work out. So we'll do like lots of carefulness. Uh, ML experimentation to show us, uh, this is actually the, the way we want to go. Yeah.Alessio Fanelli [00:37:58]: Is there a reverse of like, we already committed to this chip design so we can not take the model architecture that way because it doesn't quite fit?Jeff Dean [00:38:06]: Yeah. I mean, you, you definitely have things where you're going to adapt what the model architecture looks like so that they're efficient on the chips that you're going to have for both training and inference of that, of that, uh, generation of model. So I think it kind of goes both ways. Um, you know, sometimes you can take advantage of, you know, lower precision things that are coming in a future generation. So you can, might train it at that lower precision, even if the current generation doesn't quite do that. Mm.Shawn Wang [00:38:40]: Yeah. How low can we go in precision?Jeff Dean [00:38:43]: Because people are saying like ternary is like, uh, yeah, I mean, I'm a big fan of very low precision because I think that gets, that saves you a tremendous amount of time. Right. Because it's picojoules per bit that you're transferring and reducing the number of bits is a really good way to, to reduce that. Um, you know, I think people have gotten a lot of luck, uh, mileage out of having very low bit precision things, but then having scaling factors that apply to a whole bunch of, uh, those, those weights. Scaling. How does it, how does it, okay.Shawn Wang [00:39:15]: Interesting. You, so low, low precision, but scaled up weights. Yeah. Huh. Yeah. Never considered that. Yeah. Interesting. Uh, w w while we're on this topic, you know, I think there's a lot of, um, uh, this, the concept of precision at all is weird when we're sampling, you know, uh, we just, at the end of this, we're going to have all these like chips that I'll do like very good math. And then we're just going to throw a random number generator at the start. So, I mean, there's a movement towards, uh, energy based, uh, models and processors. I'm just curious if you've, obviously you've thought about it, but like, what's your commentary?Jeff Dean [00:39:50]: Yeah. I mean, I think. There's a bunch of interesting trends though. Energy based models is one, you know, diffusion based models, which don't sort of sequentially decode tokens is another, um, you know, speculative decoding is a way that you can get sort of an equivalent, very small.Shawn Wang [00:40:06]: Draft.Jeff Dean [00:40:07]: Batch factor, uh, for like you predict eight tokens out and that enables you to sort of increase the effective batch size of what you're doing by a factor of eight, even, and then you maybe accept five or six of those tokens. So you get. A five, a five X improvement in the amortization of moving weights, uh, into the multipliers to do the prediction for the, the tokens. So these are all really good techniques and I think it's really good to look at them from the lens of, uh, energy, real energy, not energy based models, um, and, and also latency and throughput, right? If you look at things from that lens, that sort of guides you to. Two solutions that are gonna be, uh, you know, better from, uh, you know, being able to serve larger models or, you know, equivalent size models more cheaply and with lower latency.Shawn Wang [00:41:03]: Yeah. Well, I think, I think I, um, it's appealing intellectually, uh, haven't seen it like really hit the mainstream, but, um, I do think that, uh, there's some poetry in the sense that, uh, you know, we don't have to do, uh, a lot of shenanigans if like we fundamentally. Design it into the hardware. Yeah, yeah.Jeff Dean [00:41:23]: I mean, I think there's still a, there's also sort of the more exotic things like analog based, uh, uh, computing substrates as opposed to digital ones. Uh, I'm, you know, I think those are super interesting cause they can be potentially low power. Uh, but I think you often end up wanting to interface that with digital systems and you end up losing a lot of the power advantages in the digital to analog and analog to digital conversions. You end up doing, uh, at the sort of boundaries. And periphery of that system. Um, I still think there's a tremendous distance we can go from where we are today in terms of energy efficiency with sort of, uh, much better and specialized hardware for the models we care about.Shawn Wang [00:42:05]: Yeah.Alessio Fanelli [00:42:06]: Um, any other interesting research ideas that you've seen, or like maybe things that you cannot pursue a Google that you would be interested in seeing researchers take a step at, I guess you have a lot of researchers. Yeah, I guess you have enough, but our, our research.Jeff Dean [00:42:21]: Our research portfolio is pretty broad. I would say, um, I mean, I think, uh, in terms of research directions, there's a whole bunch of, uh, you know, open problems and how do you make these models reliable and able to do much longer, kind of, uh, more complex tasks that have lots of subtasks. How do you orchestrate, you know, maybe one model that's using other models as tools in order to sort of build, uh, things that can accomplish, uh, you know, much more. Yeah. Significant pieces of work, uh, collectively, then you would ask a single model to do. Um, so that's super interesting. How do you get more verifiable, uh, you know, how do you get RL to work for non-verifiable domains? I think it's a pretty interesting open problem because I think that would broaden out the capabilities of the models, the improvements that you're seeing in both math and coding. Uh, if we could apply those to other less verifiable domains, because we've come up with RL techniques that actually enable us to do that. Uh, effectively, that would, that would really make the models improve quite a lot. I think.Alessio Fanelli [00:43:26]: I'm curious, like when we had Noam Brown on the podcast, he said, um, they already proved you can do it with deep research. Um, you kind of have it with AI mode in a way it's not verifiable. I'm curious if there's any thread that you think is interesting there. Like what is it? Both are like information retrieval of JSON. So I wonder if it's like the retrieval is like the verifiable part. That you can score or what are like, yeah, yeah. How, how would you model that, that problem?Jeff Dean [00:43:55]: Yeah. I mean, I think there are ways of having other models that can evaluate the results of what a first model did, maybe even retrieving. Can you have another model that says, is this things, are these things you retrieved relevant? Or can you rate these 2000 things you retrieved to assess which ones are the 50 most relevant or something? Um, I think those kinds of techniques are actually quite effective. Sometimes I can even be the same model, just prompted differently to be a, you know, a critic as opposed to a, uh, actual retrieval system. Yeah.Shawn Wang [00:44:28]: Um, I do think like there, there is that, that weird cliff where like, it feels like we've done the easy stuff and then now it's, but it always feels like that every year. It's like, oh, like we know, we know, and the next part is super hard and nobody's figured it out. And, uh, exactly with this RLVR thing where like everyone's talking about, well, okay, how do we. the next stage of the non-verifiable stuff. And everyone's like, I don't know, you know, Ellen judge.Jeff Dean [00:44:56]: I mean, I feel like the nice thing about this field is there's lots and lots of smart people thinking about creative solutions to some of the problems that we all see. Uh, because I think everyone sort of sees that the models, you know, are great at some things and they fall down around the edges of those things and, and are not as capable as we'd like in those areas. And then coming up with good techniques and trying those. And seeing which ones actually make a difference is sort of what the whole research aspect of this field is, is pushing forward. And I think that's why it's super interesting. You know, if you think about two years ago, we were struggling with GSM, eight K problems, right? Like, you know, Fred has two rabbits. He gets three more rabbits. How many rabbits does he have? That's a pretty far cry from the kinds of mathematics that the models can, and now you're doing IMO and Erdos problems in pure language. Yeah. Yeah. Pure language. So that is a really, really amazing jump in capabilities in, you know, in a year and a half or something. And I think, um, for other areas, it'd be great if we could make that kind of leap. Uh, and you know, we don't exactly see how to do it for some, some areas, but we do see it for some other areas and we're going to work hard on making that better. Yeah.Shawn Wang [00:46:13]: Yeah.Alessio Fanelli [00:46:14]: Like YouTube thumbnail generation. That would be very helpful. We need that. That would be AGI. We need that.Shawn Wang [00:46:20]: That would be. As far as content creators go.Jeff Dean [00:46:22]: I guess I'm not a YouTube creator, so I don't care that much about that problem, but I guess, uh, many people do.Shawn Wang [00:46:27]: It does. Yeah. It doesn't, it doesn't matter. People do judge books by their covers as it turns out. Um, uh, just to draw a bit on the IMO goal. Um, I'm still not over the fact that a year ago we had alpha proof and alpha geometry and all those things. And then this year we were like, screw that we'll just chuck it into Gemini. Yeah. What's your reflection? Like, I think this, this question about. Like the merger of like symbolic systems and like, and, and LMS, uh, was a very much core belief. And then somewhere along the line, people would just said, Nope, we'll just all do it in the LLM.Jeff Dean [00:47:02]: Yeah. I mean, I think it makes a lot of sense to me because, you know, humans manipulate symbols, but we probably don't have like a symbolic representation in our heads. Right. We have some distributed representation that is neural net, like in some way of lots of different neurons. And activation patterns firing when we see certain things and that enables us to reason and plan and, you know, do chains of thought and, you know, roll them back now that, that approach for solving the problem doesn't seem like it's going to work. I'm going to try this one. And, you know, in a lot of ways we're emulating what we intuitively think, uh, is happening inside real brains in neural net based models. So it never made sense to me to have like completely separate. Uh, discrete, uh, symbolic things, and then a completely different way of, of, uh, you know, thinking about those things.Shawn Wang [00:47:59]: Interesting. Yeah. Uh, I mean, it's maybe seems obvious to you, but it wasn't obvious to me a year ago. Yeah.Jeff Dean [00:48:06]: I mean, I do think like that IMO with, you know, translating to lean and using lean and then the next year and also a specialized geometry model. And then this year switching to a single unified model. That is roughly the production model with a little bit more inference budget, uh, is actually, you know, quite good because it shows you that the capabilities of that general model have improved dramatically and, and now you don't need the specialized model. This is actually sort of very similar to the 2013 to 16 era of machine learning, right? Like it used to be, people would train separate models for lots of different, each different problem, right? I have, I want to recognize street signs and something. So I train a street sign. Recognition recognition model, or I want to, you know, decode speech recognition. I have a speech model, right? I think now the era of unified models that do everything is really upon us. And the question is how well do those models generalize to new things they've never been asked to do and they're getting better and better.Shawn Wang [00:49:10]: And you don't need domain experts. Like one of my, uh, so I interviewed ETA who was on, who was on that team. Uh, and he was like, yeah, I, I don't know how they work. I don't know where the IMO competition was held. I don't know the rules of it. I just trained the models, the training models. Yeah. Yeah. And it's kind of interesting that like people with these, this like universal skill set of just like machine learning, you just give them data and give them enough compute and they can kind of tackle any task, which is the bitter lesson, I guess. I don't know. Yeah.Jeff Dean [00:49:39]: I mean, I think, uh, general models, uh, will win out over specialized ones in most cases.Shawn Wang [00:49:45]: Uh, so I want to push there a bit. I think there's one hole here, which is like, uh. There's this concept of like, uh, maybe capacity of a model, like abstractly a model can only contain the number of bits that it has. And, uh, and so it, you know, God knows like Gemini pro is like one to 10 trillion parameters. We don't know, but, uh, the Gemma models, for example, right? Like a lot of people want like the open source local models that are like that, that, that, and, and, uh, they have some knowledge, which is not necessary, right? Like they can't know everything like, like you have the. The luxury of you have the big model and big model should be able to capable of everything. But like when, when you're distilling and you're going down to the small models, you know, you're actually memorizing things that are not useful. Yeah. And so like, how do we, I guess, do we want to extract that? Can we, can we divorce knowledge from reasoning, you know?Jeff Dean [00:50:38]: Yeah. I mean, I think you do want the model to be most effective at reasoning if it can retrieve things, right? Because having the model devote precious parameter space. To remembering obscure facts that could be looked up is actually not the best use of that parameter space, right? Like you might prefer something that is more generally useful in more settings than this obscure fact that it has. Um, so I think that's always attention at the same time. You also don't want your model to be kind of completely detached from, you know, knowing stuff about the world, right? Like it's probably useful to know how long the golden gate be. Bridges just as a general sense of like how long are bridges, right? And, uh, it should have that kind of knowledge. It maybe doesn't need to know how long some teeny little bridge in some other more obscure part of the world is, but, uh, it does help it to have a fair bit of world knowledge and the bigger your model is, the more you can have. Uh, but I do think combining retrieval with sort of reasoning and making the model really good at doing multiple stages of retrieval. Yeah.Shawn Wang [00:51:49]: And reasoning through the intermediate retrieval results is going to be a, a pretty effective way of making the model seem much more capable, because if you think about, say, a personal Gemini, yeah, right?Jeff Dean [00:52:01]: Like we're not going to train Gemini on my email. Probably we'd rather have a single model that, uh, we can then use and use being able to retrieve from my email as a tool and have the model reason about it and retrieve from my photos or whatever, uh, and then make use of that and have multiple. Um, you know, uh, stages of interaction. that makes sense.Alessio Fanelli [00:52:24]: Do you think the vertical models are like, uh, interesting pursuit? Like when people are like, oh, we're building the best healthcare LLM, we're building the best law LLM, are those kind of like short-term stopgaps or?Jeff Dean [00:52:37]: No, I mean, I think, I think vertical models are interesting. Like you want them to start from a pretty good base model, but then you can sort of, uh, sort of viewing them, view them as enriching the data. Data distribution for that particular vertical domain for healthcare, say, um, we're probably not going to train or for say robotics. We're probably not going to train Gemini on all possible robotics data. We, you could train it on because we want it to have a balanced set of capabilities. Um, so we'll expose it to some robotics data, but if you're trying to build a really, really good robotics model, you're going to want to start with that and then train it on more robotics data. And then maybe that would. It's multilingual translation capability, but improve its robotics capabilities. And we're always making these kind of, uh, you know, trade-offs in the data mix that we train the base Gemini models on. You know, we'd love to include data from 200 more languages and as much data as we have for those languages, but that's going to displace some other capabilities of the model. It won't be as good at, um, you know, Pearl programming, you know, it'll still be good at Python programming. Cause we'll include it. Enough. Of that, but there's other long tail computer languages or coding capabilities that it may suffer on or multi, uh, multimodal reasoning capabilities may suffer. Cause we didn't get to expose it to as much data there, but it's really good at multilingual things. So I, I think some combination of specialized models, maybe more modular models. So it'd be nice to have the capability to have those 200 languages, plus this awesome robotics model, plus this awesome healthcare, uh, module that all can be knitted together to work in concert and called upon in different circumstances. Right? Like if I have a health related thing, then it should enable using this health module in conjunction with the main base model to be even better at those kinds of things. Yeah.Shawn Wang [00:54:36]: Installable knowledge. Yeah.Jeff Dean [00:54:37]: Right.Shawn Wang [00:54:38]: Just download as a, as a package.Jeff Dean [00:54:39]: And some of that installable stuff can come from retrieval, but some of it probably should come from preloaded training on, you know, uh, a hundred billion tokens or a trillion tokens of health data. Yeah.Shawn Wang [00:54:51]: And for listeners, I think, uh, I will highlight the Gemma three end paper where they, there was a little bit of that, I think. Yeah.Alessio Fanelli [00:54:56]: Yeah. I guess the question is like, how many billions of tokens do you need to outpace the frontier model improvements? You know, it's like, if I have to make this model better healthcare and the main. Gemini model is still improving. Do I need 50 billion tokens? Can I do it with a hundred, if I need a trillion healthcare tokens, it's like, they're probably not out there that you don't have, you know, I think that's really like the.Jeff Dean [00:55:21]: Well, I mean, I think healthcare is a particularly challenging domain, so there's a lot of healthcare data that, you know, we don't have access to appropriately, but there's a lot of, you know, uh, healthcare organizations that want to train models on their own data. That is not public healthcare data, uh, not public health. But public healthcare data. Um, so I think there are opportunities there to say, partner with a large healthcare organization and train models for their use that are going to be, you know, more bespoke, but probably, uh, might be better than a general model trained on say, public data. Yeah.Shawn Wang [00:55:58]: Yeah. I, I believe, uh, by the way, also this is like somewhat related to the language conversation. Uh, I think one of your, your favorite examples was you can put a low resource language in the context and it just learns. Yeah.Jeff Dean [00:56:09]: Oh, yeah, I think the example we used was Calamon, which is truly low resource because it's only spoken by, I think 120 people in the world and there's no written text.Shawn Wang [00:56:20]: So, yeah. So you can just do it that way. Just put it in the context. Yeah. Yeah. But I think your whole data set in the context, right.Jeff Dean [00:56:27]: If you, if you take a language like, uh, you know, Somali or something, there is a fair bit of Somali text in the world that, uh, or Ethiopian Amharic or something, um, you know, we probably. Yeah. Are not putting all the data from those languages into the Gemini based training. We put some of it, but if you put more of it, you'll improve the capabilities of those models.Shawn Wang [00:56:49]: Yeah.Jeff Dean [00:56:49]:

February 12, 2026 ~ Chris Renwick and Lloyd Jackson talk with Mike Rogers, former Congressman, about Donald Trump's comments on the Gordie Howe Bridge, housing plans, and the SAVE Act. Hosted by Simplecast, an AdsWizz company. See https://pcm.adswizz.com for information about our collection and use of personal data for advertising.

​ @rossbyrd5474  Jordan Hall | The Future of the Church https://youtu.be/XXkM3yRY_Ng?si=DF9bMYxoLgOu2ooZ https://paulvanderklay.substack.com/p/the-dream  @ChadMatthewAlvin  saturday night time burn https://www.youtube.com/live/5CXVCO0kF-g?si=qDF9eJ7Ud2bo6t2P  @MarkDParker  Friend or F—k Buddy? https://www.youtube.com/live/85ePTRZKVM4?si=9dWRKNEIetM5pxPH A Co What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give njunction for Dysfunction https://www.youtube.com/live/mvW6MUnmK24?si=UPoyU_BRr-uAMGMA CNN September 08: 1998 Khatami interview part 2 (Originally aired January 07, 1998) https://youtu.be/qiK6KOKQNqg?si=kwuvHZgI0oXDtPs- https://performativebafflement.substack.com/p/cheating-much-more-than-you-wanted  @joerogan   Joe Rogan Experience #2450 - Tommy Wood https://youtu.be/UPfN2G0RyQM?si=BnSR_UU1lbtFpcJq     

Colin, Shroppy and Fitty react live to the suspensions of Moussa, Bridges, Duren and Stewart and give their thoughts about the rulings.See omnystudio.com/listener for privacy information.

The Detroit Bad Boy Pistons are sooooo back, AND SO IS JUSTIN VERLANDER. All vibes. GO LIONS. SPENCER AND EAZY LOVE YOU!

​ @pillarandstep  His-Story: Fantasy, Facts or Faith? | Tom Holland & Peter J. Williams | FULL FILM https://youtu.be/RwAKlbMhF3M?si=IdyDNyat_QoRNGVh   @RealCoffeewithScottAdams  Scott Adams Celebration of Life 01/25/26 https://www.youtube.com/live/nEIECyM8U8U?si=02mW5EOX9U4ZtQvq    What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Your skin heals after a scratch. What if our roads, bridges and cities could self-repair after getting damaged, too? Scientist and engineer Mark Miodownik describes a new class of materials — animate matter — with the potential to sense damage, self-heal and even biodegrade when the job is done. Humanity's next great leap isn't making more stuff, he says — it's making stuff that doesn't fall apart.Learn more about our flagship conference happening this April at attend.ted.com/podcast Hosted on Acast. See acast.com/privacy for more information.

​ ⁨@thefreepress⁩  Inside OneTaste: The Wellness Trend That Hid a Sex Cult https://youtu.be/vHtcaNxdo0k?si=XEMQuMVSylHzQMdm  Ross Douthat asks why doesn't Marianne Williamson found a church?   ⁨@VanderKlips⁩  https://youtu.be/mfXXzeg5lDE?si=DAbiehQSdugrzcSD   ⁨@samharrisorg⁩  Why No One Is Standing Up for Iranians https://youtu.be/EGlal8VojEM?si=Z-G995X--zEKlt9r  What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-  

This episode walks you through this week's astrology + practical and magical tactics to help you harness and navigate the energetics February 9th - 15th, 2026. This week is definitely more. Venus goes for a swim, Mercury gets shady, and Saturn, officially shifts into Aries. Saturn's move is the one to watch. In general grounding is still our focus. Confusion ramps up, but so does the desire to create self-discipline around progress. Mo(o)nday, February 9th: We have significant shifts this week. Continue to focus on care of you so you can care for you and yours. We continue the long game that is 2025 - 2026. More of the energetics that are so major from 2025 take hold in 2026, this week and next. General reminder: The Year of the Snake (2025 energy) is still in play until next week Lunar New Year, February 17th - on the first eclipse of the season. This is when the Fire Horse energy officially begins. Until then, we are shedding, listening, evaluation, releasing, squirming to transform and let go. Don't look away, do not disassociate, escape, or look away. These are defining moments personally, and collectively. We are called to get radically honest about what bad behavior we have let slide and what we really, really, really want..from the depth of our soul....and to then take action towards said thing(s). We still have no personal planets in Earth. My loves, the issue of general stability is real. We will not have support from the astrology on this until March 30th (when Venus moves into Taurus) and May 2nd (When Mercury moves into Taurus). Grounding is everything this year. Mat, meditation, prayer, time alone, root veggies, nourishing food, decrease in caffeine, lifting heavy things, weighted blankets, hugs, slathered in vetiver and honey, conversations with safe community. All of your tools need to be at the ready and you'll need to stick to basics. This is one of those times when motivation will not serve. It's going to be self-discipline and adulting and understanding the long game. We have equal placements in Fire, Air, and Water and this is a nice harmony....again...in theory...without Earth it still feels chaotic, mutable, and in general unstable....because it is...and if we focus on harnessing all the mutability...we can create incredible outcomes because of it, not in spite. We are in transition. As an individual and as a collective. Focus on what you want. Participate at a pace and in ways you can. All is helpful, just please do not tap out completely. Boundaries, limits, expectations, and hopes continue to sharpen. This week as Saturn moves into Aries for the first time since 1999 we gain focus on self-discipline, ambition, responsibility, and self assertion. And although Saturn doesn't do so well in Pisces (where it's been since 2023), it's considered to be in its fall in Aries. I don't prescribe to binaries and try to stay away from it. In astrology nothing is good or bad...but there can be ease or challenges and this is definitely a challenge. It sets a fire under our collective asses. It has us all focusing on what is best for us as an individual (more equity) but we can see how that can create conflict and challenge if everyone individually is focused on personal centering, yes? To harmonize this, we must embrace intersectionality. Freedom for one, is freedom for none. Justice for one is justice for none. We rise together. We thrive together. Our practices are genuinely meant for this. When we calm and center ourselves, we can earnestly do the same for the collective and the future. Tiny and mighty. It still matters. It always matters. This transit takes us to task in a really good way. We will start stepping up in ways we have not before. Go with it. Embrace it. It's a 3 year process. On top of all of this, we're in the eclipse portal. We just need to be aware of how big all the energetics are right now. On top of no Earth in the chart, a shift from one of our major planets (Saturn) the Universe says it's time for buckets full of energy/magic to be dumped on us as it hits the reset button of astrology (power off/power on) in eclipse season. This eclipse portal begins now, essentially, and closes March 13th. This is the period of time we will be uttering "Plot twist! " "That was not on my bingo card for 2026" or "I did not see that coming." PLEASE REMEMBER these things can be incredible gifts, happy surprises, opportunities, and blessings! It is truly wild times with incredible potential and wonderful Easter eggs tucked in them. Stay curious about what your soul really wants, and stay focused and committed to what you want. Where attention goes, energy flows. Tuesday, February 10th: Day 1 of Supportive Solutions - You'll need a wall space for this workout. I know it can be a tricky prop to require, but again I'm a super fan of this no cost support that can also create resistance. Simple is best and always works. Venus in Pisces. This is a regular transition. Venus continues to move her way through the chart house by house. She stays in a sign an average of 4 weeks at a time. Venus loves to be here! We are here for this romantic, poetic, creative, backstroke through our fantasies and realities. Embrace this. Fuel this. Spend extra time with Aphrodite in this period of time (till March 6th) to expand, grow, and protect all the good things in our lives (friendships, networks, communities, partners....overall connections). They both want our desires to become a reality. This is one of the major Easter eggs of 2026. Wednesday, February 11th: Listen to The Magic Spark. Thursday, February 12th: Connect in The Unicorn Wellness Studio private member group. Friday, February 13th: It's Goddess Day! Time to ask: What does my inner goddess need in order to remember she is sacred, divine, and designed to receive? Today is actual Goddess Day - a Friday on the 13th. This is not bad luck, this is a historical celebration of the female divine, in its origin terms, in honor of the 13 moon cycles, our personal 13 moon cycles. It's truly an anti-patriarchal day. Reclaim it. Celebrate. Embrace creative life force, it's unlimited hope and potential to forever recreate, birth, make new, and begin again. However it calls to you, spend time at your altar, spend time with your vessel/body. Remind yourself of the potential YOU are and can generate and participate in. -Mercury Retroshade begins. We know the drill: ▪️Mercury stations retrograde 3xs a year ▪️The slow down prior to stationing Rx is called the pre-shadow or as I call it Retroshade. ▪️The actual Rx is lighter than the pre or post shadow. ▪️This week and next (Retroshade) is the brochure of the lesson/blessing we are to work with in this cycle. ▪️We will revisit this opportunity again in the Rx (February 26th - March 19th) and post shadow (March 20th - April 3rd). This Retrograde isn't great. I cannot sugar coat it. Mercury is not the best swimmer. Things get mucky, confused, poetic, and sound really great but could just be pretty words and empty promises. It could, at its best, offer feeling to heal things, honest words, the get raw and hit soul truths but will take effort after retrograde to bring to actual fruition. Triple check communications, travel, and finances. As clarifying questions. If you think you should check on something, DO. We will thrive and survive, but know this one isn't set up for ease. Check what house Pisces is in in your natal chart. This is where your themes and focus will be. This is great energy for making and creating. Focus on that. Craft, write, sing, dance, garden, cook....this is the way through. Saturn moves into Aries. Please see Monday. But here's the repeat: Saturn moves into Aries for the first time since 1999. We gain focus on self-discipline, ambition, responsibility, and self assertion. And although Saturn doesn't do so well in Pisces (where it's been since 2023), it's considered to be in its fall in Aries. I don't prescribe to binaries and try to stay away from it in the astrology...nothing is good or bad...but there can be ease or challenges and this is definitely a challenge. It sets a fire under our collective asses. It has us all focusing on what is best for us as an individual (more equity) but we can see how that can create conflict and challenge if everyone individually is focused on personal centering, yes? To harmonize this, we must embrace intersectionality. Freedom for one, is freedom for none. Justice for one is justice for none. We rise together. We thrive together. Our practices are genuinely meant for this. When we calm and center ourselves, we can earnestly do the same for the collective and the future. Tiny and mighty. It still matters. It always matters. This transit takes us to task in a really good way. We will start stepping up in ways we have not before. Go with it. Embrace it. It's a 3 year process. This is one of the major shifts we experienced a toe dip into in 2025 but takes root now, in 2026. Neptune and Saturn are travel partners these days. Delusion, dreams, and what it takes to bring outcomes to fruition is the lesson they are trying to teach the collective. Day 1 of Core Solutions - You'll need a set of yoga blocks for this workout. It's extra core focused and you'll be better supported with a cork set of blocks for stability and resistance. Saturday, February 14th: First day of New Moon Energy. We begin the down turn of energy today. But this is no regular new moon we're headed towards on the 17th. We're in the eclipse portal and the energy may have gotten weirder already, as early as Monday or Tuesday. This is a new moon so it's all about clearing the schedule for restoration, rejuvenation, rest, and meditation. Things will shift. Let them. Whatever is leaving, going, releasing....let it. Welcome in the new, emotional intelligence upgrade. Use your monthly meditation (it's a 3rd eye cleanse), work with any of the Energy Healings; Frequency or Goddesses in your UWS member library. Now is the time for recalibration and healings. Sunday, February 15th: Your weekly mantra. I surrender to the pivot. I embrace the plot twist. I keep my heart and mind focused on what I want, wish, and desire. I allow the upgrades, the reveals, the resets, and the fresh timelines. Our wildest dreams are still possible. We hold the vision. Additional Resources: Explore Mentoring Lite for the Spring/Summer session. We begin March 20th. Schedule an Exploration Call for Mentoring Lite February 28th - March 6th. UnicornWellnessStudio.com Offering 30-min Pilates based workouts in alignment to the astrological season and lunar cycles. Activate 30-day guest access at UnicornWellnessStudio.com Subscribe to Tandy's weekly newsletter Follow and DM on Instagram @tandy_gutierrez Additional episodes you might enjoy: EP 103: 2025 Year of the Snake: A Journey into the Heart of Lilith EP 140: Lilithian Language: Creating Boundaries and Bridges in a Single Breath.

Could we build wormholes and travel the galaxy? Exploring stable wormholes, spacetime shortcuts, and the future of interstellar civilization.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video The Future of Interstellar Communication: https://nebula.tv/videos/isaacarthur-chronoengineering-manipulating-time-as-technologyCheck out Joe Scott's Oldest & Newest: https://nebula.tv/videos/joescott-oldest-and-newest-places-on-earth?ref=isaacarthur

Could we build wormholes and travel the galaxy? Exploring stable wormholes, spacetime shortcuts, and the future of interstellar civilization.Get Nebula using my link for 50% off an annual subscription: https://go.nebula.tv/isaacarthurWatch my exclusive video The Future of Interstellar Communication: https://nebula.tv/videos/isaacarthur-chronoengineering-manipulating-time-as-technologyCheck out Joe Scott's Oldest & Newest: https://nebula.tv/videos/joescott-oldest-and-newest-places-on-earth?ref=isaacarthur

John 4   What is the TLC? ("This little corner of the Internet" also know as "the corner" https://youtu.be/Y3vqSjywot8?si=IVS3bnriwje5syPO https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/mtKUnMKS Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Wine Barrels, Duomo Marble, and Florence: Paoletti Custom Guitars at NAMM 2026I've been away from Florence for 25 years. I didn't know there was a guitar company like this back home.At NAMM 2026, I found Filippo Martini from Paoletti Custom Guitars—a boutique manufacturer based in the heart of Tuscany, building instruments that are equal parts guitar and artwork.Paoletti does something no one else does: they build guitars from chestnut wood sourced from Italian wine barrels. The material offers a wide harmonic spectrum, but it's difficult to work with. You need to know how to handle it. Founder Fabrizio Paoletti figured it out, and now every guitar they produce shows the natural grain—no opaque finishes, no hiding the wood.The craftsmanship runs deep. Bridges, pickguards, pickups—all made in-house. Necks carved from Canadian maple, roasted on-site. 99% of the process happens in Tuscany. As Filippo put it, "Kilometer zero." Zero miles. Everything local except the screws.Their model is 100% custom. You don't buy a Paoletti off the rack. You tell them your style, your sound, the genre you play. They build around your vision while keeping the Italian essence intact—chestnut wood, Italian-made components, tailored to your idea.But what stopped me cold was the Duomo collection.Eight individual guitars, each hand-engraved by Fabrizio Paoletti himself. Three years of work. The subject: Florence's cathedral—the Duomo di Santa Maria del Fiore.This isn't just decoration. Paoletti secured an official partnership with the Opera del Duomo, the authority that oversees the cathedral. The back of each guitar reproduces the marble floor pattern from inside the Duomo. And when the collection is complete this October, every guitar will contain an actual piece of marble from the cathedral.I got shivers standing there.This is what happens when guitar making meets Italian heritage. It's not about specs or market positioning. It's about place, history, and craft passed down through generations.Filippo invited me to visit the workshop in Florence when I return in April. I'm going. I want to see where this happens—where wine barrel wood becomes an instrument, where cathedral marble gets embedded into a guitar body, where a team of artisans builds one-of-one pieces for players around the world.Florence is known for many things. Leather. Art. Architecture. The Renaissance itself. Now I know it's also home to some of the most distinctive guitars being made anywhere.Paoletti proves that boutique doesn't mean small ambitions. They're partnering with galleries in Dubai, working with the Duomo authorities, and bringing Florence to NAMM.Not bad for a company I didn't even know existed until I walked the show floor and heard an Italian accent.Sometimes you find home in unexpected places.Marco Ciappelli interviews Filippo Martini from Paoletti Custom Guitars at NAMM 2026 for ITSPmagazine.Part of ITSPmagazine's On Location Coverage at NAMM 2026.

We are seeing the end of Sky's dinner from hell and she ends up Ubering home from Palm Springs. Back in LA, we get a lot of little blips from everyone's lives and Raza J is trying to play peacekeeper between Sky and Tanin.If you enjoyed this episode please share it with your Bravo friends and follow us on Instagram at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@taglinetwinks⁠⁠

​ @theeconplayground1193  Law & Revolution by Harold Berman Part 4: Chapters 13-Conclusion https://youtu.be/vcRF9NGIruc?si=mukWIEqO6vLfeWoO  Playlist: https://www.youtube.com/watch? v=vcRF9NGIruc&list=PLWz9ZVHG_zBSRFq2hasw7r4qayXIXNHNk&index=4  @faturechi  https://www.youtube.com/live/0Kklk67Cduk?si=QVNdrvWadiqu3-HD    https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

You can find  @O.G.Rose.Michelle.and.Daniel  on Youtube And on the web: https://www.og-rose.com/    https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

David Senra: Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Jimmy Iovine is the co-founder of Interscope Records, Beats by Dre, and the USC Jimmy Iovine and Andre Young Academy. Iovine is widely regarded as one of the most influential figures in the modern music industry. Growing up in the Red Hook neighborhood of Brooklyn, New York, Iovine was raised in an Italian working-class family.  He began working as a recording engineer in the early 1970s, and went on to engineer landmark albums including Bruce Springsteen's Born to Run and John Lennon's Rock 'n' Roll and Walls and Bridges, before transitioning into production with Patti Smith's Easter, Tom Petty's Damn the Torpedoes, Stevie Nicks' Bella Donna, and U2's Rattle and Hum. In 1990, Iovine co-founded Interscope Records with Ted Field. Under his leadership, the label became one of the most dominant forces in popular music, launching or elevating the careers of Dr. Dre, Tupac Shakur, Nine Inch Nails, No Doubt, Eminem, 50 Cent, Lady Gaga, and Kendrick Lamar. He rose to become chairman of Interscope Geffen A&M Records. In 2006, he and Dr. Dre co-founded Beats by Dre, which Apple acquired in 2014 for $3 billion — the largest acquisition in Apple's history at the time. Iovine subsequently helped launch Apple Music in 2015 before departing Apple in 2018. His accomplishments include being inducted into the Rock & Roll Hall of Fame in 2022 with the Ahmet Ertegun Award, being honored by the Recording Academy's Producers & Engineers Wing during Grammy Week 2012, co-founding the USC Jimmy Iovine and Andre Young Academy in 2013 with a $70 million donation alongside Dr. Dre, launching the Iovine and Young Center high school program in Los Angeles in 2022 with additional locations in Atlanta and Inglewood, and donating to the city of Compton during the COVID-19 pandemic to fund medical supplies, testing, and meals for residents. https://davidsenra.com/episode/jimmy-iovine Made possible by Ramp: ⁠https://ramp.com⁠ Eight Sleep: https://eightsleep.com/senra Function: https://functionhealth.com/senra Chapters (00:00:00) Introduction: The Corny World of Fame (00:00:54) The Impact of Social Media on Fame (00:01:27) Chasing Greatness: Personal Reflections (00:02:10) Technological Shifts in the Music Industry (00:03:24) The Streaming Service Dilemma (00:05:34) The Artist's Perspective on Streaming (00:06:39) Early Career and Influences (00:09:40) The Importance of Humility (00:11:19) Working with the Best: A Career Retrospective (00:13:07) The Role of Brutal Honesty (00:15:00) Navigating the Music Industry (00:33:50) The Birth of Beats by Dre (00:46:14) The Music Industry's Customer Problem (00:46:44) Vertically Integrating Culture and Fashion (00:47:13) Building Beats: From Music Videos to Headphones (00:48:03) Marketing is Empathy (00:50:28) The Journey of Beats Music (00:59:09) The Future of the Music Industry with AI (01:14:40) The Bend in the Pipe: Harnessing Fear and Obsession (01:29:12) Comparing Work Approaches with Dr. Dre (01:30:50) The Tortured Path to Success (01:32:41) Balancing Happiness and Ambition (01:35:22) The Importance of Peace and Therapy (01:49:30) Learning from Legends (01:55:57) The Influence of Bono and Dre (02:00:15) California Dreams and Career Milestones (02:07:20) Final Thoughts and Reflections Learn more about your ad choices. Visit megaphone.fm/adchoices

https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Revolutionary Iran https://www.amazon.com/Revolutionary-Iran-audiobook/dp/B07TKCGR4S DW History and Culture The Iranian Revolution 1979 explained: From the Pahlavis to mass protests and the Islamic Republic https://youtu.be/1uFGWkd_65k?si=nIvge7HLo_s0cyVz   https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Evan and Tiki dive into the idea of “forbidden fruit” trades and what it would actually take for Yankees fans to part with elite young talent in a true blockbuster scenario. The conversation shifts to roster flexibility, prospects earning real opportunities, and why patience still matters more than panic. From there, the focus moves to the Knicks, where recent wins clash with ongoing trade rumors. The guys break down why Mikal Bridges still divides the fan base, how his own comments about coachability and entitlement stood out, and why any serious pursuit of Giannis Antetokounmpo would almost certainly have to include Bridges. A classic Evan and Tiki segment that blends big swings, reality checks, and a few entertaining detours along the way.

Evan and Tiki react to Brian Cashman's media session and the line that set Yankee fans off: the idea the Yankees are not “running it back.” Is he right, just terrible at saying it, or both? The guys debate whether last year's trade deadline basically was the Yankees' offseason, what's still missing without a true Soto replacement, and how the team should handle Anthony Volpe's rehab and role when he returns. Then the calls roll in, from prospect trade debates and “go get a bat” arguments, to a Mets tangent on Eugenio Suárez vs. giving Mark Vientos one last runway. Hour wraps with Knicks trade chatter and Mikal Bridges' brutally honest “entitlement” quote as Giannis rumors hang in the background. Time Codes 00:00 — Cashman meets the media, Yankees fans immediately annoyed 01:18 — “Just say it's similar” vs Cashman over-explaining why they're different 02:23 — The blunt truth: “They added ONE player” and it feels like the same roster 04:41 — Bigger issue: 15 years, one World Series run, and no Soto replacement 05:15 — Tiki's counter: Cashman is right, just said it in the worst way 05:55 — The trade deadline as the real “offseason” and why that's actually unique 07:03 — AL East framing: Blue Jays, Red Sox, and why “track record” matters 10:40 — “Leave no doubt” offseason vs Yankees budgeting, Dodgers standards, and choices 16:24 — Volpe update: “110%” and “deploy properly” sounds like a role change 18:49 — Call: Yankee fan talks trades, Dominguez and Spencer Jones, and patience 24:30 — Call: Mets tangent, Kyle Tucker opt-out mechanics and the Suárez debate 26:12 — Mark Vientos “final stand” season and why a one-year vet could block him 28:05 — Call: Paul Skenes trade fantasy, prospect “forbidden fruit,” and control years 31:17 — The “pied-à-terre” detour and why it turns into a comedy bit 35:42 — Call: Yankees flexibility, then Knicks trade anxiety after a win 40:14 — Mikal Bridges' “entitlement” quote, being coachable, and trade-rumor pressure 43:16 — Giannis reality check: if it happens, Bridges is likely in the deal

https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

At a time when some may feel divisiveness and isolation is pervasive, this year's Silicon Valley Reads theme explores the concept of belonging in unique ways.  Join us for a thought-provoking conversation with featured authors Keeonna Harris (Mainline Mama: A Memoir), Annie Harnett (Unlikely Animals: A Novel), and John Powell (The Power of Bridging: How to Build a World Where We All Belong).  Hear more about how people find and build community in different ways. In-person attendees are encouraged to visit the Euphrat Museum of Art to enjoy the show A Sense of Belonging. Hosted with Santa Clara County Library District, Santa Clara County Office of Education, San José Public Library, and DeAnza College This program contains EXPLICIT language.    Learn more about your ad choices. Visit megaphone.fm/adchoices

​ @restishistorypod  How the Iranian Revolution Was Hijacked | EP 2 https://youtu.be/VojWVIF3HSg?si=wV0fqImpWd62Kbc1  https://paulvanderklay.substack.com/p/what-do-doug-wilson-and-the-ayatollahs   @InterestingTimesNYT  No, Young Men Are Not Returning To Church. | Interesting Times with Ross Douthat https://youtu.be/JOoYdVlTIzw?si=0drnVSSwkaM64jpK   @InterestingTimesNYT  Christian Nationalism vs Clown World | Interesting Times with Ross Douthat https://youtu.be/WAYWbbSeIhE?si=jNjVg5E5UzUHcPAg  https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

Evan unloads a rapid-fire stack of reports that all point to one wild possibility: the Knicks making a real run at Giannis Antetokounmpo before the NBA trade deadline. They dig into the smoke around Giannis potentially leaving Milwaukee, Rich Paul circling, Portland lurking as a multi-team power broker, and the Knicks quietly testing the market on Karl-Anthony Towns. Then the debate gets real: does a Giannis blockbuster raise the ceiling or shrink the window? What does it cost (Bridges, KAT, McBride, swaps), and can the Knicks actually win with chemistry and health risks midseason? Plus, the guys react to fan calls, the idea that Giannis' personality might play very differently in New York, and a head-scratching Mike Brown moment where he admits he doesn't even know the upcoming schedule. To close out Hour 1, the conversation swings to Super Bowl talk: Seahawks vs Patriots, why Seattle feels like the better team, and whether New England can keep pulling off wins even if the score doesn't always look pretty.

​ @restishistorypod  The Iranian Revolution: The Fall of the Shah | EP 1 https://youtu.be/N8OW0aK-oaA?si=LoeoFLO5dlN6Ejnz  @realryanchapman  How Iran Became a Theocracy https://youtu.be/v7Yl9P9zcQY?si=4UPl53zlOR10niI_  @InterestingTimesNYT  Christian Nationalism vs Clown World | Interesting Times with Ross Douthat https://youtu.be/WAYWbbSeIhE?si=9cv87tqWJzHNwad4  @WhiteStoneName  Is Pluralism Actually Possible? https://www.youtube.com/live/azyvgOUxt-8?si=ICyKFo4E8YFsGQIG Church and Marriage as Universal Basic Institutions out of which Western Civilization Springs https://www.youtube.com/live/KIHbKew73tc?si=rY4fbLXK3iwWW2Hc  https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/WA2RmWx2 Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give  

SURPRISE! Karli is sharing a secret we've been keeping for a few months on today's episode. Then we jump into one of the hardest things we've ever done…ranking our 13 favorite Taylor Swift bridges! Taylor Swift is known for some of the most iconic bridges of all time and somehow we have chosen our top 13 favorites and ranked them. We discuss iconic bridges like Getaway Car, Cruel Summer, Death By A Thousand Cuts and All Too Well. Plus we react to some of our favorite lines in other classic Taylor Swift bridges such as The Smallest Man Who Ever Lived, Tolerate It, You're Losing Me, and more!Let us know via text, email or DM what you think about our rankings. Did we miss any you would've included in the top 13? Which ones did we rank too low or too high?SPONSORS:WALLI 10% off with code “ttn” // https://wallicases.com/?rstr=ttn Love Olive Co 10% off with this link // https://loveoliveco.com/?ref=TTNPODTaylor Swift Podcast || Best Taylor Swift Podcast || Taylor Swift Songs || Taylor Swift Bridges || Best Taylor Swift Bridges || SwiftiesSend us a textSupport the showFollow along to hear a new Taylor Swift related episode every single Tuesday.Watch our episodes on YouTube!Follow Us On Social Media:Typical Tuesday Night Podcast @typicaltuesdaynight.podcastKarli @everyday_ellisJess @jess.taitJoin our Patreon for bonus episodes and exclusive Taylor Swift group chat!Shop Our Merch!Feel free to contact us at typicaltuesdaynightpodcast@gmail.com

Originally posted  ⁨@treyhuntley⁩  https://youtu.be/KDViTqb-zXQ?si=jeWyKYs1gSgeE0G0    https://www.livingstonescrc.com/give Register for the Estuary/Cleanup Weekend https://lscrc.elvanto.net/form/94f5e542-facc-4764-9883-442f982df447 Paul Vander Klay clips channel https://www.youtube.com/channel/UCX0jIcadtoxELSwehCh5QTg https://www.meetup.com/sacramento-estuary/ My Substack https://paulvanderklay.substack.com/ Bridges of meaning https://discord.gg/VPaK2vCX Estuary Hub Link https://www.estuaryhub.com/ There is a video version of this podcast on YouTube at http://www.youtube.com/paulvanderklay To listen to this on ITunes https://itunes.apple.com/us/podcast/paul-vanderklays-podcast/id1394314333  If you need the RSS feed for your podcast player https://paulvanderklay.podbean.com/feed/  All Amazon links here are part of the Amazon Affiliate Program. Amazon pays me a small commission at no additional cost to you if you buy through one of the product links here. This is is one (free to you) way to support my videos.  https://paypal.me/paulvanderklay Blockchain backup on Lbry https://odysee.com/@paulvanderklay https://www.patreon.com/paulvanderklay Paul's Church Content at Living Stones Channel https://www.youtube.com/channel/UCh7bdktIALZ9Nq41oVCvW-A To support Paul's work by supporting his church give here. https://tithe.ly/give?c=2160640 https://www.livingstonescrc.com/give

Michael breaks down the fantasy world of college football, the Houston bridge that keeps getting clobbered, and a Taco Cabana worker’s accidental groin shooting. Callers share unbelievable “I shot myself” stories, plus nostalgia, veterans, and a surprising amount of fudge talk.See omnystudio.com/listener for privacy information.