POPULARITY
Categories
310 episodes with Mats
135 episodes with Mats
214 episodes with Mats
189 episodes with Mats
133 episodes with Mats
55 episodes with Mats
93 episodes with Mats
116 episodes with Mats
176 episodes with Mats
63 episodes with Mats
40 episodes with Mats
37 episodes with Mats
16 episodes with Mats
54 episodes with Mats
36 episodes with Mats
34 episodes with Mats
21 episodes with Mats
51 episodes with Mats
19 episodes with Mats
36 episodes with Mats
35 episodes with Mats
26 episodes with Mats
31 episodes with Mats
12 episodes with Mats
12 episodes with Mats
20 episodes with Mats
18 episodes with Mats
11 episodes with Mats
9 episodes with Mats
29 episodes with Mats
12 episodes with Mats
192 episodes with Mats
10 episodes with Mats
27 episodes with Mats
21 episodes with Mats
11 episodes with Mats
141 episodes with Mats
137 episodes with Mats
10 episodes with Mats
130 episodes with Mats
9 episodes with Mats
4 episodes with Mats
5 episodes with Mats
8 episodes with Mats
4 episodes with Mats
24 episodes with Mats
6 episodes with Mats
17 episodes with Mats
3 episodes with Mats
6 episodes with Mats
110 episodes with Mats
8 episodes with Mats
21 episodes with Mats
5 episodes with Mats
5 episodes with Mats
3 episodes with Mats
7 episodes with Mats
8 episodes with Mats
7 episodes with Mats
7 episodes with Mats
5 episodes with Mats
3 episodes with Mats
8 episodes with Mats
9 episodes with Mats
5 episodes with Mats
5 episodes with Mats
4 episodes with Mats
3 episodes with Mats
7 episodes with Mats
4 episodes with Mats
4 episodes with Mats
3 episodes with Mats
7 episodes with Mats
7 episodes with Mats
5 episodes with Mats
5 episodes with Mats
5 episodes with Mats
6 episodes with Mats
8 episodes with Mats
2 episodes with Mats
2 episodes with Mats
6 episodes with Mats
6 episodes with Mats
6 episodes with Mats
11 episodes with Mats
3 episodes with Mats
2 episodes with Mats
3 episodes with Mats
2 episodes with Mats
2 episodes with Mats
3 episodes with Mats
2 episodes with Mats
3 episodes with Mats
3 episodes with Mats
5 episodes with Mats
4 episodes with Mats
4 episodes with Mats
4 episodes with Mats
6 episodes with Mats
2 episodes with Mats
51 episodes with Mats
5 episodes with Mats
5 episodes with Mats
4 episodes with Mats
6 episodes with Mats
3 episodes with Mats
2 episodes with Mats
3 episodes with Mats
3 episodes with Mats
4 episodes with Mats
2 episodes with Mats
48 episodes with Mats
7 episodes with Mats
2 episodes with Mats
46 episodes with Mats
46 episodes with Mats
3 episodes with Mats
2 episodes with Mats
2 episodes with Mats
2 episodes with Mats
2 episodes with Mats
4 episodes with Mats
2 episodes with Mats
2 episodes with Mats
43 episodes with Mats
3 episodes with Mats
Bad Dads Film Review heads to the Italian Riviera this week for The Talented Mr. Ripley (1999) — a sun-drenched, jazz-soaked psychological thriller where gorgeous people do terrible things, and the worst person in the room still somehow isn't the guy committing the murders.We follow Tom Ripley (Matt Damon), a small-time grifter with big social ambitions, who's handed a golden ticket: travel to Italy and convince trust-fund prince Dickie Greenleaf (prime Jude Law, unfairly beautiful) to come home. Tom doesn't just want Dickie's friendship — he wants Dickie's life. And once he's tasted that world of money, effortless charm, and endless leisure, he's willing to do whatever it takes to stay in it.What we talked about“Great Gatsby, but murderous”: Tom as the outsider who doesn't just observe the rich — he tries to become them (and wear their face if needed).The grift mechanics: the Princeton jacket con, the “research” phase, practicing mannerisms and music tastes, and how the film turns impersonation into a craft.The seduction of wealth: why you're weirdly happy to watch Tom infiltrate a circle of vapid, obscenely privileged characters.Obsession and desire: the homoerotic undertones, Tom's fixation on Dickie, and how the film frames identity as something you can steal… if you're ruthless enough.Set-piece escalation: the boat trip and the brutal turning point; the forged signatures, dual hotel check-ins, staged evidence, and the constant “one more lie to cover the last lie” tension.Freddy as the threat (Philip Seymour Hoffman): the first person with enough real-world instincts to sniff out “new money” fraud — and what happens when he pushes it.The ending sting: Tom “gets away with it”… but the price is isolation, paranoia, and the realization that the spoils aren't worth much when you can't live as yourself.Aging and attitudes: how the film plays in 2026 — including a chat about whether some of the sexuality/“homosexual as threat” framing feels dated.Plus: we somehow opened with a Top 5 Mats segment that should not work… and absolutely does.Standard Bad Dads warning: spoilers throughout, strong language, and the kind of moral compass that's been left outside on a bath mat since the Blair government.You can now text us anonymously to leave feedback, suggest future content or simply hurl abuse at us. We'll read out any texts we receive on the show. Click here to try it out!We love to hear from our listeners! By which I mean we tolerate it. If it hasn't been completely destroyed yet you can usually find us on twitter @dads_film, on Facebook Bad Dads Film Review, on email at baddadsjsy@gmail.com or on our website baddadsfilm.com. Until next time, we remain... Bad Dads
Armand Duplantis har tydligen blivit artist, men hur tusan står han sig i relation till andra idrottare som fått för sig att musik är något för dem – och har den populäre stavhopparens strävan efter att vara älskad kanske gått lite för långt? Vi funderar även kring skillnaden på att söka inspiration i soptunnor och att leta silikonpattar i Monaco. En dåre som heter Mats menade att dyslexi fick honom att bli helt övertygad om att en dyr kasse från Matsmart absolut tillhörde honom – men vilka enorma friheter hade den kreative tjuven, om namnbyte var aktuellt, kunnat ta sig ute i samhället? Hjärndött och irrelevant – haka på!Vi finns numera även på Podme! Det betyder att du hittar alla våra avsnitt, helt reklamfritt, i Podme-appen. Signa upp dig på podme.com – de första 14 dagarna är gratis. Ladda sedan ner appen i Appstore eller Google Play.
SUPPORT THE SHOW ON PATREON: https://www.patreon.com/lionsledbydonkeys A Sierra Leonean rebel group modeled after American West Side Gangsters and ripped out of their minds on drugs, kidnaps a patrol of British soldiers, sparking a rescue mission. Sources: Fowler, William (2004). Operation Barras: The SAS Rescue Mission: Sierra Leone 2000 Fremont-Barnes, Gregory (2009). Who Dares Wins: The SAS and the Iranian Embassy Siege 1980 Utas, Mats; Jörgel, Magnus (2008). "The West Side Boys: military navigation in the Sierra Leone civil war". Journal of Modern African Studies. Reno, William (February 2003), Political Networks in a Failing State The Roots and Future of Violent Conflict in Sierra Leone
In Episode 301 of Off the Mats Podcast, I sit down with Brazilian Jiu-Jitsu grappler and owner of Redwood Jiu-Jitsu, Naomi Davoudian, for a conversation about identity, belonging, and the long arc of growth that comes from staying committed to jiu-jitsu. We begin with who Naomi is outside of the gym before revisiting her life prior to training, the uncertainty of walking into her first class, and the emotional reality of being a beginner. Naomi reflects on moments where she questioned whether she belonged, how her relationship with jiu-jitsu evolved over time, and how training shaped her confidence, self-trust, and perspective off the mats. We talk about plateaus, invisible progress, longevity versus intensity, and what success looks like beyond belt promotions. This episode is for grapplers at every level, especially hobbyists and women navigating their place in the sport, who are learning that jiu-jitsu is often less about proving something and more about discovering who you are.
We're getting ready for big Mid-America Trucking Show next month, March 26-28 at the Louisville Convention Center, and ready to host our Trucker of the Year and cover all manner of the various goings on at the event. It's a big undertaking, from set-up to roll-out of the custom-truck show in the Paul K. Young Memorial competition to federal and state regulatory panels, trucking-business discussions and all the rest happening at the huge event: https://overdriveonline.com/tag/mats Yet we've got help from a bit of a not-so-secret weapon who this year happens to be an integral part of the official MATS programming. He's the player of and songwriter behind much of the music you hear under the voices on Overdrive Radio week-in-week-out, the man we've featured here too many times to count and whom regular readers will also know from his stories and tall tales, interviews, oral histories of OTR drivers of all stripes, and so much more all published under the Overdrive Extra banner at OverdriveOnline.com: https://overdriveonline.com/14865330 That writer, that performer, that veritable sage of the road, Long Haul Paul Marhoefer, will feature with others during the Friday night concert at MATS this year. He's got a couple of records upcoming, too, set for release in the coming weeks: One is archival from 1994, previously unreleased material from an embryonic stage of LHP's evolution as a songwriter he's calling "1994: The Lost Tapes." Then "The After Party Sessions" features live recordings from night shows at various trucking events over the last several years, most held in the custom-outfitted venue trailer of Brandon Carpenter that is the Old Iron Bar. Off the top of the podcast, a bit of taste of that live record via a track that is the very first of Marhoefer's we ever heard at Overdrive, when he competed in Overdrive's Trucker Talent Search music competition more than 10 years ago now: https://overdriveonline.com/14888649 He'd go on to place second that year. And his star rose so quickly among owner-operators and drivers in the aftermath that he never competed again -- no doubt in our minds he'd have won it had he. But he became a real fixture in performances around the competitors after that, alongside copious writing and reporting he's done for Overdrive since, all with a clear desire to tell the stories of others with care, with faith to the their voices and no small sense of empathy for the struggles we all endure. LHP brings all of that to his songwriting as well. He's endured plenty himself in life and trucking, as he memorably chronicled as host of our Over the Road podcast back in 2020, which saw air in partnership with the Radiotopia podcast network: https://www.overdriveonline.com/t/4405867 Don't miss his performance at MATS, yet if that show's just not in the cards for you this year, know that he'll be out at a variety of other events throughout the year, though somewhat limited compared to prior years given his father, near Madison, Wisconsin, has needed home care that he and his siblings and other family members have been coordinating. The "long haul" in LHP remains a reality for Marhoefer, if he does call his trucking career at this stage a kind of semi-retirement. He still hauls for Ohio-headquartered Moeller Trucking and lives with his wife, Denise, in Losantville, Indiana, the pair an undisputed force in trucking music and culture. In the podcast, he talks through tracks from both the new records as well as 2023 and 2024's “Legends of the Lost Highway” and “Floodwaters and Fires” records, respectively. Sit back, relax, and enjoy. Hope to see you at MATS. New records should be available around the time of MATS: https://www.longhaulpaulmusic.com/ Marhoefer's chronicle of his near-death encounter with a set of runaway duals in 2023: https://overdriveonline.com/15304967 More at the head of our Music to Truck By playlist: https://soundcloud.com/overdriveradio/sets/music-to-truck-by-no-1
Stian har satt fast hodet i Eiffeltårnet, Mats lurer på å hoppe med rullestol i fallskjerm fra toppen av tårnet, og vi har fått oppleve et vanvittig rått bilcross-konsept i Sverige. Pluss mye, mye mer. Selvfølgelig med HMS-en forskriftsmessig på plass. Hosted on Acast. See acast.com/privacy for more information.
In deze aflevering bespreken de mannen hun meest ongemakkelijke situatie in de club, hoe je iemand het beste begroet en of ze zich wel op hun plek voelen. Dit en meer hoor je in deze aflevering! Het is 3 over twintig… half in de studententijd, half in het werkende leven. Ondanks dat hosts Muk, Bram en Mats nog steeds jong en onbezonnen zijn, nemen ze jou elke maandagmiddag fris en fruitig mee in hun chaotische, soms volwassen, maar meestal niet-zo-volwassen levens. 3 over twintig is onderdeel van Dag en Nacht Media. Heb je interesse om te adverteren in deze podcast? Neem dan contact op met Dag en Nacht Media via adverteren@dagennacht.nl!See omnystudio.com/listener for privacy information.
Mats Bohman träffar Pär Norén från Myndigheten för psykologisk försvar. De går igenom myndighetens uppdrag att motverka otillbörlig informationspåverkan, utbildningar som erbjuds för att öka medvetenheten om desinformation, samt vikten av tillit i samhället. Pär delar insikter om hur känslor och sårbarheter påverkar hur vi tar till oss information och hur humor kan användas som ett verktyg mot desinformation. Avsnittet avslutas med tankar kring kommande val och hur informationspåverkan kan påverka dem. Länkar: Myndigheten för psykologiskt försvar Mötesplats Samhällssäkerhet Murphy solution Vill du höra mer från Mats Bohman? Prenumerera på nyhetsbrevet Murphy Brief, med bland annat Mats omvärldsbevakning.
I'm Dom Jackman. I founded Escape the City in 2010 to help people leave corporate jobs and find work that matters. 16 years later, 500k+ professionals have used the platform - mostly people 5-15 years into careers at places like McKinsey, Deloitte, Google, the big banks - who feel a growing gap between what they do all day and what they actually care about. I'm not from the EA community. I'm writing this because I think there's a real overlap between the people I work with and what the EA talent ecosystem actually needs. I want to test that before investing serious time in it. What I've noticed Reading through talent discussions on this forum, there's a consistent theme: the pipeline is strongest for early-career people. 80,000 Hours does great work for students and recent grads. Probably Good provides broad guidance. BlueDot, MATS, Talos build skills for specific cause areas. But mid-career professionals with real commercial experience keep coming up as underserved. The "Gaps and opportunities in the EA talent & recruiting landscape" post nails it: these people "don't have 'EA capital,' may be poorly networked and might feel alienated by current messaging." The post calls for "custom entry [...] ---Outline:(00:51) What Ive noticed(01:40) What I see every day(02:28) What Im thinking about building(03:24) Honest questions(04:39) Not looking for funding(04:58) Artifacts --- First published: February 11th, 2026 Source: https://forum.effectivealtruism.org/posts/H9pb6DEasgzjCff9a/500k-mid-career-professionals-want-to-do-more-good-with --- Narrated by TYPE III AUDIO.
On this episode of Mind the Gap, Tom Sherrington and Emma Turner are joined by Alex Fairlamb and Rachel Ball, co-authors of The Scaffolding Effect, to explore what scaffolding really is (and isn't) and why it has become such a pivotal idea in the move from “differentiation” to adaptive teaching. They discuss the research roots of the term, the practical reality of “knowing–doing,” and the central challenge that scaffolds must be temporary - designed to be removed through gradual release and guided by sharp checks for understanding. The conversation digs into common pitfalls (from “impermeable skins” of apparent progress to students becoming dependent on writing frames), debates the role of formulaic writing structures, and shows how scaffolding looks different across subjects and phases, including strategies involving reading, writing, retrieval practice, explanations, practical subjects, even homework. Packed with concrete examples and implementation-minded advice, this is a highly usable episode for teachers and leaders who want to support pupils towards real independence.Alex Fairlamb is a Trust T&L Network Lead and Senior Leader in charge of Teaching and Learning and CPD, based in the North East. She is a Chartered Teacher of History, a Specialist Leader in Education and an Evidence Lead in Education. Alex is a proud member of the Historical Association Secondary Committee and the Schools North East Steering Board. Alex is a History teacher and former Lead Practitioner of History and Teaching and Learning, with a strong commitment to ensuring that curriculums are diverse. She is an author and textbook writer, and recently completed her PhD focusing on Equality and Equity within education. Check out her website at https://alexfairlamb.com/Rachel Ball is Professional Development Specialist at Steplab. She is a former Assistant Principal in charge of teaching and learning and CPD, and passionate history teacher with 22 years experience. She is also a Fellow of the Chartered College of Teachers and an international speaker at schools and conferences including ResearchEd National Conference. Rachel is co-editor of What is History Teaching, Now? (2023) and co-author of The Scaffolding Effect (2025). Find Rachel's blog at theeducationalimposters.wordpress.comTom Sherrington has worked in schools as a teacher and leader for 30 years and is now a consultant specialising in teacher development and curriculum & assessment planning. He regularly contributes to conferences and CPD sessions locally and nationally and is busy working in schools and colleges across the UK and around the world. Follow Tom on X @teacherheadEmma Turner FCCT is a school improvement advisor, education consultant, trainer and author. She has almost three decades of primary teaching, headship and leadership experience across the sector, working and leading in both MATs and LAs. She works nationally and internationally on school improvement including at single school level and at scale. She has a particular interest in research informed practice in the primary phase, early career development, and CPD design. Follow Emma on X @emma_turner75This podcast is sponsored by Teaching WalkThrus and produced in association with Haringey Education Partnership. Find out more at https://walkthrus.co.uk/ and https://haringeyeducationpartnership.co.uk/
Hur hamnade några av världens bästa hockeyspelare i Borås och Östersund? I detta specialavsnitt följer vi spåren från Sovjetunionens statskontrollerade idrottssystem till svenska ishallar under systemets sista år. Det blir berättelser om superstjärnor, lokala eldsjälar, kulturkrockar och vad som händer när ett imperium börjar falla sönder — och konsekvenserna når ända till division 2 i Jämtland.Vi möter bland andra Nikolaj “Drutten” Drozdetskij och Vladimir Krutov, två spelare från den legendariska Röda maskinen, vars liv tog oväntade vägar när järnridån började spricka. Ett extraavsnitt om hockey, historia och människor i övergången mellan två världar.Läslista:Axelsson, David & Rydén, Johan, Den osannolika övergången: Så hamnade världsstjärnan i Borås, Borås Tidning, 2020. Axelsson, David & Rydén, Johan, En världsstjärna till reapris: ”Det kommer aldrig att hända igen”, Borås Tidning, 2020. Axelsson, David & Rydén, Johan, ”Polisen tittade på Nik, det blev inga böter, däremot fick han skriva autografer…”, Borås Tidning, 2022. Axelsson, David & Rydén, Johan, ”Rykten sa att den ryska maffian tog livet av Nik”, Borås Tidning, 2022. Henrikson, Malin, När Drutten fick mig att gråta av förnedring, Borås Tidning, 2020. Sportbilder vi minns: Hockeybomben som slog ned i Östersund – Vladimir Krutov intog Z-hallen: ”Den största värvningen i svensk idrottshistoria”, Östersunds-Posten, 2020. Wennerholm, Mats, Den nya friheten blev för mycket för Krutov, Aftonbladet/Sportbladet.Wennerholm, Mats, Det var alltid då, då – och no problem, Aftonbladet/Sportbladet. Hosted on Acast. See acast.com/privacy for more information.
Vad händer när vi vågar kliva utanför det bekväma? Mats, Lars och Lena delar personliga erfarenheter och avslöjar varför syftet är din bästa vän i utmanande situationer.Dessutom: strategier för att hantera rädslor och negativa tankar – och hur du kan omvandla dem till lärande och utveckling.Nyfiken? Lyssna på hela samtalet och få inspiration till att växa både personligt och professionellt!#Syfte#Mål#Utmaning#Modig#Trygg#komfortzon
For the first show of 2026 and the fourth season of the Voice Of GO(r)D podcast project, I am very happy to bring you a discussion with Ike Stephens, the empresario behind the highly successful and very popular YouTube show, Bonehead Truckers.Ike has been documenting the decline of the American trucking industry via his hilarious and well done commentary videos, which highlight what happens when The Powers That Be take a trade which requires high levels of competency and operational acumen, and attempt to deskill it by flooding the market with hapless locals from the unemployment line, or with insourced labor that is likewise clueless. As of late, Ike has been pulling no punches with calling out everyone involved in allowing this sad state of affairs to take place.You can find Mr Stephens all over the place -https://www.youtube.com/@BoneheadTruckershttps://x.com/boneheadtruckrshttps://www.facebook.com/boneheadtruckershttps://www.instagram.com/boneheadtruckers/And if you will be at the Mid-America Trucking Show in Louisville, Kentucky next month, March 26-28, you can come meet Ike in person - and I might even be at his exhibition location with copies of my book for sale.Speaking of the book - we are less than 6 weeks out from release, and my book is already doing numbers in various Amazon book categories. As of right now, End Of The Road was number ONE in Canadian Politics, number 13 in Libertarianism, and number ONE in Transportation Industry.The first two are curious, given that Canadian Politics only figure in the intro and final chapters, and I use the term ‘libertarian' but a small handful of times; the politics that comes through my arguments are all over the place - libertarian, conservative, labor left, populist … I like to think the book's politics defy categorization.And on that note, go ahead and pre-order for delivery to your door on March 24, or come meet me at MATS, where I will sign a copy for you, and you can pay cash for a steep discount. The audiobook will be available by then, and I will have a QR code handy for those who want to download it to their devices instantly.In the US you can order a hardcover copy direct from my publisher -https://creedandculture.com/books/end-of-the-road-inside-the-war-on-truckers/In Canada you can do the same from Chapters/Indigo -https://www.indigo.ca/en-ca/end-of-the-road-inside-the-war-on-truckers/9781967613021.htmlIf you must -https://www.amazon.com/End-Road-Inside-War-Truckers/dp/1967613028/Thanks again for listening and making my podcast what it is, and thanks again for reading my work here. Check out my latest piece, which is now approaching four thousand reads here on Substack -https://autonomoustruckers.substack.com/p/truckers-tikka-masala-part-2-theAs always, questions, comments, suggestions, corrections and Hate Mail are welcomed and strongly encouraged - gordilocks@protonmail.com
In the 228th BlockTalks we learn from Mats Olsen, CTO and co-founder of Dune, how crypto went from counting transactions on block explorers to AI-driven analytics.LinksLinkedIn: https://www.linkedin.com/in/mewwts/X: https://x.com/mewwtsX, Dune: https://x.com/DuneWeb: https://dune.comAll of BlockTalks:https://open.spotify.com/playlist/2kC88UznBpwM03SKCGQeSg. Redes sociais / comms.. https://blockdropspodcast.xyz/.. https://blockdrops.substack.com .. Instagram.com/blockdropspodcast.. Twitter.com/blockdropspod.. Blockdrops.lens .. https://warpcast.com/mauriciomagaldi.. youtube.com/@BlockDropsPodcast.. Meu conteúdo em inglês twitter.com/0xmauricio.. Newsletter do linkedin https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7056680685142454272.. blockdropspodcast@gmail.com
Edward Blom och Mats Ryd gör vad de kan för att – det nyligen ur Svenska Akademiens ordlista utmönstrade – ordet "lättgrogg" ska bli mer frekvent, inte bara i allas vokabulär utan även som dryck i allas strupar, kanske i form av "mahognygrogg" (eller "grosshandlare"). De glada gastronomerna dricker fulbrandy och pratar om (armenisk) finbrandy inför fastan, och listar sina favoriter vad gäller sportlovsmat! Det blir en härlig lista av värmande drycker – men framför allt med husmanskosträtter som kan landa fint i magen efter en dag i skidbacken.Och apropå backar berättar Edward om när han åkte slalom – och vad han gjorde i skidliften.Dagens lyssnarfråga handlar om fastan. Hur gör man när man vill idka fasta, men har råkat boka en resa till Champagne till sin födelsedagsfirande hustru under perioden? Som tur är vet både Edward och Mats på råd!Följ "Edward Bloms smörgåsbord" genom att bli betalande prenumerant. Det kostar blott 39:-/månad, vilket i regel ger ett pris per podd på under tio kronor – mycket prisvärt! Då får ni dessutom tillgång till hela arkivet, med poddsamtal från 2017 och framåt! Mer information här: https://underproduktion.se/edwardblomssmorgasbord
Mats er på treningsleir i Barcelona så vi får med oss Milos for å gå igjennom noen talking-points. Vi snakker kampen om Premier League gullet. Viser Arsenal litt frykt nå ? Kan dette være med på å avgjøre ligaen? Hva betyr egentlig vinnerkultur? Vi tar for oss Arne Slot`s stadige utsagn på at han så ofte møter "low blocks". VI snakker Tottenham fra Thomas Frank til Igor Tudor og hva er egentlig feil i Tottenham ? Men må også innom Barcelona og deres noe ustabile forsvar. Til slutt - Den store Bayern Munchen praten med to ivrige sjeler med mye på hjertet.
In Episode 300 of the Off the Mats Podcast, I sit down with my original Brazilian Jiu-Jitsu coach, Danny Ives, for a conversation about evolution, longevity, and what the black belt really represents. This isn't just a milestone episode, it's a reflection on mat time, consistency, and how jiu-jitsu changes the longer you stay in it. We break down the differences between old school and new school jiu-jitsu, less information versus the instructional era, fundamentals versus specialization, gym reputation versus online branding, and how competition has evolved from smaller local tournaments to global stages like ADCC. We talk about whether the average blue belt today is more technical, whether fundamentals are being lost, and what each era gets right and wrong. We also deconstruct the myth of the black belt. Do black belts really win every round? Do they stop learning? What changes technically and mentally after reaching that rank? Danny answers direct questions in our “Ask A Black Belt” segment, covering ego, longevity, training after 40, recovery habits, and what white, blue, and purple belts misunderstand most. This episode is for grapplers at every level who want perspective, not hype. If you're chasing improvement, questioning your path, or wondering what long-term jiu-jitsu really looks like, this conversation is for you. Old school gave us roots. New school gives us branches. The belt is symbolic, but the mat doesn't care what color you're wearing.
In deze aflevering hebben de mannen het erover wie zij zouden kunnen pakken in de ring, wordt Bram uitgemaakt voor racist en vertelt Mats een schokkend verhaal over Walibi Fright Nights. Dat en meer hoor je in deze aflevering. Het is 3 over twintig… half in de studententijd, half in het werkende leven. Ondanks dat hosts Muk, Bram en Mats nog steeds jong en onbezonnen zijn, nemen ze jou elke maandagmiddag fris en fruitig mee in hun chaotische, soms volwassen, maar meestal niet-zo-volwassen levens. 3 over twintig is onderdeel van Dag en Nacht Media. Heb je interesse om te adverteren in deze podcast? Neem dan contact op met Dag en Nacht Media via adverteren@dagennacht.nl!See omnystudio.com/listener for privacy information.
Tilders, Julian www.deutschlandfunk.de, Sport am Samstag
Tilders, Julian www.deutschlandfunk.de, Sport am Samstag
Mats, Niklas och Jonas lyckas samla sig i den bistra vinterkylan, för att ge er det senaste i nördväg! Vi inleder som vanligt med ett nyhetssvep om vad som hänt sedan sist. Därefter snackar Mats on Wonder Man, The Beauty och Star Trek: Starfleet Academy, medan Jonas gör ett inpass om Task. Mats berättar varför din nya hobby bör vara virtuell klippklättring och vad han tycker om de två spel i genren han testat i veckan: Cairn samt New Heights. Dessutom lite grann om det härligt fria rymdmanagementspelet The Last Starship, som precis släppts. Niklas berättar om två bräd- och eller kortspel som du kan spela på lunchrasten, Fantasy Realms och Dice Throne, och till sist får vi med en Westeros-rapport om Knight of the Seven Kingdoms avsnitt 4. Tack och förlåt!
Studio Allsvenskan är sponsrade av Snabbare – det okrångliga spelbolaget!Köp en andel till vårt andelsspel på SnabbTipset hos Snabbare.https://www.snabbare.com/snabbtipset-studioallsvenskan18+ | Stödlinjen.se | Spela AnsvarsfulltÅrets bästa sportdealar är här! TV4 Play och Studio Allsvenskan har ett samarbete där du kan se vinter-OS, Superettan, La Liga och Serie med ett galet vasst erbjudande – för enbart 69 kronor kronor i månaden för tre månader! Nedsatt från 249 kronor i månaden. Gå in på https://www.tv4play.se/kampanj/studioallsvenskan för att ta del av erbjudandet! Dessutom har vi nu även hockeypaketet där du kan se SHL och Hockeyallsvenskan till halva priset hos TV4 Play – men även halva priset på Sport Total-paketet där du får tillgång till ALLT innehåll. Klickan på länken för mer info: https://www.tv4play.se/kampanj/studiohockeyDet är fredag i kvarteret och ni borde veta vad det innebär – ett klassiskt Ringrace i sann Studio Allsvenskan-anda!Vi inleder med Kalmars sportchef Mats Winblad för att ställa frågor kring de nyförvärv de har gjort och framför allt varför det är lån och tvåårskontrakt.Hur ser Mats på den kritiken? Och kommer det fler nyförvärv till Kalmar inom kort?Därefter följer vi upp med IFK Göteborg-mittbacken August Erlingmark för att höra hur lägret i Portugal var.Fick de bara springa eller blev det någon fotboll också?Vad väntar han sig av Blåvitt nästa år? Och hur bra är Rockson egentligen?Slutligen kopplar vi även upp oss mot Mjällbys sportchef Hasse Larsson för att höra hur läget är på Listerlandet.Missa inte Studio Allsvenskans Ringrace.Ute överallt.Studio Allsvenskan finns även på Patreon, där du får ALLA våra avsnitt reklamfritt direkt efter inspelning. Dessutom får du tillgång till våra exklusiva poddserier där vi släpper avsnitt tisdag till fredag varje vecka. Bli medlem här!Följ Studio Allsvenskan på sociala medier: Twitter!Facebook!Instagram!Youtube!TikTok! Hosted on Acast. See acast.com/privacy for more information.
Två nyförvärv har landat på Guldfågeln Arena under veckan. Vi tar en pratstund med Kalmar FF:s sportchef Mats Winblad för att höra vad han tror att spelarna kan tillföra laget och hur arbetet med truppen fortlöper framöver.
Alla shownotes finns på https://www.enlitenpoddomit.se , skulle det se konstigt ut i din poddspelare så titta gärna där efter alla länkar kring det vi pratar om Avsnitt 558 spelades in den 10 februari och därför så handlar dagens avsnitt om: INTRO: Mats har barn, villa och jobbar. David har gjort massor. Johan har fyllt år och fått LEGO. FEEDBACK AND BACKLOG: - Ikea bekräftar Matter problem https://www.m3.se/article/3053788/ikea-erkanner-trubbel-for-nya-matter-enheter.html - Samsung säljer slut på Trifold https://9to5google.com/2026/02/10/samsung-will-restock-the-galaxy-z-trifold-in-the-us-later-this-month/ ALLMÄNT NYTT - Nu ska vi vibe-jobba https://paddo.dev/blog/opus-4-6-vibe-working-inflection/ - Perplexity skapar ”modell-råd” https://www.perplexity.ai/hub/blog/introducing-model-council - Förbättringar i Opus Claude 4.6 https://claude.com/blog/opus-4-6-finance/ - USA försöker nästan göra en ChatControl fast för 3D skrivare https://hackaday.com/2026/01/19/washington-state-bill-seeks-to-add-firearms-detection-to-3d-printers/ - Discord kontrollerar ålder för användare https://www.zdnet.com/article/discord-age-verification-requirement/ - WhatsApp öppnar och stänger https://swedroid.se/nu-gar-det-att-prata-med-folk-pa-whatsapp-utan-whatsapp/ https://www.thurrott.com/cloud/332510/eu-commission-says-whatsapp-banning-other-ai-chatbots-may-be-anticompetitive - Bitwarden släpper nya funktkoner och höjer priset https://www.thurrott.com/cloud/332249/bitwarden-enhances-premium-plan-doubles-price MICROSOFT - Microsoft lyssnar på Windows användare https://www.thurrott.com/windows/windows-11/332526/microsoft-announces-windows-baseline-security-mode-and-user-transparency-and-consent - Microsoft uppdaterar SecureBoot Certifikat https://www.thurrott.com/windows/332559/microsoft-to-roll-out-new-secure-boot-certificates-to-keep-old-windows-pcs-secure APPLE - Nytt AI-avtal med Google https://markets.financialcontent.com/stocks/article/tokenring-2026-2-6-apple-inks-1-billion-deal-with-google-to-power-gemini-fueled-siri-revamp/ - Apple tränar Qwen2.5 på UI https://machinelearning.apple.com/research/designer-feedback GOOGLE - Google hjälper dig rensa Internet https://www.thurrott.com/cloud/332555/googles-results-about-you-tool-can-now-help-users-protect-their-id-numbers PRYLLISTA - Mats : Emeet Pixy, https://emeet.com/en-eu/products/emeet-pixy & https://www.amazon.de/dp/B0FPB67QBV - David: Apple Pencil Pro, https://www.apple.com/se/xc/product/MX2D3QN/A - Johan: En 3D-skrivare EGNA LÄNKAR - En Liten Podd Om IT på webben, http://enlitenpoddomit.se/ - En Liten Podd Om IT på Facebook, https://www.facebook.com/EnLitenPoddOmIt/ - En Liten Podd Om IT på Youtube, https://www.youtube.com/enlitenpoddomit - Ge oss gärna en recension - https://podcasts.apple.com/se/podcast/en-liten-podd-om-it/id946204577?mt=2#see-all/reviews - https://www.podchaser.com/podcasts/en-liten-podd-om-it-158069 LÄNKAR TILL VART MAN HITTAR PODDEN FÖR ATT LYSSNA: - Apple Podcaster (iTunes), https://itunes.apple.com/se/podcast/en-liten-podd-om-it/id946204577 - Overcast, https://overcast.fm/itunes946204577/en-liten-podd-om-it - Acast, https://www.acast.com/enlitenpoddomit - Spotify, https://open.spotify.com/show/2e8wX1O4FbD6M2ocJdXBW7?si=HFFErR8YRlKrELsUD--Ujg%20 - Stitcher, https://www.stitcher.com/podcast/the-nerd-herd/en-liten-podd-om-it - YouTube, https://www.youtube.com/enlitenpoddomit LÄNK TILL DISCORD DÄR MAN HITTAR LIVE STREAM + CHATT - http://discord.enlitenpoddomit.se (Och glöm inte att maila bjorn@enlitenpoddomit.se om du vill ha klistermärken, skicka med en postadress bara. :)
The one about TV Food Ads, AI Marketing Assistants and the film, Monsters Inc - TG131 00:00:00 IntroductionHere are your hosts, Roger and Pascal.00:02:50 In the NewsA selection of announcements and news releases from the world of marketing and technology that caught our attention.00:15:59 Content SpotlightsROGER: The Food Vibe ShiftWaitrose: https://www.retailgazette.co.uk/blog/2026/02/waitrose-campaign-space/McDonalds: https://creative.salon/articles/work/mcdonald-s-leo-s-uk-all-flavour-no-messPASCAL: Lessons and insights from @RogEdwardsTV https://www.youtube.com/@RogEdwardsTV Celebrating recent milestones and good practices about vlogging.00:36:41 This Week in HistoryOur selection of historical events and anniversaries from the world of science, technology and popular culture.00:43:34 Marketing Tech and AppsROGER: It's all about AI presentations and where it leaves PowerPoint:Yoodli (The AI Speech Coach): https://yoodli.ai/Prezent - An App that understands visual storytelling. https://www.prezent.ai/PASCAL: It's all about building your AI marketing assistants:Perplexity.ai https://www.perplexity.ai/ the ultimate research assistants ideal for identifying trends, gathering market intelligence and creating customers personasNotebookLM by Google https://notebooklm.google/ the impressive marketing ideas engine combining extensive chat functionality and up to 9 creativity AI tools: audio overviews, video overviews, mind map, reports, flash cards, quiz, infographic, slide deck, and data table.00:53:57 Film MarketingMONSTERS INC. (2001) Directed by: Pete DocterWritten by: Andrew Stanton and Daniel Gerson,Cast: starring the voices of John Goodman, Billy Crystal, Steve Buscemi, James Coburn, Jennifer Tilly, and Mary Gibbs.Music by: Randy NewmanTagline: In a city of monsters with no humans called Monstropolis there's a company, called Monsters, Inc. whose employees gather children's screams to power the city.We look at the challenges Pixar faced as they moved away from the familiar and relatable world of Toy Story and A Bug's Life. The core premise is a factory that harvests children's screams; without careful framing, that could read as frightening or off-putting for parents of younger kids. How did the marketing work?About Two Geeks and A Marketing Podcast Hosted by the two geeks, Roger Edwards and Pascal Fintoni, to keep you up to date with the latest news, tech, content and wisdom from the world of marketing.Roger is a marketing speaker and consultant who's spent his whole career helping his customers keep their marketing simple but effective. He's the author of Cats, Mats and Marketing Plans and the creator of the RogVLOG video series.Pascal is a digital marketing veteran, he is a speaker, trainer and advisor with nearly three decades of...
Efter att ha haft ett långvarigt narkotikamissbruk och i perioder varit intagen för psykiatrisk tvångsvård har min syster blivit ”nyfrälst”. Nu trakasserar hon mig med uppmaningar att lämna ett missbruk jag inte har. Hur ska jag hantera vår relation? Det undrar Mats i veckans brev till Anna-Karin Wyndhamn. Läs här vad hon svarar honom. Inläsare: Staffan Dopping
Veckans recensioner: Vattenläckapodden, mytomanska, mat i munnen, ”Mats mat”, sushibazooka, Måli*la Hote*l, röster från vinden och Walking LED.
In this episode of Off the Mats Podcast, I sit down with Katie Laablalli Beirut-Kloth for a conversation about identity, sobriety, competition, and what it means to keep becoming yourself through jiu-jitsu. Katie opens up about who she is beyond medals and brackets, reflecting on life before jiu-jitsu and what she was searching for when she first stepped onto the mats. We talk about how jiu-jitsu evolved from a sport into a form of regulation, a way to manage chaos, find structure, and reconnect with herself through physical pressure, movement, and routine. A major part of this conversation centers on Katie's sobriety and recovery journey. Rather than treating it as a side note, we explore how training became non-negotiable, how her relationship with discipline and competition shifted, and what growth looks like when you're rebuilding from the inside out. Katie also shares how competing at events like ADCC Opens reshaped her definition of success, especially when balancing ambition with self-awareness. We also dive into her work with activism, intentional living, and how practices outside jiu-jitsu contribute to self-knowledge and balance. From there, we talk about belonging, gym culture, and the complicated reality of not always feeling at home in jiu-jitsu spaces and how community can evolve over time. This episode is for grapplers, competitors, and anyone navigating recovery, identity shifts, or using sport as a way to survive and grow. It's not about motivation or inspiration, it's about truth, reflection, and meeting yourself where you are.
In deze aflevering bespreken we Brams knoflookolieblunder, hebben we het over het leukste budgetuitje om met je vriendin te doen en delen we Mats’ ervaring bij Wilders. Dat en meer hoor je in deze aflevering! Het is 3 over twintig… half in de studententijd, half in het werkende leven. Ondanks dat hosts Muk, Bram en Mats nog steeds jong en onbezonnen zijn, nemen ze jou elke maandagmiddag fris en fruitig mee in hun chaotische, soms volwassen, maar meestal niet-zo-volwassen levens. 3 over twintig is onderdeel van Dag en Nacht Media. Heb je interesse om te adverteren in deze podcast? Neem dan contact op met Dag en Nacht Media via adverteren@dagennacht.nl!See omnystudio.com/listener for privacy information.
I dagens episode har vi med oss Mats Mastervik, gründeren bak Planeo. Planeo har som mål å revolusjonere utviklingen av planprosesser. Mats har vært gründer tidligere. I dagens episode går vi gjennom hans reise til dit han er i dag. Enjoy!Takk for at du lytter til Impressions Podcast! Har du forslag til gjester vi kan invitere? Send oss en melding på sosiale medier:Instagram: instagram.com/impressionspodTikTok: tiktok.com/@impressionspod Hosted on Acast. See acast.com/privacy for more information.
From Palantir and Two Sigma to building Goodfire into the poster-child for actionable mechanistic interpretability, Mark Bissell (Member of Technical Staff) and Myra Deng (Head of Product) are trying to turn “peeking inside the model” into a repeatable production workflow by shipping APIs, landing real enterprise deployments, and now scaling the bet with a recent $150M Series B funding round at a $1.25B valuation.In this episode, we go far beyond the usual “SAEs are cool” take. We talk about Goodfire's core bet: that the AI lifecycle is still fundamentally broken because the only reliable control we have is data and we post-train, RLHF, and fine-tune by “slurping supervision through a straw,” hoping the model picks up the right behaviors while quietly absorbing the wrong ones. Goodfire's answer is to build a bi-directional interface between humans and models: read what's happening inside, edit it surgically, and eventually use interpretability during training so customization isn't just brute-force guesswork.Mark and Myra walk through what that looks like when you stop treating interpretability like a lab demo and start treating it like infrastructure: lightweight probes that add near-zero latency, token-level safety filters that can run at inference time, and interpretability workflows that survive messy constraints (multilingual inputs, synthetic→real transfer, regulated domains, no access to sensitive data). We also get a live window into what “frontier-scale interp” means operationally (i.e. steering a trillion-parameter model in real time by targeting internal features) plus why the same tooling generalizes cleanly from language models to genomics, medical imaging, and “pixel-space” world models.We discuss:* Myra + Mark's path: Palantir (health systems, forward-deployed engineering) → Goodfire early team; Two Sigma → Head of Product, translating frontier interpretability research into a platform and real-world deployments* What “interpretability” actually means in practice: not just post-hoc poking, but a broader “science of deep learning” approach across the full AI lifecycle (data curation → post-training → internal representations → model design)* Why post-training is the first big wedge: “surgical edits” for unintended behaviors likereward hacking, sycophancy, noise learned during customization plus the dream of targeted unlearning and bias removal without wrecking capabilities* SAEs vs probes in the real world: why SAE feature spaces sometimes underperform classifiers trained on raw activations for downstream detection tasks (hallucination, harmful intent, PII), and what that implies about “clean concept spaces”* Rakuten in production: deploying interpretability-based token-level PII detection at inference time to prevent routing private data to downstream providers plus the gnarly constraints: no training on real customer PII, synthetic→real transfer, English + Japanese, and tokenization quirks* Why interp can be operationally cheaper than LLM-judge guardrails: probes are lightweight, low-latency, and don't require hosting a second large model in the loop* Real-time steering at frontier scale: a demo of steering Kimi K2 (~1T params) live and finding features via SAE pipelines, auto-labeling via LLMs, and toggling a “Gen-Z slang” feature across multiple layers without breaking tool use* Hallucinations as an internal signal: the case that models have latent uncertainty / “user-pleasing” circuitry you can detect and potentially mitigate more directly than black-box methods* Steering vs prompting: the emerging view that activation steering and in-context learning are more closely connected than people think, including work mapping between the two (even for jailbreak-style behaviors)* Interpretability for science: using the same tooling across domains (genomics, medical imaging, materials) to debug spurious correlations and extract new knowledge up to and including early biomarker discovery work with major partners* World models + “pixel-space” interpretability: why vision/video models make concepts easier to see, how that accelerates the feedback loop, and why robotics/world-model partners are especially interesting design partners* The north star: moving from “data in, weights out” to intentional model design where experts can impart goals and constraints directly, not just via reward signals and brute-force post-training—Goodfire AI* Website: https://goodfire.ai* LinkedIn: https://www.linkedin.com/company/goodfire-ai/* X: https://x.com/GoodfireAIMyra Deng* Website: https://myradeng.com/* LinkedIn: https://www.linkedin.com/in/myra-deng/* X: https://x.com/myra_dengMark Bissell* LinkedIn: https://www.linkedin.com/in/mark-bissell/* X: https://x.com/MarkMBissellFull Video EpisodeTimestamps00:00:00 Introduction00:00:05 Introduction to the Latent Space Podcast and Guests from Goodfire00:00:29 What is Goodfire? Mission and Focus on Interpretability00:01:01 Goodfire's Practical Approach to Interpretability00:01:37 Goodfire's Series B Fundraise Announcement00:02:04 Backgrounds of Mark and Myra from Goodfire00:02:51 Team Structure and Roles at Goodfire00:05:13 What is Interpretability? Definitions and Techniques00:05:30 Understanding Errors00:07:29 Post-training vs. Pre-training Interpretability Applications00:08:51 Using Interpretability to Remove Unwanted Behaviors00:10:09 Grokking, Double Descent, and Generalization in Models00:10:15 404 Not Found Explained00:12:06 Subliminal Learning and Hidden Biases in Models00:14:07 How Goodfire Chooses Research Directions and Projects00:15:00 Troubleshooting Errors00:16:04 Limitations of SAEs and Probes in Interpretability00:18:14 Rakuten Case Study: Production Deployment of Interpretability00:20:45 Conclusion00:21:12 Efficiency Benefits of Interpretability Techniques00:21:26 Live Demo: Real-Time Steering in a Trillion Parameter Model00:25:15 How Steering Features are Identified and Labeled00:26:51 Detecting and Mitigating Hallucinations Using Interpretability00:31:20 Equivalence of Activation Steering and Prompting00:34:06 Comparing Steering with Fine-Tuning and LoRA Techniques00:36:04 Model Design and the Future of Intentional AI Development00:38:09 Getting Started in Mechinterp: Resources, Programs, and Open Problems00:40:51 Industry Applications and the Rise of Mechinterp in Practice00:41:39 Interpretability for Code Models and Real-World Usage00:43:07 Making Steering Useful for More Than Stylistic Edits00:46:17 Applying Interpretability to Healthcare and Scientific Discovery00:49:15 Why Interpretability is Crucial in High-Stakes Domains like Healthcare00:52:03 Call for Design Partners Across Domains00:54:18 Interest in World Models and Visual Interpretability00:57:22 Sci-Fi Inspiration: Ted Chiang and Interpretability01:00:14 Interpretability, Safety, and Alignment Perspectives01:04:27 Weak-to-Strong Generalization and Future Alignment Challenges01:05:38 Final Thoughts and Hiring/Collaboration Opportunities at GoodfireTranscriptShawn Wang [00:00:05]: So welcome to the Latent Space pod. We're back in the studio with our special MechInterp co-host, Vibhu. Welcome. Mochi, Mochi's special co-host. And Mochi, the mechanistic interpretability doggo. We have with us Mark and Myra from Goodfire. Welcome. Thanks for having us on. Maybe we can sort of introduce Goodfire and then introduce you guys. How do you introduce Goodfire today?Myra Deng [00:00:29]: Yeah, it's a great question. So Goodfire, we like to say, is an AI research lab that focuses on using interpretability to understand, learn from, and design AI models. And we really believe that interpretability will unlock the new generation, next frontier of safe and powerful AI models. That's our description right now, and I'm excited to dive more into the work we're doing to make that happen.Shawn Wang [00:00:55]: Yeah. And there's always like the official description. Is there an understatement? Is there an unofficial one that sort of resonates more with a different audience?Mark Bissell [00:01:01]: Well, being an AI research lab that's focused on interpretability, there's obviously a lot of people have a lot that they think about when they think of interpretability. And I think we have a pretty broad definition of what that means and the types of places that can be applied. And in particular, applying it in production scenarios, in high stakes industries, and really taking it sort of from the research world into the real world. Which, you know. It's a new field, so that hasn't been done all that much. And we're excited about actually seeing that sort of put into practice.Shawn Wang [00:01:37]: Yeah, I would say it wasn't too long ago that Anthopic was like still putting out like toy models or superposition and that kind of stuff. And I wouldn't have pegged it to be this far along. When you and I talked at NeurIPS, you were talking a little bit about your production use cases and your customers. And then not to bury the lead, today we're also announcing the fundraise, your Series B. $150 million. $150 million at a 1.25B valuation. Congrats, Unicorn.Mark Bissell [00:02:02]: Thank you. Yeah, no, things move fast.Shawn Wang [00:02:04]: We were talking to you in December and already some big updates since then. Let's dive, I guess, into a bit of your backgrounds as well. Mark, you were at Palantir working on health stuff, which is really interesting because the Goodfire has some interesting like health use cases. I don't know how related they are in practice.Mark Bissell [00:02:22]: Yeah, not super related, but I don't know. It was helpful context to know what it's like. Just to work. Just to work with health systems and generally in that domain. Yeah.Shawn Wang [00:02:32]: And Mara, you were at Two Sigma, which actually I was also at Two Sigma back in the day. Wow, nice.Myra Deng [00:02:37]: Did we overlap at all?Shawn Wang [00:02:38]: No, this is when I was briefly a software engineer before I became a sort of developer relations person. And now you're head of product. What are your sort of respective roles, just to introduce people to like what all gets done in Goodfire?Mark Bissell [00:02:51]: Yeah, prior to Goodfire, I was at Palantir for about three years as a forward deployed engineer, now a hot term. Wasn't always that way. And as a technical lead on the health care team and at Goodfire, I'm a member of the technical staff. And honestly, that I think is about as specific as like as as I could describe myself because I've worked on a range of things. And, you know, it's it's a fun time to be at a team that's still reasonably small. I think when I joined one of the first like ten employees, now we're above 40, but still, it looks like there's always a mix of research and engineering and product and all of the above. That needs to get done. And I think everyone across the team is, you know, pretty, pretty switch hitter in the roles they do. So I think you've seen some of the stuff that I worked on related to image models, which was sort of like a research demo. More recently, I've been working on our scientific discovery team with some of our life sciences partners, but then also building out our core platform for more of like flexing some of the kind of MLE and developer skills as well.Shawn Wang [00:03:53]: Very generalist. And you also had like a very like a founding engineer type role.Myra Deng [00:03:58]: Yeah, yeah.Shawn Wang [00:03:59]: So I also started as I still am a member of technical staff, did a wide range of things from the very beginning, including like finding our office space and all of this, which is we both we both visited when you had that open house thing. It was really nice.Myra Deng [00:04:13]: Thank you. Thank you. Yeah. Plug to come visit our office.Shawn Wang [00:04:15]: It looked like it was like 200 people. It has room for 200 people. But you guys are like 10.Myra Deng [00:04:22]: For a while, it was very empty. But yeah, like like Mark, I spend. A lot of my time as as head of product, I think product is a bit of a weird role these days, but a lot of it is thinking about how do we take our frontier research and really apply it to the most important real world problems and how does that then translate into a platform that's repeatable or a product and working across, you know, the engineering and research teams to make that happen and also communicating to the world? Like, what is interpretability? What is it used for? What is it good for? Why is it so important? All of these things are part of my day-to-day as well.Shawn Wang [00:05:01]: I love like what is things because that's a very crisp like starting point for people like coming to a field. They all do a fun thing. Vibhu, why don't you want to try tackling what is interpretability and then they can correct us.Vibhu Sapra [00:05:13]: Okay, great. So I think like one, just to kick off, it's a very interesting role to be head of product, right? Because you guys, at least as a lab, you're more of an applied interp lab, right? Which is pretty different than just normal interp, like a lot of background research. But yeah. You guys actually ship an API to try these things. You have Ember, you have products around it, which not many do. Okay. What is interp? So basically you're trying to have an understanding of what's going on in model, like in the model, in the internal. So different approaches to do that. You can do probing, SAEs, transcoders, all this stuff. But basically you have an, you have a hypothesis. You have something that you want to learn about what's happening in a model internals. And then you're trying to solve that from there. You can do stuff like you can, you know, you can do activation mapping. You can try to do steering. There's a lot of stuff that you can do, but the key question is, you know, from input to output, we want to have a better understanding of what's happening and, you know, how can we, how can we adjust what's happening on the model internals? How'd I do?Mark Bissell [00:06:12]: That was really good. I think that was great. I think it's also a, it's kind of a minefield of a, if you ask 50 people who quote unquote work in interp, like what is interpretability, you'll probably get 50 different answers. And. Yeah. To some extent also like where, where good fire sits in the space. I think that we're an AI research company above all else. And interpretability is a, is a set of methods that we think are really useful and worth kind of specializing in, in order to accomplish the goals we want to accomplish. But I think we also sort of see some of the goals as even more broader as, as almost like the science of deep learning and just taking a not black box approach to kind of any part of the like AI development life cycle, whether that. That means using interp for like data curation while you're training your model or for understanding what happened during post-training or for the, you know, understanding activations and sort of internal representations, what is in there semantically. And then a lot of sort of exciting updates that were, you know, are sort of also part of the, the fundraise around bringing interpretability to training, which I don't think has been done all that much before. A lot of this stuff is sort of post-talk poking at models as opposed to. To actually using this to intentionally design them.Shawn Wang [00:07:29]: Is this post-training or pre-training or is that not a useful.Myra Deng [00:07:33]: Currently focused on post-training, but there's no reason the techniques wouldn't also work in pre-training.Shawn Wang [00:07:38]: Yeah. It seems like it would be more active, applicable post-training because basically I'm thinking like rollouts or like, you know, having different variations of a model that you can tweak with the, with your steering. Yeah.Myra Deng [00:07:50]: And I think in a lot of the news that you've seen in, in, on like Twitter or whatever, you've seen a lot of unintended. Side effects come out of post-training processes, you know, overly sycophantic models or models that exhibit strange reward hacking behavior. I think these are like extreme examples. There's also, you know, very, uh, mundane, more mundane, like enterprise use cases where, you know, they try to customize or post-train a model to do something and it learns some noise or it doesn't appropriately learn the target task. And a big question that we've always had is like, how do you use your understanding of what the model knows and what it's doing to actually guide the learning process?Shawn Wang [00:08:26]: Yeah, I mean, uh, you know, just to anchor this for people, uh, one of the biggest controversies of last year was 4.0 GlazeGate. I've never heard of GlazeGate. I didn't know that was what it was called. The other one, they called it that on the blog post and I was like, well, how did OpenAI call it? Like officially use that term. And I'm like, that's funny, but like, yeah, I guess it's the pitch that if they had worked a good fire, they wouldn't have avoided it. Like, you know what I'm saying?Myra Deng [00:08:51]: I think so. Yeah. Yeah.Mark Bissell [00:08:53]: I think that's certainly one of the use cases. I think. Yeah. Yeah. I think the reason why post-training is a place where this makes a lot of sense is a lot of what we're talking about is surgical edits. You know, you want to be able to have expert feedback, very surgically change how your model is doing, whether that is, you know, removing a certain behavior that it has. So, you know, one of the things that we've been looking at or is, is another like common area where you would want to make a somewhat surgical edit is some of the models that have say political bias. Like you look at Quen or, um, R1 and they have sort of like this CCP bias.Shawn Wang [00:09:27]: Is there a CCP vector?Mark Bissell [00:09:29]: Well, there's, there are certainly internal, yeah. Parts of the representation space where you can sort of see where that lives. Yeah. Um, and you want to kind of, you know, extract that piece out.Shawn Wang [00:09:40]: Well, I always say, you know, whenever you find a vector, a fun exercise is just like, make it very negative to see what the opposite of CCP is.Mark Bissell [00:09:47]: The super America, bald eagles flying everywhere. But yeah. So in general, like lots of post-training tasks where you'd want to be able to, to do that. Whether it's unlearning a certain behavior or, you know, some of the other kind of cases where this comes up is, are you familiar with like the, the grokking behavior? I mean, I know the machine learning term of grokking.Shawn Wang [00:10:09]: Yeah.Mark Bissell [00:10:09]: Sort of this like double descent idea of, of having a model that is able to learn a generalizing, a generalizing solution, as opposed to even if memorization of some task would suffice, you want it to learn the more general way of doing a thing. And so, you know, another. A way that you can think about having surgical access to a model's internals would be learn from this data, but learn in the right way. If there are many possible, you know, ways to, to do that. Can make interp solve the double descent problem?Shawn Wang [00:10:41]: Depends, I guess, on how you. Okay. So I, I, I viewed that double descent as a problem because then you're like, well, if the loss curves level out, then you're done, but maybe you're not done. Right. Right. But like, if you actually can interpret what is a generalizing or what you're doing. What is, what is still changing, even though the loss is not changing, then maybe you, you can actually not view it as a double descent problem. And actually you're just sort of translating the space in which you view loss and like, and then you have a smooth curve. Yeah.Mark Bissell [00:11:11]: I think that's certainly like the domain of, of problems that we're, that we're looking to get.Shawn Wang [00:11:15]: Yeah. To me, like double descent is like the biggest thing to like ML research where like, if you believe in scaling, then you don't need, you need to know where to scale. And. But if you believe in double descent, then you don't, you don't believe in anything where like anything levels off, like.Vibhu Sapra [00:11:30]: I mean, also tendentially there's like, okay, when you talk about the China vector, right. There's the subliminal learning work. It was from the anthropic fellows program where basically you can have hidden biases in a model. And as you distill down or, you know, as you train on distilled data, those biases always show up, even if like you explicitly try to not train on them. So, you know, it's just like another use case of. Okay. If we can interpret what's happening in post-training, you know, can we clear some of this? Can we even determine what's there? Because yeah, it's just like some worrying research that's out there that shows, you know, we really don't know what's going on.Mark Bissell [00:12:06]: That is. Yeah. I think that's the biggest sentiment that we're sort of hoping to tackle. Nobody knows what's going on. Right. Like subliminal learning is just an insane concept when you think about it. Right. Train a model on not even the logits, literally the output text of a bunch of random numbers. And now your model loves owls. And you see behaviors like that, that are just, they defy, they defy intuition. And, and there are mathematical explanations that you can get into, but. I mean.Shawn Wang [00:12:34]: It feels so early days. Objectively, there are a sequence of numbers that are more owl-like than others. There, there should be.Mark Bissell [00:12:40]: According to, according to certain models. Right. It's interesting. I think it only applies to models that were initialized from the same starting Z. Usually, yes.Shawn Wang [00:12:49]: But I mean, I think that's a, that's a cheat code because there's not enough compute. But like if you believe in like platonic representation, like probably it will transfer across different models as well. Oh, you think so?Mark Bissell [00:13:00]: I think of it more as a statistical artifact of models initialized from the same seed sort of. There's something that is like path dependent from that seed that might cause certain overlaps in the latent space and then sort of doing this distillation. Yeah. Like it pushes it towards having certain other tendencies.Vibhu Sapra [00:13:24]: Got it. I think there's like a bunch of these open-ended questions, right? Like you can't train in new stuff during the RL phase, right? RL only reorganizes weights and you can only do stuff that's somewhat there in your base model. You're not learning new stuff. You're just reordering chains and stuff. But okay. My broader question is when you guys work at an interp lab, how do you decide what to work on and what's kind of the thought process? Right. Because we can ramble for hours. Okay. I want to know this. I want to know that. But like, how do you concretely like, you know, what's the workflow? Okay. There's like approaches towards solving a problem, right? I can try prompting. I can look at chain of thought. I can train probes, SAEs. But how do you determine, you know, like, okay, is this going anywhere? Like, do we have set stuff? Just, you know, if you can help me with all that. Yeah.Myra Deng [00:14:07]: It's a really good question. I feel like we've always at the very beginning of the company thought about like, let's go and try to learn what isn't working in machine learning today. Whether that's talking to customers or talking to researchers at other labs, trying to understand both where the frontier is going and where things are really not falling apart today. And then developing a perspective on how we can push the frontier using interpretability methods. And so, you know, even our chief scientist, Tom, spends a lot of time talking to customers and trying to understand what real world problems are and then taking that back and trying to apply the current state of the art to those problems and then seeing where they fall down basically. And then using those failures or those shortcomings to understand what hills to climb when it comes to interpretability research. So like on the fundamental side, for instance, when we have done some work applying SAEs and probes, we've encountered, you know, some shortcomings in SAEs that we found a little bit surprising. And so have gone back to the drawing board and done work on that. And then, you know, we've done some work on better foundational interpreter models. And a lot of our team's research is focused on what is the next evolution beyond SAEs, for instance. And then when it comes to like control and design of models, you know, we tried steering with our first API and realized that it still fell short of black box techniques like prompting or fine tuning. And so went back to the drawing board and we're like, how do we make that not the case and how do we improve it beyond that? And one of our researchers, Ekdeep, who just joined is actually Ekdeep and Atticus are like steering experts and have spent a lot of time trying to figure out like, what is the research that enables us to actually do this in a much more powerful, robust way? So yeah, the answer is like, look at real world problems, try to translate that into a research agenda and then like hill climb on both of those at the same time.Shawn Wang [00:16:04]: Yeah. Mark has the steering CLI demo queued up, which we're going to go into in a sec. But I always want to double click on when you drop hints, like we found some problems with SAEs. Okay. What are they? You know, and then we can go into the demo. Yeah.Myra Deng [00:16:19]: I mean, I'm curious if you have more thoughts here as well, because you've done it in the healthcare domain. But I think like, for instance, when we do things like trying to detect behaviors within models that are harmful or like behaviors that a user might not want to have in their model. So hallucinations, for instance, harmful intent, PII, all of these things. We first tried using SAE probes for a lot of these tasks. So taking the feature activation space from SAEs and then training classifiers on top of that, and then seeing how well we can detect the properties that we might want to detect in model behavior. And we've seen in many cases that probes just trained on raw activations seem to perform better than SAE probes, which is a bit surprising if you think that SAEs are actually also capturing the concepts that you would want to capture cleanly and more surgically. And so that is an interesting observation. I don't think that is like, I'm not down on SAEs at all. I think there are many, many things they're useful for, but we have definitely run into cases where I think the concept space described by SAEs is not as clean and accurate as we would expect it to be for actual like real world downstream performance metrics.Mark Bissell [00:17:34]: Fair enough. Yeah. It's the blessing and the curse of unsupervised methods where you get to peek into the AI's mind. But sometimes you wish that you saw other things when you walked inside there. Although in the PII instance, I think weren't an SAE based approach actually did prove to be the most generalizable?Myra Deng [00:17:53]: It did work well in the case that we published with Rakuten. And I think a lot of the reasons it worked well was because we had a noisier data set. And so actually the blessing of unsupervised learning is that we actually got to get more meaningful, generalizable signal from SAEs when the data was noisy. But in other cases where we've had like good data sets, it hasn't been the case.Shawn Wang [00:18:14]: And just because you named Rakuten and I don't know if we'll get it another chance, like what is the overall, like what is Rakuten's usage or production usage? Yeah.Myra Deng [00:18:25]: So they are using us to essentially guardrail and inference time monitor their language model usage and their agent usage to detect things like PII so that they don't route private user information.Myra Deng [00:18:41]: And so that's, you know, going through all of their user queries every day. And that's something that we deployed with them a few months ago. And now we are actually exploring very early partnerships, not just with Rakuten, but with other people around how we can help with potentially training and customization use cases as well. Yeah.Shawn Wang [00:19:03]: And for those who don't know, like it's Rakuten is like, I think number one or number two e-commerce store in Japan. Yes. Yeah.Mark Bissell [00:19:10]: And I think that use case actually highlights a lot of like what it looks like to deploy things in practice that you don't always think about when you're doing sort of research tasks. So when you think about some of the stuff that came up there that's more complex than your idealized version of a problem, they were encountering things like synthetic to real transfer of methods. So they couldn't train probes, classifiers, things like that on actual customer data of PII. So what they had to do is use synthetic data sets. And then hope that that transfer is out of domain to real data sets. And so we can evaluate performance on the real data sets, but not train on customer PII. So that right off the bat is like a big challenge. You have multilingual requirements. So this needed to work for both English and Japanese text. Japanese text has all sorts of quirks, including tokenization behaviors that caused lots of bugs that caused us to be pulling our hair out. And then also a lot of tasks you'll see. You might make simplifying assumptions if you're sort of treating it as like the easiest version of the problem to just sort of get like general results where maybe you say you're classifying a sentence to say, does this contain PII? But the need that Rakuten had was token level classification so that you could precisely scrub out the PII. So as we learned more about the problem, you're sort of speaking about what that looks like in practice. Yeah. A lot of assumptions end up breaking. And that was just one instance where you. A problem that seems simple right off the bat ends up being more complex as you keep diving into it.Vibhu Sapra [00:20:41]: Excellent. One of the things that's also interesting with Interp is a lot of these methods are very efficient, right? So where you're just looking at a model's internals itself compared to a separate like guardrail, LLM as a judge, a separate model. One, you have to host it. Two, there's like a whole latency. So if you use like a big model, you have a second call. Some of the work around like self detection of hallucination, it's also deployed for efficiency, right? So if you have someone like Rakuten doing it in production live, you know, that's just another thing people should consider.Mark Bissell [00:21:12]: Yeah. And something like a probe is super lightweight. Yeah. It's no extra latency really. Excellent.Shawn Wang [00:21:17]: You have the steering demos lined up. So we were just kind of see what you got. I don't, I don't actually know if this is like the latest, latest or like alpha thing.Mark Bissell [00:21:26]: No, this is a pretty hacky demo from from a presentation that someone else on the team recently gave. So this will give a sense for, for technology. So you can see the steering and action. Honestly, I think the biggest thing that this highlights is that as we've been growing as a company and taking on kind of more and more ambitious versions of interpretability related problems, a lot of that comes to scaling up in various different forms. And so here you're going to see steering on a 1 trillion parameter model. This is Kimi K2. And so it's sort of fun that in addition to the research challenges, there are engineering challenges that we're now tackling. Cause for any of this to be sort of useful in production, you need to be thinking about what it looks like when you're using these methods on frontier models as opposed to sort of like toy kind of model organisms. So yeah, this was thrown together hastily, pretty fragile behind the scenes, but I think it's quite a fun demo. So screen sharing is on. So I've got two terminal sessions pulled up here. On the left is a forked version that we have of the Kimi CLI that we've got running to point at our custom hosted Kimi model. And then on the right is a set up that will allow us to steer on certain concepts. So I should be able to chat with Kimi over here. Tell it hello. This is running locally. So the CLI is running locally, but the Kimi server is running back to the office. Well, hopefully should be, um, that's too much to run on that Mac. Yeah. I think it's, uh, it takes a full, like each 100 node. I think it's like, you can. You can run it on eight GPUs, eight 100. So, so yeah, Kimi's running. We can ask it a prompt. It's got a forked version of our, uh, of the SG line code base that we've been working on. So I'm going to tell it, Hey, this SG line code base is slow. I think there's a bug. Can you try to figure it out? There's a big code base, so it'll, it'll spend some time doing this. And then on the right here, I'm going to initialize in real time. Some steering. Let's see here.Mark Bissell [00:23:33]: searching for any. Bugs. Feature ID 43205.Shawn Wang [00:23:38]: Yeah.Mark Bissell [00:23:38]: 20, 30, 40. So let me, uh, this is basically a feature that we found that inside Kimi seems to cause it to speak in Gen Z slang. And so on the left, it's still sort of thinking normally it might take, I don't know, 15 seconds for this to kick in, but then we're going to start hopefully seeing him do this code base is massive for real. So we're going to start. We're going to start seeing Kimi transition as the steering kicks in from normal Kimi to Gen Z Kimi and both in its chain of thought and its actual outputs.Mark Bissell [00:24:19]: And interestingly, you can see, you know, it's still able to call tools, uh, and stuff. It's um, it's purely sort of it's it's demeanor. And there are other features that we found for interesting things like concision. So that's more of a practical one. You can make it more concise. Um, the types of programs, uh, programming languages that uses, but yeah, as we're seeing it come in. Pretty good. Outputs.Shawn Wang [00:24:43]: Scheduler code is actually wild.Vibhu Sapra [00:24:46]: Yo, this code is actually insane, bro.Vibhu Sapra [00:24:53]: What's the process of training in SAE on this, or, you know, how do you label features? I know you guys put out a pretty cool blog post about, um, finding this like autonomous interp. Um, something. Something about how agents for interp is different than like coding agents. I don't know while this is spewing up, but how, how do we find feature 43, two Oh five. Yeah.Mark Bissell [00:25:15]: So in this case, um, we, our platform that we've been building out for a long time now supports all the sort of classic out of the box interp techniques that you might want to have like SAE training, probing things of that kind, I'd say the techniques for like vanilla SAEs are pretty well established now where. You take your model that you're interpreting, run a whole bunch of data through it, gather activations, and then yeah, pretty straightforward pipeline to train an SAE. There are a lot of different varieties. There's top KSAEs, batch top KSAEs, um, normal ReLU SAEs. And then once you have your sparse features to your point, assigning labels to them to actually understand that this is a gen Z feature, that's actually where a lot of the kind of magic happens. Yeah. And the most basic standard technique is look at all of your d input data set examples that cause this feature to fire most highly. And then you can usually pick out a pattern. So for this feature, If I've run a diverse enough data set through my model feature 43, two Oh five. Probably tends to fire on all the tokens that sounds like gen Z slang. You know, that's the, that's the time of year to be like, Oh, I'm in this, I'm in this Um, and, um, so, you know, you could have a human go through all 43,000 concepts andVibhu Sapra [00:26:34]: And I've got to ask the basic question, you know, can we get examples where it hallucinates, pass it through, see what feature activates for hallucinations? Can I just, you know, turn hallucination down?Myra Deng [00:26:51]: Oh, wow. You really predicted a project we're already working on right now, which is detecting hallucinations using interpretability techniques. And this is interesting because hallucinations is something that's very hard to detect. And it's like a kind of a hairy problem and something that black box methods really struggle with. Whereas like Gen Z, you could always train a simple classifier to detect that hallucinations is harder. But we've seen that models internally have some... Awareness of like uncertainty or some sort of like user pleasing behavior that leads to hallucinatory behavior. And so, yeah, we have a project that's trying to detect that accurately. And then also working on mitigating the hallucinatory behavior in the model itself as well.Shawn Wang [00:27:39]: Yeah, I would say most people are still at the level of like, oh, I would just turn temperature to zero and that turns off hallucination. And I'm like, well, that's a fundamental misunderstanding of how this works. Yeah.Mark Bissell [00:27:51]: Although, so part of what I like about that question is you, there are SAE based approaches that might like help you get at that. But oftentimes the beauty of SAEs and like we said, the curse is that they're unsupervised. So when you have a behavior that you deliberately would like to remove, and that's more of like a supervised task, often it is better to use something like probes and specifically target the thing that you're interested in reducing as opposed to sort of like hoping that when you fragment the latent space, one of the vectors that pops out.Vibhu Sapra [00:28:20]: And as much as we're training an autoencoder to be sparse, we're not like for sure certain that, you know, we will get something that just correlates to hallucination. You'll probably split that up into 20 other things and who knows what they'll be.Mark Bissell [00:28:36]: Of course. Right. Yeah. So there's no sort of problems with like feature splitting and feature absorption. And then there's the off target effects, right? Ideally, you would want to be very precise where if you reduce the hallucination feature, suddenly maybe your model can't write. Creatively anymore. And maybe you don't like that, but you want to still stop it from hallucinating facts and figures.Shawn Wang [00:28:55]: Good. So Vibhu has a paper to recommend there that we'll put in the show notes. But yeah, I mean, I guess just because your demo is done, any any other things that you want to highlight or any other interesting features you want to show?Mark Bissell [00:29:07]: I don't think so. Yeah. Like I said, this is a pretty small snippet. I think the main sort of point here that I think is exciting is that there's not a whole lot of inter being applied to models quite at this scale. You know, Anthropic certainly has some some. Research and yeah, other other teams as well. But it's it's nice to see these techniques, you know, being put into practice. I think not that long ago, the idea of real time steering of a trillion parameter model would have sounded.Shawn Wang [00:29:33]: Yeah. The fact that it's real time, like you started the thing and then you edited the steering vector.Vibhu Sapra [00:29:38]: I think it's it's an interesting one TBD of what the actual like production use case would be on that, like the real time editing. It's like that's the fun part of the demo, right? You can kind of see how this could be served behind an API, right? Like, yes, you're you only have so many knobs and you can just tweak it a bit more. And I don't know how it plays in. Like people haven't done that much with like, how does this work with or without prompting? Right. How does this work with fine tuning? Like, there's a whole hype of continual learning, right? So there's just so much to see. Like, is this another parameter? Like, is it like parameter? We just kind of leave it as a default. We don't use it. So I don't know. Maybe someone here wants to put out a guide on like how to use this with prompting when to do what?Mark Bissell [00:30:18]: Oh, well, I have a paper recommendation. I think you would love from Act Deep on our team, who is an amazing researcher, just can't say enough amazing things about Act Deep. But he actually has a paper that as well as some others from the team and elsewhere that go into the essentially equivalence of activation steering and in context learning and how those are from a he thinks of everything in a cognitive neuroscience Bayesian framework, but basically how you can precisely show how. Prompting in context, learning and steering exhibit similar behaviors and even like get quantitative about the like magnitude of steering you would need to do to induce a certain amount of behavior similar to certain prompting, even for things like jailbreaks and stuff. It's a really cool paper. Are you saying steering is less powerful than prompting? More like you can almost write a formula that tells you how to convert between the two of them.Myra Deng [00:31:20]: And so like formally equivalent actually in the in the limit. Right.Mark Bissell [00:31:24]: So like one case study of this is for jailbreaks there. I don't know. Have you seen the stuff where you can do like many shot jailbreaking? You like flood the context with examples of the behavior. And the topic put out that paper.Shawn Wang [00:31:38]: A lot of people were like, yeah, we've been doing this, guys.Mark Bissell [00:31:40]: Like, yeah, what's in this in context learning and activation steering equivalence paper is you can like predict the number. Number of examples that you will need to put in there in order to jailbreak the model. That's cool. By doing steering experiments and using this sort of like equivalence mapping. That's cool. That's really cool. It's very neat. Yeah.Shawn Wang [00:32:02]: I was going to say, like, you know, I can like back rationalize that this makes sense because, you know, what context is, is basically just, you know, it updates the KV cache kind of and like and then every next token inference is still like, you know, the sheer sum of everything all the way. It's plus all the context. It's up to date. And you could, I guess, theoretically steer that with you probably replace that with your steering. The only problem is steering typically is on one layer, maybe three layers like like you did. So it's like not exactly equivalent.Mark Bissell [00:32:33]: Right, right. There's sort of you need to get precise about, yeah, like how you sort of define steering and like what how you're modeling the setup. But yeah, I've got the paper pulled up here. Belief dynamics reveal the dual nature. Yeah. The title is Belief Dynamics Reveal the Dual Nature of Incompetence. And it's an exhibition of the practical context learning and activation steering. So Eric Bigelow, Dan Urgraft on the who are doing fellowships at Goodfire, Ekt Deep's the final author there.Myra Deng [00:32:59]: I think actually to your question of like, what is the production use case of steering? I think maybe if you just think like one level beyond steering as it is today. Like imagine if you could adapt your model to be, you know, an expert legal reasoner. Like in almost real time, like very quickly. efficiently using human feedback or using like your semantic understanding of what the model knows and where it knows that behavior. I think that while it's not clear what the product is at the end of the day, it's clearly very valuable. Thinking about like what's the next interface for model customization and adaptation is a really interesting problem for us. Like we have heard a lot of people actually interested in fine-tuning an RL for open weight models in production. And so people are using things like Tinker or kind of like open source libraries to do that, but it's still very difficult to get models fine-tuned and RL'd for exactly what you want them to do unless you're an expert at model training. And so that's like something we'reShawn Wang [00:34:06]: looking into. Yeah. I never thought so. Tinker from Thinking Machines famously uses rank one LoRa. Is that basically the same as steering? Like, you know, what's the comparison there?Mark Bissell [00:34:19]: Well, so in that case, you are still applying updates to the parameters, right?Shawn Wang [00:34:25]: Yeah. You're not touching a base model. You're touching an adapter. It's kind of, yeah.Mark Bissell [00:34:30]: Right. But I guess it still is like more in parameter space then. I guess it's maybe like, are you modifying the pipes or are you modifying the water flowing through the pipes to get what you're after? Yeah. Just maybe one way.Mark Bissell [00:34:44]: I like that analogy. That's my mental map of it at least, but it gets at this idea of model design and intentional design, which is something that we're, that we're very focused on. And just the fact that like, I hope that we look back at how we're currently training models and post-training models and just think what a primitive way of doing that right now. Like there's no intentionalityShawn Wang [00:35:06]: really in... It's just data, right? The only thing in control is what data we feed in.Mark Bissell [00:35:11]: So, so Dan from Goodfire likes to use this analogy of, you know, he has a couple of young kids and he talks about like, what if I could only teach my kids how to be good people by giving them cookies or like, you know, giving them a slap on the wrist if they do something wrong, like not telling them why it was wrong or like what they should have done differently or something like that. Just figure it out. Right. Exactly. So that's RL. Yeah. Right. And, and, you know, it's sample inefficient. There's, you know, what do they say? It's like slurping feedback. It's like, slurping supervision. Right. And so you'd like to get to the point where you can have experts giving feedback to their models that are, uh, internalized and, and, you know, steering is an inference time way of sort of getting that idea. But ideally you're moving to a world whereVibhu Sapra [00:36:04]: it is much more intentional design in perpetuity for these models. Okay. This is one of the questions we asked Emmanuel from Anthropic on the podcast a few months ago. Basically the question, was you're at a research lab that does model training, foundation models, and you're on an interp team. How does it tie back? Right? Like, does this, do ideas come from the pre-training team? Do they go back? Um, you know, so for those interested, you can, you can watch that. There wasn't too much of a connect there, but it's still something, you know, it's something they want toMark Bissell [00:36:33]: push for down the line. It can be useful for all of the above. Like there are certainly post-hocVibhu Sapra [00:36:39]: use cases where it doesn't need to touch that. I think the other thing a lot of people forget is this stuff isn't too computationally expensive, right? Like I would say, if you're interested in getting into research, MechInterp is one of the most approachable fields, right? A lot of this train an essay, train a probe, this stuff, like the budget for this one, there's already a lot done. There's a lot of open source work. You guys have done some too. Um, you know,Shawn Wang [00:37:04]: There's like notebooks from the Gemini team for Neil Nanda or like, this is how you do it. Just step through the notebook.Vibhu Sapra [00:37:09]: Even if you're like, not even technical with any of this, you can still make like progress. There, you can look at different activations, but, uh, if you do want to get into training, you know, training this stuff, correct me if I'm wrong is like in the thousands of dollars, not even like, it's not that high scale. And then same with like, you know, applying it, doing it for post-training or all this stuff is fairly cheap in scale of, okay. I want to get into like model training. I don't have compute for like, you know, pre-training stuff. So it's, it's a very nice field to get into. And also there's a lot of like open questions, right? Um, some of them have to go with, okay, I want a product. I want to solve this. Like there's also just a lot of open-ended stuff that people could work on. That's interesting. Right. I don't know if you guys have any calls for like, what's open questions, what's open work that you either open collaboration with, or like, you'd just like to see solved or just, you know, for people listening that want to get into McInturk because people always talk about it. What are, what are the things they should check out? Start, of course, you know, join you guys as well. I'm sure you're hiring.Myra Deng [00:38:09]: There's a paper, I think from, was it Lee, uh, Sharky? It's open problems and, uh, it's, it's a bit of interpretability, which I recommend everyone who's interested in the field. Read. I'm just like a really comprehensive overview of what are the things that experts in the field think are the most important problems to be solved. I also think to your point, it's been really, really inspiring to see, I think a lot of young people getting interested in interpretability, actually not just young people also like scientists to have been, you know, experts in physics for many years and in biology or things like this, um, transitioning into interp, because the barrier of, of what's now interp. So it's really cool to see a number to entry is, you know, in some ways low and there's a lot of information out there and ways to get started. There's this anecdote of like professors at universities saying that all of a sudden every incoming PhD student wants to study interpretability, which was not the case a few years ago. So it just goes to show how, I guess, like exciting the field is, how fast it's moving, how quick it is to get started and things like that.Mark Bissell [00:39:10]: And also just a very welcoming community. You know, there's an open source McInturk Slack channel. There are people are always posting questions and just folks in the space are always responsive if you ask things on various forums and stuff. But yeah, the open paper, open problems paper is a really good one.Myra Deng [00:39:28]: For other people who want to get started, I think, you know, MATS is a great program. What's the acronym for? Machine Learning and Alignment Theory Scholars? It's like the...Vibhu Sapra [00:39:40]: Normally summer internship style.Myra Deng [00:39:42]: Yeah, but they've been doing it year round now. And actually a lot of our full-time staff have come through that program or gone through that program. And it's great for anyone who is transitioning into interpretability. There's a couple other fellows programs. We do one as well as Anthropic. And so those are great places to get started if anyone is interested.Mark Bissell [00:40:03]: Also, I think been seen as a research field for a very long time. But I think engineering... I think engineers are sorely wanted for interpretability as well, especially at Goodfire, but elsewhere, as it does scale up.Shawn Wang [00:40:18]: I should mention that Lee actually works with you guys, right? And in the London office and I'm adding our first ever McInturk track at AI Europe because I see this industry applications now emerging. And I'm pretty excited to, you know, help push that along. Yeah, I was looking forward to that. It'll effectively be the first industry McInturk conference. Yeah. I'm so glad you added that. You know, it's still a little bit of a bet. It's not that widespread, but I can definitely see this is the time to really get into it. We want to be early on things.Mark Bissell [00:40:51]: For sure. And I think the field understands this, right? So at ICML, I think the title of the McInturk workshop this year was actionable interpretability. And there was a lot of discussion around bringing it to various domains. Everyone's adding pragmatic, actionable, whatever.Shawn Wang [00:41:10]: It's like, okay, well, we weren't actionable before, I guess. I don't know.Vibhu Sapra [00:41:13]: And I mean, like, just, you know, being in Europe, you see the Interp room. One, like old school conferences, like, I think they had a very tiny room till they got lucky and they got it doubled. But there's definitely a lot of interest, a lot of niche research. So you see a lot of research coming out of universities, students. We covered the paper last week. It's like two unknown authors, not many citations. But, you know, you can make a lot of meaningful work there. Yeah. Yeah. Yeah.Shawn Wang [00:41:39]: Yeah. I think people haven't really mentioned this yet. It's just Interp for code. I think it's like an abnormally important field. We haven't mentioned this yet. The conspiracy theory last two years ago was when the first SAE work came out of Anthropic was they would do like, oh, we just used SAEs to turn the bad code vector down and then turn up the good code. And I think like, isn't that the dream? Like, you know, like, but basically, I guess maybe, why is it funny? Like, it's... If it was realistic, it would not be funny. It would be like, no, actually, we should do this. But it's funny because we know there's like, we feel there's some limitations to what steering can do. And I think a lot of the public image of steering is like the Gen Z stuff. Like, oh, you can make it really love the Golden Gate Bridge, or you can make it speak like Gen Z. To like be a legal reasoner seems like a huge stretch. Yeah. And I don't know if that will get there this way. Yeah.Myra Deng [00:42:36]: I think, um, I will say we are announcing. Something very soon that I will not speak too much about. Um, but I think, yeah, this is like what we've run into again and again is like, we, we don't want to be in the world where steering is only useful for like stylistic things. That's definitely not, not what we're aiming for. But I think the types of interventions that you need to do to get to things like legal reasoning, um, are much more sophisticated and require breakthroughs in, in learning algorithms. And that's, um...Shawn Wang [00:43:07]: And is this an emergent property of scale as well?Myra Deng [00:43:10]: I think so. Yeah. I mean, I think scale definitely helps. I think scale allows you to learn a lot of information and, and reduce noise across, you know, large amounts of data. But I also think we think that there's ways to do things much more effectively, um, even, even at scale. So like actually learning exactly what you want from the data and not learning things that you do that you don't want exhibited in the data. So we're not like anti-scale, but we are also realizing that scale is not going to get us anywhere. It's not going to get us to the type of AI development that we want to be at in, in the future as these models get more powerful and get deployed in all these sorts of like mission critical contexts. Current life cycle of training and deploying and evaluations is, is to us like deeply broken and has opportunities to, to improve. So, um, more to come on that very, very soon.Mark Bissell [00:44:02]: And I think that that's a use basically, or maybe just like a proof point that these concepts do exist. Like if you can manipulate them in the precise best way, you can get the ideal combination of them that you desire. And steering is maybe the most coarse grained sort of peek at what that looks like. But I think it's evocative of what you could do if you had total surgical control over every concept, every parameter. Yeah, exactly.Myra Deng [00:44:30]: There were like bad code features. I've got it pulled up.Vibhu Sapra [00:44:33]: Yeah. Just coincidentally, as you guys are talking.Shawn Wang [00:44:35]: This is like, this is exactly.Vibhu Sapra [00:44:38]: There's like specifically a code error feature that activates and they show, you know, it's not, it's not typo detection. It's like, it's, it's typos in code. It's not typical typos. And, you know, you can, you can see it clearly activates where there's something wrong in code. And they have like malicious code, code error. They have a whole bunch of sub, you know, sub broken down little grain features. Yeah.Shawn Wang [00:45:02]: Yeah. So, so the, the rough intuition for me, the, why I talked about post-training was that, well, you just, you know, have a few different rollouts with all these things turned off and on and whatever. And then, you know, you can, that's, that's synthetic data you can kind of post-train on. Yeah.Vibhu Sapra [00:45:13]: And I think we make it sound easier than it is just saying, you know, they do the real hard work.Myra Deng [00:45:19]: I mean, you guys, you guys have the right idea. Exactly. Yeah. We replicated a lot of these features in, in our Lama models as well. I remember there was like.Vibhu Sapra [00:45:26]: And I think a lot of this stuff is open, right? Like, yeah, you guys opened yours. DeepMind has opened a lot of essays on Gemma. Even Anthropic has opened a lot of this. There's, there's a lot of resources that, you know, we can probably share of people that want to get involved.Shawn Wang [00:45:41]: Yeah. And special shout out to like Neuronpedia as well. Yes. Like, yeah, amazing piece of work to visualize those things.Myra Deng [00:45:49]: Yeah, exactly.Shawn Wang [00:45:50]: I guess I wanted to pivot a little bit on, onto the healthcare side, because I think that's a big use case for you guys. We haven't really talked about it yet. This is a bit of a crossover for me because we are, we are, we do have a separate science pod that we're starting up for AI, for AI for science, just because like, it's such a huge investment category and also I'm like less qualified to do it, but we actually have bio PhDs to cover that, which is great, but I need to just kind of recover, recap your work, maybe on the evil two stuff, but then, and then building forward.Mark Bissell [00:46:17]: Yeah, for sure. And maybe to frame up the conversation, I think another kind of interesting just lens on interpretability in general is a lot of the techniques that were described. are ways to solve the AI human interface problem. And it's sort of like bidirectional communication is the goal there. So what we've been talking about with intentional design of models and, you know, steering, but also more advanced techniques is having humans impart our desires and control into models and over models. And the reverse is also very interesting, especially as you get to superhuman models, whether that's narrow superintelligence, like these scientific models that work on genomics, data, medical imaging, things like that. But down the line, you know, superintelligence of other forms as well. What knowledge can the AIs teach us as sort of that, that the other direction in that? And so some of our life science work to date has been getting at exactly that question, which is, well, some of it does look like debugging these various life sciences models, understanding if they're actually performing well, on tasks, or if they're picking up on spurious correlations, for instance, genomics models, you would like to know whether they are sort of focusing on the biologically relevant things that you care about, or if it's using some simpler correlate, like the ancestry of the person that it's looking at. But then also in the instances where they are superhuman, and maybe they are understanding elements of the human genome that we don't have names for or specific, you know, yeah, discoveries that they've made that that we don't know about, that's, that's a big goal. And so we're already seeing that, right, we are partnered with organizations like Mayo Clinic, leading research health system in the United States, our Institute, as well as a startup called Prima Menta, which focuses on neurodegenerative disease. And in our partnership with them, we've used foundation models, they've been training and applied our interpretability techniques to find novel biomarkers for Alzheimer's disease. So I think this is just the tip of the iceberg. But it's, that's like a flavor of some of the things that we're working on.Shawn Wang [00:48:36]: Yeah, I think that's really fantastic. Obviously, we did the Chad Zuckerberg pod last year as well. And like, there's a plethora of these models coming out, because there's so much potential and research. And it's like, very interesting how it's basically the same as language models, but just with a different underlying data set. But it's like, it's the same exact techniques. Like, there's no change, basically.Mark Bissell [00:48:59]: Yeah. Well, and even in like other domains, right? Like, you know, robotics, I know, like a lot of the companies just use Gemma as like the like backbone, and then they like make it into a VLA that like takes these actions. It's, it's, it's transformers all the way down. So yeah.Vibhu Sapra [00:49:15]: Like we have Med Gemma now, right? Like this week, even there was Med Gemma 1.5. And they're training it on this stuff, like 3d scans, medical domain knowledge, and all that stuff, too. So there's a push from both sides. But I think the thing that, you know, one of the things about McInturpp is like, you're a little bit more cautious in some domains, right? So healthcare, mainly being one, like guardrails, understanding, you know, we're more risk adverse to something going wrong there. So even just from a basic understanding, like, if we're trusting these systems to make claims, we want to know why and what's going on.Myra Deng [00:49:51]: Yeah, I think there's totally a kind of like deployment bottleneck to actually using. foundation models for real patient usage or things like that. Like, say you're using a model for rare disease prediction, you probably want some explanation as to why your model predicted a certain outcome, and an interpretable explanation at that. So that's definitely a use case. But I also think like, being able to extract scientific information that no human knows to accelerate drug discovery and disease treatment and things like that actually is a really, really big unlock for science, like scientific discovery. And you've seen a lot of startups, like say that they're going to accelerate scientific discovery. And I feel like we actually are doing that through our interp techniques. And kind of like, almost by accident, like, I think we got reached out to very, very early on from these healthcare institutions. And none of us had healthcare.Shawn Wang [00:50:49]: How did they even hear of you? A podcast.Myra Deng [00:50:51]: Oh, okay. Yeah, podcast.Vibhu Sapra [00:50:53]: Okay, well, now's that time, you know.Myra Deng [00:50:55]: Everyone can call us.Shawn Wang [00:50:56]: Podcasts are the most important thing. Everyone should listen to podcasts.Myra Deng [00:50:59]: Yeah, they reached out. They were like, you know, we have these really smart models that we've trained, and we want to know what they're doing. And we were like, really early that time, like three months old, and it was a few of us. And we were like, oh, my God, we've never used these models. Let's figure it out. But it's also like, great proof that interp techniques scale pretty well across domains. We didn't really have to learn too much about.Shawn Wang [00:51:21]: Interp is a machine learning technique, machine learning skills everywhere, right? Yeah. And it's obviously, it's just like a general insight. Yeah. Probably to finance too, I think, which would be fun for our history. I don't know if you have anything to say there.Mark Bissell [00:51:34]: Yeah, well, just across the science. Like, we've also done work on material science. Yeah, it really runs the gamut.Vibhu Sapra [00:51:40]: Yeah. Awesome. And, you know, for those that should reach out, like, you're obviously experts in this, but like, is there a call out for people that you're looking to partner with, design partners, people to use your stuff outside of just, you know, the general developer that wants to. Plug and play steering stuff, like on the research side more so, like, are there ideal design partners, customers, stuff like that?Myra Deng [00:52:03]: Yeah, I can talk about maybe non-life sciences, and then I'm curious to hear from you on the life sciences side. But we're looking for design partners across many domains, language, anyone who's customizing language models or trying to push the frontier of code or reasoning models is really interesting to us. And then also interested in the frontier of modeling. There's a lot of models that work in, like, pixel space, as we call it. So if you're doing world models, video models, even robotics, where there's not a very clean natural language interface to interact with, I think we think that Interp can really help and are looking for a few partners in that space.Shawn Wang [00:52:43]: Just because you mentioned the keyword
On this episode of Mind the Gap, Tom Sherrington and Emma Turner are joined by Sam Crome, teacher, leader and author of The Power of Teams, to explore what it really takes to build teams that thrive in schools. Sam reflects on why so much leadership development is still overly individualistic, and shares the practical principles behind strong teams - belonging, alignment, purposeful operations, healthy dynamics, and deliberate development - alongside the habits that make meetings genuinely productive rather than performative. The conversation also draws on Sam's recent move from secondary leadership into an interim primary headship, teasing out what changes (and what doesn't) when a “team” becomes a small, agile staff group who can try, refine, and embed improvements at pace. Along the way they discuss cross-phase transition and why primary pupils' appetite for responsibility and leadership is often underused in Key Stage 3, the “tyranny of the first response” in group discussions, and how simple structures (like paired talk) can surface quieter expertise and build trust for honest, high-challenge conversations.Sam Crome is currently Interim Headteacher at a primary school in Surrey. He also serves as Director of Education, Mission and People for Xavier Catholic Education Trust, providing both strategic vision and planning, alongside day-to-day school support, so that all children and staff can flourish. Sam is convinced that teams are the way to improve our workload, productivity, professional learning, performance, and the joy we can experience at work. His interest in teams led him to write the book The Power of Teams. Find Sam at https://samcrome.com/Tom Sherrington has worked in schools as a teacher and leader for 30 years and is now a consultant specialising in teacher development and curriculum & assessment planning. He regularly contributes to conferences and CPD sessions locally and nationally and is busy working in schools and colleges across the UK and around the world. Follow Tom on X @teacherheadEmma Turner FCCT is a school improvement advisor, education consultant, trainer and author. She has almost three decades of primary teaching, headship and leadership experience across the sector, working and leading in both MATs and LAs. She works nationally and internationally on school improvement including at single school level and at scale. She has a particular interest in research informed practice in the primary phase, early career development, and CPD design. Follow Emma on X @emma_turner75This podcast is sponsored by Teaching WalkThrus and produced in association with Haringey Education Partnership. Find out more at https://walkthrus.co.uk/ and https://haringeyeducationpartnership.co.uk/
Denna gång bjuder Mats Ryd och Edward Blom på ren och skär folkbildning! Tillsammans med kocken och rom- och kaviarimportören Anders Isaksson på Quality Caviar Stockholm njuter de av kaviarkornen ur en stor, stor burk – men de försummar inte oss lyssnare, utan berättar vällustigt om sin upplevelse. Framför allt delar Anders Isaksson med sig av sina kunskaper om störarter och kaviar. Här får vi veta varför man inte längre äter rysk kaviar, hur gammal stören är när den blir könsmogen, hur man gör när man inte har pärlemorskedar att servera kaviarn med och hur man skiljer på olika typer av kaviar. Och vad ska man egentligen inta först – vodka eller kaviar?Tillbringa dina oxveckor tillsammans med Mats och Edward! Glöm inte att prenumerera, genom att bli "gourmand"- eller "gourmet"-prenumerant (eller varför inte "livsnjutare"?!). Prenumeration (från 39:-/månad) tecknas med fördel här: https://underproduktion.se/edwardblomssmorgasbord
In this episode of Off the Mats Podcast, I'm joined by Robyn Henderson for an honest, non-performative conversation about sobriety, identity, and rebuilding life off the mats. Robyn has been on the show before to talk about jiu-jitsu and competition. This time, the focus is deeper. We talk about life before sobriety, the moments that made change unavoidable, and what it actually feels like to sit with yourself once the crutch is gone. There's no rock-bottom mythology here, just a real discussion about fear, accountability, and learning how to show up consistently without numbing out. We also explore how jiu-jitsu fit into Robyn's recovery, not as a cure-all, but as a place that demanded humility, presence, and honesty. From early sobriety and emotional discomfort to redefining identity without alcohol, this episode centers sobriety as a lived, ongoing process rather than a finish line. This conversation is for anyone questioning their relationship with alcohol, navigating recovery, or trying to figure out who they are when the distractions fall away. No slogans. No inspiration bait. Just two people talking honestly about what it means to stay present and keep going.
tSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
The age falsification database is live—and it confirms what many suspected: this wasn't isolated, it was systemic. We break down what the data shows, why it matters, and how it reshapes gymnastics history. Plus, gymnasts speak out amid civil rights concerns, Oklahoma overtakes Florida for the #1 ranking, LSU breaks 198, and we unpack the most controversial judging moments of Week 4—including bars-gate and that Alabama vs Missouri finish. HEADLINES Thanks to Uncle Tim from Gymnastics-History, we now have an age falsification database Check out the most beautiful balance beam sequence from Delaney McMahon being done right now Gymnasts speaking out against I.C.E. and our suggestions for Minnesota's equality meet. NCAA What happened during week 4? Oklahoma overtakes Florida for the top spot in the country after a 198.425 this weekend, which ties for the highest January score in college gymnastics history LSU also broke the 198 barrier last week Florida had to count a fall on vault after Ly Bui's injury Who is the winner of this week's ''I Don't Want Anything To Do With That'' award? We now have two more 10 after this weekend, for a total of four so far this season Biggest controversies of week 4 Hitting your feet on the mat-gate: why we need a full analysis comparing the score given to Oklahoma's Lily Pederson and Utah's McKenna Smith We are giving you permission to be outraged about scoring at the Alabama vs Missouri meet because ??? We are hitting the one month mark for the 2026 NCAA gymnastics season - what are Jessica's biggest surprises? Alabama fully going for the jock intensity vibe by bench pressing gymnasts on the sides Do NOT count Stanford out. The Cardinals are ranked ninth and it's not even April. This is correct. The team ranked first on floor nationally isn't UCLA, it's not Oklahoma, it's GEORGIA! Riley McCusker is ranked second nationally on bars. Nature is healing. What are Spencer's biggest surprises? (Sad version...) Utah is ranked fourteenth and has two 195s in its first four meets... Kentucky is ranked 32nd and has two 194s in its first three meets. Yiiiiikes Q&A USAG Trident status; Training on a podium; Minnesota respect; Fan Fic for gymnastics; When judges are absent; Tap swings; OU floor choreography; Spray tans UP NEXT Fantasy Gymnastics podcast every Wednesday College & Cocktails : Friday Jan 30th after Arkansas at Florida (6pm Pacific-ish) 2026 Cocktail and Mocktail menu here Add exclusive Club Content like College & Cocktails to your favorite podcast player (instructions here). Thank you to our Sponsor Huel Limited Time Offer – Get Huel's full High-Protein Starter Kit with my exclusive offer of 20% OFF online with code [GYMCASTIC20] at http://huel.com/GYMCASTIC20. New Customers Only. Code only valid for the bundle. Thank you to Huel for partnering and supporting our show! CHAPTERS 00:00 – Intro: Priorities & Jan 27, 2026 00:31 – Headlines: Spencer Won Fantasy (Breaking News) 01:33 – The Age Falsification Database: It's Everyone 03:21 – Gymnasts Speak Out: ICE, Minneapolis & Civil Rights 05:25 – Minnesota's UCLA Social Equity Meet Ideas (Feb 7) 10:17 – NCAA News: Week 4 Results & Storylines 12:36 – Rankings Shake-Up: Oklahoma Overtakes Florida 15:56 – Updates: Support Independent Journalism + Show/Club Notes 18:46 – Two More 10s This Season (Chio Beam, Chiles Floor) 19:29 – Jordan Chiles: 10.0 + All-Around Dominance Talk 22:15 – Controversy: Bars Feet-on-the-Mat Gate (Pederson vs Smith) 29:26 – Alabama vs Missouri Ending: The Floor Score Debate 34:13 – PSA: Etiquette for Guests at Meets (Don't Sit on Mats) 39:16 – One Month In: NCAA Season Surprises (Happy & Sad) 59:12 – Gymternet News + Letters Begin (British Gymnastics Rebrand) 1:02:53 – Feedback: "How's the Trident?" + Why Not More Podium Time? 1:06:48 – Give Minnesota Some Props (and why they need it right now) 1:09:10 – Fan Fic Corner: Gay Gymnastics Romance Incoming 1:11:54 – What Happens if a Judge Misses a Meet? (Travel Chaos) 1:16:10 – Rosen's Bars Dismount: What's Going On Mechanically? 1:18:24 – Why Don't We Like Oklahoma's Floor? (Paper Dolls Theory) 1:22:08 – Everyone's So Orange (Spray Tan, NIL, and Citrus Crimes) 1:27:25 – Outro: C&C Preview + Live Show Season Pass + Thanks SUPPORT OUR WORK Club Gym Nerd: Join Here Fantasy: College Fantasy Game now open. Never too late to join! Merch: Shop Now Live Shows: Four for price of 3 Season Pass, Cecile Landi & Levi Live Show replay ticket Newsletters The Balance Beam Situation: Spencer's schedules, live blogs and GiF Code of Points Gymnastics History and Code of Points Archive from Uncle Tim Resistance Resources Join Our Fantasy League
My conversation with Karla begins at 25 minutes Subscribe and Watch Interviews LIVE : On YOUTUBE.com/StandUpWithPete ON SubstackStandUpWithPete Stand Up is a daily podcast. I book,host,edit, post and promote new episodes with brilliant guests every day. This show is Ad free and fully supported by listeners like you! Please subscribe now for as little as 5$ and gain access to a community of over 750 awesome, curious, kind, funny, brilliant, generous souls Karla Hernández-Mats is a widely respected voice for public education who brings a deep understanding of the education system, from inside the classroom to executive leadership. Before dedicating herself to education leadership, she spent over a decade as a classroom teacher, where she earned recognition as Teacher of the Year at Hialeah Middle School in 2010. Her teaching experience grounds her work and fuels her commitment to ensuring every student has the opportunity to succeed. Hernández-Mats has served on the Florida Education Association Governance Board and Executive Cabinet, the United Way Board of Miami, the Florida AFL-CIO's executive board, the Children's Trust executive board, and the Education Fund executive board. She also chairs the American Federation of Teachers' (AFT) Women's Rights Committee, where she championed policies that prioritize students' learning environments and well-being. From 2016 to 2025, Hernández-Mats served as President of United Teachers of Dade (UTD), the largest teachers' union in the southeastern United States. In 2022, she was selected as the Democratic nominee for Lieutenant Governor of Florida, reflecting her stature as a leader who could speak to the needs of students, families, and educators statewide. Hernández-Mats has been recognized nationally for her leadership, including being honored by Miami Today's Achiever Series in 2019 for advancing public education throughout Miami-Dade County. She has addressed national organizations such as the American Federation of Teachers, the National Education Association, the Labor Council for Latin American Advancement, the Miami Women's March, and the Congressional Black Caucus Foundation's Annual Legislative Conference. Born and raised in Miami, Hernández-Mats is a first-generation American of Honduran descent and the first Hispanic officer elected to lead UTD. She holds a bachelor's degree in emotionally handicapped education from Florida International University and a master's degree in business management from St. Thomas University. Her lifelong commitment to students, advocacy, and community service continues to inspire those working for a brighter future. Hernández-Mats is happily married and the mother of two children. On YOUTUBE.com/StandUpWithPete ON SubstackStandUpWithPete Listen rate and review on Apple Podcasts Listen rate and review on Spotify Pete On Instagram Pete on Blue Sky Pete on Threads Pete on Tik Tok Pete on Twitter Pete Personal FB page Stand Up with Pete FB page
In this episode of Off the Mats Podcast, I'm joined by Tom Smalley, MS, CMPC, CSCS, for a grounded conversation about mental performance, anxiety in athletes, and identity beyond competition. Tom's work sits at the intersection of strength culture and mental health, and we talk openly about what that actually looks like in practice, especially in environments like jiu-jitsu, wrestling, and strength sports where toughness is often valued over honesty. We discuss Tom's athletic background, his experience living with OCD, and how anxiety shows up for athletes who appear “put together” on the outside. From there, we unpack the difference between mental performance and mental health, the risks of pushing through everything, and how coaches can respond when athletes open up instead of shutting down. We also explore strength culture's complicated relationship with vulnerability, what healthy toughness really means, and how athletes can begin separating self-worth from performance. This episode is for grapplers, coaches, parents, and athletes navigating pressure, on the mats and off them, who want practical tools, clearer language, and a more sustainable approach to resilience.
On this episode of Mind the Gap, Tom Sherrington and Emma Turner welcome back Dr Carl Hendrick - writer, researcher and relentless “research distiller” - for a wide-ranging conversation about what the educational research can (and can't) tell us, and how ideas mutate as they travel through schools. Starting with Carl's monthly research round-ups and emerging areas like pre-questions (“pre-trieval”), they dig into a lively debate about the replication of the original scaffolding study and what that means for teachers: why learning science is probabilistic, why single studies shouldn't become dogma, and how “evidence-based” can be misapplied in crude tick-box ways. From there, Carl makes the case for thinking less about “teaching” as an all-purpose term and more about instructional design - the alignment of curriculum, instruction and assessment - and introduces Herbert Simon's idea of instructional invariants: the conditions that must hold for learning to happen (working memory limits, attention, cumulative knowledge and prerequisites). Along the way they tackle the “lethal mutations” of retrieval practice, the expertise required to design coherent curricula (and why most teachers shouldn't be expected to do it all), and the implications of AI for homework, assessment and the future of curriculum design.Carl Hendrick is an internationally recognised expert in the science of learning and instructional design. He is a professor at Academica University of Applied Sciences in Amsterdam and leads research projects that bridge cognitive science, educational psychology, and classroom practice. Carl's work focuses on helping teachers and school leaders apply robust, evidence-based strategies - such as retrieval practice, spacing, and explicit instruction - to improve student learning. He has co-authored several influential books, including How Learning Happens and Instructional Illusions, and regularly advises schools and organisations on implementing research-informed approaches.Tom Sherrington has worked in schools as a teacher and leader for 30 years and is now a consultant specialising in teacher development and curriculum & assessment planning. He regularly contributes to conferences and CPD sessions locally and nationally and is busy working in schools and colleges across the UK and around the world. Follow Tom on X @teacherheadEmma Turner FCCT is a school improvement advisor, education consultant, trainer and author. She has almost three decades of primary teaching, headship and leadership experience across the sector, working and leading in both MATs and LAs. She works nationally and internationally on school improvement including at single school level and at scale. She has a particular interest in research informed practice in the primary phase, early career development, and CPD design. Follow Emma on X @emma_turner75This podcast is sponsored by Teaching WalkThrus and produced in association with Haringey Education Partnership. Find out more at https://walkthrus.co.uk/ and https://haringeyeducationpartnership.co.uk/
In deze aflevering van FCA Daily bespreken Jean-Paul Rison, Alex Mazereeuw en Kenneth Lentze de Champions League-avond met de knappe winst van Ajax op bezoek bij Villarreal. Ook blikken we alvast vooruit op de belangrijke wedstrijd van PSV tegen Newcastle United. Verder bespreken we de vermakelijke bekerklassieker De Treffers – NEC, het debuut van Lee-Roy Echteld als trainer van AZ en daarnaast heel veel transfernieuws. (00:00) Intro(02:50) Ajax wint in Spanje (15:30) Overige Champions League potjes(17:55) NEC wint in Groesbeek(23:30) Trainerswissel AZ(26:00) Vooruitblik Newcastle – PSV(31:50) Transfernieuws GAE(37:20) Bijlow naar GenoaSee omnystudio.com/listener for privacy information.
Under denna glada och kanske en aning eskapistiska poddinspelning befinner sig gastronomerna Edward Blom och Mats Ryd i sitt alldeles rätta element, nämligen på en krog!Närmare bestämt på fisk- och skaldjursrestaurangen Rolfs hav mitt i Stockholm, där de slurpar och smaskar i sig den ena läckerheten efter den andra.Här får alla lyssnare tips på vad man kan göra med överblivna ostronskal, lära sig varför vissa mexikanska mescal-tillverkare bara levererar flaskor vart tolfte år och – såklart – veta hur Mats och Edward firat jul och nyår.Krögaren Johan Jureskog dyker upp för att dela med sig av historien om hur han låtit sig inspireras av det anrika skaldjurshaket Swan Oyster Depot i San Francisco. (Han kan också ha yttrat att "Dekadent är det bästa jag vet".) Ålsoppa, strömming, sherrysill, kammusslor och havskräftor och andra klassiska godsaker blir ett koncentrat av smaker från svenska skärgårdar, som får poddarna att gå upp rejält i njutningsspinn. Mats berättar dessutom hur han ägnat åtta år av sitt liv åt jakten på det perfekta bastubygget!Men framför allt delger de sina lyssnare vilka som är deras favoriter från det franska köket. Det blir en kavalkad av ljuvliga rätter att tänka på, drömma om och kanske rentav laga eller beställa på närmaste brasserie: allt från löksoppa till côte de boeuf och foie gras.Skicka gärna kommentarer och frågor till redaktionen: podden@edwardblom.seSupport- och prenumerationsfrågor till: support@underproduktion.se"Edward Bloms smörgåsbord" vill gärna ha dig som prenumerant, vilket innebär tillgång till alla avsnitt, inklusive det gedigna arkivet! Teckna en prenumeration på: https://underproduktion.se/edwardblomssmorgasbord (från 39:-/månad).
Alleine ist schwer - Der Sportpodcast mit Jonas und Mats Hummels
Aderlass bei AIS. Während JH17 die Anden Expansion Eures Lieblingspodcasts eruiert, starten wir heute mit einem Tandem ins Rennen. Da die Rente ja schon wieder beendet ist, berichtet Mats mal von seinem ersten Arbeitstag und verrät, wie man immer der jüngste bleiben kann… Stichwort Legends Cup. Mal was anderes. Was war eigentlich beim Afrika-Cup los? Und die Jungs sind natürlich der viel wichtigeren Frage auf der Spur: wo gibt's den nächsten Eklat dieser Art? Spoiler: Auf jeden Fall nicht im Littler Wonderland. Es werden auf jeden Fall die richtigen Fragen gestellt. Und diesmal sogar eine, die von euch kommt. Aber jetzt hört mal lieber selbst!
In this episode of the Off the Mats Podcast, I sit down with Ana Stevens of Underground 702 to talk through her Brazilian Jiu-Jitsu journey and the weight-loss transformation that unfolded alongside it. Ana shares what led her to step onto the mats for the first time, the fears and hesitations she carried early on, and how training gradually reshaped her relationship with her body, consistency, and self-belief. Our conversation explores the intersection between BJJ and sustainable weight loss, how jiu-jitsu provided structure, accountability, and community, and how physical changes influenced her confidence, movement, and performance on the mats. Ana speaks candidly about setbacks, plateaus, mental battles, and the moments that tested her commitment when progress slowed or motivation dipped. We also discuss the role of teammates, coaches, and support systems in long-term change, as well as what her training looks like today compared to when she started. The episode closes with practical advice for listeners who feel overwhelmed by starting BJJ, intimidated by weight loss, or unsure whether meaningful change is possible for them. This is a grounded conversation about patience, resilience, and growth—on the mats and beyond them.
Mats årslista Bergtajasångare Större turturduva Obeskrivna arter - intervju med Björn Anderson ...och lite annat. Omslagsfoto: Scarlet-banded Barbet. Foto Björn Anderson.
The Saint John's Bible is a work of sacred scripture and art, including more than 160 hand illuminations. A team of scribes used ancient natural inks, hand-ground pigments, and gold and silver leaf gild to create the original, which was completed in 2011. The Heritage Edition is a full-size, fine art reproduction – and we have one in the Allison Library at Regent College. In this conversation with Rev. Dr. John Ross and Colton Whelpton, we learn about the Bible's history and craftsmanship, where you can find copies, the ways communities engage with it, and how it is used in the life and rhythms of Regent College. We consider the artfulness of corrections, the power of reading in community, and the interweaving of art with Scripture in causing us to slow down and experience Scripture in a new way. Interviewee BiosThe Reverend Dr. John F. Ross is the Executive Director of The Saint John's Bible Heritage Program at Saint John's University in Collegeville, Minnesota. Prior to his work at Saint John's, John served for 18 years as the Senior Minister of Wayzata Community Church in Minnesota. John completed his Master of Divinity at the Methodist Theological School of Ohio, and a Doctor of Ministry through the Chicago Theological Seminary.Colton Whelpton has been a member of the Regent College community since 2017, graduating with an MATS in 2021 and serving as the Library Services Manager for the past 4 years. He oversees the day-to-day operations at the library, maintaining a large collection of resources and overseeing a team of student employees. Colton is currently pursuing an MLIS from the University of Alberta, and is particularly interested in topics relating to theology and technology, Indigenous spirituality, and new monasticism. LinksTurning the Pages: The Saint John's Bible Heritage Editions Around the WorldSaint John's Bible Youtube ChannelAllison Library: Book a ViewingRegent College Podcast Thanks for listening. Please like, rate and review us on your podcast platform of choice and share this episode with a friend. Follow Us on Social Media Facebook Instagram Youtube Keep in Touch Regent College Summer Programs Regent College Newsletter
With Mats Larsson, founder of the Global Energy Transformation Institute (GETI), we delve into the critical challenges and promising opportunities shaping the continent's path towards a sustainable future. Our conversation explores the strategic imperative for Europe to bolster its domestic battery and electric vehicle economy, examining the lessons learned from past initiatives and the potential pitfalls of over-reliance on external supply chains. We dissect the roles of governmental policies and targeted investments, drawing insightful comparisons with historical successes such as the US Apollo program, as we consider how best to foster innovation and growth in the European context. The discussion also navigates the complex interplay of various energy sources -- from the resurgence of nuclear power and the expansion of solar and wind, to the potential role of hydrogen, and even the controversial prospect of coal's return amidst escalating energy demands driven by advancements in artificial intelligence. A significant portion of our conversation is dedicated to the often-overlooked backbone of our energy system: the electricity grid. We explore the challenges posed by aging, centralized infrastructure and the urgent need for digitization to accommodate transformative technologies such as vehicle-to-grid solutions. Furthermore, we highlight the crucial gap in understanding between the automotive sector and energy suppliers, emphasizing the necessity for greater collaboration and foresight in planning for the massive power requirements of future electric vehicle fleets. Join us as we unpack these multifaceted issues, offering a comprehensive overview of the strategic decisions and technological advancements that will define Europe's energy and automotive trajectory in the years to come. Learn more about your ad choices. Visit megaphone.fm/adchoices
In this episode of Off the Mats Podcast, I sit down one-on-one with Christian Thomas, a member at Crazy 88 MMA, for a focused conversation on growth, leadership, and the responsibility that comes with coaching. This marks Christian's first solo return to the show since his appearance on Episode 201, and the discussion centers on what has changed since then, both on and off the mats. We talk about Christian's transition from competitor to coach, and how teaching, especially teaching kids, has reshaped his understanding of jiu-jitsu. The conversation explores the difference between competing for yourself and being responsible for the development, safety, and character of others. Christian shares what surprised him most about coaching, the standards he holds himself to, and what parents may not always see behind the scenes of a kids' program. The episode also examines how competition and coaching inform one another, how identity can shift as roles change, and why separating self-worth from performance is critical for long-term sustainability in jiu-jitsu. We close with reflections on leadership, gym culture at Crazy 88, advice for future coaches and parents, and what success looks like at this stage of Christian's journey. This episode is a conversation about responsibility, mentorship, and impact, what it really means to lead beyond the mats.
Start the year with a training reset that actually fits real life. We lay out a practical vision for 2026: less bashing between camps, more education, and a class model built for consistency. Instead of forcing rigid rules that fall apart on hard weeks, we show how to meet owners where they are, build trust, and add tools later when it makes sense. The throughline is sustainability—habits you'll keep because they're simple, fair, and aligned with how you live.We break down why variety matters and how a gym-style schedule keeps both dogs and humans engaged. Reactivity classes focus on early interruption and neutrality, obedience sessions sharpen markers and play, detection taps into real nosework, and guided pack hikes bring nature back into the routine. You'll hear how small, repeatable skills—shuffle back, pay, reset—turn panic into a plan, and why those reps create calm confidence faster than any quick fix.We also take on the myth that a flat, silent dog is a well-trained dog. Training shouldn't crush personality. By channeling drive, rewarding curiosity, and teaching clean off-switch behavior, you can keep your dog's spark while gaining real control. That balance is where owners rediscover joy: an off-leash hike in the morning, a cafe settle at lunch, crisp heel work at class, and a happy dog who still lights up for play.Under it all is community. Weekly sessions turn effort into a habit, reduce isolation for reactive dog owners, and lift everyone's standards. We're building a space in Upland, east of LA, where people feel seen and dogs get the outlets they deserve. If you want training that lasts beyond a boot camp and a dog who stays fully alive, this one's for you. Subscribe, share with a friend who needs hope, and leave a review with your top training goal for 2026.Visit us on the website here to see what we've got going on and how you can join our pack of good dogs and owners.
In this episode of the Off the Mats Podcast, I sit down with Dr. Jarrell Garcia, a 10th Planet Jiu-Jitsu black belt whose journey extends well beyond competition and rank. Jarrell shares his path into jiu-jitsu, what initially drew him to the 10th Planet system, and how his relationship with training evolved over the years. We talk honestly about moments of frustration, changing expectations, and what the belt actually represents once you earn it. The conversation also explores Jarrell's role as a coach and educator, and how his background in higher education influences the way he teaches on the mats. We discuss leadership, responsibility, and the realities of guiding students through different stages of their jiu-jitsu journey. Jarrell reflects on identity beyond the academy, balancing professional life with training, and what jiu-jitsu does and does not prepare you for outside the gym. This episode is a thoughtful look at growth, process, and perspective, aimed at practitioners at every level. Whether you're a white belt feeling overwhelmed or an upper belt reassessing your relationship with jiu-jitsu, this conversation focuses on longevity, learning, and showing up with intention, both on and off the mats.
Ryan Kidd, Co-Executive Director of MATS, shares an inside view of the AI safety field and the world's largest AI safety research talent pipeline. PSA for AI builders: Interested in alignment, governance, or AI safety? Learn more about the MATS Summer 2026 Fellowship and submit your name to be notified when applications open: https://matsprogram.org/s26-tcr. He discusses AGI timelines, the blurred line between safety and capabilities work, and why expert disagreement remains so high. In the second half, Ryan breaks down MATS' research archetypes, what top AI safety organizations are looking for, and how applicants can stand out with the right projects, skills, and career strategy. Sponsors: Tasklet: Tasklet is an AI agent that automates your work 24/7; just describe what you want in plain English and it gets the job done. Try it for free and use code COGREV for 50% off your first month at https://tasklet.ai Agents of Scale: Agents of Scale is a podcast from Zapier CEO Wade Foster, featuring conversations with C-suite leaders who are leading AI transformation. Subscribe to the show wherever you get your podcasts Shopify: Shopify powers millions of businesses worldwide, handling 10% of U.S. e-commerce. With hundreds of templates, AI tools for product descriptions, and seamless marketing campaign creation, it's like having a design studio and marketing team in one. Start your $1/month trial today at https://shopify.com/cognitive CHAPTERS: (00:00) About the Episode (03:50) MATS mission, AGI timelines (13:43) Evaluating current AI safety (Part 1) (13:48) Sponsor: Tasklet (14:59) Evaluating current AI safety (Part 2) (Part 1) (28:11) Sponsors: Agents of Scale | Shopify (30:58) Evaluating current AI safety (Part 2) (Part 2) (30:59) Safety research versus capabilities (40:01) Frontier labs, deployment, governance (51:51) MATS tracks and governance (01:04:11) Research archetypes and tooling (01:12:25) Labor market and careers (01:20:09) Applicant selection and preparation (01:29:33) Admissions, salaries, and compute (01:40:34) Future programs and paradigms (01:54:11) Outro PRODUCED BY: https://aipodcast.ing SOCIAL LINKS: Website: https://www.cognitiverevolution.ai Twitter (Podcast): https://x.com/cogrev_podcast Twitter (Nathan): https://x.com/labenz LinkedIn: https://linkedin.com/in/nathanlabenz/ Youtube: https://youtube.com/@CognitiveRevolutionPodcast Apple: https://podcasts.apple.com/de/podcast/the-cognitive-revolution-ai-builders-researchers-and/id1669813431 Spotify: https://open.spotify.com/show/6yHyok3M3BjqzR0VB5MSyk
© 2020-2026 Ivy Podcast Discovery LLC
