Podcasts about Personality

On The Other Side of Midnight, Walter Sterling explains why the overnight shift has always felt like home—and why the later it gets, the more honest people can become. From the quiet streets of New York City to the freedom of working while everyone else is asleep, the overnight hours offer a different kind of connection.The conversation also dives into the science and personality differences between introverts, extroverts, and the newly discussed “outroverts.” Why do introverts need solitude to recharge? Why do workplaces often misunderstand quiet employees? And why can “the plans have been canceled” be the greatest words an introvert can hear?Become a supporter of this podcast: https://www.spreaker.com/podcast/the-other-side-of-midnight-with-walter-sterling--7177415/support.

ADHD in women is far more complex than being distracted, forgetful, or unable to sit still. In this episode, Dr. Jolene Brighten, ND, author of ADHD and Women, breaks down how ADHD actually presents in women, why so many women are first diagnosed with anxiety or depression, and how estrogen, progesterone, dopamine, the menstrual cycle, pregnancy, postpartum, and perimenopause can influence symptoms. We explore executive dysfunction, time blindness, rejection sensitivity, procrastination, medication, hormone therapy, exercise, sleep, nutrition, caffeine, meditation, and practical strategies for working with an ADHD brain instead of constantly fighting against it. Ultimately, Dr. Brighten reframes ADHD not as personal failure, but as a different operating system that requires different tools to thrive. Follow Jolene @drjolenebrighten Follow Chase @chase_chewning ----- 00:00 What science gets wrong about women and ADHD 02:32 Why studying the female brain is so complicated 04:18 Hormones and ADHD medication effectiveness 06:45 Can we recover decades of missing female health data? 08:01 Estrogen, dopamine and the menstrual cycle 09:32 Personality flaw or ADHD symptom? 11:50 Why women are diagnosed with anxiety and depression first 13:56 Why female ADHD doesn't always look hyperactive 14:42 Time blindness explained 16:33 ADHD is really a problem of dysregulation 17:27 What ADHD actually is—and isn't 20:03 Are you born with ADHD? 22:56 Hormones, masking and the female ADHD experience 26:37 When ADHD begins showing up in girls 27:50 ADHD medication in children 30:03 Can a brain scan diagnose ADHD? 31:13 Procrastination vs. task paralysis 33:47 ADHD in high-performing women 36:32 Rejection sensitivity dysphoria 39:07 Can changing your self-talk improve symptoms? 40:08 How to interrupt negative ADHD thought loops 44:46 Dopamine, phones and doomscrolling 45:54 Why ADHD brains need pleasure 48:24 What Parisian cafés can teach us about attention 51:02 ADHD medications: what women should know 53:42 HRT, estrogen and ADHD symptoms 57:30 Should the goal be getting off ADHD medication? 1:00:03 When medication becomes a bigger conversation 1:02:10 Exercise, sleep, environment and nutrition—ranked 1:03:05 20 minutes of exercise and focus 1:03:42 Iron deficiency, sleep and ADHD 1:04:12 Why nutrition comes last—but still matters enormously 1:06:01 Are women simply not eating enough? 1:09:31 Rapid fire: the best and worst ADHD morning habits 1:15:51 The "different operating system" approach 1:19:06 What Ever Forward means to Dr. Brighten ----- Episode resources: FREE sample of MitoPure from Timeline Strong Coffee Company code CHASE for 15% off Get Jolene's new book on Amazon

We conclude the FakeClaiming series with a public statement approved by the Board.Our website is HERE:  System Speak Podcast and sponsoring nonprofit website is HERE: S3C Foundation.You can submit an email to the podcast HERE.You can JOIN THE COMMUNITY HERE.  Once you have registered with the network, you will receive an invitation to orientation, and then can use a non-Apple device or non-safari browser to join groups HERE. Once you are set up, then the website and app work on any device just fine.  We have peer check-in groups, an art group, recovery groups, social events, and classes.  Additional zoom groups are optional, but only available by joining the groups. Join us!Content Note: Content on this website and in the podcasts is assumed to be trauma and/or dissociative related due to the nature of what is being shared here in general.  Content descriptors are generally given in each episode.  Specific trigger warnings are not given due to research reporting this makes triggers worse.  Please use appropriate self-care and your own safety plan while exploring this website and during your listening experience.  Natural pauses due to dissociation have not been edited out of the podcast, and have been left for authenticity.  While some professional material may be referenced for educational purposes, Emma is not your therapist nor offering professional advice.  Any informational material shared or referenced is simply part of our own learning process, and not guaranteed to be the latest research or best method for you.  Please contact your therapist or nearest emergency room in case of any emergency.  This website does not provide any medical, mental health, or social support services. ★ Support this podcast on Patreon ★

Lund's Last Call: What KNBR personality would you absoutely NOT want to be stranded with on a desert island? PLus more from the White Sox locker room, Tom Brady gives love to Brock Purdy, and we preview a huge Thursday night of Sports!See omnystudio.com/listener for privacy information.

Śrī Kṛṣṇa, the Personality of Godhead, who is the Paramātmā [Supersoul] in everyone's heart and the benefactor of the truthful devotee, cleanses desire for material enjoyment from the heart of the devotee who has developed the urge to hear His messages, which are in themselves virtuous when properly heard and chanted. (SB 1.2.17) ------------------------------------------------------------ To connect with His Grace Vaiśeṣika Dāsa, please visit https://www.fanthespark.com/next-steps/ask-vaisesika-dasa/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 https://vaisesikadasayatra.blogspot.com/ ------------------------------------------------------------ Add to your wisdom literature collection: https://iskconsv.com/book-store/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 https://www.bbtacademic.com/books/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 https://thefourquestionsbook.com/?utm_source=youtube&utm_medium=video&utm_campaign=launch2025 ------------------------------------------------------------ Join us live on Facebook: https://www.facebook.com/FanTheSpark/ Podcasts: https://podcasts.apple.com/us/podcast/sound-bhakti/id1132423868 For the latest videos, subscribe https://www.youtube.com/@FanTheSpark For the latest in SoundCloud: https://soundcloud.com/fan-the-spark ------------------------------------------------------------ #spiritualawakening #soul #spiritualexperience #spiritualpurposeoflife #spiritualgrowthlessons #secretsofspirituality #vaisesikaprabhu #vaisesikadasa #vaisesikaprabhulectures #spirituality #bhaktiyoga #krishna #spiritualpurposeoflife #krishnaspirituality #spiritualusachannel #whybhaktiisimportant #whyspiritualityisimportant #vaisesika #spiritualconnection #thepowerofspiritualstudy #selfrealization #spirituallectures #spiritualstudy #spiritualquestions #spiritualquestionsanswered #trendingspiritualtopics #fanthespark #spiritualpowerofmeditation #spiritualteachersonyoutube #spiritualhabits #spiritualclarity #bhagavadgita #srimadbhagavatam #spiritualbeings #kttvg #keepthetranscendentalvibrationgoing #spiritualpurpose

Waarom raakt een stille reactie van je partner je harder dan de situatie rechtvaardigt? En waarom voelt een simpel gesprek over een vakantie voor de één ontspannen, en voor de ander als een reden om het maar uit te stellen?In deze aflevering van Omvatten neem ik je mee in hechting en hechtingspatronen, en in hoe bepalend ze zijn voor je hele leven. Ik laat je zien hoe hechting ontstaat, hoe ze je relaties en je verwachtingen daarin stuurt zonder dat je het doorhebt, en wat de link is met hoogbegaafdheid. Aan de hand van onderzoek van onder meer Bowlby, Ainsworth en Sroufe, en voorbeelden uit mijn praktijk, ontrafel ik de relatie dansen bezien vanuit hechting en krijg je haalbare adviezen hoe daar vandaag al een volgende stap in te zetten. Bronvermeldingen:-Alan Soufre, onderzoek: Minnesota Longitudinal Study of Risk and Adaptation. Boek: The development of the person. -Chris Fraley, Meta Analyse in 2002 gepubliceerd in Personality and Social Psychology Review-John Bowlby, boek: Attachment and Loss-Mary Ainsworth, boek: Patterns of attachment-Cindy Hazan & Philip Shaver, studie in 1987 gepubliceerd in Journal of Personality and Social Psychology-Sue Johnson, Emotionally Focussed Therapy. Boek: Hold me Tight-Glenn Roisman, earned security

September brings a new, and much loved by us both, season, so it's time to talk Colour Psychology and dig into the Seasonal Personality of Autumn. As the creator of Colour Psychology for Branding, Fi shares her abundant wisdom and helps us makes sense of how we translate the energy of this glorious season into the colours, fonts, shapes, textures, photography and illustrative styles for our brands. This is the third in this series and you can find Spring and Summer episodes here.We really hope you find it useful. Hosted on Acast. See acast.com/privacy for more information.

Most lawyers know relationships lead to referrals. The challenge is keeping those relationships alive when everything else gets busy. In this episode of the Lawyerist Podcast, Stephanie Everett talks with Jay Ruane about analog marketing and the simple systems that make staying connected part of running a firm.  Jay explains why offline marketing often falls apart after the first month and how a repeatable approach can help lawyers follow through. They explore using AI to identify forgotten connections in your inbox, making time for short coffee meetings, and becoming the person others trust to make a useful introduction.  The conversation also covers networking as an introvert, asking about someone else's ideal client, and choosing thoughtful gifts that people actually want to keep. Jay shares why his firm sends clients blankets without its logo and why a manageable network of 50 referral partners can support a successful practice.  If your marketing plan depends on remembering to reach out when things slow down, this episode offers a more practical way to build relationships, generate referrals, and keep showing up.    Listen to the previous episodes of our Referral Marketing, Relationship Building & Law Firm Growth.  #636: Why Past Clients May Be Your Law Firm's Best Growth Strategy, with EJ Stern & Katherine Wilson Apple | Spotify | LTN  #608: Business Development for Lawyers: Building Real Relationships That Lead to Clients, with Megan Senese Apple | Spotify | LTN  #606: Breaking the Copycat Cycle: Building a Law Firm with Personality, with Patrick Patino Apple | Spotify | LTN  #515: Simple Marketing Hacks Lawyers Swear By, with Gyi Tsakalakis Apple | Spotify | LTN  Have thoughts about today's episode? Join the conversation on LinkedIn, Facebook, Instagram, and X!   If today's podcast resonates with you and you haven't read The Small Firm Roadmap Revisited yet, get the first chapter right now for free! Looking for help beyond the book? See if our coaching community is right for you.   Access more resources from Lawyerist at lawyerist.com.   Subscribe to Lawyerist Podcast: https://play.megaphone.fm/xrm0mqp4tqwi0ozntiu41g Chapters / Timestamps  00:00 – Introduction  00:59 – Stephanie's Blog and the Lawyerist Community  03:02 – Meet Jay Ruane  03:57 – Why Relationship Marketing Needs a System  07:17 – Keeping Your Systems Simple  08:46 – Why Analog Marketing Still Works  11:01 – Using AI to Rediscover Referral Connections  12:07 – Building a Network by Connecting Others  14:13 – Networking as an Introvert  17:19 – Preparing for Better Conversations  19:31 – Talking Business Without Forcing a Pitch  20:32 – Asking for Introductions  21:43 – Moving Beyond a Scarcity Mindset  22:41 – Thoughtful Gifts vs. Branded Merchandise  26:16 – Conference Giveaways People Actually Want  27:11 – Making a Book a Personal Gift  28:31 – Building a Repeatable Marketing Routine  29:49 – Why 50 Referral Partners Can Be Enough  30:46 – Closing Thoughts 

Are you a spontaneous person who still loves a good spreadsheet? In this episode of the No Vacation Required podcast, Kent and Caanan wrap up their facets series by breaking down the Judging and Perceiving (J/P) pairing. Discover why you might act like a completely different person at work versus at home, why waiting until the last minute doesn't mean you are disorganized, and how to embrace your unique approach to time management.CHAPTERS(00:00) Mind Share: Trade Secret(03:19) Why personality facets take you from 1-in-16 to 1-in-a-million(05:55) The Judging vs. Perceiving (J/P) personality pairing explained(07:05) Real-life examples: The casual J(10:11) Client story: Code-switching between work and home(19:56) Mailbag: Understanding stress responsesCOMMON QUESTIONS ANSWERED IN THIS EPISODE❓ What are the Judging and Perceiving (J/P) facets? This pairing is all about how you manage your life and your time. Judgers (J) generally prefer decisiveness, structure, and closure, while Perceivers (P) prefer flexibility, spontaneity, and keeping their options open. Facets allow you to have traits from both sides.❓ Can I be a structured person who still procrastinates? Absolutely. You can be a dominant Judger who loves a clean calendar, but still have a "pressure-prompted" facet that means you do your best work right before a deadline. This doesn't mean you are disorganized – it's just how you are wired.❓ Why do I act like a J at work and a P at home? The J/P pairing is where we see the biggest split between our professional and personal lives. Many people "code-switch" by using their structured J facets to succeed at work, while fully leaning into their spontaneous P facets on the weekend.❓ If I am a Perceiver, does that mean I am naturally disorganized? Not at all. Being a Perceiver simply means you prefer to keep your options open and stay flexible. It does not mean you are incapable of planning or keeping your life in order.SUPPORT NO VACATION REQUIREDIf this episode resonated with you, please leave a review. It is one of the best ways to help more people discover the podcast.✅ Subscribe: Never miss an episode by hitting the follow button✅ Visit Our Website: https://novacationrequired.com/✅ Read The Book: https://novacationrequired.com/book✅ Follow Us On Instagram: https://www.instagram.com/novacationrequired/✅ Talk To Us: https://novacationrequired.com/contactLINKS AND RESOURCES

Wed, 30 Sep 2026 05:31:00 +0000 https://jungeanleger.podigee.io/3358-borsepeople-im-podcast-s26-09-ines-hein 5698e1b9bb40636fdc98aaa4ab896ffe Ines Hein ist Head of Communications & Marketing der Baader Bank AG. Die Erlangerin ist seit 1995 kreativ und beratend für Kunden im DACH-Raum und den USA tätig – mit Berufsstationen in München, Hamburg, New York und Berlin. Bis 2025 begleitete sie Unternehmen als freiberufliche Branding- und Kommunikationsberaterin, Texterin und Moderatorin. Seit 2026 gehört Ines zum Team der Baader Bank, u.a. um die Marke Baader Trading dauerhaft nachhaltig zu positionieren. Wir sprechen über Baader Trading, die 15. Bader Investment Conference, die von 21. bis 24. September 2026 in München stattgefunden hat (und der ich beiwohnen durfte), über die anstehenden Baader Trading Days für Private, über das Sprechen generell und natürlich musste ich auch Wissenswertes über Erlangen einwerfen. https://www.baaderbank.de https://www.baaderbank.de/leistungen/trading https://www.baadertrading.de/baader-trading-days https://www.baaderinvestmentconference.com Presented wird die Season 26 von der TIMETOACT GROUP Österreich. About: Die Serie Börsepeople des Podcasters Christian Drastil, der im Q4/24 in Frankfurt als "Finanznetworker #1 Austria" und Q3/26 als "Stock Market Education Austria #1 LinkedIn" ausgezeichnet wurde, findet im Rahmen von http://www.audio-cd.at und dem Podcast "Audio-CD.at Indie Podcasts" statt. Es handelt sich dabei um typische Personality- und Werdegang-Gespräche. Die Season 26 mit 25 Folgen wird auch die Folge 600 enthalten und ist präsentiert von https://www.timetoact-group.at . Welcher der meistgehörte Börsepeople Podcast ist, sieht man unter http://www.audio-cd.at/people. Der Zwischenstand des laufenden Rankings ist tagesaktuell um 12 Uhr aktualisiert. Bewertungen bei Apple (oder auch Spotify) machen mir Freude: http://www.audio-cd.at/spotify , http://www.audio-cd.at/apple . Du möchtest deine Werbung in diesem und vielen anderen Podcasts schalten? Kein Problem!Für deinen Zugang zu zielgerichteter Podcast-Werbung, klicke hier.Audiomarktplatz.de - Geschichten, die bleiben - überall und jederzeit! 3358 full no Christian Drastil Comm. (Agentur für Investor Relations und Podcasts) 2337

In the latest episode of The Science of Personality, Blake and Jackie are joined by Christopher Duffy, Hogan's director of strategic accounts, and Jennifer Lowe, Hogan's director of solution delivery and learning, for a fascinating journey through Hogan history and lore. Having a combined nearly 60 years of Hogan experience, Chris, Jennifer, and Jackie have worked directly with some of the world's largest organizations, and this episode explores their favorite client projects, their biggest challenges, and their favorite tales from their time at Hogan.

Get AudioBooks for FreeBest Self-improvement MotivationDiscover Your Business Personality | Dan Martell's GuideDiscover your business personality with Dan Martell's insights and learn how your natural strengths, style, and habits can shape entrepreneurial success.⁠We Need Your Love & Support ❤️⁠⁠Get 3 Audiobooks Free -

One of the earliest examples of DISC? Shakespeare's'' "Julius Caesar!" Personality preferences are not an excuse for a lack of integrity. Brutus, Shakespeare's noble assassin, points the way. Interested in coaching or training on these topics for you or your team? We'd love to hear from you! Email Mike and Mark.

Emma and Fiona want Dave to enter the Traitors... but with a whole new personality!

My guest today is Noah Shinn. Noah is the founder of Instinct, a personal assistant that you text, call, or email the same way you would a person. It has its own phone and its own computer, and it can do almost anything on your behalf that you would do yourself online. Instinct is about a year old, still invite-only, and growing roughly 10% day over day without any marketing spend. We discuss the surprising ways people are already using Instinct, the trusted network that lets two people's agents coordinate directly, and what Noah has learned about how long it takes users to trust an agent with their credit card, inbox, and calendar. He explains why he refuses to build an ad model and why he believes a personal agent should never influence users against their own interests. We also cover the take rate model behind the more than $1 billion a year now flowing through the platform, how travel and food delivery businesses should prepare for a world of agents, why he spends 40% of his time thinking about compute, and why he believes all of software will eventually collapse into one simple interface. Please enjoy my conversation with Noah Shinn. For the full show notes, transcript, and links to mentioned content, check out the episode page ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠.  ----- Become a Colossus member to get our quarterly print magazine and private audio experience, including exclusive profiles and early access to select episodes. Subscribe at ⁠colossus.com/subscribe⁠. ----- ⁠Ramp's⁠ mission is to help companies manage their spend in a way that reduces expenses and frees up time for teams to work on more valuable projects. Go to⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠ramp.com/invest⁠⁠ to sign up for free and get a $250 welcome bonus. ----- Trusted by thousands of businesses, ⁠Vanta⁠ continuously monitors your security posture and streamlines audits so you can win enterprise deals and build customer trust without the traditional overhead. Invest Like the Best listeners get a special offer of $1,000 off Vanta when you go to ⁠vanta.com/invest⁠.  ----- WorkOS⁠ is the infrastructure B2B and AI-native companies use to sell to enterprise. It covers everything enterprise security requires: SSO, SCIM, RBAC, Audit Logs, AI governance, and more. Trusted by 2,000+ fast-growing companies, including OpenAI, Anthropic, Cursor, and Vercel. ----- Rogo is the AI platform for finance. They're building agents for Wall Street that are trained to understand how bankers and investors actually do work: from diligence and modeling, to turning analysis into deliverables. To learn more, visit rogo.ai/invest. ----- ⁠Ridgeline⁠ has built a complete, real-time, modern operating system for investment managers. It handles trading, portfolio management, compliance, customer reporting, and much more through an all-in-one real-time cloud platform. Visit⁠ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ridgeline.ai⁠. ----- Timestamps: (00:00:00) The Most Exciting Software Race Ever (00:00:49) What Instinct Is (00:04:11) The Wildest Things Users Have Done With Instinct (00:07:15) The Instinct to Instinct Trusted Network (00:13:24) How Agents Will Reorder the Internet (00:14:44) Reinventing Restaurant Reservations (00:17:23) Travel and $1 Billion in Transaction Volume (00:21:00) How Users Learn to Trust an Agent (00:23:25) Keeping Sensitive Data Safe (00:26:08) Alignment and the Business Model (00:31:07) Take Rates and the Payments Stack (00:34:52) When Incumbents Push Back on Agents (00:40:46) How Businesses Should Prepare for Agents (00:44:43) Designing for Understandability (00:48:15) Taste Versus Data (00:50:03) Invite-Only Growth at 10% a Day (00:54:46) How Far Ahead to Buy Compute (00:56:58) The Cost to Serve Each User (00:59:24) How Much Compute Proactive Agents Will Need (01:02:30) Thoughts on Muse (01:03:59) Mistakes and Staying Proactive (01:05:34) The Future of Security (01:08:32) Where the Interface Goes Next (01:12:35) Agents That Pursue Goals (01:14:35) Personality and the Movie Her (01:16:27) Why It's Called Instinct (01:17:34) Allies, Enemies, and Distribution Channels (01:18:43) Raising Capital (01:20:34) The Kindest Thing

Mally Roncal is a celebrity makeup artist who has worked with Beyoncé, Jennifer Lopez, Rihanna, Celine Dion, and so many more, and the founder of Mally Beauty.A big theme in Mally's life is learning not to make herself smaller. We get into the moments that made her question whether she should tone herself down, how she learned to see what made her different as a strength, and what working with some of the biggest women in entertainment taught her about confidence, intuition, and listening to her gut.Then there's the business story. Mally launched Mally Beauty on QVC in 2005. We talk about what it actually looked like building a company for nearly two decades, becoming a mom while growing the business, raising three daughters, and the harder chapters that taught her about trust and what happens when you hand parts of your company over to other people.Mally has experienced loss, rejection, setbacks, and plenty of moments that could have made her bitter or afraid, but instead she's built a practice around gratitude, perspective, and choosing her energy over and over again. We get into how to trust your instincts, how to build without losing the people and parts of life that matter most, how to recover when things don't go according to plan, and why authenticity can become one of your biggest advantages in both business and life.In this episode, we'll talk to Mally about:* How losing her mother shaped her gratitude and courage. [02:30]* Growing up with two inspiring Filipino doctor parents. [05:44]* Turning childhood bullying into a belief in her uniqueness. [08:37]* Learning to celebrate your differences instead of fitting in. [09:57]* Discovering makeup artistry after studying fashion design. [15:59]* Choosing authenticity after being told to change her appearance. [17:56]* How staying true to herself led to an InStyle opportunity. [21:05]* Building a celebrity makeup career and trusting her instincts. [22:12]* The Beyoncé makeup moment that changed her career. [24:01]* Finding creative freedom through collaborative client relationships. [26:53]* Balancing a demanding celebrity career with building a family. [28:36]* Creating Mally Beauty from personalized makeup formulas. [29:58]* Why she chose QVC to teach women makeup techniques. [31:41]* Building a business and raising twins while redefining success. [34:13]* Challenging the myth that women can't have it all. [38:52]* Finding the courage to expand beyond Mally Beauty. [42:58]* Why entrepreneurs must understand every part of their business. [45:34]* Prioritizing mental, physical, and spiritual well-being over business. [46:22]* Choosing joy, empathy, and gratitude through life's challenges. [50:31]* Manifesting a bigger vision and trusting the journey. [52:43]* Why you should acknowledge hard moments, then “fix your crown” and move forward. [57:52]* Remembering that life, family, and relationships matter more than business. [01:00:06]This episode is brought to you by Beeya:* If you or anyone you know have been struggling with hormonal imbalances and bad periods, go to https://beeyawellness.com/free to download the free guide to tackling hormonal imbalances* Plus, get $10 off your order by using promo code BEHINDHEREMPIRE10Follow Yasmin:* Instagram: https://www.instagram.com/yasminknouri/* Website: https://www.behindherempire.com/Follow Mally:* Instagram: https://www.instagram.com/mallyroncal/* QVC: https://www.qvc.com/catalog/psearch.html?keyword=Mally Hosted on Acast. See acast.com/privacy for more information.

We talk about the new FakeClaiming.Our website is HERE:  System Speak Podcast and sponsoring nonprofit website is HERE: S3C Foundation.You can submit an email to the podcast HERE.You can JOIN THE COMMUNITY HERE.  Once you have registered with the network, you will receive an invitation to orientation, and then can use a non-Apple device or non-safari browser to join groups HERE. Once you are set up, then the website and app work on any device just fine.  We have peer check-in groups, an art group, recovery groups, social events, and classes.  Additional zoom groups are optional, but only available by joining the groups. Join us!Content Note: Content on this website and in the podcasts is assumed to be trauma and/or dissociative related due to the nature of what is being shared here in general.  Content descriptors are generally given in each episode.  Specific trigger warnings are not given due to research reporting this makes triggers worse.  Please use appropriate self-care and your own safety plan while exploring this website and during your listening experience.  Natural pauses due to dissociation have not been edited out of the podcast, and have been left for authenticity.  While some professional material may be referenced for educational purposes, Emma is not your therapist nor offering professional advice.  Any informational material shared or referenced is simply part of our own learning process, and not guaranteed to be the latest research or best method for you.  Please contact your therapist or nearest emergency room in case of any emergency.  This website does not provide any medical, mental health, or social support services. ★ Support this podcast on Patreon ★

Get Promoted Faster: How the Dolphin Strategy Took One Stuck Supervisor to VP — and What It Means for Women Leaders Last updated: September 26, 2026 Trusted by leaders at Stanford University, Ernst & Young, Autodesk, MGM Grand Resorts, and Farmers Insurance Executive Summary: Have you been told you "don't have the personality" for promotion? Sabrina Braham shares how her coaching client Martin, stuck five years as supervisor, reached VP using five moves: decode feedback, recruit dolphins, build your voice, make the Half-Point Ask, and volunteer for visibility. Use them to get promoted faster. Quick Takeaways: Vague feedback like "personality" isn't a verdict — translate it into observable behaviors. Recruit "dolphins": allies in the room who back your ideas when you speak. Employees with sponsors are twice as likely to be promoted (McKinsey & LeanIn.Org, 2025). Ask your manager for a 1–10 rating, then ask what earns one more half point. Martin: five stuck years, then manager in six months — then director and VP. Jump to: Martin's Story · Why You're Stuck · The 5 Moves · The Results · Action Plan · Mistakes to Avoid · FAQ · 2026 Trends As an executive leadership coach with over 30 years of experience (MA, MFT, PCC) and host of the Women's Leadership Success Podcast — on air since 2007 and ranked in the top 1.5% of podcasts worldwide — I hear one question more than any other: how do I get promoted faster when I'm already doing a great job? The question is urgent. By September 10, layoffs.fyi counted more than 128,000 tech layoffs in 2026 — already more than all of 2025. And McKinsey and LeanIn.Org's Women in the Workplace 2025 found only about half of companies still prioritize women's advancement. Good work alone won't help you get promoted faster. In Episode 169, the tables turned. My co-founder and executive producer, Tim Warren, interviewed me about Martin — a Fortune 500 supervisor told he "didn't have the personality" to be a manager. He believed it. Then, step by step, he proved it wrong. His story is the clearest map I know to get promoted faster, especially if you're the only one like you in the room. The Feedback That Kept Martin Stuck for Five Years At Martin's company, supervisors usually became managers within a year. Martin had been a supervisor for five. His numbers were strong, his people loved him, and his leaders said he was doing a great job. Then came the "but": he just didn't have the personality to be a manager. Martin grew up speaking English as a second language, was the first in his family to attend college, and graduated with honors. None of that protected him. When someone with authority labels you, you tend to believe it. I know that feeling. I was raised in a blue-collar family, and when someone with authority said I had a flaw, I assumed it was true. It took me years to unlearn. If you've absorbed a label like Martin's, take this from his story: the label can be wrong, and you can change the evidence behind it. His question to me was painful: could he change his personality to move up? Why Talented Leaders Don't Get Promoted Faster in 2026 Martin's situation isn't rare. A strong performer gets fuzzy feedback, loses confidence, goes quiet in the rooms where promotions are shaped — and stalls. Here's why that pattern makes it harder to get promoted faster right now. The "broken rung" is still broken For every 100 men promoted to first-level manager, only 93 women are promoted (McKinsey & LeanIn.Org, 2025). That first step — the one Martin was stuck on — shapes every level above it. The sponsorship gap is real At entry level, 31% of women have a sponsor versus 45% of men, and employees with sponsors are about twice as likely to be promoted. The finding that matters most: when women and men get equal career support, the gap in promotion ambition disappears. The problem isn't drive. It's backing. Being "the only" changes how you're heard Roughly one in five women are often the only woman in the room, more for senior and technical women (LeanIn.Org). Being "the only" tends to make people cautious about sharing ideas — less visibility when you need more. The cost of waiting In 2026's market, "I'll speak up once I feel confident" is a risky plan. To get promoted faster — or stand out after a layoff — treat visibility as a skill you practice. Ready to get promoted faster — before you feel fully ready? Leading Before You're Ready — a practical playbook for leaders stepping into bigger roles. Inside, you'll find: Language for speaking up with confidence before you feel fully ready Ways to build trust fast with the decision-makers who shape your next role A framework for positioning yourself as promotion-ready — actively, not passively GET THE COMPLIMENTARY PLAYBOOK The Dolphin Promotion Framework™: 5 Moves to Get Promoted Faster Here's exactly what Martin and I worked on. None of it required a new personality — just consistent, specific action. Each move helps you get promoted faster on its own; together they compound. Move 1: Decode the vague feedback "Personality" is nearly useless feedback. What does it even mean? So we started at ground zero: what would Martin need to do differently to be seen as a manager? The answer was concrete. In meetings with peers or senior leaders, Martin went quiet. That silence, and the confidence gap behind it, was what his leaders called "personality." Once we named the behavior, we could change it. Success metric: The feedback becomes two or three observable behaviors — your first step to get promoted faster. Move 2: Recruit your dolphins Picture a shipwreck survivor clinging to boards while a shark circles. When dolphins surround a person in the water, sharks tend to stay away — and dolphins have been reported guiding swimmers to shore. A dolphin at work is someone in the room who has your back, believes you're capable, and supports you when you speak up: A mentor shares knowledge and advice, often in private. A sponsor uses their power and influence to advocate for you — often when you're not in the room. A dolphin is in the meeting with you, backing your idea in real time. Far fewer leaders have dolphins than mentors. Lean In reports that high-potential women often have more mentors than men, yet mentorship didn't correlate with promotion. If you want to get promoted faster, real-time backing does what advice can't. How to find your dolphins: Look for a friend in your key meetings, or someone who often shares your viewpoint. If no one comes to mind, hold one-on-ones, share the idea you want to raise, and see who's aligned. Then make a simple ask. Try This Now (3 minutes): Pick the idea you most want to raise next meeting, then send one colleague: "Here's an idea I'd like to share Thursday. Would you be willing to support it when I bring it up?" That's the whole ask. Move 3: Build your speaking muscle — and rehearse your one main point The most cost-effective confidence builder I know is Toastmasters. Clubs are in nearly every U.S. city, dues are modest (often around $20 a month), and the program works. At a district meeting years ago, I was struck by the room: real confidence and presence, built through structured practice. Martin joined, and it helped him learn to speak up. The second half is rehearsal. You usually know the agenda and what would help your team. Pick your main point and practice it out loud. What surprises people: the CEOs I work with still rehearse their main points before meetings. Success metric: One prepared point, delivered weekly. Small reps like this are how you get promoted faster. Move 4: Make the Half-Point Ask With practice behind him, Martin went directly to the leaders who had formed the wrong impression. Most people skip this step, yet it's the move that helps you get promoted faster than any other. Here's the conversation: State the goal. "I'd like to be promoted to manager. What's helping, and what do I need to do differently?" Ask for a number. "On leading my team, from 1 to 10, what would you give me?" Ask for the half point. If it's a 7: "What would I need to do to be a 7.5?" Always just a half point. Schedule the follow-up. "Could I check back in a few weeks?" Why a half point? It's achievable, and it pulls your manager into problem-solving mode. Once they give a number, they become invested in your progress. There's a psychological bonus. It's why you notice red cars everywhere after buying one: the brain's attention filter, the reticular activating system, scans for what it's primed to find. After the Half-Point Ask, your manager watches for your improvement. Success metric: You have a baseline number from at least one decision-maker and a follow-up date on the calendar. Move 5: Volunteer for visibility Martin also began joining committees. On one sat five vice presidents — and Martin, a newly promoted manager. He practiced his idea for turning a project around. In the meeting, the VPs talked over him toward a decision. So Martin said, "I have an idea." The room stopped. The lead VP asked to hear it. Martin explained it in detail. When he finished, the room went silent. His heart sank. I blew it, he thought. Then the senior vice president said: "Good idea, Martin. Let's do that." That was the game changer. Rehearsal plus visibility had become executive presence — and the surest way to get promoted faster is to be seen doing the next job. What Happened Next: From Supervisor to VP After five stuck years, here's how Martin's trajectory changed: About 6 months: promoted to manager — roughly a 30% raise. About 4 months after that meeting: director. Two to three years later: promoted to vice president, with stock options, earning roughly double his supervisor pay. What moves me most is what didn't change: Martin kept his kindness and has mentored many others to promotion. His words: "I wish I would have contacted you sooner. It was a game changer. It changed my life....

In this episode of Healthy Mind, Healthy Life, host Swati talks with Sheila N. Glazov, an internationally recognized personality expert and creator of the What Color Is Your Brain? methodology, about why two people can experience the exact same moment and walk away with completely different interpretations of it. Sheila traces her own path into brain-based personality work back to being diagnosed with dyslexia as a child in the 1960s, and explains why she built a framework around four brain colors, yellow, blue, green, and orange, rather than a fixed personality box people get placed into once and never revisited. The conversation moves into practical, everyday language for communicating across differences, including Sheila's memorable expression "wet paint" for describing when someone is not feeling emotionally settled and needs space before a conversation, and her mother's saying "feed them with a long spoon" for creating healthy distance during conflict. Sheila and Swati talk through what it actually looks like to speak someone else's brain color in real time, especially when emotions are running high, and why simply acknowledging how someone naturally thinks and feels can defuse a disagreement before it starts. About the Guest: Sheila N. Glazov is an internationally recognized personality expert, award-winning educator, and author of What Color Is Your Brain?® A Fun and Fascinating Approach to Understanding Yourself and Others, along with a series of related books and a children's book series that includes Princess Shana's Invisible, Visible Gift. Her brain color methodology draws on her decades of experience as an educator, including her own diagnosis of dyslexia as a child, to help people understand themselves and communicate more effectively with others. Key Takeaways: The What Color Is Your Brain? framework uses four brain colors, yellow, blue, green, and orange, to describe natural thinking and communication styles, without putting people in a fixed, unchanging box. Brain colors can blend and shift depending on setting, circumstances, and age, much like colors blending in a rainbow, rather than staying fixed for life. The expression "wet paint" describes the state of not feeling emotionally settled or esteemed, and naming it can help a person, or someone talking to them, recognize that it is not the right moment for a difficult conversation. Creating distance during a conflict, captured in the saying "feed them with a long spoon," gives both people time and space to respond in a healthier, less reactive way. Speaking someone else's brain color means acknowledging their natural traits directly, such as recognizing a yellow person's need for a plan or a green person's need for privacy to process, rather than communicating only in your own natural style. Sincerely listening, making time for a real conversation rather than a rushed one, and acknowledging another person's praiseworthy gifts are described as small, doable habits that build stronger relationships over time. Connect With Sheila Glazov: Website: https://sheilaglazov.com/  Book: What Color Is Your Brain?® A Fun and Fascinating Approach to Understanding Yourself and Others, available on Amazon and from her publisher Children's book: Princess Shana's Invisible, Visible Gift 11 brain color quizzes available on her website Episode Chapters: 00:00 - Cold open: why two people can experience the same thing differently 02:31 - Welcome to Healthy Mind, Healthy Life and introducing Sheila Glazov 03:37 - The biggest misconception people have about personality types and brain colors 06:26 - Why Sheila built What Color Is Your Brain instead of a fixed personality box 15:35 - What it looks like when someone is not working with their natural brain color: the wet paint concept 25:35 - Bringing brain colors into everyday conversations with partners, family, and friends 39:21 - How to connect with Sheila Glazov, take the quizzes, and find her books   Want to be a guest on Healthy Mind, Healthy Life? DM on PM - Send me a message on PodMatch DM Me Here: https://www.podmatch.com/hostdetailpreview/avik Disclaimer: This episode is produced for educational and informational purposes only. All views expressed by the guest are their personal opinions alone and do not represent the views of the host or Healthy Mind by Avik™. The Network does not verify, endorse, or assume responsibility for any guest statements. Nothing in this episode constitutes medical, legal, financial, or professional advice, please consult a qualified professional before making any decisions. Listeners are encouraged to engage critically and independently with all content do not consume blindly. Use this content as a starting point for your own reflection and research, not as a substitute for professional guidance. Third-party content is referenced under fair use for informational purposes only. Guest speakers are solely responsible for their own statements. If you have concerns about any content, please contact us here By listening, you acknowledge and accept this disclaimer in full. Read detailed disclaimer here. Healthy Mind By Avik™️ is a global platform redefining mental health as a necessity, not a luxury. Born during the pandemic, it's become a sanctuary for healing, growth, and mindful living. Hosted by Avik Chakraborty, storyteller, survivor, and wellness advocate. With over 6500+ episodes and 200K+ global listeners, we unite voices, break stigma, and build a world where every story matters.

Send us Fan MailDiscover your inner Winnie the Pooh archetype and how it shapes your fitness journey in this insightful episode of Fitbody Lifestyle. Jami and Greg explore the 'The Dao of Pooh,' revealing how character traits like Pooh's effortless flow and Rabbit's meticulous analysis manifest in athletes. Learn to identify your personality type, understand its inherent strengths and weaknesses, and master the art of balancing your approach to training and life. This discussion offers a unique perspective on goal setting, performance, and achieving a sustainable, fulfilling lifestyle by embracing your authentic self.What You'll Learn:How Winnie the Pooh characters can represent different personality archetypes.The strengths and weaknesses of the 'Pooh personality' (intuitive, effortless).The strengths and weaknesses of the 'Rabbit personality' (analytical, detail-oriented).Strategies for balancing your dominant archetype's traits for optimal performance.The importance of self-awareness and adaptability in your fitness and life journey.Tips for avoiding burnout and analysis paralysis.Tune in to unveil your inner Pooh or Rabbit and gain valuable insights into personal growth and athletic success!#PoohPersonality #Archetypes #FitbodyLifestyle #PersonalityTest #TheDaoOfPoohWelcome to FitBody Lifestyle the podcast hosted by Jami and Greg DeBernard! Join us as we explore the multifaceted world of fitness, health, business, relationships, and the art of leading a well-rounded life. Whether you're pumping iron at the gym, grinding in your entrepreneurial endeavors, or simply striving for balance in your daily routine, you've landed in the right spot.In each episode, we'll embark on enlightening discussions, provide you with actionable tips, and share inspiring stories that touch on every aspect of your journey towards a healthier, more fulfilling life. We'll cover everything from fitness tips to expert guidance on nutrition,  and effective weight loss strategies. Dive deep with us into topics like strength training for both body and mind, fostering cardiovascular health, and discovering the harmony between your daily lifestyle and your personal well-being. We're here to help you unlock your full potential, empowering you to transform your mind, body, and overall life. Connect With Us:https://www.fitbodylifestylepodcast.com/https://www.fitbodyfusion.com/https://www.instagram.com/jamidebernard/https://www.instagram.com/fbf_papa_bear/https:/...

Angela Stribling, the pioneering BET personality and radio host known for "Pillow Talk," has died at 58. Her husband said she died at home after a two-year battle with brain cancer. Subscribe to our newsletter to stay informed with the latest news from a leading Black-owned & controlled media company: https://aurn.com/newsletter Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In the second week of the Replanted series, Jason dove into Jesus' address to the church in Ephesus in Revelation 2:1–7 to uncover how a thriving, highly effective church can slowly go astray. On paper, the Ephesians were doing everything right: they worked hard, endured suffering, stood for doctrinal truth, and rooted out false teaching. Yet, Jesus brought a serious indictment against them: they had abandoned the love they had at first. Like doing all the right things for all the wrong reasons, it is entirely possible to serve God tirelessly while drifting away from intimate relationship with Him and placing our ultimate affection on the tools and people rather than Christ Himself.Spiritual drift and church failure often happen when we idolize or demonize what Jason called the “5 Ps” of church life: Place, People, Personality, Programs, and Position. When these secondary things become primary, we reduce the body of Christ to a mere country club or gym, seeking power, control, or personal preference rather than gospel transformation. To prevent our roots from withering and our lampstand from being removed, Jesus gives us a clear path back: remember where we fell, repent of the false loves we have turned to, and return to the simple, humble works we did at first.Support the show

Fat Joe's recent use of the N-word sparked a debate about who gets to say it. In this episode, I talk about how New York has its own personality, language, and social rules. Just as America can feel different from the rest of the world, New York can feel different from the rest of America. That context shapes what people consider normal and how their words land elsewhere. CONQUER SHYNESS

Links For The Occult Rejectshttps://linktr.ee/theoccultrejectsOccult Research Institutehttps://www.occultresearchinstitute.org/Substackhttps://substack.com/@theoccultrejects?r=7auau0&utm_campaign=profile&utm_medium=profile-pageCash Apphttps://cash.app/$theoccultrejectsVenmo@TheOccultRejectsPatreonhttps://www.patreon.com/TheOccultRejectsBIBLIOGRAPHYFear, Negativity, Attention, and StressBaumeister, Roy F., Ellen Bratslavsky, Catrin Finkenauer, and Kathleen D. Vohs. “Bad Is Stronger Than Good.” Review of General Psychology 5, no. 4 (2001): 323–370. https://doi.org/10.1037/1089-2680.5.4.323.Bar-Haim, Yair, Dominique Lamy, Lee Pergamin, Marian J. Bakermans-Kranenburg, and Marinus H. van IJzendoorn. “Threat-Related Attentional Bias in Anxious and Nonanxious Individuals: A Meta-Analytic Study.” Psychological Bulletin 133, no. 1 (2007): 1–24. https://doi.org/10.1037/0033-2909.133.1.1.Tannenbaum, Melanie B., Justin Hepler, Rick S. Zimmerman, Lindsey Saul, Samantha Jacobs, Kristina Wilson, and Dolores Albarracín. “Appealing to Fear: A Meta-Analysis of Fear Appeal Effectiveness and Theories.” Psychological Bulletin 141, no. 6 (2015): 1178–1204. https://doi.org/10.1037/a0039729.Juster, Robert-Paul, Bruce S. McEwen, and Sonia J. Lupien. “Allostatic Load Biomarkers of Chronic Stress and Impact on Health and Cognition.” Neuroscience & Biobehavioral Reviews 35, no. 1 (2010): 2–16. https://doi.org/10.1016/j.neubiorev.2009.10.002.Negative News, Trauma Coverage, and Stress ReactivityMarin, Marie-France, Julie-Katia Morin-Major, Tania E. Schramek, Annick Beaupré, Andrea Perna, Robert-Paul Juster, and Sonia J. Lupien. “There Is No News Like Bad News: Women Are More Remembering and Stress Reactive after Reading Real Negative News than Men.” PLoS ONE 7, no. 10 (2012): e47189. https://doi.org/10.1371/journal.pone.0047189.Holman, E. Alison, Dana Rose Garfin, and Roxane Cohen Silver. “Media's Role in Broadcasting Acute Stress Following the Boston Marathon Bombings.” Proceedings of the National Academy of Sciences 111, no. 1 (2014): 93–98. https://doi.org/10.1073/pnas.1316265110.Thompson, Rebecca R., Nickolas M. Jones, E. Alison Holman, and Roxane Cohen Silver. “Media Exposure to Mass Violence Events Can Fuel a Cycle of Distress.” Science Advances 5, no. 4 (2019): eaav3502. https://doi.org/10.1126/sciadv.aav3502.Fear, Negativity, and the Attention EconomyRobertson, Claire E., Nicolas Pröllochs, Kaoru Schwarzenegger, Philip Pärnamets, Jay J. Van Bavel, and Stefan Feuerriegel. “Negativity Drives Online News Consumption.” Nature Human Behaviour 7 (2023): 812–822. https://doi.org/10.1038/s41562-023-01538-4.Shabahang, Reza, Hyeyeon Hwang, Emma F. Thomas, Mara S. Aruguete, Lynn E. McCutcheon, Gábor Orosz, Abbas Ali Hossein Khanzadeh, Benyamin Mokhtari Chirani, and Ágnes Zsila. “Doomscrolling Evokes Existential Anxiety and Fosters Pessimism about Human Nature? Evidence from Iran and the United States.” Computers in Human Behavior Reports 15 (2024): 100438. https://doi.org/10.1016/j.chbr.2024.100438.Conspiracy Exposure and Paranoid ThoughtMolenda, Zuzanna, Marta Marchlewska, Adam Karakula, Wojciech Podsiadłowski, Marta Rogoza, Paulina Bagrowska, and Dagmara Szczepańska. “Thought Contagion? Conspiracy Beliefs Boost Paranoid Thoughts.” Applied Psychology: Health and Well-Being 16, no. 4 (2024): 2065–2082. https://doi.org/10.1111/aphw.12577.Repetition and the Illusory Truth EffectYe, Steeven, David Attali, Maria Ghazi, Arnaud Cachia, Mathieu Cassotti, Grégoire Borst, et al. “Systematic Review and Meta-Analysis of the Evidence for an Illusory Truth Effect and Its Determinants.” Nature Communications 17 (2026): 3270. https://doi.org/10.1038/s41467-026-70041-x.Intolerance of Uncertainty, Worry, and AnxietyAkbari, Mehdi, Sonay Sheikhi, Mahsa Sadat Navab Safiadin, Minoo Rahmani, Roya Forootan, and Gordon J. G. Asmundson. “A Hierarchical Uncertainty Framework of Anxiety: Preregistered Meta-Analytic Structural Model of Intolerance of Uncertainty and Worry across Anxiety Disorders.” Clinical Psychology Review 128 (2026): 102773. https://doi.org/10.1016/j.cpr.2026.102773.Intergroup Threat, Prejudice, and Negative GeneralizationRiek, Blake M., Eric W. Mania, and Samuel L. Gaertner. “Intergroup Threat and Outgroup Attitudes: A Meta-Analytic Review.” Personality and Social Psychology Review 10, no. 4 (2006): 336–353. https://doi.org/10.1207/s15327957pspr1004_4.Paolini, Stefania, and Kylie McIntyre. “Bad Is Stronger Than Good for Stigmatized, but Not Admired Outgroups: Meta-Analytical Tests of Intergroup Valence Asymmetry in Individual-to-Group Generalization Experiments.” Personality and Social Psychology Review 23, no. 1 (2019): 3–47. https://doi.org/10.1177/1088868317753504.Paolini, Stefania, Meghann Gibbs, Brett Sales, Danielle Anderson, and Kylie McIntyre. “Negativity Bias in Intergroup Contact: Meta-Analytical Evidence That Bad Is Stronger Than Good, Especially When People Have the Opportunity and Motivation to Opt Out of Contact.” Psychological Bulletin 150, no. 8 (2024): 921–964. https://doi.org/10.1037/bul0000439.Satanic Panic, McMartin, Suggestion, and False AllegationsGarven, Sena, James M. Wood, Roy S. Malpass, and John S. Shaw III. “More Than Suggestion: The Effect of Interviewing Techniques from the McMartin Preschool Case.” Journal of Applied Psychology 83, no. 3 (1998): 347–359. https://doi.org/10.1037/0021-9010.83.3.347.Garven, Sena, James M. Wood, and Roy S. Malpass. “Allegations of Wrongdoing: The Effects of Reinforcement on Children's Mundane and Fantastic Claims.” Journal of Applied Psychology 85, no. 1 (2000): 38–49. https://doi.org/10.1037/0021-9010.85.1.38.Goodman, Gail S., Jodi A. Quas, Bette L. Bottoms, Jianjian Qin, Phillip R. Shaver, Holly Orcutt, and Cheryl Shapiro. “Children's Religious Knowledge: Implications for Understanding Satanic Ritual Abuse Allegations.” Child Abuse & Neglect 21, no. 11 (1997): 1111–1130. https://doi.org/10.1016/S0145-2134(97)00070-7.Trust, Loneliness, Social Exclusion, and Conspiracy BeliefsGodžáková, Dana, and Jakub Šrol. “Mind in Doubt and Isolated Soul: Examining Longitudinal Relationships Between Conspiracy Beliefs Related to COVID-19, Interpersonal Trust, Loneliness and Social Exclusion.” Journal of Community & Applied Social Psychology 36, no. 3 (2026): e70267. https://doi.org/10.1002/casp.70267.Also want to remind people about the website, if you're into reading we have tons of information by multiple contributors, and we got t-shirts up on the site if you're interested. Fun fact, the art is all based on the eyeball. 

Regardless of how it's measured, not knowing how TIMELY to apply knowledge is MALADAPTIVE. Learning to learn and apply, or risk getting behind!Contact Us: TheWORDHouse.com; DrMDClay@TheWORDHouse.com; @WORDHouse; or call 304.523.WORD (9673).

Meist verliert man Freunde nicht, weil man sich gestritten hat. Irgendwann sind sie weg — ohne dass je etwas passiert wäre. Heute geht es um Freundschaft: darüber, warum uns Freunde abhandenkommen, wie man sie hält und wie man sie wiederfindet. Warum ist nach sieben Jahren die Hälfte des Freundeskreises ausgetauscht? Unterschätzen wir, wie sehr sich alte Freunde über eine Nachricht freuen? Gibt es echte Freundschaft unter Verwandten und ist das eher gut oder hat das Nachteile? Es geht um Kaffeezubereiter und Schimpansen, um große Fragen und kleine Gefallen und um die Frage, ob man eine Freundschaft auch beenden darf — und wie sie sich retten lässt. Francas neues Buch: "Die innere Oma" https://shop.autorenwelt.de/products/die-innere-oma-von-franca-cerutti Alle Tourdaten und Tickets für Dezember: https://www.190a.de/psychologie-to-go/ Unterstütze uns auf Steady: https://steady.page/de/psychologie-to-go/about Hinterlasse eine Frage oder einen Kommentar auf unserem Anrufbeantworter: https://www.speakpipe.com/Psychologietogo Quellen (Auszug): Liu, P. J., Rim, S., Min, L. & Min, K. E. (2022). The Surprise of Reaching Out: Appreciated More Than We Think. Journal of Personality and Social Psychology: Interpersonal Relations and Group Processes. https://www.apa.org/pubs/journals/releases/psp-pspi0000402.pdf Mollenhorst, G. (2009). Networks in Contexts: How Meeting Opportunities Affect Personal Relationships. Dissertation, Universität Utrecht. https://dspace.library.uu.nl/bitstream/handle/1874/33616/mollenhorst.pdf?sequence=2[rug] Holt-Lunstad, J., Smith, T. B. & Layton, J. B. (2010). Social Relationships and Mortality Risk: A Meta-analytic Review. PLoS Medicine, 7(7), e1000316. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000316 Sandstrom, G. M. & Dunn, E. W. (2014). Is Efficiency Overrated? Minimal Social Interactions Lead to Belonging and Positive Affect. Social Psychological and Personality Science, 5(4), 437–442. https://open.library.ubc.ca/media/stream/pdf/24/1.0074024/1[ubc] Du möchtest mehr über unsere Werbepartner erfahren? Hier findest du alle Infos & Rabatte: https://linktr.ee/psychologietogo Du möchtest Werbung in diesem Podcast schalten? Dann erfahre hier mehr über die Werbemöglichkeiten bei Seven.One Audio: https://www.seven.one/portfolio/sevenone-audio

Why do MTB skills seem to disappear the moment you feel scared, frustrated, overwhelmed or under pressure? You KNOW how to brake. You KNOW where to look. You KNOW what your body should be doing — and yet, on a difficult section of trail, suddenly none of it seems accessible. In previous episodes I've talked about how a lack of automaticity may be the cause, in THIS episode we talk about how you may be sabotaging yourself mentally! Because maybe it's the way you talk to yourself. In this episode of the Ride & Inspire RAWcast, we explore a sport psychology tool called Ileism. It's actually ridiculously simple — but psychological and neuroscience research into self-distancing and emotion regulation helps explain why changing the way we talk to ourselves can influence how we respond under pressure.In this episode, you'll learn:Why your MTB skills can feel inaccessible when pressure risesHow self-talk influences fear, attention and performanceWhat third-person self-talk and ileism areWhy psychological distance can help us regulate emotionsPractical examples on how to replace identity-based thoughts with useful process cuesHow to coach yourself through difficult MTB sectionsWhy the RIGHT technical cues still matterHow this technique can also help with overwhelm, procrastination and stressful situations away from the bikeBecause becoming a better mountain biker isn't "just" about learning what your body needs to do. It's also about learning how to "coach" your brain when it matters.Try the practical self-talk exercise from this episode on your next ride and notice what changes. And DO share it with me

What happens when the hardest part of stroke recovery isn't physical?In this episode of Stroke, Surviving the Odds, fellow Canadian stroke survivor Heidi shares her experience surviving not one, but two strokes—and the long road of recovery that continues today.After trying to return to work, Heidi was encouraged by her medical team to step away and focus fully on rehabilitation. But for Heidi, one of the biggest challenges of life after stroke has been mental health—an often overlooked part of stroke recovery that deserves to be talked about.We have an open conversation about stroke recovery, mental health after stroke, returning to work after stroke, emotional recovery, rehabilitation, and learning to navigate life as a stroke survivor.GUEST AFTER-STROKE GROUP: https://victoriastrokerecovery.org/CONTACT US:https://wwwlinktr.ee/klsurvivor101MEDICAL DISCLAIMER: Any content used in this episode, are those of the creator and guest. And should NEVER be replaced for professional physicians help.#StrokeRecovery #LifeAfterStroke #StrokeSurvivor #MentalHealthAfterStroke #StrokeRehabilitation #EmotionalRecovery #StrokeMentalHealth #ReturningToWorkAfterStroke #StrokeRecoveryJourney #StrokeSurvivingTheOddsmentalhealthafterstroke lifeafterstroke

Sports radio personality Joe Benigno joins Sid for his weekly appearance on the morning show to discuss where he thinks both the Giants and Jets stand heading into Week 3 NFL action this weekend, before he dives into New York Yankees' hopes heading into the MLB postseason and the American League Wild Card Series starting Tuesday of next week.Become a supporter of this podcast: https://www.spreaker.com/podcast/sid-friends-in-the-morning--7177409/support.

Earlier this month, world model company Runway introduced GWM Worlds 2, a research preview that “turns high-fidelity video and audio generation into real-time interactive simulation.” Runway calls this an “autoregressive diffusion” model; with autoregressive describing how it generates over time.One new feature in particular caught our eye: WorldPrompt, a proposed input format for specifying a generated world and the actions within it. It allows you to fix some aspects of a simulated environment — including the first frame — and then create a series of timestamped events. The events, or actions, can even be prompted in real-time.To understand the implications of WorldPrompt, we spoke to Kamil Sindi, Runway's CTO, and Robin Kahlow, its Principal Research Scientist for generative video and multimodal AI. We also have exclusive comments from Anastasis Germanidis, co-founder & co-CEO of Runway, courtesy of a podcast swyx and Vibhu did with him.Who's building real-time interactive world models?First, some context about world models that can generate interactive video and audio in real-time.Runway is reportedly valued at $5.3 billion, based on its most recent fund raise of $315 million in February. Its first release, GWM Worlds, was launched last December.Alongside Runway, there are several other notable projects in this domain: Google DeepMind's Genie 3 (which also generates at 720p and 24 fps), Odyssey-2 Pro, and World Labs' RTFM (Real-Time Frame Model). We've summarized their differences in the following table:Given the complexity and massive latency demands of real-time video and audio generation (which we'll get into below), all of the projects listed above have limitations. For instance, Google notes that Genie 3 “can currently support a few minutes of continuous interaction, rather than extended hours.”But as our interviews with Runway show, real progress is being made.The central idea of WorldPromptWorldPrompt, a new feature in GWM Worlds 2, helps differentiate Runway from its competition. You can think of it as a control layer for characters, cameras and the environment. As Kahlow put it, it's a way to “control all the different subjects in the world” — similar to a computer game.“Like, if there's an NPC [Non-Player Character] somewhere, the NPC might walk up to you and say something. So you could achieve the same thing with this kind of model, where you can have very detailed control over everything in the scene.”As the name suggests, WorldPrompt is a prompting mechanism — not a programming language. So, unlike virtual world games like Minecraft or Roblox, GWM Worlds 2 doesn't offer scripting capabilities or the ability to control state. But there's a power to that, as Sindi pointed out.“You can create promptable worlds on-demand with video and audio in sync, across all these different domains and environments. That's not a distant-future hypothetical thing,” he said.But there are also limitations to prompting a world model. We asked how reliably the model would follow an instruction to create, for example, a law of gravity or a certain ability in a character?“Yeah, so it's a research preview,” Kahlow replied. “So it's not perfect, of course, and there are still flaws. It really depends on how difficult the action is. I would say movement works quite reliably.”Sindi added that more training plus scaling the data and models is resulting in “better following.”How a video model becomes a real-time runtimeDespite the current limitations of GWM Worlds 2 — especially if you compare it to pre-designed and scriptable worlds like Minecraft or Roblox — the true promise of world models like Runway is that they'll eventually lead to fully self-generated, real-time games and experiences. Which is an extremely hard engineering problem, as Kahlow reminded us.“There are two challenges. One is making the model not generate a whole clip at once. So instead, you want it to generate frame by frame while you're looking at it. And the other challenge is actually making the generation fast, so you can play it in real time.”GWM Worlds 2 offers real-time interactive worlds streamed in continuous 720p video at 24 frames per second (fps) and audio at 48,000 Hz.Runway achieved this firstly by taking its foundational audio-video generation model and fine-tuning it to the new WorldPrompt format, so the model can follow that. It then post-trains the model to generate autoregressively.“And after that, we work on making it real-time through distillation methods,” Kahlow added.Co-CEO Anastasis Germanidis offered more technical details in our podcast with him. He told us that the process starts from “bidirectional diffusion that basically generates an entire video at once and [makes] it autoregressive.” This allows the model to “generate one frame or a few frames at a time.”Germanidis described two possible forms of distillation in order to make it real-time: distilling a larger model into a smaller one or reducing its diffusion steps. As a general example, he said a model might go from around 50 denoising steps to four, with some quality loss but potentially comparable results.The challenges of real-time generationGermanidis admitted that there were issues with how it generates real-time interactive video.“The biggest challenge with autoregressive models is error accumulation,” he said. “You're feeding generated frames back into the model to generate the next frames, and if there are any small errors, they accumulate over time.”Sindi told us there are also challenges dealing with “infinite generations” of content.“There's all these challenges around what context to keep, what to discard that's not important. And so there's all these optimizations we have to think about, so we're not blowing up our GPU memory.”Another current limitation is long-term memory. “The model does not have perfect memory,” Kahlow said. “That's still an open research problem.”Causality and correctnessWhile performance is the primary challenge for Runway at this time, its world model also has to produce plausible consequences when a user takes different actions.Germanidis used the example of simulating football; he pointed out that online video training data contains more successful goals than failed goal attempts, so a video model might render the first more convincingly.“If I take this action versus this action, you want it to generate equally realistic outcomes,” he told us. “That's, I think, the big gap between video models and world models: that idea of counterfactual generation.”Sindi told us that evaluation gets harder the more complex interactions get.“If you have this multi-prompt, multi-character, multi-scene [environment], how do you really understand what was causal and what was not?”To try and solve that, Runway has some automated verifiable tests. But since GWM Worlds 2 is a research preview, Kahlow noted that doing tests yourself is also advisable — “trying out your model to see what doesn't work is really important.”More than gaming — there are agent use cases tooGaming is the obvious use case for what Runway is building, but there are others. Kahlow mentioned robotics — for example using a simulated environment to test how a robot works.Another, more intriguing, use case is to use it to test agents at scale.“Having thousands of simulated environments is much less challenging if you have a suitable model like GWM Worlds,” Kahlow said.But how does an agent know what's changed in the world — is there a structured state that it can read, or is it just the generated video and audio that it's consuming and understanding?“So there's no structured state here,” Kahlow replied. “It's just observing the same thing you might observe in real life, just [in this case] from cameras.”Sindi noted that GWM Worlds can also be used for “synthetic data generation for agents.”Finally, Germanidis suggested there's potential to use these world models alongside reasoning models.“You're maybe using some reasoning [for] planning of the scene, and then you're passing it into the diffusion head that's actually generating the pixels.”Anastasis Germanidis* LinkedIn: https://www.linkedin.com/in/agermanidis/* X: https://x.com/agermanidisTimestamps00:00:00 Introduction00:05:17 Runway's Origins and the Bet on Generative Video00:12:23 The Stable Diffusion Story00:18:44 Gen-2, Controllability, and the Weekend Hack00:23:02 From Video Generation to World Models00:28:03 Learning From the World, Not Just Language00:35:04 Sora, Runway's Existential Crisis, and Gen-300:39:39 Why Real-Time Video Is Inevitable00:43:06 Interface World Models: Software Without Code00:50:25 The Fully Neural Operating System00:55:11 World Models for Robotics01:02:32 Robot Policies and World Action Models01:07:47 The Lucid Dream Test01:11:41 Video Agents and Omni Models01:23:12 Artists, AI, and Creative Workflows01:27:14 Physical AI and the Future of World ModelsTranscriptIntroduction: Runway, Creative AI, and the Early ThesisSwyx [00:00:00]: Okay, we're here with, Anastassios from Runway, with, me and Vibhu in the studio. Welcome.Anastasis [00:00:08]: Good to be here.Swyx [00:00:09]: Congrats on all your success and progress with Runway. You're opening offices all over the world. Did you envision this when you first started out?Anastasis [00:00:16]: Not quite. I think even when we started, we had this idea that, It was more a matter of when, not if, we were seeing the early generative models of 2016, 2017, and just extrapolating, assuming, we resolution, quality increases predictably over time. There's gonna be a point where most of content will be generated, and that was maybe the initial thesis of Runway was we will need, as a result of those generative models, rethink how creative tools are made. and as we built out the research behind, our generative models, it then became clear that they were useful far beyond that as well.Anastasis' Background: Art, Simulation, and Machine LearningSwyx [00:00:57]: And it is more obvious now with, like, the real-world stuff and the world models that we'll talk about later. I'm just kinda curious how you go from a background in, like, Zocdoc and, computer vision into Runway. Like, take us back to that early conversations with Chris and, whoever else is on your founding team.Anastasis [00:01:14]: I was always splitting through those two worlds. One was the I had my own art practice. I was making a lot of interactive art, I think for a long time. and then on the other side, I was working in startups, and I was working as a ML engineer, as a backend engineer at different companies. I've always been interested in, coding and computation, and especially interested in simulation and brought it back into my early artwork as well. And at the same time, I was interested inSwyx [00:01:43]: The personal site has a few, right?Anastasis [00:01:44]: Yeah.Swyx [00:01:45]: Is there one that we should pull up? Just in case there's something that's like. I just like to go down memory lane.Anastasis [00:01:50]: Yeah.Swyx [00:01:50]: Okay, what is this?Anastasis [00:01:51]: So this was, a project that I made, I think back in 2015, where I built this software that would give, voice instructions to people in a gallery space. So it would coordinate interactions between people. And so it will first give you an identity, like you're an, architect, you're 30 years old, and, you like sports. and then it would match you with another person, and you have this completely generated interaction. language models were not quite there at the time, and so it was it was a mix of some templates and some, like, some Markov chain-generated text, and it would just completely simulate these small talk conversations between, everyone in the gallery space. so was always very fascinated on the one hand with, generative models and, like, the early machine learning work that was being at that time. But at the same time, there was this separate thread of simulation and what it means. Like, what can we learn about humans by creating those very simple models of their interactions and their behavior?Early Generative Art: pix2pix, GANs, and Uncanny ValleyVibhu [00:02:56]: Did you generate the prompts or, the 30-year-old, whatever? Was it you generating them? How'd you, how'd youAnastasis [00:03:03]: Exactly. So the program would just generate- those, from. Yeah, a lot of it would be Mad Libs style of justVibhu [00:03:10]: YesAnastasis [00:03:10]: You have lists of different professions, lists of different,Vibhu [00:03:14]: HobbiesAnastasis [00:03:15]: Personality types, lists of different, ages, things like that. And then it would just combine those things together. And then maybe the next project we go is, Uncanny Valley, Uncanny Road, which wasSwyx [00:03:27]: GansAnastasis [00:03:27]: One of the first projects that, we built with, one of my two co-founders, Chris. This was taking, pix2pixHD, which was one of the early image-to-image models that NVIDIA released back in 2016 or 2017. and it was a model that would take a semantic map of a scene and then generate a photorealistic, let's call it, output. very early days, so it was not very high-fidelity outputs, but it w I think was the first image-generation model that could generate at 1K resolution. And it was all trained on self-driving datasets. So the semantic categories it would support were only, things you would encounter on the road. So it would be pedestrians, traffic signs,Vibhu [00:04:16]: StoplightsAnastasis [00:04:17]: Bikes, stoplights. And so that was one of our first indications that we built this and people were making all this, like, very surreal imagery of, yeah, a million plus a million pedestrians or a million traffic signs or, like, gigantic humans. And it was a indication that you could take a model that was trained on this very boring dataset, essentially, of, like, not that many interesting things happen when you're on the road, and then you can repurpose it and go very out of distribution and make something that was artistically compelling. And that was It's a summary of the thesis of Runway in some ways, that you can take the same generative models, and if you look at them from another direction, if you build interesting tools around them and you give them to artists, they're gonna do things that you don't expect.Vibhu [00:05:02]: Very cool. I like the, UX of it. You're just given an empty canvas, try whatever, do whatever. And then the other one, like, you see everyone with wired headphones? Like, that's, that's a sign that it's, it's veryAnastasis [00:05:16]: The AppleVibhu [00:05:17]: YeahAnastasis [00:05:17]: Apple, your version.Vibhu [00:05:17]: Original ads. Yeah. Take us to today. You've been doing this for seven years at Runway. How have we got to this? Like, how do we go from driving simulator data to all this? And you cover the whole stack of generative media?From Creative Tools to a Research LabAnastasis [00:05:33]: Interestingly, we're almost back in, we're, we're full circle. We're, we're now applying our models and beyond creative tools into real-world scenarios. But it was a, it was a long journey. It was very early on we realized the first version of Runway was a way to easily use the, all the open source model of the day, things like pix2pix to. and give them to artists. That was the initial idea, is those models are too difficult to use if you're not a machine learning engineer. Like, what happens when you give them to artists? Very quickly, we realized we needed to build a research org, inside of Runway, and that happened maybe on year one. And, a lot of the mandate there was. The image-generation models of the time, the video generation models of the time, or there were barely any video generations all the time, but they were not quite there where they could be productionized and brought into tools that would be part of creative workflows. so we need to push the frontier of the research. And so maybe the first four years of Runway, research was almost happening on the background until there was a moment in 2022, with latent diffusion, with, DALL-E 2, where, there was that step function change, and you guys maybe remember around the time.Swyx [00:06:49]: I started in this space because of latent diffusion and Stable Diffusion.Anastasis [00:06:54]: Yeah.Swyx [00:06:54]: Because I was like, “Wow, this is not only, like, feasible, it is doable on consumer hardware.”Anastasis [00:07:01]: Exactly, yeah.Vibhu [00:07:01]: I think the delta is also huge. Like, I learned pix2pix. Like, this was intro to ML, the TensorFlow, like, Jupyter, Google Colab notebooks were like this, and then you have a sudden step function change, with diffusion and whatnot. Any other ones since that. Like, there were clear examples of what early diffusion were to get to here. Any other changes in key technology research?Green Screen, Rotoscoping, and Early RunwayAnastasis [00:07:26]: Between, 2018 when we started and 2022?Vibhu [00:07:29]: Yeah.Anastasis [00:07:29]: So one of the early work that we did in Runway was solving segmentation, image and video segmentation. It was a very important problem because most VFX involves essentially separatingSwyx [00:07:42]: RotoscopeAnastasis [00:07:42]: Subjects. Yeah, rotoscoping. Extremely manual process. Nobody enjoys doing that. and so a lot of the early days of Runway was building this tool. It was called Green Screen, and it was for a long time the main thing that people were using Runway for. It ended up being used in, Everything Everywhere All at Once and a bunch of other high-visibility films and series. But that was essentially, Runway for a long time was a post-production tool until latent diffusion and generat- Gen-1, Gen-2, happened.Swyx [00:08:12]: Cool. let's, let's go past that moment. You've come a long way. Then you started releasing your own models. Maybe describe that journey as well.Scaling Video Models and the Bet on 1,000 A100sAnastasis [00:08:20]: Yeah, so we go to the other point, yeah, in mid-2022 when it became clear that we're doing research at a fairly small scale of compute, and it became clear that, like, scaling laws would apply to, image and video gen in the same way that we're applying to language generation. So we made a big bet, and I think at so at the time, we signed this deal to build a cluster of a thousand A100s, which at the time we were a Series B startup. That was a almost, slightly irrational decision maybe, but we really believed that if we trained a video model at a large scale, we would get, like, a great model at the end. And at the time, the goal or we set the goal around fall of 2022 of what is, what does the latent diffusion, Stable Diffusion moment look like for video? And at the time, the best model of the time was called CogVideo. it was one of the early video models. It was very 256 by 256 resolution, very not very high quality. and so we decided we're gonna build out this cluster, and we're gonna just invest in, like, in building out our own video model. it became clear as we're training Gen-1 that it was difficult to get to fully. we wanted to build text-to-video, but it became clear to us that an easier starting point would be to start from video to video. Because when you have a stronger conditioning, it's, it's an easier problem to restylize an existing video versus generate the video from scratch. And so we released Gen-1 first back in, it was January of, 2023. Yeah.Vibhu [00:10:04]: It's just a fun visual podcast, honestly. Like, if we can see February 2023, what was the state of stuff?Gen-1: Video-to-Video and Depth ConditioningAnastasis [00:10:10]: It's so interesting ‘cause at the time when you see those results, you think this is so incredible, and this is like, it's almost like image generation or video generation is solved. And then you look back a few years after, and it's like, it's It's just like you get used to the results very quickly, with those models. But at the time when we started seeing those results, it was, it felt quite incredible, and the level of, like, quality that you could get. And, so the Gen-1 was a depth-conditioned video model, so it would turn. it would take a input video, it would predict. it would it would first convert it into the depth map, and then we would generate, pixels with a latent diffusion model.Swyx [00:11:01]: Yeah, very effective.Vibhu [00:11:02]: Yeah. I didn't realize how distracting the blog post would be. Sorry.Anastasis [00:11:05]: Yeah, but, one of my favorite examples of on those, on Gen-1 was both, if you go up to mode three or mode two, there was this storyboard use case where people would makeVibhu [00:11:18]: OohAnastasis [00:11:18]: WouldVibhu [00:11:20]: You can mess around with theAnastasis [00:11:20]: Make a city out of books or out of boxes, and then they would shoot a video with their phone and then translate it into a photo-photorealistic output. There was all these ways in which those models were starting to be used for storyboarding and also for really. and then if you go to mode four, like, of taking untextured 3D scenes and then turning them into photorealistic output. So we saw a lot of use cases early on where people that were familiar, were power VFX editors would just take a blender, render, and then they would get translated in with Gen-1 or create a scene in Unity and then take a capture a video of it and then translate into, restylize it. So I still think video to video is powerful. I think we had a recent video-to-video model as well, and it's one of my favorite ways of using those models is essentially using them to use ground truth video as, like, the initial inspiration and then translate into different styles or different outputs.Stable Diffusion, Stability AI, and Open SourceSwyx [00:12:23]: But I think we're gonna go into, like, the rest of Runway and catch people up to speed today. I did wanna cover the, let's call it the Stable Diffusion controversy, or, what happened with Stability AI, whatever. I think there was a two sides of the story. I think there's part of that is a normal thing of, like, people, join and leave companies, but what is the, retrospective now that, there's been some years behind it?Anastasis [00:12:49]: Yeah, it's a very, it's a very long story to go into. I think it wouldSwyx [00:12:53]: Which I remember you wrote a really long post about.Anastasis [00:12:56]: We would probably cover the whole hour to go into it in more detail. But, essentially, there was the latent diffusion paper that came in, I think that was at the end of, 2021. And then Patrick Esser, who was one of the researchers behind, latent diffusion, and he worked at Runway at the time, he built latent diffusion in collaboration with Robin Rumbach and a few other folks back, in the in, CompVis, which was, a labSwyx [00:13:26]: Like a research group, yeah.Anastasis [00:13:27]: And, after releasing the early latent diffusion model, they, essentially they were. the goal was to keep working on versions of the model, scale it up, incorporate new data, incorporate new tasks. And Stable Diffusion was the same model, but trained on more compute, and then with a few more tricks, like a classifier-free guidance paper came at some point, I think in the early 2022. And thatSwyx [00:13:52]: Which, like, was a big prompting improvement.Anastasis [00:13:55]: Yeah.Swyx [00:13:55]:?Anastasis [00:13:56]: That improved results. it was trained on better data, so like, the esthetic subset of LAION, but it was effectively, the same underlying architecture. And there was that big training run, that, happened on Stability's cluster. Stability financed that run. And looking back at that story, I think it was the work to build and train that model was done. It was a, it was a research project. It was done as part of, like, continuation of the latent diffusion work. It then, I think it the model became very successful, and it, I think there were the. And I think as a result of its success, other companies tried to, figure out the commercialization path for it. But for us, it was very important that we try to, we make sure that we. It was meant to be an open source research project, and so the we decided that we should continue releasing versions of it, since that was the original goal of Stable Diffusion, and that led to releasing Stable Diffusion 1.5. There was maybe a day of, a bit of, miscommunication there, but ultimately that was resolved very quickly within hours. so yeah, there wasSwyx [00:15:12]: OkayAnastasis [00:15:12]: Not a niceSwyx [00:15:13]: I just wanted to. you have toAnastasis [00:15:15]: Yeah.Swyx [00:15:15]: You're one of the main players in that journey, and so it's nice to hear from the source of, like, what happened. Yeah.Anastasis [00:15:22]: Yeah. I think it's all, it's all in the past nowSwyx [00:15:26]: YeahAnastasis [00:15:26]: I would say. and, like, both companies, Stability took its own path, Runway took its own path.Swyx [00:15:32]: Yeah. There's still. James Cameron is backing the new Stability, whatever they're doing with the Hollywood studios.Anastasis [00:15:38]: Right.Swyx [00:15:38]: I don't know what they are doing. I think one thing that impresses me, and I'm happy to move on, is that back in the that time, let's say, like 2021, 2022, there was this community of people that you were involved in that was researching all this stuff, right? And, like, from everyone I talked to who was active then, it seemed like it was fairly obvious that somebody would do the hero training run that would produce Stable Diffusion. So, like, I guess the question is, like, you had the you were you had made investments. You were you had the foresight. Is it accurate to say, like, that is reflective of, like, what people were thinking at the time? Or was it still very much like, “Well, we'll use it as, like, a post-production tool or something. I don't know.”? Like, where in the sentiment were we that maybe you can think back to, like, what the community was like back then?The Early Creative AI CommunityAnastasis [00:16:28]: I reminisce and I think very fondly those early years, from like 2018 to 2022, because it was a very small community that, as you said, were very convinced that this was gonna be a big thing. And at the time, anyone who. Because it was such a small circle and, everyone who would, like, be part of that circle and, like, make projects with it would, immediately get, go viral. so likeSwyx [00:16:55]: And you didn't know who they are, right? They're just some name on a, GitHub or Hugging Face somewhere.Anastasis [00:16:59]: Exactly, yeah. So I remember one of the first big viral moments of creative AI was, there was the neural style transfer paperSwyx [00:17:09]: HuhAnastasis [00:17:09]: ThatSwyx [00:17:10]: Something dreaming?Anastasis [00:17:11]: I think it was called neural style transfer.Swyx [00:17:14]: Okay.Anastasis [00:17:14]: There was also Deep Dream, the puppy sliceSwyx [00:17:16]: YesAnastasis [00:17:16]: Which was, also really cool. but, yeah, there was this project that, Jim Kogan, who was an early advisor of Runway and one of those,Swyx [00:17:25]: Marketing guysAnastasis [00:17:26]: Big, creative AI, folks, he literally just, like, showed a video of himself taking the New York Subway and going over the Williamsburg Bridge and then stylized it with, I think in the style of Van Gogh or, like, one, painter. And that was. Like, at the time, that was, like, so cool and it went viral and it was completely revelation to people that you could do this with generative models. And that was only, it was less than. It was maybe 10 years ago. So just, like, as an indication of, like, how quickly things have gone.Vibhu [00:18:02]: It's pretty crazy. Like, even since then, you've got people at every level of the stack. You've got devs, creatives, artists, hobbyists. You've got everyone using it. And for people that tried stuff early, they'll remember how hard it was to use regular diffusion, right? Like, nowadays, you can use your favorite ChatGPT image gen or whatever, give a sentence, get a beautiful output. But diffusion was like, the whole ultra HD, 4K, high resolution. Like, prompting these things was very different. anything you learned on the tooling side, like from the offerings you guys have now, so like creatives, devs, you really took the. Research and brought it to everyone to use. anything interesting there to share?From Gen-2 to Controllable Video GenerationAnastasis [00:18:44]: We had to build the entire model serving infrastructure for video diffusion models. There was nothing else, already, like, because we had Gen-2 was the first text-to-video model, I think, out in the market. So many things that we learn over time. I think the I think the biggest one was, like, we. it was very clear early on that text-to-video was not gonna be the answer. Like, you. Like, people wanted a lot more control than that, and so we invested in, like, control building on top of those models very quickly. how do you use the camera trajectory as control? How do you use an initial input frame as control? So that was a very early learning for us. With text-to-video was, like Gen-2 was an amazing, step function improvement in the quality of video models, but it was used much more in an exploratory way because there was nothing to ground it to. There was no reference that you could bring into it. There was no. You couldn't really control the camera motion. You couldn't control the object motion. And so the first year, in 2023, was really all about what are all the interesting ways in which we can condition those models? And it was a lot of just post-training rounds on top of the base model to figure out, like, what, -- how do people wanna control them? And so there was, like, this quick succession of the we it was called Motion Brush, which was you could, like, you could draw arrows and dictate where things should move in the scene.Vibhu [00:20:09]: That's so cool.Anastasis [00:20:09]: There was camera control that was you could just describe, like, how you want the camera to move in the scene. And because we work with filmmakers from the most of the history of Runway, we immediately got this feedback and got this, decided that this was worth investing in. And so control ability became a big theme, I think, very early on as we were building, as we were building those models. Something fun that I haven't really talked about too much was just how Gen-2 came to be out of Gen-1. So it was a bit strange because we announced Gen-2 two months after Gen-1 andHow Gen-2 Came From a Weekend HackVibhu [00:20:43]: We're accelerating.Anastasis [00:20:44]: It was before Gen-1 was even generally available. But Gen-1 was a depth-to-video model, so it would take a depth map and it would convert it into RGB. and we couldn't get, text or image-to-video to work directly, and that's why we started from depth to video. but, and we had discussions of like, okay, we need to spend the next six months investing in text-to-video, maybe increasing the compute scale or the model scale, like train a larger model. And I had this weekend project idea, which was, what if I take a model that, starts from text input and converts to depth maps and then use Gen-1 to convert the depth maps Into RGB?Vibhu [00:21:29]: It would probably work.Anastasis [00:21:30]: And so Gen-2 was that.Vibhu [00:21:32]: Oh. The hackathon pipeline.Swyx [00:21:35]: The weekend hackathon pipeline.Anastasis [00:21:36]: Yeah.Vibhu [00:21:37]: But it looks good.Anastasis [00:21:38]: And it worked pretty well. there were if you, with the knowledge that it has this, like, two-stage pipeline, you can tell in some cases that the structure of the video looks a bit off because you had to generate the depth first before you go into the output video. But it worked and it allowed us to bring this to our, to users very quickly. But it's now it's interesting because, like, people are coming back to this almost two-stage approach. Like, if you look at the Reve text-to-image model that came a few months ago, it had this planner model that would generate bounding boxes before it fed that into the diffusion transformer.Swyx [00:22:19]: Yeah, Ideogram also the same day.Anastasis [00:22:22]: Yeah.Swyx [00:22:22]: I remember that was very strange that both of them came out the same day with the same exact innovation.Anastasis [00:22:26]: It's a small community, I think.Swyx [00:22:28]: I'm like, this is like, this is completely coincidental, right?Anastasis [00:22:32]: People talk. So yeah, there's, there's definitely something into this approach. And, now, like every single like, video generation model in production uses a complex prompt completion pipeline under the hood. I think that's no secret that there is. ThatSwyx [00:22:48]: Humans are terrible at prompting.Prompt Rewriting, Camera Control, and the Seed of World ModelsVibhu [00:22:51]: I think across the board.Anastasis [00:22:51]: Yes.Vibhu [00:22:52]: But yeah, I think like the original Sora one blog post even told you that what happens after your input is rewriting your prompt. It's much more descriptive about what you would want.Anastasis [00:23:02]: Exactly. I, And there was the DALL-E 3 paper beforehand that, was the first public, description of the fact that synthetic captions and really detailed captions work really well. And then Sora built on that. Yeah, so it was 2023. We were releasing all these updates to Gen-2, like the camera control, Motion Brush. And there was something very interesting about camera control because it was the first time that you felt that instead of, like, you were creating video, you were creating a short video, you were navigating inside the world. And I think camera control was maybe the seed of some of the ideas that we had around world models and really opening up that research direction. We realized, it was this era and this series of, Gen-1 and Gen-2 models really proved to ourselves, yeah, this is theSwyx [00:23:56]: Cool.Anastasis [00:23:57]: So this is not the original camera control. This was the updated camera control on top of Gen-3. But yeah, I think it made those models usable to filmmakers, I would say. The so camera control was very popular. And so we realized, there is one way of seeing those models, which is, you're just as content creation machines, and there is the other way, which is you're. As you're predicting video in order to predict video well, you need to simulate the world in an increasing and increasing capacity. And if scaling laws apply on video, just like they apply on language models, then as we scale the compute that we put into those models, then they're gonna be able to simulate physics, they're gonna be able to simulate human actions and dynamics increasingly well and predictably well. That was the thesis about around our efforts on world models, and we spin up this research group to just focus on the world models and how do we turn the video generation models that we're building into something broader and something that would be useful beyond, also content creation as well.Swyx [00:25:04]: And that was roughly when?Anastasis [00:25:06]: Yeah, so that was inSwyx [00:25:06]: OhAnastasis [00:25:07]: In late 2023.Vibhu [00:25:08]: Interesting. like, I think, a lot of people have been saying a lot of video gen model companies have all pivoted to world models these days, but like, 2023, you're posting it. oneWorld Models: From Video Generation to SimulationSwyx [00:25:21]: It's, it's debatable whether it's a pivot.Vibhu [00:25:23]: Yeah.Swyx [00:25:23]: Like, arguablyVibhu [00:25:24]: YeahSwyx [00:25:24]: That's what you always had to do anyway, right?Anastasis [00:25:26]: It's in a way an expansionVibhu [00:25:28]: YeahAnastasis [00:25:28]: Of the applicationsVibhu [00:25:29]: YeahAnastasis [00:25:29]: Of the models as they become more capable.Vibhu [00:25:31]: The early signs, it seems like the original models you guy had, guys had, people would say it's very not bitter lesson pilled, right? You're adding, rewriting prompts, you're having all these one-off things, but that's just the state of the tech as it was versus the future of as you said, you can scale it up as, we can scale up to world models.Anastasis [00:25:50]: Yeah. So it just became. And if you looked at the outputs of Gen-2Vibhu [00:25:56]: YeahAnastasis [00:25:56]: It was not. I think it was not obvious to people that this would scale to become a general simulator of the world. Like, you had very limited movement, you had, very low fidelity or low resolution, like obvious mistakes in human anatomy, like all kinds of limitations. But it was just, the idea was that's just GPT-two, and GPT-two, it can barely generate, like, coherent sentences. Similar, Gen-2 can barely create coherent video, but if you scale it up, you're gonna. There is no reason why it shouldn't work in a way. It's, And I think that was. That's, that's always the mindset of Runway is like this extrapolation of, like, if, like, even when we started in 2018 and you looked at the results of the day, you need to look more at the trend of, like, where we were in 2018 versus when we were at the, when the first GAN came out in twenty, four 2014 or twenty, fifteen. And, you started from, like, thirty-two by thirty-two images of faces, and then by the time in 2018, you could generate, street images at the 1K resolution. And it was the same with world models, very early signs of something much bigger.Swyx [00:27:08]: Yeah. I was gonna say, like, it's diffusing into focus. Like, if you look at our visible output from year to year, it looks like a diffusion process itself.Anastasis [00:27:17]: Yeah.Vibhu [00:27:17]: Especially watching the early, like, old blog posts, you can really see the choppiness, the details.Anastasis [00:27:24]: Yeah. Like human civilization starting from random noise and thenVibhu [00:27:27]: YeahAnastasis [00:27:27]: Denoising intoSwyx [00:27:28]: Yeah. Just run it a hundred years.Anastasis [00:27:30]: Civilization.Swyx [00:27:30]: Yeah.Vibhu [00:27:31]: That's how you're on track, you're still noising, right?Swyx [00:27:34]: Yeah. I like the way that you guys phrased it when you, announced it in June, which is, oh, that you had a video essay. “The human mind is no longer the center of AI. Our world is.” Right? Which is, let's, let's call it the past five years of LLM-based AI is very much like trying to emulate human preferences and human speech. But now that's, like, mostly solved. I think that's, like, some of the context of your essay, which you also wrote around the time. And now it's like the focus is on modeling the world accurately.Scaling Laws for Video and Why Predicting Pixels MattersAnastasis [00:28:03]: Exactly, yeah. So the way we see it is, there is that, initial mission statement of DeepMind, which is, solve intelligence and then use it to solve everything else. But I think it's starting from everything else, could be valuable of, like, starting from. there is just so much complexity, and detail in the world that in order to. That it's, it's hard to learn directly from just human descriptions of the world. Like, we're assuming that, like, language models learn from everything that humans have written about the world, like our own understanding as of, the twenty twenties. And there is just so much that we don't know and so much that's not captured by existing text, about both the low level dynamics of the world, like we're not describing in detail. if I tell you to describe, like, how do you tie your shoes, that's a very difficult thing to describe in words, but it's very obvious thing to demonstrate. And so I think there's been. And there's, more of X paradox, like we're constantly underestimating all the complexity that goes into very, like, things that we do subconsciously as humans, and we don't even necessarily always have the words to describe them. And so in my mind, the simulating the world and simulating, physics, simulating the dynamics of the world has always been underestimated, compared to, we place too much emphasis on the things that are easy to talk about. but there is just all this complexity and richness of the world that if we just try and train directly on that observational data instead of training on how people describe the world, we would learn something new that we wouldn't otherwise know.Swyx [00:29:54]: You think that the present architectural paradigm is fine? You don't need, like, another layer, like JEPA, like another famous, New York AI leader would say?Anastasis [00:30:05]: We're a very pragmatic research lab. If, we have evidence that an approach works better than the approach that we're taking, then we have no qualms to taking it. We just have seen no indication that video prediction itself doesn't scale. And even if you look now, not just our work, but the work of others, you're seeing in robotics some of the most promising work, starts from video prediction models, and then you adapt them to also the action models, for example. so there is very little evidence that you need something else and that your time is better spent on a novel architectural change compared to improving data and improving the, and scaling the current approach. And so, We don't have any indication that. the, there is that counterargument that I think there was a tweet by Yann LeCun a few days ago that, understanding the dynamics of the world is very different than, generating, cute videos.Swyx [00:31:05]: And your answer is no, they're the same thing.Anastasis [00:31:07]: Yeah, they're the same thing.Swyx [00:31:08]: My cat videos are the same as understanding physics.Anastasis [00:31:11]: Right, because if you wanna generate. video models can cheat and, like, they could you could give, like, successive dif shots of the scene in a way that doesn't require you to simulate difficult physics. There is like, all these different ways in which you can hide the deficiencies of the model, and it's important not to be too tricked by the performance of the current video models. It's easy to, cherry-pick examples and think that video models are further advanced than they are. So there is a lot more work that we need to do to improve those models. But in my mind, very similar to language, and, like, we've. you go from barely coherent sentences to something that, could hold a conversation with a human to something that could can operate autonomously for a day and, like, create entire code bases. And the main difference, there is some architecture improvements along the way, but the main thing is scale. And so it's the same bet for video, and we have no indications that this is saturating. Like, we have benchmarks that we use for measuring the physics of those models, and we see those predictably improve as we scale those models. So there is. If you want to Google up, Physics-IQ, is one of those benchmarks that measures how well does the model perform at solid mechanics or fluid dynamics or optics.Vibhu [00:32:32]: I'm curious if you've seen any emergence, any scaling law around this.Swyx [00:32:37]: Yeah, he's saying there is a scaling law, right?Anastasis [00:32:39]: Exactly.Vibhu [00:32:40]: Yeah,Anastasis [00:32:40]: So the way those models, those benchmarks work is you. the researchers have gone and, like, captured, a few videos that are representative of different physical phenomena, and then you can take the first frame and then pass it through an image-to-video model and then generate a rollout that shows what should happen next. So you have, a ball hanging from the ceiling, and then you use that as input, and then you the model predicts how the ball should fall on the ground. and this measures. we have an intuitive understanding of physics. I know, you can imagine what will happen next if I drop this bottle. So it's measuring that same intuitive physics understanding of those models, and we've measured that at different model scales, and we see, and compute scales, and we see that the score on physics IQ predictably improves. There's other, tricks and techniques that you can make to improve the score even further, but even scale alone helps, in the model learning better physics.Swyx [00:33:40]: My main sympathy with Yann LeCun is the, Plato's cave allegory, right? Like, you're, you're, like, learning on the output of a thing, not the internal process of a thing, and it's very noisy. And, if only you could observe the internals of a thing. It's hard to observe the internals of a human mind, but you can very much observe, or at least we have a whole branch of science and physics that we're ignoring on how to model Physics and movement and, gravity and, other interactions. and we're just, like, throwing away all of that and just saying just scale data, which is very much the lesson of unsupervised learning, but it feels wrong. that's the main idea.Anastasis [00:34:21]: I think the history of machine learning is, at large, it feels wrong.Swyx [00:34:25]: Yeah. It's a bitter lesson, right? Yeah. It's, it's, it's the simple answer to that.Vibhu [00:34:29]: I guess, how much can you scale? So, like, even on, let's say, the video generation side, like, there's one side of video understanding. Video generation, are we still gonna have tools where it's like, I wanna generate two hours, twenty hours? there's a infra way to do it in batches and stitch it together, but, like, do we just keep scaling? Do we just continue long generation consistency, all that at scale? And, like, tying it into where we're at now from we looked at Runway two to four point fiveGen-3, Sora, and Runway's Scaling InflectionAnastasis [00:34:58]: Yeah.Vibhu [00:34:58]: Like, technically, what advancements have we made to today, and then where do you see things still going?Anastasis [00:35:04]: So part of the answer is definitely scale. and that was. We learned that lesson in a big way for with Gen-3. So Gen-3 was the model we released the year after, like in 2024. That was a few months after Sora was released. so yeah, there's an interesting story of that came to be as well. Gen-3 for us was, the first time that we really needed to build. we had to learn all the lessons that the language model world learned in two in three years in the span of a few months. one of the biggest changes of Sora was using diffusion transformers instead of convnets. So a lot of the early, latent diffusion models were all, convnets for the diffusion model part. And the diffusion transformer paper came at some point in 2023, and it showed scaling laws for image, diffusion transformers. And we realized at that point that we needed to invest in infrastructure for model parallelism, for really scaling training to larger than, a few billion parameter models. And we spent maybe the, most of the fall of 2023 building out our infrastructure for distributed training. And we had a lot of false starts and a lot of failure in trying to scale, image and video diffusion transformers. And at that point, February 2024, Sora comes out, and the results areAnastasis [00:36:35]: Very much superior to what Gen-2 could produce. There were a lot of, a lot of chatter on Twitter about Runway. Runway's done. like, there is no way Runway will catch up. And if you remember, also OpenAI in the early twenty-It felt very, like it's aSwyx [00:36:56]: To the moonAnastasis [00:36:57]: It's a formidable opponent now, but at that point, it, they were on the top of their game. nobody could even get close to them. There was maybe Gemini was just the first version of Gemini had just released. So when OpenAI came with Sora and it was such a big jump of like quality, it gave me, there was like an existential crisis for a few hours. But that, I think the amazing thing about Runway and like I think the, we've been around eight years now, which is almost we're dinosaur in AI, and we had to like, we had there was a lot of those moments we had to learn, adapt very quickly and build out skill set in the team that we didn't have. And so, if you ask anyone what is their favorite time at Runway that was there during that time, it was that push in like three months to get to a model better than Sora. and it, we scaled 10x the model scale, the model size and the, compute that we were training on. we figured out model parallelism. We had zero expertise in that. And then we came out with Gen-3 during that summer. So that was a big turning point, I think, for the company where the research org grew very quickly, and we really started pursuing this vision of the general world model, in earnest, I think after Gen-3 was out.Swyx [00:38:12]: Yeah. that's the amazing thing about building when you're building. There's no stack to. You have to invent everything yourself. You have to be completely full stack. Now I think like there are inference specialists like Fal or whatever that can help with like, model serving, and I think you guys work with them as well. but yeah, like it's, it. But at the time, it was just. It's very interesting to think about what you do when Sora comes out and people are questioning whether your company should still exist.Distillation, Turbo Models, and Real-Time VideoAnastasis [00:38:41]: Yeah. And yeah, there was no, there was no VLM of diffusion models. Like, we had to build the whole model serving infrastructure and make things efficient. And a few months after we released Gen-3, we released the Turbo version, which I think was the first step-distilled model in production.Swyx [00:38:56]: That was a whole trend that we covered as well. Yeah.Anastasis [00:38:59]: So that allowed us, to serve those models at the larger scale, ‘cause I think the first version of Gen-3 was quite, expensive to serve.Swyx [00:39:09]: I think the whole like trend in like consistency models, Lightning and, Turbo and all these things somehow didn't really stick around. I don't know if you have any reflections on this. Because at the time, I was like, “Well, everything should start with a distilled model first, and then you can upscale,” right? It. your bigger models just turn into fancy upscalers, but like you should always draft with a smaller model and faster model, right? Because you can get it so quickly, like near real-time.Anastasis [00:39:39]: Yeah. I would not be so sure to say that didn't stick around. I think that, it's, it's likely to. that there is a lot of step-distilled models that are actively used in production. there is still a gap in quality compared to the, non-distilled model. but in my mind, we're still. there is a two to three year offset from language models. So the things that, So it's just a matter of time before there is better distillation techniques. we use. Right now we have a real-time model core character that I think is the largest deployment of real-time video models, that's a step-distilled model, and it's actively being used. It's a very specific use case compared to a general video model. So this is aSwyx [00:40:27]: Very cool, by the way.Anastasis [00:40:27]: This is avatars stuff, right?Swyx [00:40:28]: Consistency, character.Anastasis [00:40:30]: Yeah. So this is a talking avatar, model. we were able to. we optimized the hell out of it, and it generates at 24 FPS, and it's a, it's a step-distilled autoregressive video model. So if we look at our world model direction, a big component of it is starting from the bidirectional diffusion that generates entire video at once and making autoregressive shows. So you generate one frame or a few frames at a time. so there's a lot that goes into that pipeline of getting to a real-time model. It's first you need to make it into a causal autoregressive model, and then you just turn it into. You need to do some additional step distillation to get it to be real-time. and I think that part is just starting. I'll be very surprised if we're, two years from now, we don't primarily use real-time models. To me, real-time video generation is just inevitable that, it has much better user experience, it's much cheaper to serve, and, the quality gap between the base model and the real-time model is only gonna close as we figure out better, distillation techniques. And we made a lot of progress there internally on maintaining the quality of the base model when we distill them.Swyx [00:41:49]: How much of this is transferable? So is it the same base model? Like if you're doing diffusion across the whole sequence and you're converting it to step autoregressive distillation, is this like distillation where you still need to train both, you can use the same base and converter? What's that process like to go from regular model to something that's real-time on a technical level?Anastasis [00:42:11]: So the nice thing about diffusion models is you have, two axes of distillation. So there is the. You can distill to a smaller model, which resembles what you do in LLMs, or you can distill in terms of taking less steps, less diffusion steps. So you could take a model that generates in fifty steps and generate in four steps and get to, You have some performance, degradation, but very often you get comparable outputs. So you can even take the large frontier model and distill it with step distillation and get to a real-time performance, and that's what we've seen. So, depending on the use case, in some cases we might also serve with a smaller model, but in a lot of use cases, we just use theSwyx [00:42:56]: Step distillationAnastasis [00:42:56]: The frontier model, and we're able to make it work in real-time.Swyx [00:42:59]: I think this might be a good time to cut over to his laptop to show off some of the real-time stuff that you're doing.Interface World Models and Neural SoftwareAnastasis [00:43:06]: This is one of the research updates that we did recently. so we've been working and f in getting our general world models to, different applications. one of them that we think is very compelling is using general world models as essentially, an interface, a universal interface to software. This is a version of our world model that's called an interface world model. and the idea is that it essentially, replaces, the, front end of a software application. It renders the pixels directly of an interface and is trained to predict what happens next as a result of, a click or another interaction you have with the interface. So this is all pixels. it's there is no HTML, CSS, React that's powering this interface. This is directly at the output of our real-time, video generation model, and it takes clicks directly as input.Swyx [00:44:09]: And drags, click and drag.Anastasis [00:44:12]: Right. So it supportsSwyx [00:44:13]: Ooh.Anastasis [00:44:14]: Yeah, clicks. It supports drags. it also supports scrolling. and the amazing thing about this is that you can effectively describe in the prompt how you want different elements, like what do you want the behavior of different elements to be. So it's almost you're you can turn, an interface from, markup language description of, like, an HTML interface, and instead you can just describe the interface. if I press this button, I expect this to happen. If I press this button, this should happen. And it's useful, we believe, both for prototyping, for, like, just testing, like, what different interactions would feel like. you can also add audio to it. So it's a video audio generation model. So you get you essentially can describe both what the visual outcome should be of your click and also what the if there is a sound effect that comes out of it. So we believe that's gonna be a much more flexible way of building software. Just render. It just, in why generate the code that generates the pixels? Just generate the pixels directly.Anastasis [00:45:18]: It's the end-to-end philosophy applying applied to front ends.Anastasis [00:45:25]: So we think there is a few interesting use case. So you can build creative tools on top of it.Anastasis [00:45:32]: We think that, for any use case that involves a lot of exploration or, like, educational use case where you wanna learn about a new concept and you want some visualization and like, and open-ended exploration, we think those this is a very powerful, approach. you can imagine new forms of, design, industrial design software that could emerge as a result of those models. And this is all, generated in real-time as well. So, you can build a lot of interesting camera transitions and forms of interaction that are very difficult to build otherwise. And one way in which we evaluate this is what if you try to generate the same interface with Claude by just, prompting Claude, “Here's an image reference of my interface that I made in Figma or that I created somewhere else. create this particular interaction,” which in this case it's, drag that object, upwards. and beyond it being slower, it's also very difficult to capture some interactions by just fully, with just LLMs. So we think that this is likely to be the way that a lot of the future, like, software in the future will be created. and one of the additional benefits is personalization might be a lot easier done with those models. Like, you can essentially try out different prompts based on who is visiting the interface. You can, more easily, prompt engineer the interface to have larger size, text for more accessibility reasons, or you can make this or, like, if you have a particular aesthetic preferences. So we're very excited about this approach. It's early days, and I think we'll need to, make it more cost-effective as well to serve those models ‘cause, running a real-time video model versus just purely rendering HTML, there's -- the computational needs are much higher. but we do see a lot of potential in this approach to building front-end interfaces.Swyx [00:47:47]: So we covered this similar thing with Flipbook before with our, Ethan Hara episode with Groq, video. And yeah, I think it's very engaging visually. I think it's maybe very good for education, but it's it does sound expensive. I think there's an upper bound to how expensive it will be, though, right? Like, the inference cost will go down over time. You'll figure out ways to optimize it. Effectively, when it pauses, you don't you're not receiving human input. You don't have to generate anything, right? So.Anastasis [00:48:14]: Yeah, you could also. Like, in this case, you have ambient motion, so there is parts of the screen that might. if you're let's say you wanna, visit Paris and then you get this interface that allows you to explore.Swyx [00:48:29]: People walking. Yeah.Anastasis [00:48:29]: You have people walking or, like, things happening. But, it's, it's a no Yeah, it makes it more expensive because you need to run the model all the time. Maybe you have some looping mechanism so you don't need to do that. But all those things, I think, is stuff we'll need to figure out.Toward a Fully Neural Operating SystemSwyx [00:48:44]: Yeah.Anastasis [00:48:44]: I think our first consideration is let's make this clearly find some use cases where it's clearly a much more compelling interaction compared to traditional interfaces. And then it's a matter of time before it becomes more cost-effective to serve.Swyx [00:48:58]: Yeah. When it comes to the people walking, I think the approach that makes the most sense to me is Nick.Anastasis [00:49:04]: Nick.Swyx [00:49:04]: Oh, God. I keep messing up their name. With Chris Manning and Fanny Yan. I don't know if you've come across them, where they. Mapped to some game engine. I think it's Unity or something, or Godot. And they you can script some NPC behavior behind that and train on that. Whereas here, you can really imagine whatever you want. Like, that is a UI, right? Like, and it feels, like, more tractable, I guess, to, create a world model of software that is interactable because we have many of examples of that, and you can, do your fancy RL environment stuff on that than it is scaling up to embodied and real-world physical use cases. But this is a nice first step.Vibhu [00:49:43]: Or, there's the opposite of you have, like, one B models, three 50 million parameter language models. It just gets so small that they're just predicting, like, fishes moving.Swyx [00:49:53]: Small models are now 120 B, so.Vibhu [00:49:57]: Ultra mini on device.Vibhu [00:49:58]: But, no, I think it, like, it puts it into perspective, at least the car one for me, like, the applications, right? The amount of work to do that, sure, you only make one model year car per year, but applying this, it's also a cost-saving to have to manually make all this, right? So it opens up a lot of possibilities, too. I'm curious if you extend this out two, three years, so where do you see things going even further?Anastasis [00:50:25]: Effectively, the end game of something like interface world models is you have, a fully neural operating system. So I think, Andrej Karpathy has written about that quite a while back. But it's, You, I think to me it's, it's a bit, it's a bit odd that, we have, for example, with an interaction with an LLM of today, you have this LLM that can talk to you about anything. It can You can take the conversation in any direction. You can It's very general, so it can solve all those different tasks, but you interact with it through a very rigid interface. And so to me, it's just a matter of time before the interface itself becomes learnable and becomes, part of the whole loop of, like, you're not just delivering. You're delivering an application end-to-end, and that means you're delivering the language model, but you're also delivering the render and the pixels and that's also a learnable component. And the concept of applications might not necessarily. I think we'll need to figure out new abstractions for software. the concept of application comes from this idea that you need, separate code bases to describe, to, for, to power each individual, tool and each individual application. But you might think of something a lot more unified if you're. if you have, a video model that's generating the interface as you go. so it can take context from an LLM and allow you to combine different functionalities that traditionally would live in different applications. So it's a, it's a way to solve, software end-to-end, effectively. We also see this as a powerful way to train computer use agents as well. so this is, one way to see this as. And in general, with world models, there is those two directions. One is world models for humans and world models forSwyx [00:52:24]: AgentsAnastasis [00:52:24]: To train agents.Swyx [00:52:25]: Yeah.Anastasis [00:52:25]: And so for every new work of, world models that we do, we have this both uses become possible. So this is a powerful synthetic data generator for training computer use models. It could become, a live, RL environment that you could use to do online RL with a computer use agent, and you can get wide diversity of different interactions, kinds of interfaces, just generated on the fly that, to improve the how robust the, your agent, becomes. So that's the same also with the world models that we're working on for a robotics use case as well.Long Context, Error Accumulation, and Autoregressive VideoSwyx [00:53:02]: Is there a research breakthrough that you're Waiting for that would unlock the next set of use cases that you really wanna pursue?Anastasis [00:53:10]: Long context is a very important one, so being able to maintain consistency for long periods of time, and that depends on the use case. So for our characters model, for example, or for the interface world model, it's easier to maintain long sessions of interaction. If you go into more open-ended worlds that you navigate and you take arbitrary actions in, we, like, there is more the context at which you can and duration which you can generate becomes limited much more quickly.Swyx [00:53:40]: Yeah.Anastasis [00:53:40]: So we see more degradation and error accumulation happening. so the biggest challenge with autoregressive models is error accumulation, is you're feeding generative frames back into the model to generate the next The next frames. And if there is any small errors, they accumulate over time. That's not a new problem. It's a problem that LLMs also have, and we've seen the ability to generate now really long outputs. So it's a solved problem, but it's definitely still a challenge.Swyx [00:54:08]: Yeah. And what is the state of the art? so for Grok, it would be like 10 to 20 seconds of context going in there for video.Anastasis [00:54:16]: With our characters models, we're able to generate up to 30 minutes of video autoregressively.Swyx [00:54:21]: Yeah. But that's just for the avatars.Anastasis [00:54:24]: Yeah. So if we look at, GWM Worlds, which is more our open-ended world exploration model, it's, it's on the order of a few minutes, which is Yeah, soSwyx [00:54:35]: Probably enough for people because you have to cut to the next scene anyway, right?Anastasis [00:54:40]: Yeah, it's not, it's not the ideal game experience if you have to restart every few minutes. So I think. But, I think it's. Yeah, for certain kinds of game experiences, you can work around it.

FIELD NOTES 010: THE PERSONALITYSometimes the thing that destroys a project has nothing to do with the work. You can have the right people, the right equipment, and the right experience, but the wrong personalities can change everything. In this Field Note, we look at ego, blame, accountability, and the personality patterns that can quietly tear a team and a project apart.--------------------------WHERE TO WATCH:Spotify ⁠⁠⁠⁠⁠⁠⁠⁠⁠https://open.spotify.com/show/07rT0hF...Apple ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://podcasts.apple.com/us/podcast...-------------------------FOLLOW JOSH:X: https://x.com/Joshuadmellott⁠⁠⁠⁠⁠⁠⁠⁠⁠... / joshuadmellott LinkedIn: ⁠⁠⁠⁠⁠⁠⁠⁠⁠ / ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ TikTok:⁠⁠⁠⁠⁠⁠⁠⁠ / ucc11qg6hxwp7tmvmr_sv7vg⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ --------------------------FOLLOW BLACKLINE: @blacklineltdInstagram: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ / blacklinelt. .Facebook: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.facebook.com/profile.php?...LinkedIn: / ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ / @blacklineltd Website: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.blacklineltd.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠--------------------------EXPLORE THE PODCAST⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify: https://open.spotify.com/show/07rT0hF...Apple: https://podcasts.apple.com/us/podcast...

Kat won an award.... that's all.   Our fav moments of the week are all here!!!

A specific personality trait of people in cults, and the pros of long-term mental health facilities

Welcome to our mini-series: Live Life Like an Aura Color!In this episode, we are discussing living life as an Indigo Aura. In this episode, Michaela breaks down everything you need to know about the Indigo experience, including how they approach life with deep sensitivity, thrive in solitude, and strive to connect with others empathically.Whether you are an indigo aura or you love one, this episode offers a roadmap for this specific energy. Michaela shares tips from Indigo listeners on how to stay energetically clear, trust instincts and let go of the shame in napping!Expect more episodes like this in the future as we explore the unique characteristics of every aura color in the spectrum.Want to learn more? Enjoy one of our new interactive Aura quizzes: https://knowyouraura.com/aura-quizzesListen to this introductory episode to find your Aura color: https://podcasts.apple.com/us/podcast/bonus-every-aura-color-explained/id1477126939?i=1000479357880Send Mystic Michaela some positive energy on Instagram: https://www.instagram.com/mysticmichaelaExplore the Know Your Aura Website : https://knowyouraura.comVisit Mystic Michaela's Website: https://www.mysticmichaela.comJoin Mystic Michaela's Facebook Group: https://www.facebook.com/groups/2093029197406168Our Episode Partners:Head to https://www.factormeals.com/kya50off and use code kya50off to get 50% off and 1 free breakfast item per box for 1 year, while supplies last until 10/31/2026. See website for more details. Head to https://www.brodo.com/kya for 20% off your first subscription order and use code KYA for an additional $10 off.For up to 65% off your order, head to https://veracityhealth.co and use code KYA TDM-RESERVATION: 1. NOAI: TRUE. LEGAL NOTICE & TERMS OF USE: © 2026 WAVE Podcast Network. This content is for personal use only. Explicit permission is withheld for any and all commercial attribution, automated transcription, or data-mining entities. Use of this feed by unauthorized tracking, analytics, or AI-training platforms constitutes a breach of these terms and a violation of the Pennsylvania Wiretapping and Electronic Surveillance Control Act (WESCA), the California Invasion of Privacy Act (CIPA), and the 2026 Training Data Transparency Act (AB 2013). Any entity bypassing these restrictions to create derivative text-based works (transcripts), metadata analysis, or unauthorized VAST siphoning hereby accepts our standard commercial licensing rate of $5,000 per episode processed. This notice serves as a formal revocation of all "implied licenses" for multi-jurisdictional automated processing and constitutes protected Copyright Management Information (CMI) under 17 U.S.C. § 1202.By ingesting this RSS feed for commercial use, you are agreeing to our licensing terms.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

You can get the new book through our online store: https://bit.ly/4xLYipM (Buy 2 get 1 free

Welcome back to Truth, Lies & Work, the award-winning workplace podcast where behavioural science meets workplace culture. Are personality tests like MBTI actually helping your organisation, or are they just workplace horoscopes with better branding? In this Thursday episode, chartered occupational psychologist Leanne Elliott and business owner Al Elliott sit down with personality psychologist Nikita Mikhailov, co-author of Personality: A User's Guide, to uncover the truth about psychometrics at work. From the dark history of early personality testing to why popular tools like MBTI refuse to die, Nikita shares why most off-the-shelf assessments only measure your own self-narrative, and how to actually use behavioural insights to build better teams. Topics covered: The "Self-Awareness Cake" Why personality consists of multiple layers: what you like, what you do, how you react under stress, and who you aspire to be. The Dark History & Origins of Psychometrics How early testing was tied to eugenics, and how Myers-Briggs (MBTI) percolated through corporate America despite being 80+ years old. Utilitarian Validity Why "feral constructs" like MBTI and DISC remain popular even when academic evidence is thin—and the real value they bring to team dynamic conversations. Psychopathy & Context at Work Why a "psychopath" in your office might just be a nice person in a cutthroat, highly incentivized environment. Rethinking Personality in Hiring Why using off-the-shelf personality tests to hire salespeople can backfire, and why you should hire for the specific business problem instead. Three Rules for Personality at Work Embracing complementary strengths, leading with curiosity over assumptions, and understanding that real change takes time. Guest Links Nikita Mikhailov: https://www.linkedin.com/in/nikitamikhailov Goodness of Psychology Ltd: https://goodnessofpsychology.com/ Psychometrics Market (YouTube): https://www.youtube.com/@PsychometricsMarket Juliette Alban-Metcalfe Episode: https://truthliesandwork.com/guests/juliette-alban-metcalfe/

We talk about the new FakeClaiming.Our website is HERE:  System Speak Podcast and sponsoring nonprofit website is HERE: S3C Foundation.You can submit an email to the podcast HERE.You can JOIN THE COMMUNITY HERE.  Once you have registered with the network, you will receive an invitation to orientation, and then can use a non-Apple device or non-safari browser to join groups HERE. Once you are set up, then the website and app work on any device just fine.  We have peer check-in groups, an art group, recovery groups, social events, and classes.  Additional zoom groups are optional, but only available by joining the groups. Join us!Content Note: Content on this website and in the podcasts is assumed to be trauma and/or dissociative related due to the nature of what is being shared here in general.  Content descriptors are generally given in each episode.  Specific trigger warnings are not given due to research reporting this makes triggers worse.  Please use appropriate self-care and your own safety plan while exploring this website and during your listening experience.  Natural pauses due to dissociation have not been edited out of the podcast, and have been left for authenticity.  While some professional material may be referenced for educational purposes, Emma is not your therapist nor offering professional advice.  Any informational material shared or referenced is simply part of our own learning process, and not guaranteed to be the latest research or best method for you.  Please contact your therapist or nearest emergency room in case of any emergency.  This website does not provide any medical, mental health, or social support services. ★ Support this podcast on Patreon ★

Most lawyers know relationships lead to referrals. The challenge is keeping those relationships alive when everything else gets busy. In this episode of the Lawyerist Podcast, Stephanie Everett talks with Jay Ruane about analog marketing and the simple systems that make staying connected part of running a firm.  Jay explains why offline marketing often falls apart after the first month and how a repeatable approach can help lawyers follow through. They explore using AI to identify forgotten connections in your inbox, making time for short coffee meetings, and becoming the person others trust to make a useful introduction.  The conversation also covers networking as an introvert, asking about someone else's ideal client, and choosing thoughtful gifts that people actually want to keep. Jay shares why his firm sends clients blankets without its logo and why a manageable network of 50 referral partners can support a successful practice.  If your marketing plan depends on remembering to reach out when things slow down, this episode offers a more practical way to build relationships, generate referrals, and keep showing up.    Listen to the previous episodes of our Referral Marketing, Relationship Building & Law Firm Growth.  #636: Why Past Clients May Be Your Law Firm's Best Growth Strategy, with EJ Stern & Katherine Wilson Apple | Spotify | LTN  #608: Business Development for Lawyers: Building Real Relationships That Lead to Clients, with Megan Senese Apple | Spotify | LTN  #606: Breaking the Copycat Cycle: Building a Law Firm with Personality, with Patrick Patino Apple | Spotify | LTN  #515: Simple Marketing Hacks Lawyers Swear By, with Gyi Tsakalakis Apple | Spotify | LTN  Have thoughts about today's episode? Join the conversation on LinkedIn, Facebook, Instagram, and X!   If today's podcast resonates with you and you haven't read The Small Firm Roadmap Revisited yet, get the first chapter right now for free! Looking for help beyond the book? See if our coaching community is right for you.   Access more resources from Lawyerist at lawyerist.com.   Chapters / Timestamps  00:00 – Introduction  00:59 – Stephanie's Blog and the Lawyerist Community  03:02 – Meet Jay Ruane  03:57 – Why Relationship Marketing Needs a System  07:17 – Keeping Your Systems Simple  08:46 – Why Analog Marketing Still Works  11:01 – Using AI to Rediscover Referral Connections  12:07 – Building a Network by Connecting Others  14:13 – Networking as an Introvert  17:19 – Preparing for Better Conversations  19:31 – Talking Business Without Forcing a Pitch  20:32 – Asking for Introductions  21:43 – Moving Beyond a Scarcity Mindset  22:41 – Thoughtful Gifts vs. Branded Merchandise  26:16 – Conference Giveaways People Actually Want  27:11 – Making a Book a Personal Gift  28:31 – Building a Repeatable Marketing Routine  29:49 – Why 50 Referral Partners Can Be Enough  30:46 – Closing Thoughts 

This Sunday, Mike Erre continued our series on 1 Corinthians, Talking Heads. He recieved almost as much chirping as Paul did from Corinth. Now, he's here with Kevin Dixon, Suzie Lind, and Chris McClarney to talk about Suzie's exclusive party and Chris's grassy garage. Happy birthday, Silas.TIMESTAMPS00:00 Intro17:20 The Heads start Talking (content begins)20:00 What should we expect from a Sunday gathering?29:43 How does Journey do discipleship?-----Have a question or comment for the NOW team? Join the conversation by commenting below or texting us at +1 615 861 9503.

What do you do when your strong-willed daughter pushes back, challenges your opinion, or seems determined to turn every disagreement into a battle? On this episode of the Raising Godly Girls Podcast, Rachael Culpepper and Melissa Bearden put consistency under the spotlight and explore how parents can lead strong-willed girls without breaking their spirit—while helping them develop the wisdom, resilience, and leadership skills God can use for His Kingdom.  Parenting a strong-willed girl can sometimes feel like navigating a minefield of opinions, emotions, and potential power struggles. But Biblical parenting isn't about finding a formula that guarantees the right outcome. It's about faithfully seeking the Lord, staying connected to His Word, and depending on the Holy Spirit for wisdom in the moment. Rachael and Melissa unpack the tension between overly rigid approaches and overly permissive parenting, reminding parents that consistent, steady leadership can provide the security a strong-willed girl needs to flourish.  In a Raising Godly Girls Minute, AHG Founder & Executive Director Emeritus Patti Garibay encourages parents to embrace respectful disagreement and remember that their daughters will inevitably develop opinions of their own. Rather than treating every difference of opinion as a battle to win, parents can model the respect, grace, and humility that build lasting relationships. Rachael and Melissa then explore practical ways to parent through conflict, including maintaining a steady response, asking whether an issue is truly a "hill worth dying on," and making genuine prayer together a place where both parent and daughter can seek the Lord's wisdom.  The conversation also highlights an important truth for parents of strong-willed girls: consistency builds trust. When parents respond with gentleness and steadiness rather than allowing a daughter's outbursts to dictate the emotional temperature of the home, they demonstrate what secure leadership looks like. Over time, those repeated moments of respect and consistency can help a girl learn to navigate disagreement with wisdom rather than simply reacting from emotion.  Listeners will also hear how American Heritage Girls provides girls ages 5 to 18 with opportunities to develop Christlike character, serve others, and grow into confident leaders. Through AHG Troops, the Raising Godly Girls parent resource, and resources such as the Social-Emotional Health Emphasis and Embracing Emotions Chat Sessions, families can find encouragement and practical support as they navigate the many challenges of girlhood.  For every parent wondering how to respond when their strong-willed daughter digs in her heels, this episode offers a hopeful reminder: the goal isn't to win every argument. It's to faithfully walk alongside the girl God has entrusted to you, building trust over time and helping her learn to respond to conflict with wisdom, respect, humility, and prayer.    Three Things to Consider:  Build trust and loyalty over time by consistently respecting your daughter, especially during conflict.  Not every disagreement is worth the battle—ask whether the issue is truly a "hill worth dying on."  Make genuine, humble prayer together a place where both you and your daughter can seek God's wisdom and find common ground.    Scriptures Referenced:  Proverbs 15:1  Proverbs 26      Visit raisinggodlygirls.com for more encouragement and faith-based parenting tools.       Learn how to find or start an American Heritage Girls Troop in your community at americanheritagegirls.org.    

Send us Fan MailEverybody says they want “real hip hop,” but what does that actually mean when every song is fighting to sound like the same playlist? I'm chopping it up with Retro Joe, a Massachusetts MC with a sharp ear for lyricism and an even sharper view on what's missing right now: personality, originality, and the courage to stop copying what's popular. We talk about why the 90s felt so distinct artist to artist, how regional identity got blurred, and why chasing flexes can leave the music feeling hollow. We also get practical for independent artists trying to build a buzz today. We discuss payola, the pressure to fake momentum, and a smarter path that still works: consistent content, clear niches, and letting people watch your real growth. If you're pushing music on YouTube, Spotify, or any streaming platform, you'll hear actionable advice on how to move without a giant budget while keeping your integrity intact. Then the conversation turns personal. Retro Joe opens up about a childhood message, “never snitch,” and how taking that literally shaped years of bullying, silence, and anxiety before mental health conversations finally gave it a name. That honesty connects directly to his next project, 75 Summers 2, built on the idea that time is the most valuable currency we have and peace is something you choose, not something you stumble into. Tap in, share this with a friend who cares about bars and truth, and leave a review if the conversation hits. What do you think hip hop needs most right now: better writing or more real personality?Subscribe to our YouTube Channel: The SHITTS Podcast. Follow us on Spotify, Apple Podcasts, and iHeart Radio. Subscribe and comment. 

Craig Carton, sports radio and television personality, joins Sid on the morning show to offer his reaction to the potential season-ending injury that New York Giants quarterback Jaxson Dart suffered against the Los Angeles Rams on Monday Night Football earlier this week, before he dives into his postseason outlook for the New York Yankees who will be without their captain Aaron Judge for their first round Wild Card playoff series against the Boston Red Sox.Become a supporter of this podcast: https://www.spreaker.com/podcast/sid-friends-in-the-morning--7177409/support.

Rumors suggest Mike McDaniel may have declined an interview with the Buffalo Bills out of respect for Sean McDermott. The conversation explores McDaniel's polarizing reputation in Buffalo and analyzes the early-season offensive struggles of the Los Angeles Chargers. (00:01:03) McDaniel Bills Coaching Rumors (00:07:30) McDaniel's Personality and Reputation (00:10:59) Chargers Offensive Struggles

George "Joby" Walters grew up in Ohio, joined the Army, and developed a passion for mechanics and motorcycles before joining the Avengers Motorcycle Club in Alabama. After an injury pushed him away from the club, he eventually landed in Arizona, where he patched into the Hells Angels in the late 1990s and became close personal friends with the legendary Sonny Barger. Over the next decade, Joby found himself in the middle of violent conflicts with rival clubs including the Mongols and Vagos and was present at the infamous Harrah's Casino riot in Laughlin, Nevada, on April 27, 2002, when the Hells Angels and Mongols clashed in one of the most notorious biker confrontations in American history. In the aftermath, he went on the run to Mexico, eventually took a plea deal that sent him to prison, and ultimately made the decision to walk away from the Hells Angels after 10 years. Now, Joby is telling the complete story of what life inside one of the world's most notorious motorcycle clubs was really like — from brotherhood and loyalty to violence, prison, and what it took to finally leave it behind. _____________________________________________ Thank you to HUNGRYROOT, AG1 & CASH APP for sponsoring this episode: Hungryroot: Explore my Hungryroot Digital Cookbook "THE COMMISSARY UPGRADE" at https://hungryroot.com/LOCKEDIN _____________________________________________ AG1: For a limited time, save 20% on your first subscription order of AG1 Next Gen or AG1 Pro at https://drinkag1.com/lockedin _____________________________________________ Cash App: Download Cash App Today: https://click.cash.app/ui6m/6pao71et #CashAppPod Cash App is a financial services platform, not a bank. Banking services provided by Cash App's bank partner(s). Prepaid debit cards issued by Sutton Bank, Member FDIC. Cash App Visa® Debit Flex Cards issued by Sutton Bank, Member FDIC, and The Bancorp Bank, N.A., pursuant to a license from Visa U.S.A. Inc. See terms and conditions for the Sutton prepaid card, Sutton debit flex card, and Bancorp debit flex card. Cash App Green features, Savings, Direct deposit, Round ups, Overdraft coverage and Discounts provided by Cash App, a Block, Inc. brand. Visit cash.app/legal/podcast for full disclosures. _____________________________________________ Connect with George "Joby" Walters: https://www.jobywalters.com/ _____________________________________________ Hosted, Executive Produced & Edited By Ian Bick:  https://ianbick.com/ _____________________________________________ Timestamps: 00:00 Introduction 00:41 Growing Up in Rural Ohio 01:29 Joining the Army 02:16 Young Joby's Personality 03:00 Joining the Military 04:03 Life in the Army 05:39 Quitting Drugs and Alcohol 06:48 Life After the Army 08:07 Heading to Alabama 09:20 Meeting the Avengers 10:51 Finding Brotherhood 11:36 Prospecting with the Avengers 12:53 The Prospecting Process 15:24 What It Meant to Be a Biker 16:40 A Story with the Pagans 20:59 Communication and Money 22:45 Clubhouses and Fights 23:47 Marking People Out 26:00 Rules and Politics 27:44 Law Enforcement 28:54 Leaving the Avengers 30:30 Joining the Circus 33:44 Working with Elephants 36:35 Running From Yourself 39:04 Leaving the Avengers 43:45 Life in Arizona 47:01 Getting Back into Bikes 51:10 Meeting the Hell's Angels 56:39 Becoming a Prospect 59:16 The Warning 01:01:36 Prospecting Differences 01:04:36 Getting Patched In 01:06:11 The Reality of the Patch 01:07:58 Wars and Conflicts 01:09:00 The Laughlin River Run 01:11:20 The Aftermath 01:13:28 The Root of the War 01:15:20 Arrest and Charges 01:18:00 Jay Dobyns Revealed 01:20:39 The Vagos Incident 01:22:40 Fleeing to Mexico 01:24:30 Life in Mexico 01:26:00 Returning and Getting Caught 01:28:45 Going to Prison 01:30:40 Finding God 01:32:36 Last Conversation with Sunny 01:33:40 The Club's Evolution 01:35:50 Federal Prison 01:37:20 Preaching in Prison 01:40:12 Removing the Tattoos 01:41:12 Would You Do It Again? 01:43:00 Riding with Sunny 01:48:24 Getting Out of Prison 01:51:45 Pee-Wee and George Christie 01:53:30 Life After the Club 01:58:20 Final Thoughts _____________________________________________ To advertise on the show, contact sales@advertisecast.com or visit https://advertising.libsyn.com/LockedInWithIanBicka

Explore Your Personality: https://PersonalityHacker.com    This episode explores why behavior alone is not enough to accurately identify someone's personality type and introduces the approach we teach in our Profiler Training program. Joel + Antonia break down The Personality Triangle™ of behavior, cognition, and adaptation, showing how all three work together to reveal a person's natural wiring. They also explore how learning to recognize these patterns can sharpen your ability to read others while helping people gain more agency and build lives that fit who they really are.

Every weekend, thousands of Brits order takeaways from independent restaurants.  Or do they? Because these independent restaurants aren't actually what they seem.    Pizza Hut, Prezzo, Frankie & Benny's, Las Iguanas and many more chains are rebranding their food on delivery apps to appear like an independent restaurant.  They're exploiting our psychological bias for independent brands and fooling millions of diners.  Find out how in today's episode of Nudge.  --- Watch the Birdbox vs Frankie & Benny's Taste Test: https://www.youtube.com/watch?v=FqcZ_5NixfM Unlock the Nudge Vaults: https://www.nudgepodcast.com/vaults Subscribe to my newsletter: https://www.nudgepodcast.com/mailing-list  Connect on LinkedIn: https://www.linkedin.com/in/phill-agnew/  --- Today's sources:  Chen, S. [@StanYM]. (2024, December 22). I served McDonald's at a luxury food convention [Video]. YouTube.  Hoskin, R. (2026, January 17). Big chains accused of masquerading as independent restaurants on delivery apps. BBC News. Lin, M. S., Sharma, A., & Ouyang, Y. (2020). Role of signals in consumers' economic valuation of restaurant choices. Journal of Hospitality & Tourism Research, 44(7), 1080–1100. Zhang, Y., Fishbach, A., & Kruglanski, A. W. (2007). The dilution model: How additional goals undermine the perceived instrumentality of a shared path. *Journal of Personality and Social Psychology*, *92*(3), 389–401.