Podcasts about super early bird

Andreas Steno, founder and CEO of Steno Research, is back with Mikkel Rosenvold, partner and head of geopolitics for Steno Research, to break down the latest news and trends driving global markets. From escalating Ukraine-Russia tensions and the Israel-Iran standoff to the latest twists in U.S.-China trade talks, they unpack how geopolitics is driving market volatility, shaping risk assets, and influencing macro positioning.

Rekt co-founders OSF and Mando, also the author of the Mando Minutes newsletter, are back to discuss the biggest narratives and themes driving cryptocurrencies right now. They discuss the USDC stablecoin-issuer Circle going public, Pump.fun launching its own token, memecoin weakness, what the best trades are right now, and HYPE's outperformance, and much more. Later in the show, they are joined by Arch Public's CEO Tillman Holloway and co-founder Andrew Parish. Recorded on June 5, 2025. Check out Arch Public's algorithmic trading platform for free at https://realvision.com/arch

There's a moment in nearly every breakthrough – one that's easy to miss if you don't know what to look for. It's often quiet, almost invisible… but it's where everything starts to shift. In last night's masterclass, I slowed things down and unpacked a recent coaching demo where one of these pivotal moments happened, and we explored: – What I was noticing beneath the surface – Why I asked the questions I did (including a few that might seem counterintuitive) – How the entire session pivoted on a single shift in perspective If you're a coach, change-worker, or just fascinated by the inside-out nature of real transformation, I think you'll find this especially useful. Big love, Jamie P.S. Towards the end of the session, I shared two possible next steps for anyone wanting to take their coaching to the next level: 1 - If you've been considering joining Clarity Certification Training and want to explore if it's the right next step for you, you can start your CCT application & diagnostic here. 

There's a moment in nearly every breakthrough – one that's easy to miss if you don't know what to look for. It's often quiet, almost invisible… but it's where everything starts to shift. In last night's masterclass, I slowed things down and unpacked a recent coaching demo where one of these pivotal moments happened, and we explored: – What I was noticing beneath the surface – Why I asked the questions I did (including a few that might seem counterintuitive) – How the entire session pivoted on a single shift in perspective If you're a coach, change-worker, or just fascinated by the inside-out nature of real transformation, I think you'll find this especially useful. Big love, Jamie P.S. Towards the end of the session, I shared two possible next steps for anyone wanting to take their coaching to the next level: 1 - If you've been considering joining Clarity Certification Training and want to explore if it's the right next step for you, you can start your CCT application & diagnostic here. 

Episode 74 – How to Administer Medications to our Pets   Giving tablets to our pets is not always easy, and cats especially are notoriously difficult to administer oral medication to! The problem with not being able to give medication is that this may interfere with your pet's medical care and have a detrimental effect on their physical or mental and emotional health. One of the most important things I stress in this episode is to ask for help from your vet or pet care professional if you are struggling to give oral medication to your pet – there is usually a different solution out there so we can ensure your pet gets the treatment they need together!   In this episode, I share my Top 10 Tips for medication administration to help you easily and successfully give tablets to your pet.   Things you'll learn in this episode: 1.      Why I dislike Pill Poppers so much! 2.      How to become a detective at finding a super high value food for your pet! 3.      How play and operant conditioning can help. …and so much more!   Get my FREE downloadable PDF on medication administration for pets by clicking the link below! https://katrin-jahn.mykajabi.com/medicating-pets   And, here's introducing my brand new online Behaviour Medication Course – PSYCHOACTIVE!!! Sign up now to get the SUPER EARLY BIRD price: https://katrin-jahn.mykajabi.com/psychoactive   We really hope you enjoy this episode; it is packed with so much information!   If you liked this episode of the show, The Pet Behaviour Chat, please LEAVE A 5-STAR REVIEW, like, share, and subscribe!   Facebook Group: Join The Pet Behaviour Community on Facebook   You can CONNECT with me: Website: Visit my website Trinity Veterinary Behaviour Instagram: Follow Trinity Veterinary Behaviour on Instagram Trinity Veterinary Behaviour Facebook: Join us on Trinity Veterinary Behaviour's Facebook page Trinity Veterinary Behaviour YouTube: Subscribe to Trinity Veterinary Behaviour on YouTube LinkedIn Profile: Connect with me on LinkedIn   Thank you for tuning in!

In dieser wieder einmal sehr persönlichen Folge geht es um Stephanies Kinderwunsch-Reise, die wie so oft keineswegs geradlinig war. Von einer (TW) Fehlgeburt, über eine Trennungen, der Frage nach dem richtigen Partner fürs Leben bis hin zum medizinischem Spießrutenlauf und am Ende doch dem Vertrauen in den Prozess ist alles dabei. Stephanies Weg war auch einer der Beweggründe für die nächste Festival-Ausgabe im Mai. Wir wollen eintauchen in das Thema Kinderwunsch und euch mitnehmen auf dem Weg, der so viele Facetten in sich birgt! Hier kannst du dir noch bis Mitte März noch dein Ticket zum Super-Early-Bird sichern: https://www.artofbeingwoman.de/festival-holistic-fertility

Xmas Special: Investing in Software: Alternatives To Project Management For Software Businesses With Vasco Duarte In the grand finale of the “5 Wishes for 2025” series, Vasco Duarte tackles the chaotic nature of software development and why traditional project management just doesn't cut it. Drawing on lessons from weather models, butterflies, and Agile practices, Vasco presents a bold manifesto for how we can thrive in uncertainty. Chaos Theory and Software Development “Project management is like trying to predict where a butterfly will land after flying through a hurricane – good luck with that!” Vasco begins with the story of Edward Lorenz, the MIT meteorologist who discovered what was later called the “butterfly effect.” This concept illuminates and explains the unpredictability of software development, where tiny changes can lead to massive, unexpected consequences – like a simple tweak spiraling into a full system refactor. Why Traditional Project Management Falls Short “Planning your year's meals in January? That's about as realistic as predicting October's sushi cravings!” Vasco humorously dismantles the premise of project management, which assumes stability, predictability, and complete information upfront. While Agile provides a more flexible approach, it's often misused as “project management in disguise,” failing to unlock the true potential of adaptability. The 2025 Manifesto: A New Way to Invest in Software “Loving Gantt charts is like loving fax machines – there's a better way!” Vasco outlines his four-point manifesto for how organizations can thrive in uncertainty: Fund Software Incrementally: Treat funding like stock market investing – small, regular investments over time. Think Like an Investor: Focus on maximizing returns, not rigidly executing plans. Experiment by Default: Acknowledge that the best ideas come from testing and iterating. Give Teams End-to-End Ownership: Empower teams to own their work from idea to delivery, eliminating micromanagement. The Need for Agility at All Levels “Scrum teams in a project management organization are like race car drivers stuck in traffic jams – all that potential, nowhere to go!” Vasco emphasizes that agility must extend beyond individual teams. Organizations need to embrace Agile principles at every level to avoid stifling innovation and potential. And his approach to funding and managing software investments does exactly that: bring agility to the decision making forums in the organization, instead of keeping it at the team level. A Wish for 2025: Embrace the Chaos “Butterflies don't follow project plans, and neither does software development!” Vasco's final wish for 2025 is for organizations to stop forcing software into rigid project management frameworks. Instead, they should embrace the unpredictable nature of development, leveraging incremental funding, iterative experimentation, and team empowerment to thrive in uncertainty. See It in Action: Global Agile Summit 2025 “Want to see how real organizations are thriving in chaos? Join us in Tallinn!” Vasco invites listeners to the Global Agile Summit 2025 in Tallinn, Estonia, where forward-thinking organizations will share their stories of breaking free from traditional project management. Holiday listeners can grab a 75% discounted Super Early Bird ticket at GlobalAgileSummit.com. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

Xmas Special: Keep Your Backlog Microscopic - The #NoBacklogs Revolution With Vasco Duarte In the fourth episode of the “5 Wishes for 2025” series, Vasco Duarte takes on a common yet overlooked productivity killer: the monster backlog. With humor, relatable analogies, and practical advice, Vasco shares how organizations can turn their overwhelming backlogs into powerful tools for focus and impact. The Backlog Problem: When More Becomes Too Much “Your backlog should be like your fridge, not your basement – keep only what you'll use soon, not what you might need someday!” Vasco opens by comparing bloated backlogs to storage boxes filled with old cables and chargers: seemingly useful but rarely touched. Sharing the story of Juha, a leader overwhelmed by a five-year backlog of epics, Vasco highlights how backlogs can grow out of control, becoming a source of stress rather than a tool for productivity. A #NoBacklogs Approach to Backlog Management “Your backlog should only contain work for the next 2-3 sprints. That's it!” Vasco introduces a game-changing rule of thumb: Short-Term Focus: Limit the backlog to items that can be completed within the next 2-3 sprints. Medium-Term Planning: Use a problem-centric roadmap to outline key issues to tackle in the next 6-9 months, and a technology strategy to align on longer term tech priorities (more on that in an upcoming episode) Long-Term Vision: Create a clear vision document to connect today's work to future goals. By managing backlogs with these three distinct timelines, teams can regain clarity and focus without sacrificing strategic alignment. The Problem-Centric Roadmap: A Tool for Clarity “Think of it as three zoom levels on your product map – focus on what you need today, tomorrow, and the distant future.” Vasco explains how a problem-centric roadmap helps teams prioritize medium-term goals by focusing on the most critical customer problems. Combined with a clear long-term vision, this roadmap empowers teams to align their efforts without being overwhelmed by irrelevant details. The Hidden Danger of Monster Backlogs “At conferences, I've met teams with 10-year-old backlog items – that's like keeping your Y2K plans ‘just in case'!” Vasco shares surprising stories of teams with decade-old backlog items. These “zombie tasks” highlight the need for a system to prevent backlogs from growing unchecked. Without proper management, backlogs can cause anxiety and hinder teams from delivering value. A Wish for 2025: Make Backlogs Short And Easy To Manage! “Let's turn our backlogs back into the focusing tools they were meant to be.” Vasco's fourth wish for 2025 is to see teams use backlogs as powerful prioritization tools, not bottomless pits of forgotten ideas. By embracing a short-term backlog, medium-term roadmap, and long-term vision, teams can stay focused, aligned, and productive. See It in Action: Global Agile Summit 2025 “Want to learn how real teams are taming their monster backlogs? Join us in Tallinn!” Vasco invites listeners to the Global Agile Summit 2025 in Tallinn, Estonia, where teams will share practical strategies for managing backlogs effectively. Holiday listeners can snag a 75% discounted Super Early Bird ticket at GlobalAgileSummit.com. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

Xmas Special: Running Experiments Over Managing A Tasklist, aka The Backlog With Vasco Duarte In the third episode of the “5 Wishes for 2025” series, Vasco Duarte takes aim at one of the most common anti-patterns in software development: the obsession with managing tasks instead of discovering what truly works.  He calls on teams to shift their mindset from backlog management to running experiments, creating a culture of learning and rapid innovation. From Backlog Secretary to Product Scientist “Managing a backlog is like planning a road trip by focusing on the gas stops instead of the destination.” Vasco reflects on how teams often lose sight of their goals, becoming bogged down in task management instead of pursuing real customer value. He humorously compares this approach to being a “backlog secretary,” organizing tasks while forgetting why the project began in the first place. His solution? A radical shift from task obsession to a learning-first approach driven by rapid experiments. The Power of 24-Hour Experiments “Why wait for weeks to learn something you could test in a day?” Vasco shares real-world success stories of teams embracing a rapid experimentation mindset: • The Skeptical Client: In just 48 hours, this team launched two market experiments and gained actionable feedback. • The Experiment-First Startup: Meeting twice weekly to design and run experiments, this startup learns more in a week than most teams do in a month. These examples showcase how rapid testing leads to faster learning and greater customer impact. The Build-Measure-Learn Framework “Or as I like to call it, the ‘Question-Experiment-Insight' cycle – it's like having a GPS for product development.” Vasco introduces a three-step approach to running experiments: 1. Start with a Concrete Goal: Define measurable business targets using a Business Value Equation. 2. Create a Metrics Tree: Break down goals into daily metrics that track progress. 3. Experiment, Experiment, Experiment: Test new features, tweaks, and ideas quickly to gain insights and adjust course. He highlights a team's transformation from a “feature factory” to “experiment mode,” where the Product Owner posed questions and the team creatively solved them. This cycle drives meaningful insights instead of aimless task completion. A Wish for 2025: From Features to Insights “A backlog full of tasks is like a restaurant full of recipes – it means nothing until you know what your customers actually want to eat!” Vasco's third wish for 2025 is a world where teams prioritize learning over task management. By embracing the “Question-Experiment-Insight” cycle, teams can focus on solving customer problems and creating real value. This mindset shift transforms teams from task managers into product scientists, driving faster, smarter innovation. See It in Action: Global Agile Summit 2025 “Want to learn how real teams are running experiments and making an impact? Join us in Tallinn!” Vasco invites listeners to the Global Agile Summit 2025 in Tallinn, Estonia, where teams will share stories about adopting rapid experimentation. Holiday listeners can snag a special “White Wednesday” deal: a 75% discount on tickets. Visit GlobalAgileSummit.com to claim your Super Early Bird ticket. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

Xmas Special: Breaking Down the Wall Between Product and Engineering With Vasco Duarte In the second episode of the “5 Wishes for 2025” series, Vasco Duarte tackles one of the most persistent and damaging divides in software development: the wall between Product and Engineering teams. Through stories, metaphors, and real-world examples, Vasco challenges the status quo and paints a vision for seamless collaboration that drives innovation and value. The Invisible Walls Holding Us Back “It's like having the ingredients and the recipe in separate rooms – how are you supposed to cook something amazing?” Vasco begins by highlighting the invisible barriers that still exist between Product and Engineering teams in many organizations. These divisions stifle innovation and slow progress. Drawing parallels to outdated structures, Vasco recounts the struggle to integrate Product Owners into Scrum teams and how that barely scratched the surface of the larger issue. He calls for a broader perspective: aligning the creative potential of engineering with the customer insights of product management to unlock real innovation. Lessons From the Field: Breaking Down Barriers 1. The Experiments-Only Team “Not the mad scientist kind, but real, product-focused experiments that bring technical innovation and product leadership together.” Vasco shares the success story of a client who created a dedicated experiments team. By combining technical expertise with clear product direction, they delivered rapid, value-driven results. This approach demonstrates the power of collaboration in turning ideas into impactful solutions. 2. Bottom-Up Product Planning “For the first time, Product and Engineering co-created a plan that aligned with strategic goals – no more top-down directives or forced OKRs!” Another client reimagined their product planning process after attending a workshop. Instead of cascading initiatives from the top, they worked collaboratively from the ground up. This innovative approach allowed them to align with company goals while fostering ownership and creativity across teams. The CTPO: A Glimpse Into the Future “It's like they turned the wall between Product and Engineering into a large living room where everyone works together.” Vasco highlights an inspiring case from Berlin, where a company merged technical and product leadership into a single CTPO (Chief Technical and Product Officer) role. This structure bridges the gap, ensuring that both technical possibilities and customer needs are seamlessly aligned. Catch Vasco's interview with this trailblazing CTPO in the show notes to explore how this innovative approach is reshaping their organization. A Wish for 2025: Common Rooms, Not Walls “Product and Engineering are like coffee and milk – different, but together they make something special.” Vasco's vision for 2025 is a world where Product and Engineering work side-by-side in shared spaces of collaboration and value creation. He calls for a shift from siloed teams to integrated partnerships where both groups speak the same language – the language of value and impact. The companies that embrace this shift will be the leaders of tomorrow, delivering innovation at the speed of market change. Join the Conversation at the Global Agile Summit 2025 “Innovation flows as freely as coffee at a developer conference when Product and Engineering collaborate.” Vasco invites listeners to experience this transformation firsthand at the Global Agile Summit 2025 in Tallinn, Estonia. The summit will showcase real-world examples of organizations successfully adopting flow-based software delivery. For holiday listeners, Vasco has a special gift: a Super Early Bird ticket with a 75% discount. Visit GlobalAgileSummit.com to grab your ticket and see what the future of software development looks like. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

Xmas Special: From Project-Driven to Flow-Driven Software Development in 2025 with Vasco Duarte In the kickoff episode of the “5 Wishes for 2025” series, Vasco Duarte dives into a topic close to his heart: why managing software like construction projects leads to failure. Drawing on his experience in the Agile community and sharing compelling real-world examples, Vasco introduces a new perspective on how software development should flow, adapt, and continuously deliver value. Software Development: Stop Building Houses, Start Growing Gardens “Software is more like a garden than a construction site—continuous care and attention are key to thriving.” Vasco begins by debunking the myth that software development can be meticulously planned like a construction project. Sharing a story about a failed 18-month software endeavor, he highlights how rigid plans crumble in the face of changing markets. Instead, he advocates for an adaptive, flow-based approach to software development, comparing it to the continuous nurturing required in a garden. Why Projects Fall Short in Software Development “You can't plan your year's meals in January—why would you try that with software?” Vasco identifies three critical flaws of project-driven software development: 1. Assumption of Stability: Markets and requirements shift too fast for static plans. 2. Front-loaded Decisions: Early decisions often fail to hold up over time. 3. Artificial Boundaries: Restrictive scopes kill innovation and flexibility. The Three-Step Framework for Flow-Based Software Development 1. Continuous Delivery “Software is like a shark—it has to keep moving or it dies.” Vasco explains how companies can succeed by continuously delivering updates to users. He shares insights from a mobile startup using experiments and feedback loops to keep evolving and delivering measurable value. 2. Incremental Funding “Fund software like a business, not like a construction project.” Drawing on ideas from Lean-Agile financial planning, Vasco introduces incremental funding as a smarter way to manage development. He points listeners to a previous episode with experts Maarit Laanti and Rami Sirkia for deeper insights. 3. Goal-Oriented Teams “Teams need goals, not just backlogs.” Vasco stresses the importance of giving teams end-to-end ownership of the value they create. The backlog is a tool, but the real focus should be on clear goals that align with business impact. He mentions his OTOG - One-Team-One-Goal blog post.  Raising Agility to the Portfolio Level “Flow-based software development lets us make quick, strategic decisions at the portfolio level.” By embracing continuous delivery, incremental funding, and goal-driven teams, organizations can elevate agility from individual teams to the entire portfolio. Vasco highlights this as a game-changer for modern businesses, enabling quicker, smarter product decisions. Global Agile Summit 2025 – Don't Miss Out! “Join us in Tallinn to see flow-based software delivery in action.” Vasco invites listeners to the Global Agile Summit 2025, where real-world examples of flow-based development will take center stage. For those listening during the holiday season, there's a Super Early Bird ticket available with a 75% discount. Visit GlobalAgileSummit.com for details. About Vasco Duarte Vasco Duarte is a thought leader in the Agile space, co-founder of Agile Finland, and host of the Scrum Master Toolbox Podcast, which has over 10 million downloads. Author of NoEstimates: How To Measure Project Progress Without Estimating, Vasco is a sought-after speaker and consultant helping organizations embrace Agile practices to achieve business success. You can link with Vasco Duarte on LinkedIn.

ON THIS EPISODE: This is the ZorkFest 2024 recap episode, we talk about how it went and the overall success that it was. We also talk about a wonderful bougie brunch in Vegas.Super Early Bird tickets are available now for ZorkFest 2025: HEREwww.zorkfest.comMarc Meltzer's article on ZorkFest 2024: HEREJoin the TravelZork FB Group -> HERETravelZork TravelZorkFestWatch this episode on YouTube -> HEREWatch, Like, and Sub on YouTubeThe Yo-11 Minutes Playlist on YouTubeSupport the show⁉️ Want to contact us or share something?Chat to TravelZork, ZorkCast and TravelZork Travel!

Afgelopen  zaterdag 14 september was de allereerste editie van de Live Masterclass Relatiekunde! Het was een feestje om te mogen geven, samen met Josien de Graaf. In deze aflevering vertellen we hoe wij en ook de deelnemers de dag hebben ervaren.De tweede editie is op zaterdag 25 januari 2025, wederom bij het prachtige ROOTS in Haaren (NB).Ben je erbij? Meld je dan meteen aan via onderstaande link en profiteer van de Super Early Bird korting.Kom in contact met SharonMeer weten of aanmelden: relatiekunde.nl of relatiekunde.com en via: Linkedin: https://www.linkedin.com/in/sharon-overweg-slap of mail me: sharon@stapelgek.comMeer info: https://stapelgek.com/Met liefde,Sharon-------------------------------------------Montage en distributie van de Stapelgek podcast via De Podcast Specialist. Ook voor Podcast workshops | www.depodcastspecialist.nl

NO MORE DRAMA - NO MORE TRAUMA - ein für alle Mal! Super Early Bird bis 24.9. 23:59 Uhr: https://juliasspiritualliving.com/no-more-drama-no-more-trauma/ Kapitel: 00:00 Willkommen 02:33 DEIN ERSTES MAL wahre weibliche Heilung 21:50 Abschluss In dieser Podcastfolge teile ich mit Dir, warum es höchstwahrscheinlich Dein erstes Mal ist, wahrhaftige, weibliche Heilung zu erfahren.

Mi-era dor de un episod despre #GândireaMeaFăcutăVizibilă! Așa că am pus în acesta răspunsurile la opt întrebări la care nu am reușit să răspund în cadrul celui mai recent #UnFelDeWebinar.#UnFelDeWebinar e întâlnirea cu oamenii din Lista mea de Contacte care vor să mă întrebe despre Marketing, Antreprenoriat, Dezvoltare Personală, Viață.Un „Q&A cu Mădălina”. :)E o întâlnire pe Zoom. Nu costă. Nu are script sau structură bătută-n cuie și poate participa oricine. Chiar și tu! Dacă nu ai făcut-o încă.  Scrie-mi un mesaj, pe orice platformă, și-ți trimit cu plăcere link-ul să te poți înscrie și să ne și vedem, live, la următoarul webinar.Am primit, la cea mai recentă întâlnire online cu oamenii care-mi urmăresc munca, multe întrebări. Atât de multe încât n-am apucat să răspund tuturor în cele 90 de minute cât am stat împreună cu cei peste 100 de oameni prezenți online.Dar ca să onorez întrebările cât mai multor oameni, răspund pe larg aici la:  

We know you're busy this week. Us too! Catt's on the road speaking at conferences and visiting Midwest markets. Brijet's rocking National Farmers Market Week in San Diego. You're doing the same, right? So take just a minute and tune in while we chat with Erica Meadows of the Mt Washington Farmers Market in Kentucky. They gained the most votes in America Farmland Trust's 2024 America's Farmers Market Celebration and scored the big prize. We also hear from our friend Sagdrina on Farmers Market Week, National Black Business Month and the latest Farmers Market Coalition initiatives. Super Early Bird tickets for InTents, the Farmers Market Conference is live now with big savings: don't sleep on that. Use the link in our bio and save your seat. 

We have a mixed bag of topics in this month's Ask the Pros episode. With hot weather advisories, fires and floods becoming more common, we've been getting a lot of questions about when closing a market is justified. Weather or not, farmers need to move their produce so it's not a decision managers take lightly. We're chatting about that and a variety of other questions from our listeners and our online community today Listen in while we chat about these quandaries and more:    • Balancing safety, comfort and farmers' and vendors' need to make a living • What to do when you're selling out mid-market • Managing vendor to vendor conflicts that go public • Listening closely to find the source of customer complaints   Remember, Super Early Bird registration for InTents, the National Farmers Market Conference 2025 starts THIS Thursday. Watch this space and our email newsletter for all the details and save.

In shame-based cultures, when a parent doesn't like something the child is doing, often times they discipline the kid's behavior but the child herself feels like she is a bad girl. She takes on guilt, embarrasment and feels like she has "failed" her family. Unless this is undone, she will carry all the anxiety of just being "herself" into adulthood.This episode connects the dots on why so many Asians have a hard time just being "themselves" and how to stop the cycle of being afraid of others' opinions of us.*Freed to Lead 3 Day VIRTUAL EVENT: June 7, June 8, June 9*Super Early Bird tix through May 19th!*[00:00] Teaser[00:47] Episode 14 Intro[02:00] Expecting the Worst[02:48] What happened to your podcast?[06:23] How Shame Started[08:47] Before Shame Stole Our Joy[11:09] When We Don't Meet Our Own Expectations[13:11] Self-Sabotage[16:19] Yoga and Meditation won't fix it[18:42] BREAK[19:19] Cycles of Shame[22:11] What Does Shame Look Like?[25:48] Jeanny's Journey to Weed Out Old Shame[33:05] Shame Assessement[34:42] Affirmation[39:17] Preview of Season 2Theme Song: Imagine by ZooMid-roll Song: Making Progress by Dan PhillipsonAffirmation Song: Sky High by AKPost-roll Song: Clarity by Zoo*Freed to Lead 3 Day VIRTUAL EVENT: June 7, June 8, June 9

Today I have an exciting episode for you! I'm still full of covid or flu, on top of preparing for my course Live and Thrive with Endo 2.0 which begins on Monday, and packing to take our rescue kitten back to the UK - today! So, there's a lot going on - no wonder I got sick! So, instead of doing a replay episode, I thought I'd give you a peak into what I'm woking on in my course, and so today, I am sharing one of my lessons which is all about the science of how pain works and how it can be influenced by the vagus nerve and our nervous system (which are pretty much one and the same, as you'll come to learn!). This is a great episode to provide you with overall pain education and here's an interesting fact - pain education actually helps to treat and reduce pain! So that's a huge benefit of this episode, and the bonus is, if you're wondering about the course and whether it's for you, this gives you a little taster as to what's in store (and remember - there's a 14 day return policy too). If you're curious about the course and want to learn more, doors close tomorrow Sunday, April 15th, 11:55pm BST and late bird pricing has just kicked in, dropping the course back down to Super Early Bird pricing of £100 upfront or with a payment plan of £35 per month for three months. You can learn more at www.theendobellycoach.com/live-thrive-with-endo or just sign up here. Free resources: This podcast!  Endometriosis Net Column Endometriosis News Column Newsletter Instagram Ways to work with me: This EndoLife, It Starts with Breakfast digital cookbook Masterclasses in endo nutrition, surgery prep and recovery and pain relief Live and Thrive with Endo: The Foundations DIY course One to one coaching info and application This episode is sponsored by BeYou Cramp Relief Patches. Soothe period cramps the natural way with these 100% natural and discreet menthol and eucalyptus oil stick on patches. Click here to find out more and to shop: https://beyouonline.co.uk/pages/how-it-works Produced by Chris Robson

My dear friend, if you have been betrayed by someone you love, listen to this message.#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024!Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

There are loads of people living outside but are actually in jail, enslaved. Here's what I mean.#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024!Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

God is working in your life!#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Your willpower will fail you. Do this instead. #FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Not all scars are ugly memories. Some scars are beautiful reminders. Let me explain.#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Avid listeners of the iGaming Daily podcast would have been teased the start of our CRM-focused podcast with Optimove's CEO, Pini Yakuel and today will see the start of this series. And on today's episode of iGaming Daily, sponsored by Optimove, a first of two parts, James Ross is joined by Pini Yakuel, where the two discuss Pini's ventures into the boxing ring, James' rollercoaster Fantasy Premier League week and discuss Optimove's 2023 Year-End letter to their stakeholders with Pini providing listeners with a educational foundation on the current state of CRM that will aid us moving forward in the series. Later in the show, Pini also offers a glimpse into Optimove Connect, a conference that's being held in London on March 20-21. To find out more about Optimove Connect, click on the following link:- https://connect.optimove.com/Host: James RossGuest: Pini YakuelProducer: Anaya McDonaldEditor: James RossRemember to check out our partners Optimove at https://hubs.la/Q02gLC5L0 or go to Optimove.com/sbc to get your first month free when buying the industry's leading customer-loyalty service.To get your Super Early Bird tickets for CasinoBeats Summit, click on the following link:- https://sbcevents.com/casinobeats-summit/tickets/

Can a multimillionaire be poor at the same time? Let me tell you this heart-striking story.#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Branded slot games have been around for decades with its popularity catapulted by the rise of online casino. The compelling mix of popular franchises, iconic characters, and beloved pop culture is a recipe for success and an important onboarding tool for attracting and retraining new players.And this will be the conversation on today's episode of iGaming Daily, sponsored by Optimove, where I am joined by Danny Lee, Business Journalist for SlotBeats, to go over all things branded slots. Host: James RossGuest: Danny LeeProducer: Anaya McDonaldEditor: James RossRemember to check out our partners Optimove at https://hubs.la/Q02gLC5L0 or go to Optimove.com/sbc to get your first month free when buying the industry's leading customer-loyalty service. To get your Super Early Bird tickets for CasinoBeats Summit, click on the following link:- https://sbcevents.com/casinobeats-summit/tickets/

Today my dear friend, I'm going to teach you how to fight your 3 worst enemies!#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Our first ever demo day aimed for 15-20 people and ended up ballooning to >200 and covered in the news. We are now running the 2024 edition in SF on Feb 23: Latent Space Final Frontiers, a startup and research competition in “The Autonomous Workforce”, ​”Beyond Transformers & GPUs”, and “​Embodied AI”. RSVP here! You can find all LS online/IRL events on our new calendar. Super Early Bird tickets have just gone on sale for AI Engineer World's Fair, June 25-27!Today we have the honor of hosting two of Together AI's co-founders: Ce Zhang (CTO) and Vipul Ved Prakash (CEO). This is a rare opportunity to recap the history of the company since our last check-in with Tri Dao (Chief Scientist), some of their big releases, and do a deep dive into the state of the AI inference market. Together has emerged as one of the most consequential new startups in the new AI summer, last announcing a ~$100m Series A raise in November (at a ~$360-565m valuation). But there are at least three Togethers - Together the Research Lab, Together the Fine Tuning & Inference platform, and Together the custom models service. As we clarify on the pod, the overarching philosophy of Together is the ability to improve on all these fronts simultaneously by being “full stack”, from the lowest level kernel and systems programming to the highest level mathematical abstractions driving new model architectures and inference algorithms.Bringing Research and Industry TogetherIn just one year, Together has been behind some of the most exciting research in AI:* RedPajama, a fully open source dataset for model pre-training which mirrored the Llama1 recipe. Then followed by RedPajama2, a 30T tokens dataset of filtered and de-duplicated tokens. * RedPajama-INCITE-3B and 7B, which were SOTA in a few benchmarks at the time of release. * FlashAttention-2, developed by Together's Chief Scientist Tri Dao. We covered FA-2 in a previous episode with him.* Mamba-3B, the most promising transformer-alternative model that they released in collaboration with Cartesia. * StripedHyena, a SOTA graft of Hyena state space models and transformer models together* Medusa, an alternative to speculative decoding that lets you use multiple decoding heads instead of a draft model. * MonarchMixer, which was one of the most popular orals at NeurIPS 2023. It's an approach to transformers that replaces many of its core parts with Monarch matrices for better computational efficiency. And I'm sure we missed something! As Vipul reveals, almost 50% of Together staff is researchers, and two of their co-founders (Chris Ré and Percy Liang) are professors at Stanford, so we can expect a lot more here.Bringing “Disaggregated” GPUs TogetherOn their cloud, they offer inference as a service, fine-tuning, pre-training, etc, but unlike other providers they think of themselves as a disaggregated cloud. Today, they have ~8,000 A100 and H100 GPUs on their platform (an exclusive revealed on the pod!) totaling over 20 exaflops of compute, but instead of just buying more and putting them in a cluster and then exposing a `us-east-1` option for customers, they are taking heterogenous compute sources and adding a unified layer on top of it for developers to consume. Building on Ce's research, Together's GPU Clusters are taking on comparable AWS and GCP offerings in both cost and speed:Take the Hessian AI center in Germany or the DoE's INCITE; they have GPUs that they want to share with researchers, but they lack the cloud layer over it. Similarly, there's starting to be more and more differentiation amongst types of GPUs: H100s, A100s, MI3000s, etc. Each of them has different availability and performance based on task, and the end user shouldn't have to be an hardware expert to run inference on a model, so Together abstracts a lot of that away.A big theme of the Together inference stack, a “bag of 50 tricks” that we discuss on the pod, is also “hardware-aware” algorithms like FlashAttention and Mamba, which further emphasize the benefits of co-developing everything together:Special Focus: Transformer AlternativesAs we mentioned above, they are also funding a lot of research in Transformer alternatives. To reiterate a few points on why they matter:* Longer context is not the motivation for sub-quadratic architectures: Transformers don't inherently have hard limitations on context size, but they just get extremely expensive. When developing sub-quadratic alternatives, you easily enable very long context, but that's now how you should compare them. Even at same context size, inference and training is much cheaper on sub-quadratic architectures like Hyena.* Emergence of hybrid architectures: a lot of early conversations have been around the “post-Transformers” era, but it might be more like “half-Transformers”. Hybrid architectures could have split layers with some transformer-based and some state-space ones. One of the challenges is that a lot of hardware kernels are optimized for transformer operations, so you'd lose a lot by moving away completely.* Higher speed = higher GPU throughput: if we could reach the same benchmark performance on subquadratic architectures, it'd solve a lot of the GPU crunch. Today we peak at ~170 tok/s on inference in some open models; if we could reach 5,000 tok/s on the same card, you'd be able to serve 30x more customers on the same hardware. As a cloud provider, you're obviously incentivized to get there.We had a lot of fun chatting with the Together guys and we covered a lot of ground, so enjoy the conversation!Note: This is the first episode of a “cloud providers mini-series”. We have Erik from Modal and Ben from Replicate coming up next!Video PodcastJoin us to watching the video version of this pod on our snazzy YouTube!Show Notes* Together AI* RedPajama Dataset v1 Announcement* RedPajama Models v1 Announcement* Together Embeddings* StripedHyena-7B* Mamba-3B-SlimPJ* Vipul's X thread on Anyscale* Vipul's Razor* SemiAnalysis' "Inference Race to the Bottom" post* Chris Ré* Mike Conover's episode* Slim Pajama by Cerebras* Dolma by AI2* Jina AI* Tengyu's Voyage AITimestamps* [00:00:00] Introductions* [00:00:43] Origin and current state of Together.ai* [00:02:15] Transition from Apple to Together and the vision for open AI* [00:04:54] How Chris Ré introduced Ce and Vipul* [00:08:43] How RedPajama came to be* [00:13:34] Model training and Transformer alternatives* [00:15:37] DSIR and the importance of data in LLMs* [00:21:19] Inference vs Fine-tuning vs Pre-training usage on Together* [00:23:20] Together's GPU stash* [00:27:02] Why standardization of inference metrics is important* [00:29:26] Building moats in AI inference* [00:31:49] Federated vs disaggregated cloud computing* [00:34:57] Opportunities for improvement in the inference stack* [00:36:13] Anyscale benchmarking drama* [00:41:27] Not just an inference platform* [00:43:50] Together Embeddings and the future of embedding models* [00:45:53] State space models and hybrid architectures* [00:53:52] The need for 5,000 tokens/s speed in AI inference* [01:00:23] What's the most interesting unsolved question in AI?TranscriptAlessio [00:00:00]: Hey, everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO in Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol.ai.Swyx [00:00:14]: Hey, and today we're together with Together. Welcome to the studio, guys.Ce / Vipul [00:00:20]: Thank you.Swyx [00:00:21]: I don't know how you typically give self intros, but does anyone want to go first? How do we get our audience acquainted, especially to who's speaking, because it's unusual for us to do a four-person pod. Yeah.Ce [00:00:33]: Hi, everyone. I'm Ce. I'm one of the co-founders of Together and the CTO, working with the team on technical things.Vipul [00:00:40]: I'm Vipul Ved Prakash, co-founder and CEO of Together.Swyx [00:00:43]: I always consider you guys as one of the sort of all-in-one companies. I always want to say labs, but I feel like you're not a lab. What is the sort of origin of Together, and then what is it today? I feel like it used to be Together.xyz, and then now you're Together.ai.Vipul [00:01:00]: I think fundamentally, Together is about open and independent AI systems. We think this is one of the most consequential technologies of our time, and when we started the company in June 2022, our focus was to build a platform for open source, independent, user-owned AI systems. One way to think about it is big labs, frontier model labs, have built their own platforms for developer platforms for their models. We think of Together as a platform for everything else, whether these are open models, whether these are models being built by companies that are owned by them. Our sort of XYZ roots, we have a fairly deep decentralization and open ethos that kind of reflects in all our platform and strategy and business. And we also, the way we structure our cloud is by combining data centers around the world instead of, you know, we are today not located in hyperscalers, we have built a footprint of AI supercomputers in this sort of very disaggregated, decentralized manner.Alessio [00:02:15]: I know before Together, you were at Apple, so you go from like the most walled garden, private, we don't say anything company, to we want everything to be open and everybody to know somebody. What maybe did you learn from like the Apple way of being super close and polished and maybe what are you taking now to Together to make it open, but also a very nice developer experience?Vipul [00:02:37]: Yeah, I would say, you know, one sort of my, you know, background has been in open source for a long time. One of the first things I created was a collaborative spam filter, you know, this was back in the day. It's called Vipul's Razor. And it became quite popular. And the first company I founded called CloudMark was built around, you know, taking open source and building both an open side of it and a commercial product around it. I think Apple is sort of very focused on providing this amazing experience to its customers with, you know, most of the technology sort of hidden behind the product. And certainly the focus on fluidity and applying complex technology to make everyday things simple is something that Apple does really well. And, you know, that's been a sort of big part of how we think about our developer platforms. I think it informs it. The other thing is that during my years at Apple, we, you know, worked a lot on deep learning. And one of the things that was sort of very viscerally accessible to me was how well these systems worked. We, you know, we built an open domain Q&A system. This was based on Facebook's LSTM paper in 2016. And it was remarkable because we had a parallel system based on sort of information retrieval techniques, which is extremely complicated, didn't work that well. And you know, this thing we wrote in a week was just incredible performance. So I think some of those experiences, at least for me personally, sort of were creating this roadmap of how important and powerful this technology is. And you know, when the scaling loss paper was published, I was very clear, like it was in some ways something very profound. We've never had algorithms that improve in capabilities with scale out. So this is almost a new era of computing. So that's been, I think, the influence of Apple, my years at Apple, really for me, like crystallized the value of what we are doing together.Alessio [00:04:54]: And how did you decide to join forces? Because you did a postdoc with Chris Ré at Stanford. You know, we already had Tri Dao from Together and we talked about Hazy. What was like the meeting of the mind of, hey, I come from like the more technical postdoc assistant professor background and we've got yet a more product thing. What got you excited to like build this now?Ce [00:05:15]: So we have been working on this together, Chris, in the essentially last like 10 years, right? So it was like a machine learning system 10 years ago was like Power BI's graphic model, right? And then convolutional neural network and then all the foundation model that we see today. But if you look at this, I think that fundamentally the thing we are actually optimizing is actually not that different. It's always about data movement across essentially all the stacks, right? So when you do distributed like computing, it's about communication across different machines. When you do, for example, flash attention, it's about data movement at a different essentially memory hierarchy, right? So we have been doing this in the last 10 years and seeing the field start grow, grow, grow. So we kind of feel the current kind of this like wave of technology is actually the perfect time to actually bring all the research essentially into something real. And we are super lucky that we got introduced to Weibo, right? And then we hope to join forces and bring this to real world.Swyx [00:06:10]: It's an unusual team of like sort of research and industry. Like you've been like a third or fourth time founder now. Third time founder, yeah. And so like what is your first order of business when you like set up together? Like how do you sort of put something like this together? Oh my God, I'm going to use this word so much.Vipul [00:06:27]: I feel AI companies are really kind of driven by research. And Chris and I had been talking about how to reduce the cost of building models. We felt that there aren't really big data modes around foundation models. They are built from a subset of the web. What is difficult is the cost of capital to build these. And one of the ways in which you can reduce this cost is by making more efficient systems. With that, it was really about finding the right set of co-founders and team. In fact, when Chris introduced me to Ce, and I think within the first five minutes of talking to Ce, I was like, we are starting this company. And our early focus was thinking about this more sort of disparate set of resources, you know, GPUs around the internet. Can we use those to build? And we really have to compress communication for, you know, when we do gradient averaging, there's just a lot of traffic. And if you can reduce that somehow, you sort of open up the possibility of using cheaper compute, you know, across the network. And Ce's research for a decade has been in that subject. You know, and from there, finding, you know, other folks in the network, I think there is generally a lot of excitement and philosophical alignment around what we are doing, which, you know, we publish papers, we publish open source libraries and code, we build open models. And I think the people in academia in, you know, machine learning and NLP, that's really what they want to do. So I think that's been really a kind of kernel for, you know, composition of the company. And we're lucky to have, you know, at this point, attracted some of the best researchers in the field. So I think that's the most important thing. And, you know, the rest of it is sort of driven by us. A couple of these philosophies around independent systems and decentralization and good developer interfaces, you want to make it accessible. That's, you know, just as important. And the rest follows from there, I think.Alessio [00:08:43]: I want to try and fill in some of the blanks in the history of Together. I think people come on your website today and they say, you raised a hundred million dollars Series A. They're like, wow, these guys are like super legit company. But it feels like Red Pajama just came out a year ago. I remember we had Mike Conover in the studio, who had built Dolly at Databricks. And you announced it literally the morning we were recording. So we're like in the studio on our phones, looking at it. And it's like, wow, this is like the first time now there's like a good curated dataset to do open pre-training. So maybe let's start from there. Like, what was the motivation behind it? Why did you decide to do that? It's, datasets are one of the things that most people don't want to work on. They just want to do models, not datasets.Ce [00:09:27]: Yeah. So, yeah, first one is not the first, right? So I think it's actually built on a whole bunch of amazing effort the community already have. For example, Eleuther have the pile, right? There's a whole bunch of amazing datasets they have, like C4, right, from Google, right? So I think really get inspired by the impact those like datasets have on the community, right? So I think when we did Red Pajama, it was a time that people are really fascinated by Lama, the model, like Lama 1, right? Which I feel like decades ago, right? But it's kind of, people are really excited about the quality, right? So that's really like a big shift in people how to think about open model. People start to see hope, right? So, but the one problem of Lama is the data recipe is being described in a pretty detailed way in the paper, but the data is actually not there. So, and our original thinking is how about we take the recipe and we try to do our best effort reproduction and try to put it out, such that we can learn from our mistakes in the reproduction together, right? So that's essentially the original thinking behind Red Pajama. And we have been pretty happy and excited about what community have been kind of build on it. For example, there's a dataset called Slim Pajama, right? Which do deduplication over our data, right?Swyx [00:10:38]: From Cerebras, did they talk to you before?Ce [00:10:39]: Oh, yeah, yeah, yeah, yeah. So, yeah, so we are very good friends so we can discuss about technical perspective. We are pretty excited because I think it's kind of why we do Red Pajama in the first place is that people can actually build not only models, but also datasets essentially over that piece of artifact, right? So that's actually what inspired us to do the first version of Red Pajama dataset.Swyx [00:11:01]: Yeah, and then you released V2 maybe two months ago.Ce [00:11:04]: Yeah.Swyx [00:11:05]: 30 trillion tokens.Ce [00:11:06]: Yeah, 30 trillion tokens. So I think what's exciting about Red Pajama V2 is not only the number of tokens, but we start to kind of learn from Red Pajama V1. So one thing that we learned was that data quality is really the core, right? So you want to take this couple trillion token dataset and try to bring them down maybe to one trillion or two trillion, right? The way that you actually filter them, deduplicate them is not something that kind of pre-decided before you see the application, right? So you kind of want to have a modular framework to think about data quality, right? So like given application, let's automatically or maybe semi-automatically try to come up with a way to filter it down. So that's why in Red Pajama V2, we kind of overlay the dataset with like 40 different pre-computed quality signal, right? If you want to reproduce your best effort, like C4 filter, it's kind of like 20 lines of code, right? And this open up this opportunity you can actually put different filter together, learn the combination of filter. We are very excited to see what community actually come up with using Red Pajama V2.Swyx [00:12:11]: It was retrospectively so obvious that this is a good idea that I wonder how come more datasets don't do this. You release the dataset with all these toggles that you can turn on and off, right? And you can sort of tune up and down the quality in ways that you believe is important to you. Yeah, I just, it makes so much sense now in retrospect. Because everyone just publishes like their pipeline and then the end result. But what about all the intermediate stages? Yeah.Ce [00:12:35]: Yeah, so I think, so there are multiple things there. I don't think we are the only one like doing that. For example, like Doma from AI2, right? They have this very flexible format to actually put in those quality signals, right? Think like, we are actually calling them some, right? So you can actually load Red Pajama using their tool. That whole thing should work, right? So I think one fundamental thing that changed in the last year, essentially, in the beginning when people think about data, it's always like a byproduct of the model, right? You release the model, you also release the data, right? The data side is there essentially to show people, ah, if you train on this data, you'll get a good model. But I think what started to change is when people started building more and more of those models, people started to realize like different subset of data side is kind of valuable for different applications, right? The data becomes something to play with, right? So I think we are kind of lucky that we happen to release Red Pajama right at that point that we get this opportunity to actually learn from that.Alessio [00:13:34]: And you guys have a custom model training platform on Together 2. You have a bunch of stuff in there for data selection, like the DSIR and things like that. How did you decide to work on that versus, because you first started with like some of the fine tunes on LLAMA. Do you see a lot of interest there? And I know you've been doing a lot of research on state space models and other transformer alternatives. Like, do you also see that as something you'll keep working on this year and push more people towards?Vipul [00:14:02]: Yeah, I mean, we, you know, we think of how to make training more efficient and building models more efficient. Part of that is being able to select the right dataset. This is why you have signals, DSIR. You can start with a small dataset and find similar documents, build models with that. So we think it's an important part of the kind of model build tooling that, you know, sort of widely useful for people building different kinds of models. Similarly, you know, we are running into the limits of how fast you can make transformers. And we want inference at 5,000 tokens per second. I don't think we will get there with transformers and we need to learn longer sequences. Data, again, becomes very, very expensive with transformers. So I work on space state models and all the research that we are doing there. And hopefully other labs will pick up on this and make it a kind of important target for optimization. But we think that, you know, open source is a great place for this. We can provide these recipes for data and for training to our customers who are building, you know, custom models themselves. And, you know, we are quite excited about the sort of progress we are seeing there.Alessio [00:15:18]: Do you have some of these models available for inference on Together? Can people play around with a strictly, you know?Swyx [00:15:25]: Yeah.Vipul [00:15:25]: Yeah, they're available for inference on our serverless platform.Swyx [00:15:29]: I always try to be the person who asks about acronyms in case, you know, people want to understand. Should we explain importance resampling, you know, that kind of stuff?Ce [00:15:37]: Oh, yeah. So DSIR essentially, it's a fundamental idea. So it's one of the paper from Percy, right? So essentially, if you know what you are doing, you can actually use that as a very strong signal about what data to put in to insert training process, right? So that's essentially the fundamental idea, right? So, and then more concretely, right? So there are actually different versions of DSIR, right? So one version is like if you have a validation site, right? You can actually somehow measure the similarity between the validation site and also your pre-trained corpus and essentially subset, like the subset. And often there's actually like less targeted version of DSIR where you'll say, yeah, maybe Wikipedia is actually a very good corpus. Let's try to find more Wikipedia, right? And you can think about it in two ways, either as a way to come up with different weights for different data slices. Yeah, so as like filter type of step. Yeah, for a data set, or think about that as like data augmentation. So that's how, yeah, that's how we think about DSIR.Swyx [00:16:33]: That makes sense. I will have to read the paper to understand a little bit more. Because when you say things like, we have to know in advance what we were trying to do with the model, then we do importance resampling. That is against the principle of general intelligence, right? Like the point is to train AGI.Ce [00:16:48]: Yeah, so it depends on what do you mean by being general or generic, right? So I think, I mean, you can always take a meta-learning perspective that we know the distribution of tasks that we care about, right? So you can always go kind of up in the ladder of how general the whole thing is, right? But also for many of the customers that we are actually talking to, right, they have kind of very targeted application, right? The benefit you can get out of that is you could build a better open model, often smaller, often easier to do inference, if you know what you want, right? So I think the whole trade-off would be, and the x-axis would be how generic the whole thing will be. The y-axis would be not only the top accuracy, but also a whole bunch of the deployment cost, right? The size of the model, right? The robustness of the model. So I think different people will navigate the space in different way. And we want to be the platform, essentially, whatever point that you want, we have a solution for you.Swyx [00:17:43]: One more thing on data before we go deeper on state-space models. Are we running out of data? Can we go in order of magnitude? Can we go five orders of magnitude? How do both of you think about how much data we have and how much we need?Ce [00:17:55]: Yeah, so I think that's a very, very good question. So I don't think we are running out of data on Earth.Swyx [00:18:02]: Right, so think about it globally. Training data, training class data.Ce [00:18:05]: Yeah, yeah, so I think, I mean, some of them are not accessible, right? But I do think there are many organizations in the world have enough data to actually train very, very good models, right? So, I mean, they are not publicly available, right? But there are people who actually have access to those, right? So I think in general, right? So if you think about the data in the open space, right? So I guess that was specifically that you actually mean whether we are running out of data. I do think there need to be some way, right? That people who are training open models get connected with essentially data that's not internet data. So I think that channel need to be opened up for the open model to get more data, right? But I'm kind of on the optimistic side that the society will figure out a way that we can train open models that's beyond this internet data.Swyx [00:18:57]: Beyond internet, meaning books?Ce [00:19:00]: I mean, there are a lot of those, right?Swyx [00:19:02]: Books, right?Ce [00:19:02]: Transcripts, right? Videos, audios, right? So there are a whole bunch of data sources that we are not integrating into open data side, right? So, and maybe they shouldn't be open, right? So I think the community need to figure out a way, yeah, like the best balance, yeah? Such that we can have open models, but on the other hand, also have a reasonable collection of data that we can actually use.Swyx [00:19:29]: I think a lot of people think that, there's a theory that Whisper was released so that you could transcribe YouTube and then use that as a source of tokens. Then I talked to other researchers who are like, you know, YouTube has very low quality tokens. You know, do you want your model to talk like a live streamer from YouTube? Because that's what they're going to do. So it's not clear, like what the quality of this data could be.Ce [00:19:53]: Yeah, I guess that depends on your application, right? So I think as a platform, right? So our goal is whatever application that you have, yeah, so we have a platform that you can actually achieve your goal, right? So there are definitely applications that kind of make sense to speak like YouTube, right? So, but there are probably also other application that kind of more on the formal side, right? So I think there are going to be a diverse collection of models, both open and closed, right? So, and we kind of want to be the engine that powers that.Swyx [00:20:21]: There's a lot of people who own data sources who are doing the locally optimal thing and humanity as a whole is losing out. So like New York Times is swinging open AI, you know, Stack Overflow shut down their API, Reddit shut down their API, X, you know, made their own model, right? On Twitter data. We're just going to have all these like tiny little gardens of data that it would be useful in a general model, but everyone's just trying to make their own model. And it seems like globally suboptimal.Vipul [00:20:47]: I think you need to have some kind of a marketplace for figuring out how to get this, you know, data into models and have, I think we'll increasingly see more of that. You know, I think there's a positive aspect to it too. There is a incentive for creators to participate in a system, which is sort of more fair relative to, you know, the capture of value by an AI company that's taking their data. But I agree. I think this is a big open problem that needs to be solved. And I hope there will be, you know, serious efforts around it.Alessio [00:21:19]: Let's talk about the most precious resource on planet earth, GPUs. You have a lot of compute obviously, but you also have a lot of product pieces. You have inference, you have fine tuning, you have pre-training. What's the split in terms of usage? Do you see most people are just running inference on off the shelf models? Do you see maybe some last mile fine tuning?Vipul [00:21:40]: I would say right now, the top five models on our inference stack are probably all fine-tuned versions of open models. And we've seen- Who fine-tuned them?Swyx [00:21:51]: You fine-tuned them?Vipul [00:21:52]: They were fine-tuned by our customers.Swyx [00:21:54]: By your customers.Vipul [00:21:55]: You know, either on our platform or off our platform. And we are generally seeing that, you know, that is the sort of trend where you can get better quality on your task by sort of now easily adapting these models to your data. We also have, I would say, over 20 big model builds happening on the platform, which are customer. We see a lot of training and it's also somewhat surprisingly a more continuous kind of workload. We sort of imagine that this would be more episodic. You train a model and then you do inference. But what we find is, you know, we train a model and then they train the next version and then the next version, which sort of grows in scale. I would say training is still the bigger portion. Some ways inference is super linear to model quality. And as the models are getting better, there's more and more inference.Swyx [00:22:48]: Oh, because they're more useful. Yeah, they're more useful, yeah. So, okay, so training is bigger. This is actually consistent with what we've heard from Mosaic, that, you know, people think that training is sort of like a one-time deal. You do one big run and then you're done. It's never true. And so I'm interested in, like, putting some numbers and I don't know what you have disclosed or what you want to disclose, but, like, how many GPUs do you have? What is the equivalent amount of compute that you have? Because I understand that your GPU setup is different than what people typically think of, like, a giant data center somewhere, right?Vipul [00:23:20]: I don't think we have shared this number publicly. It's, you know, so this will be the first time, I guess. Like, we have close to 7,000 to 8,000 GPUs today. It's growing monthly.Swyx [00:23:31]: What class of GPU are they?Vipul [00:23:32]: They're mostly A100s and H100s.Swyx [00:23:35]: Okay.Vipul [00:23:36]: And probably more, I think, split towards H100s now. You know, we'll be sort of building this best-of-class hardware. So as there are other versions of these coming out later this year, we plan to have those in the fleet as well.Alessio [00:23:53]: I know when we talked last year, you were also using some of the supercomputers by the Department of Energy. There was kind of like a lot of random GPU compute in the world. Have you seen that kind of getting timed out? I think maybe a year ago, people were like, oh, yeah, you can use this GPU computer that is going to be end-of-life. Has the bar changed to give access to those resources?Ce [00:24:13]: From our perspective, it's actually getting better. Yeah, so from the community perspective, because many of the institutions in the world, they're actually investing in hardware, right? So for example, we are working with one of the institutes in Germany called Hessian AI, right, which gives us a lot of help on the compute side. So they start to have this very big GPU cluster, and they're actually sharing that with the community, right? And it's not super big, right, but also not a small one, right? So you start to see this, like, different lives that start to pop up, right? And because of the power of the community, they start to actually share that. So we actually find as a researcher today, it's probably easier for them to actually get a GPU than last year.Swyx [00:24:56]: Interesting.Alessio [00:24:56]: And then for you to buy them, what's the state of the market right now? Is it still extremely hard to get any? Do you have Jensen's phone number? Do you have like GM phone number? Do you guys get like the SDR because you're like under 10,000?Vipul [00:25:12]: NVIDIA is obviously motivated to help us, both as an investor and we are their customers. I would say the market is very tight still, and it's likely going to be this way for a while, is my sense that the demand for AI computing is just kind of ramped up very, very quickly, and it will take a while for supply to catch up.Swyx [00:25:37]: So how tight it is, and let's say compared to like a year ago, two years ago, what do you mean when you say tight? The things you want, you can't get?Vipul [00:25:42]: You can't get them immediately. They're sort of, you know, minimally like two to three months out. Any inventory that shows up tends to clear very, very rapidly. And, you know, we obviously sort of look at this in a very detailed and analytic. There is four to 5 million GPUs that will be sold this year from NVIDIA and others buying. And if you think about 512 to 1,000 GPU cluster for a company, that's 4,000 to 8,000 companies, right? So it's in some ways a very small number. In other ways, the cost of GPUs will be, you know, 80 to $100 billion, and then you layer servers and data center space and electricity on top of that, and that's, you know, close to $250 billion worth of kind of compute, which when you compare it to the cloud computing of today, you know, AWS's last year was $88 billion in revenue. So this is really kind of a build-out happening of AI hyperscalers. It is much more disaggregated, and it's very, very global. So, you know, we think that GPUs are going to be sort of a precious resource for a long time, and using them optimally is very valuable.Swyx [00:27:02]: Yeah.Alessio [00:27:02]: Our friend, Dylan Patel from Semianalysis, he wrote a post about the inference market recently and obviously mentioned you guys. In his post, he said, our model indicates that Together is better off using two A180 gig system rather than a H100-based system. The temperature and performance testing also point to Together utilizing speculative decoding. Any thoughts? Is Dylan right? I don't know, what's-Swyx [00:27:26]: What is his model, man? What does he know that they don't know? Yeah, exactly.Alessio [00:27:30]: I wanna know, I guess like from the outside, and sometimes we even do it, we try and speculate on what people are actually doing. So for the first time, now we have a former guest writing about a current guest. So we wanna know what you guys thought and maybe what are some of the misconceptions that people from the outside have on what it takes to run like a GPU cloud today?Vipul [00:27:50]: Yeah, big fan of Dylan's, by the way. I religiously read Semianalysis. I think there were some errors in that analysis. In particular, we were trying to decode it and one of the things we noticed is that it assumed that input tokens weren't being priced. So I think that may have been an error in the model. I also don't think that there's this assumption that people are running this at a loss. I think it's very expensive. You can't do that for very long. And there are trade-offs in terms of batch sizes you use and the kind of tokens per second performance that are kind of system trade-offs. We've done a lot of work. This is one of the key areas of research for us. So our inference stack is a combination of 50 different sort of tricks and techniques and we think there's a lot of room for optimization here. So whichever hardware provides better performance, whether it's H100 or A100s or L40s, we can sort of measure price performance on particular hardware and we tend to use that for that model or in some cases, certain customers have data streams which can be then optimized for a particular configuration regime. So we do fairly detailed work on how to make this more efficient and so it's hard to, from the outside, looking at memory bandwidth and estimating what's actually happening.Alessio [00:29:26]: How much of these 50 tricks are you giving to yourself and how many are you gonna open? Because we have three now, obviously Flash Attention 2 is open source. He mentioned he'd love to come work together because of how much you care about open source. Yeah, how do you weigh that as a CEO and CTO?Vipul [00:29:43]: A lot of it is open, right? Flash Attention, Flash Decoding, et cetera, and we publish something that's very generally universally useful. It's going to produce better open source AI. We tend to publish as open source. I think on the inference stack, there are open source inference stacks which are pretty good and definitely today, it gives us a competitive advantage to have the best one. So we are not sort of rushing out to release everything about it. It's not overall that additive to open source out there and it is particularly useful as a business for us to provide best price performance. Yeah, we make these decisions. We have discussions. Anything that we keep closed, we generally talk about it quite a bit and decide like this is the piece that is closed for today and it may not be the case six months from now. It may not matter as much.Ce [00:30:40]: Yeah, so I think being open is kind of very important, right? So I think the whole company actually built on this idea that there's going to be ecosystem built on our open models, right? And that's also how we are really lucky to attract this top group of talents to actually join us because of the dream and the mission that we have on our side to really facilitate the open ecosystem, right? So I think in general, it's like I think all the ideas should be open. So that's why we publish papers, right? We actually talk about ideas, right? So I don't think it makes any sense to keep idea like close, right? So there are some software artifact that are kind of really deeply embedded into our kind of own kind of like stack. It kind of only useful when you're trying to build a disaggregated cloud, right? Maybe at some point that we're going to be open as people said, right? But at this moment, right? So we are kind of busy actually building it, right? So that's probably kind of getting to the picture about when that piece is going to be open, right? But I think on the research side, the ideas and for our people to publish things, I think that's really, really important, right? So I think that's how we get talent. That's how I think we as a company going to move the field forward.Swyx [00:31:49]: I noticed that you never used the word federated learning or inference. Is there a distinction that you draw?Ce [00:31:55]: So, I mean, it's definitely not intentional, but I think federated learning is, have been used in so many different ways by so many different people. It starts to lose a very precise meaning about what that really mean, right? If you go back to the original Google paper of federated learning, I think that's very different from what people are talking about today when they say federated. Yeah, we kind of want to be really precise about it.Swyx [00:32:18]: And so your term is disaggregated.Ce [00:32:19]: Yeah, so as an infrastructure, right? So that's disaggregated.Swyx [00:32:22]: Aren't most clouds disaggregated? Like what's different about it?Ce [00:32:27]: So one way is that most of the cloud are disaggregated, but some of that is actually being exposed to the user, right? If you go to AWS, you do know which region you are in, right? So I think one thing that we are trying to do is you have this disaggregated cloud, not only about location or geographically where they are, but about this reliability and also this diversity of this infrastructure. So, and if we want to build a reliable, high-quality layer over that, the user actually don't know, right? What's actually happening under the cover, right? So I think that's one of the difference of the way that we are thinking about infrastructure.Swyx [00:33:06]: Yeah, a bit closer to Cloudflare than AWS. Yeah. Yeah. We have one question here, which we'll just throw out, it's kind of fun. So going back to this sort of inference stack piece, maybe if you had to pull out like a call for researcher or just like point out interesting areas of work that you're interested in, what pieces of the stack have the most opportunity for improvement?Ce [00:33:27]: Yeah, so I think the way we are thinking about the inference stack is, so there are multiple things that can happen, right? So you can do better algorithms, like speckle decoding, you can change the model architecture, you can go really crazy on the system side, right? And you can also code it on the hardware, right? So it's not really clear innovation on a single dimension will get you there. So the key thesis on our side is, if you only push on one direction, you are going to reach diminishing return really, really quickly. Yeah, there's only that much you can do on the system side, only that much you can do on the algorithm side. I think the only big thing that's going to happen is when you ask all those dimensions to actually compound, right? So to have algorithm, model, and system all come together, so I think that's how we reach the next 10 times improvement on inference, right? So I don't think there's a single dimension that is particularly important, but looking at this space in a joint way, right? Try to co-optimize jointly multiple dimensions, I think that's going to be really important for the community to look at.Vipul [00:34:28]: Yeah, we often see, I see numbers from the team and you have these multiple methods, not all of them compound. So you mix these together, it's still similar results and some combination of them will have this incredible effect that is really, really super interesting. So it's very systems, you know, a kind of broad systems approach to it that's the most effective.Swyx [00:34:51]: I think I finally get the name of the company, like- Bring it together, yeah. Everything needs to be automated together.Alessio [00:34:57]: All right, just quickly, how does all this work change, just like some of the architectures change? I know a mixture of experts like speculative decoding is a little less efficient because of memory bandwidth. How much of it do you invest when it's a maybe model-specific improvement versus more horizontal thing? Also, you're researching different architectures, so how much do you want to spend time optimizing what state of the art today versus what's coming next?Vipul [00:35:24]: We do spend time on what state of the art today as well as what's next. You know, the value we get from doing specific optimization, even for, you know, what works well for a particular model on A100s with a particular bus versus H100s, it's a worthwhile investment for us. So we will go down fairly deep into a specific architecture and specific hardware. It does also inform what works better where, and you don't have to take the same approach for, you know, every model and every sort of hardware setup. We can take these different approaches and we do have these multiple systems now. We know that this, you know, system B is better for mixed role and system C is going to be better for stripe tying or Mamba.Alessio [00:36:13]: Before we move on from inference, we need to talk about any scale of drama. So we're actually having Sumit on the podcast tomorrow, who also talked about, kind of came to your guys' support about how, yeah, how important it's not just like, oh, together saying this benchmark's not good because they look bad in it. How, I guess like, it's a hard question to ask, but like, why did you decide to just come out and say it? And how maybe does that also reflect the values that you guys have about open source and openness and kind of like being transparent about what's real and maybe hopes for standardizing some of these benchmarks to make it more clear?Ce [00:36:56]: So it's a great service and skills doing for the community, right? I mean, it's very hard to do benchmark. The moment you do benchmark comparing N players, right, N minus one will be unhappy. You have two tables, then maybe N of them will be unhappy, right? So it's a very great thing that they're doing. And in some of the work that we are doing, we actually use RMOperf, right? So it's a great thing that they're actually doing. So I think one thing about benchmark is, and probably the professor part of me are talking, is a good benchmark should think about how it's going to incentivize the field to actually move forward, right? So if the benchmark really become a kind of standard, how are people going to over-optimize to the benchmark if you are going to do that? And when people are doing that, what are we actually trying to incentivize, right? Will that move the world to a better place? Or will that essentially have every single player focus on marketing or spending time or money on something that actually do not matter on technical side, right? It's very hard to actually strike a balance, right? So I think the reason we kind of try to give feedback on the benchmark is kind of want to open up the discussion about how does the industry should come together and define maybe a common way that we compare with each other, right? So like how database people doing TPC, right? Maybe you should have something actually similar, right? So we are trying to start some of the conversation. So it's not really that we jump out to say it's not good because there's no way we can have a perfect benchmark. That doesn't really exist, right? So just try to kickstart a conversation that maybe we should come together and do something that the community agree and align with the benefit a user going to get, right? So just get the conversation started.Vipul [00:38:42]: I've spoken to the AnyScale team after that, and I think they had really great intentions. And partly, I think it felt very objective and everyone sort of had a reaction to it because it just didn't match their benchmarks that we've all run internally against different services. I think a common industry benchmark run by an independent party versus one of the vendors.Swyx [00:39:04]: Is there one that you appoint to?Vipul [00:39:06]: I don't think one exists today. I think there should be. We're having some conversations about someone setting one up. And there's lots of interesting aspects of this. Time to first token is a function of where the test was run from. There is different load on these services at different times of the day and weekday or weekend. So you have to measure that well. And I think if all of that were done very well by an independent source, that will be a very useful service to customers and in the services themselves.Swyx [00:39:39]: Yeah, I'll point people to artificialanalysis.ai, which is a new one that recently emerged. I don't know if they've done it right. It looks like a side project of a couple people. But I think it's in all the provider's interest to work with them. And ensure that there's an independent third party that's measuring these things, right? At least on the baseline. For me, what's worrying is more about what Toa was saying, which is, do these benchmarks skew things in ways that customers might not be mindful of? Like, what are these things overemphasizing that we might be missing? And I don't really know. It seems like a lot of these services bundled together, they're a version of quantization as well. So that means there's performance trade-offs, right? You're not comparing apples to apples, the same model itself, even though it's like a llama variant or whatever. So what do people trade off? They trade off latency, they trade off price. Obviously, those are the first two. But what else, right? What factors matter in an inference business?Ce [00:40:33]: Yeah, so I think there's also the throughput, right? So there's the time to first token, right? So, and then there are things that users do not often see, for example, the reliability, right? The capacity, right? So that also have impact on user experience at a global scale. Maybe not a single query, right? But in aggregation, you can also see a whole bunch of, like, whether you are emphasizing P50, P95, right? So the whole bunch of things that you can actually play with. And of course, there's also quality. So there are different ways to actually make the whole thing faster, specification, quantization, or combination of those, right? So yeah, so there are so many things to actually play with. So they probably need a benchmark that the protocol is transparent to make sure, like, it's very clear what we are doing and a whole bunch of check on the quality to make sure we are putting the right group of stories in the same table. So I think then essentially the user can actually navigate the space. So I think that's going to be good for everyone.Swyx [00:41:27]: Yeah, makes sense. It's a very important field and I think hopefully there's a good third party that emerges from this. So I just want to touch on one more piece, which is I think I'm appreciating from this discussion that fine tuning is a bigger part of your business than I thought. The other big player in fine tuning is Mosaic. Well, Mosaic is more training, but like there's a bunch of other players in the fine tuning space. If I was a prospective fine tuning customer, what do I come to you with? Do I come to you with my custom data and that's it? Do I also have to write the fine tuning code? What level of engagement do you do with your customers?Vipul [00:42:01]: I think across the spectrum, our customers are training models, pre-training models from scratch and many of them will bring their data sets, you know, user infrastructure and training stack to train their models. There are others who have trained smaller models and want to scale up, scale up across infrastructure, scale up across data. So we'll sort of help them do that. We will have customers who are sort of initially started a little bit more consultative. They have a particular task and idea in mind and we will help them get from there to the data set and the right model to achieve that task. So it's a spectrum and, you know, our goal is to, we're trying to productize as much of this as possible. So that the whole process can be fast and scalable. I would say there is a lot more understanding around fine tuning now, like even the last six months, there are, you know, source tools, recipes, literature, podcasts, discord channels where people are figuring out and it really is in many ways, one of the successes of open source is you have small collectives of, you know, engineers who have created, who are now creating the top models on open source leaderboards. And I have tried out all sorts of different sort of, you know, data recipes, creating synthetic data. Merging models. Merging models. So it's, that's really fun to see. And I think that sort of agency that exists now is exciting. And that is, we see a lot of that sort of being applied into products and, you know, more commercial models that people are deploying in their applications.Alessio [00:43:50]: And then just to, I guess, wrap up the together, it's almost becoming like a platform as a service, because now you release together embeddings. How did you get 92.5 accuracy on 32K retrieval? And do you think we're kind of like getting to embeddings or just like, we did everything that we could, you know, we're getting to like the most optimized it's gonna get and then we should just focus on models and inference or do you think there's still room there to improve?Ce [00:44:17]: Oh, I don't think we haven't even got started on embedding. Yeah. So I think there are so many things. So like embedding is really fundamental for many things, for example, rack, right? So deep in application. So that's how people bring knowledge in. That's also the fundamental piece when you want to build a better model, right? So that's give you this understanding about what actually get into the model. You can actually use that to actually build a better data set, get a better model, then get better embedding, you'll start this loop, right? Without the good embedding, the loop is not closed, right? So I think both on the quality side, how to embed more like dedicated semantics, like into those vectors, how to deal with negation, for example, right? So, and how can you make the whole thing really, really fast? So I think for the next couple years, yeah, we will see a whole bunch of new embeddings maybe of different size and much, much faster than today. Yeah, so I think it's a very active research area. I think people should invest more, yeah.Swyx [00:45:14]: I was surprised to see, I think Jina or, yeah, there's Jina AI, and then there's another guy, Tengyu's Voyage. They are coming out as startups purely focused on embeddings.Ce [00:45:25]: Yeah. Yeah, so I think it's a very, very important piece of the system, right? So you people haven't focused on a lot on them before, and they should definitely start to do that.Swyx [00:45:36]: Yeah. Why are the Chinese universities so good at embeddings? You know what I mean, right? Like the BGE and- Yeah, yeah, yeah.Ce [00:45:44]: So I don't know. We just released our first embedded model, so we still try to learn how to build an embedded model. Yeah, so ask me again in six months.Swyx [00:45:53]: I'll probably have more insight about how to build a better one. I just noticed that you saw 8002 was used to be at the top of the MTB chart, and then it's just like sliding down and down and down, and all the new models are coming out of China for some reason. And I'm like, I don't know what's going on there. So we cannot leave this discussion without talking about state space models. But first of all, how much of the company is dedicated to research? Like it's obviously like not production quality yet, but-Vipul [00:46:17]: I would say it's like 40, 45% I was counting this morning. That's huge.Swyx [00:46:22]: Yeah, so that's the biggest- It's a big investment. Yeah. Okay, well, I mean, it looks like it's paying off, so. And then high level, I will confess or admit or mention for the listeners who are also similarly skeptical, I did not used to care about long contexts because I was like, you know, 30K is enough, 100K is enough, right? I'm not, you know, modeling DNA sequences or anything like that. Why do I need long context? And I mean, first of all, I'll throw that open to you. But second of all, I think what Mamba did for me was change that perception of that. It's only about a long context. The only reason you want sub-quadratic architectures is for long context. Actually, that's not true. And it's also just more efficient to train, period. Right? I'll just leave that open to you. Like what's the motivation that people should keep in their heads? There are multiple things, right?Ce [00:47:09]: So one thing is that, I mean, the moment a model can do for long context well, so it often means that it's kind of cheaper. Yeah, so I mean, that's why it's kind of long. I mean, in principle, transformer can do long context. It's just very expensive. So I think what those like state-based models trying to do is try to push the size of the state, right? Like as small as possible. That's why it's kind of long context, right? And try to kind of like decouple this like quadratical dependency, right? To make sure you can have a much better execution pattern.One direct consequence of those is you can do long context really cheaply, but on the other hand, also introduce a whole bunch of benefit even you are not doing long context. Right? So I think that's actually probably equally important. Because data gets smaller, you can do really large batch size, right? You can actually be very faster. Right? So yeah. And another thing is like, one of the hypothesis that we have is, like in Stripe Hyena, it start to have a hybrid architecture, right? It has part of it has like state-based model and part of it is still the transformer. So different component probably deal with different things kind of better. So maybe by putting them together, by thinking about how information propagate, over this whole horizon of this context, you can probably get an even better quality model than transformer. Right? So I think that's why we are kind of invest a lot of things, on those models. Not only for the context, which is very important, but also for a whole bunch of benefit it could get.Swyx [00:48:42]: Yeah. How should people treat the distinction between Mamba and Stripe Hyena? Like what's the point of releasing these two as separate models? Is one like sort of the together proprietary one and then the other is like the more open research one?Ce [00:48:53]: Yeah. So I think it's pretty much a different stage of exploration. So they kind of have different hypothesis when we try to build those. Yeah. Like for instance, there are different view about state-based model. One is Hyena, another is like Mamba, right? They're actually different architecture. So when we build Stripe Hyena, right? So the curiosity that we have is how good can we... So what is the highest quality non-transformer model we can ever build? The goal of Stripe Hyena is try to see whether we can match Mistral. And by fine-tuning well, whether we can outperform that in some way, right? So it has a very, very strong baseline that we are trying to beat. So that's why there's hybrid scene, like getting the picture, right? And for Mamba, it's kind of more... The curiosity was how far can we push for pure architecture? Then we start from this very system make from small to large, right? All the way to 3 billion, right? So the baseline was essentially the best 3 billion model. So I guess at a different stage of exploration, at some point, I think they are going to converge. We actually learn different things, like when building different models. I think they are just like this intermediate stage in the exploration at different points.Alessio [00:50:02]: You mentioned the hybrid architecture. Is that the model grafting that you mentioned in the Stripe Hyena post where I mentioned you can have transformers and not together? Like this is a concept that I hadn't heard before reading about this. So I think most people's mental models, like transformers or something else, it's not transformers AND something else. How do you train a model that is hybrid? Is there any difference in like how you construct your datasets? Is there any difference in then how you run inference on it? How should people think about starting research in this field?Ce [00:50:36]: Yeah, so we were also very surprised. Yeah, so when we come up with this hybrid architecture. So the way to think about it is like you have different layers in the neural network, right? So like the stateless model for some layer will already give you the benefit. For the other layer, they could be transformers, right? They could give you this more global view of the sequence, but for me, for other layer, don't have to have that, right? I still can have all the other things that kick in, right? So we don't know what is the optimal mixture between different architectures. I mean, in principle, we can have a mamba, hyena, and transformer, all those things that come together, right? And then you can see what makes sense. We have no idea what is optimal doing that. So what we are excited about is now the community have a whole bunch of building blocks that they can actually like playing like a Lego, right? So just put together and see what happen, right? So we are kind of very excited about that. Yeah, we are in the process of trying to learn more like about this architecture. And when we know what we are talking about, we will definitely share with the community about how to do that in a systematic way.Swyx [00:51:41]: Cool. What are we still unsure about? Like, why don't we just, you know, put all the money in the world and training these things now? Like what is left to figure out before we scale this thing?Ce [00:51:53]: So like if you look at how transformer like it's been developed, right? In the last like five to 10 years, right? So people don't start from like, you have this attention to all you need the paper and then let's put all the money in, right? Always start from this very systematic understanding about the scaling, about data quality, about essentially the limits, right? I think for a state-based model from the labs to the real world, you kind of need to go through the same process. But of course, the second time doing that is kind of easier, right? But I think there's no way we can get rid of this systematic step of studying scaling law, study what data to put in, right? So what's the impact of different data slices to the data, yeah, to the final model quality.Swyx [00:52:33]: Do you expect that the data inputs will be different?Ce [00:52:37]: I don't know, but I wouldn't take that for granted that they should be the same, right? So that's one of the hypothesis that, so we have no opinion on that because I think that's the result of the study, not the assumption. Yeah, we do not need to assume that.Swyx [00:52:51]: Okay, scaling laws and data, anything else like architectural that we are not sure about? Because now you have this selection mechanism that you're pretty happy with.Ce [00:52:59]: Yeah, so, I mean, first of all, how to mix them, right? So, and second is what is the architecture? So if you look at transformer, right? So one very interesting piece there is people optimize also the hardware, yeah, to make sure that things run very fast, right?They're very efficient kernel, they're very efficient hardware. And then that's add another boost, right, for the transformer architecture, right? So that's something that should happen for state-based model. Which architecture is kind of easier kind of to run on the hardware, right? So, hosting going kind of faster, you can put more data, it add another dimension in the scaling law. So I think we just need to plow the whole space and just be really systematic from small model to 1 billion, 3 billion, 7 billion, just go all the way up, right? So I wouldn't jump around in the space. I would just like be patient and just like be systematic. Yeah, I think we'll get there, yeah.Swyx [00:53:52]: Yeah, well, I'm looking forward for more research from you guys to figure that out. So one dimension, which we didn't talk about, we talked about long context, we talked about efficiency, but speed is very, speed is also very important. A good inference provider provides, let's say 70 tokens per second, and then maybe that's faster than less good inference providers that are more like 30 tokens per second. But that's the rough range, right? State-of-the-art today. That's around the human speaking speed, human reading speed is about 200 words per minute. Why do we need 5,000 tokens per second is my question back to Vipul. And maybe is this something that is an emphasis for research as well, or is this more just an inference only thing?Vipul [00:54:29]: There are applications that are consuming the tokens that are produced from unmodeled, so they're not necessarily being read or heard by humans. That's a place where we see that level of requirement today that really nobody can quite satisfy. There is, can I think about, as intelligence grows, how do you sort of increase the bandwidth of, you know, how do you reduce the latency of it? If we can do 5,000 tokens a second, the same card can produce, the throughput of that card goes up significantly and can support more applications. So I think it's important from that perspective. And then there are, it opens up new UX possibilities. Once you can get sort of an immediate answer

Do you feel so stressed lately? If you answered yes, I invite you to hear my story.#FULLTANKwithBroBo #FULLTANKwithBroBo2024---P.S. Are you feeling a bit tired from your life's journey? How about taking a break with me at the Founders Retreat?Yes, my dear friend! I am inviting you for a Founders retreat. And guess where? In South Korea! Yay! This is happening on April 23-26, 2024! Let me tell you that it's not your usual trip – I'm talking soul-refreshing vibes, meaningful connections, and life skills that'll change your life radically all rolled into one. Take advantage of the Super Early Bird deal until February 29 when you click here right now: https://bosanchez.ph/founders/Support the show

Florian and Esther discuss the language industry news of the week, with Super Early Bird ending soon for SlatorCon Remote March and a save-the-date announcement for SlatorCon London, scheduled in person for May 23, 2024.Florian talks about how translation GPTs are becoming increasingly available on OpenAI's GPT store, highlighting the ease of building these models and the payment model for creators. The duo touches on the topic of AI-generated lip-synced translations, using the example of a machine-translated speech by Argentina's new president at the World Economic Forum and debating its ethical implications.Esther's M&A and funding corner features the acquisition of Systran by ChapsVision, the sale of Balthasar Ltd. to Translate.One, and the USD 18 million Series B funding round by Contents.com.

Oh, what a month…4 moves and a FIRE all over the holidays. Plus 2024 updates what's new and the sneak peek you've all been waiting for. SUPER Early Bird is on NOW for the Get Your Sexy Back Program- https://getyoursexyback.ca/get-your-sexy-back-program/------------------------------------- Follow Kim below and continue the convo!Facebook - https://www.facebook.com/profile.php?id=569755109Instagram - https://www.instagram.com/get_your_sexy_back_coach/Website - https://getyoursexyback.ca/Private FB Group - https://www.facebook.com/groups/2251812558445958/

Sharing some channeled wisdom for you here at the end of 2023 as well as one of the Honoring 2023 teachings from Seeding the Year 2024. I want everyone to have this, whether or not you have capacity for Seeding the Year right now. Learn about Seeding the Year at the course page. Go straight to enrollment in Seeding the Year. Unshaming the Signs: Capricorn only. Reminder: Today (Dec 31) is the last day to apply for The Magician's Table 2024 and receive the Super Early Bird bonus gifts. +++ Podcast art Angela George. Podcast music Jonathan Koe.

This week on Tent Talk, Farmers Market Pros and InTents Conference founder Catt Fields White takes us inside the evolution of  InTents: The National (actually, multi-national) Farmers Market Conference. From the start, the purpose of the InTents Conference has been to educate, connect, share, and build community in this wonderfully weird world of farms, food and event management!  Because we all know, farmers markets are so InTents.    Listen for the inside track on: How the conference started and where it is now Who comes and who should come to InTents How to join the livestream online What's new for the 2024 conference   How Farmers Market Pros is building a bigger tent    Join us at InTents, the Farmers Market Conference in March 2024. If you have knowledge to share with farmers market managers, participants and policymakers, submit your proposal now at www.conferencerfp.com  A limited number of Super Early Bird tickets will be available on August 28th.    This week's episode is made possible by support from MarketWurks, the online platform for market management.

We're talking with James Grevious of Rebel Marketplace in Aurora, Colorado. He's creating neighborhood food security with the hyper local farmers market he has developed and managed, featuring urban gardeners and farmers.    Listen in For James' views and tips on: • Intentionally developing and incubating urban farmers  • Increasing community capacity from the inside vs outside intervention • Market growth pacing based on operator capacity • Funding education for farmers and vendors  • Balancing financial security and community needs   James started Rebels in the Garden, then the Rebel Marketplace farmers market, and now Urban Symbiosis, a non-profit focused on education and fundraising.    Join us at InTents, the Farmers Market Conference in March 2024. If you have knowledge to share with farmers market managers, participants and policymakers, submit your proposal now at www.conferencerfp.com  A limited number of Super Early Bird tickets will be available on August 28th.    Today's episode of Tent Talk, the Farmers Market Podcast, is supported by The Kitchen Door, connecting food entrepreneurs throughout the US with well-organized and equipped shared-use kitchens.

Do you have a copy of ‘Think and Grow Rich' on your bookshelf? Throw it out! In this episode I'm sharing how that book and it's guidance kept me radically under-earning for WAY TOO LONG and what I did to change it. I'm also sharing two things I do in my business to keep money flowing in a reliable and safe way. Also, remember to sign up for the Abundant Yoga Teacher Retreat. The Super Early Bird ends Wednesday night.Learn all about the Abundant Yoga Teacher Retreat here: https://www.amymcdonald.com.au/retreatsSupport the show by becoming a Patron here: www.patreon.com/AmyMcDonald

Discover the Prospecting and Sales trends for insurance brokers to dominate the market in the next 5 years.Join The #1 Sales and Marketing Event For Healthcare Brokers - High Stakes Advising 2023 

Got final questions before signing up for my amazing Abundant Yoga Teacher Retreat? This is the replay of the info session where I'm going through what you can expect from the retreat as well as answering many of the frequently asked questions. Remember: the super early bird rate goes away at the end of this month. If you have any more questions that I didn't cover, or you just want to chat, reach out!Learn all about the Abundant Yoga Teacher Retreat here: https://www.amymcdonald.com.au/retreats

As retailers consider investing in in-store technology, their goals typically fall into two categories: efficiency and engagement. Some retailers may want to focus on making employees' lives easier while others may want to prioritize high-touch service to shoppers. How can retailers determine which model makes the most sense? Is it possible to prioritize both goals to create a differentiated customer experience? During this episode of Retail Remix, we listen in on a conversation between our host Alicia Esposito, Glenn Allison, VP of Customer-Facing Applications Development at Tractor Supply, and Tony Boncore, Global Customer Marketing Principal at Honeywell. They discuss how the two companies are collaborating to provide store technology that supports both associates and customers. Listen to learn how Tractor Supply is:  Keeping leadership aligned on store technology goals and investment priorities;  Effectively measuring the impact of these investments using qualitative and quantitative insights; and Collaborating with partners like Honeywell to establish a vision for long-term innovation.  RELATED LINKS Connect with Glenn on Linkedin. Connect with Tony on LinkedIn. Learn more about mobile trends at Retail TouchPoints. Want to learn more about balancing efficiency and innovation? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. All-Access Pass holders will get access to three days of content, including sessions on new revenue models like resale, social commerce, and more. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types. 

Expanding your brand into a new market or category can be tricky. How much should you innovate and expand upon what you already do? What do customers expect from such an experience? Rick Gomez, EVP and Chief Food & Beverage Officer at Target, played a crucial role in transforming the retailer's identity from a typical retailer with limited food and grocery options to a comprehensive grocery store. Last summer, at the Retail Innovation Conference & Expo in Chicago, Rick shared a behind-the-scenes look at how Target approaches innovation and growth to give customers what they want and expect from their shopping experiences.During this episode of Retail Remix, we give you exclusive access to Rick's session to learn how he and his team helped transform the retail giant from a typical chain of stores into a one-stop destination for shoppers' culinary needs. Listen to learn:  How Target uses data and digital tools to innovate; How to show up in new markets in a unique way; Ways to create powerful, personalized moments; and Industry trends Rick is excited about and considering to drive future growth. RELATED LINKS Learn more about Rick's work in our Retail Innovator Awards report! Follow Rick on LinkedIn and Twitter. Learn more about food and beverage trends at Retail TouchPoints. Want to learn more about what it takes to evolve your brand and fuel growth? Want to learn from other innovative executives like Rick? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. All-Access Pass holders will get access to three days of content, including sessions on new revenue models like resale, social commerce, and more. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types. 

In the luxury space, in-person experiences are still king. Brand representatives are able to provide high-touch service that allows them to personally consult, fit and connect with customers. But as consumers increasingly consult digital channels, luxury brands are struggling to truly capitalize on new service and engagement opportunities. During this episode of Retail Remix, host Alicia Esposito chats with Olivia Steele, Co-founder of Conversation Couture, a virtual sales training and consulting firm for the luxury retail industry. They look at what luxury brands can do to bridge the disparity between digital and physical experiences. Listen to learn:  Olivia's “magic trifecta” for creating seamless customer experiences across channels; How to connect the dots between technology and customer experience strategy; Tips and tactics for branded ecommerce experiences, including virtual services; and How Olivia believes the luxury market will evolve over the next year.  RELATED LINKS Learn more about Conversation Couture Follow Olivia and Conversation Coutre on LinkedIn and Instagram Read more about luxury trends and news at Retail TouchPoints Want to learn more about how to refine and optimize your omnichannel customer experiences? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. All-Access Pass holders will get access to three days of content, including sessions on new revenue models like resale, social commerce, and more. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types. 

Connected product experiences require so much more than a QR code and call to action. Brands need detailed insight into audience interests and expectations, robust technology to bridge the gap between physical products and digital experiences and, of course, powerful storytelling forged by a genuine connection established between customers, brands and products. With a highly functional and engaging connected product experience, businesses can foster brand loyalty while boosting sales. During this episode of Retail Remix, host Alicia Esposito sits down with Cameron Worth, Founder of SharpEnd, to discuss the secret sauce for rolling out IoT programs and connected product experiences that are effective and “badass.” Listen in to learn:  How the role of IoT in the consumer experience has evolved since the pandemic hit; What it means to create a genuine connected-product experience that delights customers and accelerates buying decisions; and  The future of interactive and digital-driven experiences in the industry. RELATED LINKS Learn more about SharpEnd Follow Cameron and SharpEnd on LinkedIn and Twitter Read more about connected-product experiences at Retail TouchPoints Want to learn more about connected product strategy and its impact on the industry? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. The SharpEnd team will be speaking with a brand partner so attendees can learn how to make some of these big ideas a reality for their business. All-Access Pass holders will get access to three days of tactical and thought-provoking sessions. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types. 

Retail TouchPoints has been studying and reporting on the evolution of resale for years. Over this time, we've seen consumer behaviors shift and demand accelerate, which means retailers have had to rethink the way they research and source “pre-loved” goods. How do they find the right wholesale partners? What are the risks they face while selecting products? How can they ensure their customers get the best deal and their business gets the best margins?During this episode of Retail Remix, host Alicia Esposito dives into the booming secondhand wholesale market with Emily Erkel, CMO and Co-founder at LePrix. Hear her insights regarding the potential risks retailers face when getting involved in reselling items, plus what exactly is propelling them to take those calculated chances. Tune in to learn:  How the vision for LePrix evolved from B2C to B2B; The unique challenges (and new developments) in the resale market; and How LePrix is investing in tech innovation and education to drive the market forward. RELATED LINKS Learn more about LePrix Follow Emily on LinkedIn and Twitter Get more resale and recommerce coverage on Retail TouchPoints Want to learn more about the apparel recommerce market and its impact on the industry? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. All-Access Pass holders will get access to three days of content, including sessions on new revenue models like resale, social commerce and more. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types. 

Branded recommerce is gaining momentum in retail. Could it be the key to success for your company? To find out, you'll have to do some deep strategic work to ensure your brand, your products and your customer align. During this episode of Retail Remix, Alicia Esposito talks with Andy Ruben, Founder & Executive Chairman at  Trove. They discuss how Andy has seen the recommerce space grow and evolve, and the unique approaches brands have taken to use ecommerce to drive acquisition, engagement and loyalty. Check out this episode to learn:  How Trove has changed the way resale is done; What is stopping some brands from embracing recommerce; How to make a profit in the secondary market; and Practical advice for venturing into the resale space. RELATED LINKS Learn more about Trove Check out how other brands are using recommerce strategies Subscribe to the Trove newsletter on LinkedIn Follow Andy on LinkedIn and Twitter Get more Recommerce coverage on Retail TouchPoints Want to learn more about the apparel recommerce market and its impact on the industry? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. Register before April 6 to get Super Early Bird savings, and use the code RRPODD225p to get an extra 25% off all pass types.

Are you in on the NFT craze or playing it safe? If you fall into the latter, you may miss out on some amazing opportunities for engaging with customers and cultivating a loyal community of fans and collectors.During this episode of Retail Remix, our host Alicia Esposito sits down to chat with Ash Pampati, Head of Partnership at the NFT creation platform Metaplex. The pair discuss who manages NFT projects in today's market, the strategic priorities, and what opportunities are available to brands and retailers. More importantly, they discuss what teams need to think about as they go on their NFT journey. Tune in to learn:  The various opportunities NFTs create for digital commerce initiatives; How NFTs are revolutionizing go-to-market strategies like influencer marketing; How NFTs are tackling security concerns for growing digital businesses; and Predictions of how the Web3 climate will evolve in the coming years. RELATED LINKS Learn more about Metaplex Learn more about the Solana blockchain Follow Ash on LinkedIn Get more NFT and Web3 coverage on Retail TouchPoints Want to learn more about how your business can capitalize on the Web3 revolution? Register for the Retail Innovation Conference & Expo, which is taking place June 13-15, 2023, in Chicago and will be laser-focused on what's new and what's next in connected commerce. All-Access Pass holders will get access to the D2 Summit: Retail Edition, a day-long program on June 13 focused solely on how Web3, the metaverse and NFTs are driving the future of retail experiences. Register before April 6 to get Super Early Bird savings and use the code RRPODD225p to get an extra 25% off all pass types. 

Did you know there is NO POSITIVE CORRELATION between time spent trying to become self-aware and actually becoming more self-aware? (Eurich, 2017)   In short, additional self-reflection doesn't necessarily make you more self-aware.    This surprising finding has since fueled the career and research of Tasha Eurich, and inspired her to teach others how to enhance the quality of their introspection.   Tasha Eurich is an organizational psychologist, researcher, and New York Times best-selling author.  Globally recognized as the #1 self-awareness coach, communication, and organizational culture expert, she uses science to help leaders achieve positive, measurable change.   In today's episode, she shares several insights about the science and strategy of self-awareness, including:   A tactical definition of what self-awareness is, and what it is NOT (12:20) The benefits and consequences of introspection (26:00) How to get GREAT feedback by asking the right questions (39:20) The seven types of self-knowledge that separate the aware from the unaware (58:10) You can also find these outlined in our FREE Downloadable Reflection Guide   To learn more about Dr. Eurich's work, buy her best-selling book, and take advantage of her Insight Quiz, you can visit her website HERE.   Speaking of books, they make GREAT stocking stuffers! Please help us support the Leukemia Lymphoma Foundation and the Alzheimer's Association by purchasing a signed copy of Conscious Coaching.  This is not only a great cause, but also gives us the chance to personally say thank you for supporting our small family-owned business.  Your support makes a tremendous difference and we appreciate our community more than you know! CLICK HERE to make your purchase of $11.99/ each!   Now maybe you're someone who is ready to move beyond books and dive deep into training your ability to navigate the dirty, messy realities of life and leadership.  If that's you, The Apprenticeship is exactly what you're looking for.  Check out the entire 2023 schedule, and find the location that best fits you!  And if you didn't already know, we will be going overseas in February to Sydney, Australia.  So if you want to make a vacation out of your professional development, make sure to take advantage of the Super Early Bird pricing that ends on Christmas Day.  It's approaching quickly, so don't wait!  Sign up HERE today!   Lastly, we are extremely grateful to our podcast sponsors for helping us bring quality content to you week after week.  Today's episode is brought to you by: Momentous: With their new, melatonin-free sleep formula, I can enjoy the benefits of a great night's sleep without having to deal with the next day's grogginess. All of their products are tested at the highest level, and they are for anyone who wants to feel better without overthinking their nutrition. Use Code: BRETT15 for 15% off your order. Dynamic Fitness & Strength: These guys are our go-to equipment partner. Fully customizable and manufactured in the heartland of America- whether you're looking to outfit your home gym or entire weight room, visit mydynamicfitness.com to get started. Tell them Brett and the Art of Coaching Team sent you!

In many circles, the National Football League (NFL) has become (just as) well known for its alternate meaning, "Not For Long".    But every once in a while, a player comes along who's able to defy those odds.    In today's episode, Richie Incognito, taken by the St. Louis Rams in the third round of the 2005 draft, four time pro-bowler, and 15 year veteran, reveals in his VERY FIRST post-retirement podcast interview what it takes to manage the brutality of a 15+ year stint in the trenches.   As he reflects on the lessons learned, and looks ahead to a future of living life on his own terms, Richie credits much of his success to a few things:    The mindset to constantly find ways to increase the standard year to year (2:10) Creating buy-in and leadership in the locker room (7:45) Using money as a motivator and managing it the right way (17:55) Being cognizant of the brand you're creating and putting out there (21:00)   If you want to learn more from Richie and his experience, you can connect with him via Twitter - @68INCOGNITO.   If you've been listening to our podcasts consistently, you'll notice a trend - defining and building your own brand is a necessity in reaching your goals. If building your brand is something you feel that you struggle with, and you're looking for help, check out our upcoming Brand Builder event.  The Super Early Bird sale ends this coming Friday, August 5. So ACT NOW to get the best deal!   We also want to thank our sponsor, Momentous, for today's episode. If you ask Richie, a large part of creating a sustainable career was fueling his body with the highest quality products.  Check out their entire line of protein and supplements at livemomentous.com and use code BRETT15 at checkout for 15% off! Lastly, if you find value in the content we provide, and you want to be the first to know about new live events, resources and weekly insights from our team- check out artofcoaching.com/begin.

A business downturn is the beginning, not the end! It gives you the chance to start new, learn, and rebuild. Whether you're struggling with finances or another one of the many aspects that make up running a business, today's episode is all about how you can turn things around. Listen in to get totally clear on what you need to do differently so you can turn around your struggling business–or the aspects of it that are challenging for you–right now! I've even put together a special free download for you to go along with the episode so you can take action on this knowledge today! Download the worksheet here to follow along → https://theunstoppablewoman.com/e310 What To Listen For Life is a struggle… or is it?? Let's unpack your mindset here! [4:16] Are you overcomplicating your marketing strategy? (Here are the telltale signs!) [15:40] How to delegate without breaking the bank [17:34] You might be addicted to the chaos if you find yourself doing this [26:35] Resources Want to learn more of the specific tactical actions that will help you grow your business fast without burnout? Then join us at The Income Breakthrough Summit from May 13th–15th! Grab a ticket NOW for our best deal–Super Early Bird pricing expires in just two days!! Check out our free resources for listeners Join our Facebook Group Join the Morning Mindset Club Schedule a Strategy to Scale Consultation

Today we are talking about how to earn more by working less! This is the perfect topic for our 2-year anniversary of the podcast!! Listen in to learn the best ways to earn a bigger income while working less, which is something I had to really master as I was leveling up and taking on more and more in my business, including through this podcast. It's been such a fun journey!! What To Listen For Intro [0:00] How to fire yourself up so you can grow with your business (And tips for hiring as you move to this next level!) [7:06] The importance of conveying to others that working with you will allow them to do, be, and have MORE [16:49] Upping your level of service [19:16] Sell without feeling sleazy—how to utilize sales to get what you desire [23:00] Resources Want to learn more of the tactical actions that will help you make BANK in your business – without the overwhelm? Then join us at The Income Breakthrough Summit May 13th–15th! Grab a ticket NOW before Super Early Bird pricing expires in less than a week!! Check out our free resources for listeners Join the Morning Mindset Club Join our Facebook Group