Podcasts about learning systems

Marketing is entering its most complex era yet. AI is accelerating everything—but the real challenge is making sense of a system that is fragmenting faster than ever. In this episode of Frontier CMO, Josh Spanier sits down with Asmita Dubey, Chief Digital and Marketing Officer at L'Oréal Groupe, who leads digital transformation across the world's largest beauty company. With more than 90,000 employees and dozens of global brands, Asmita is responsible for navigating how AI, data, and creativity reshape marketing at enterprise scale. The conversation explores why fragmentation defines modern marketing—from the consumer journey to the marketing organization itself—and how leaders must respond by building systems that scale learning. Asmita shares how L'Oréal has operationalized transformation through massive upskilling, AI-powered content creation, and a culture built around what she calls the “dual muscle” of math and magic: the balance of technology, creativity, speed, and brand building.  For CMOs and founders navigating a moment where AI is reshaping every layer of marketing—from insight to creation to commerce—this conversation offers a practical blueprint for leading transformation while protecting the creative heart of the brand. 00:00 – The Marketer's Dilemma: Fragmentation in the AI Era 01:00 – Meet Asmita Dubey & L'Oréal's “Math + Magic” Philosophy 02:00 – A Global Career & How Background Shapes Leadership 03:30 – Growing Up in a Family of Teachers & Lifelong Learning 04:45 – Leading Through Influence in a Complex Organization 06:00 – Inside L'Oréal's Massive Marketing Ecosystem 07:30 – Stakeholders Then vs. Now: The Expanding Marketing Universe 09:00 – Marketing Meets Engineering: The Rise of Beauty Tech 10:30 – Staying Ahead: Culture, Curiosity & Continuous Reinvention 11:45 – Building an Entrepreneurial Culture at Scale 13:00 – Upskilling 30,000+ Marketers & Skill-Based Organizations 15:00 – L'Oréal's Digital Transformation: From 5% to 30% E-Commerce 17:00 – Changing Consumer Behavior & New Operating Models 19:00 – Measurement Matters: Balancing Short-Term ROI & Brand Equity 21:00 – Lessons from China: Speed, Scale & Consumer-First Thinking 23:30 – Agentic Commerce & the Future of Beauty Shopping 26:00 – Why Fragmentation Is the Biggest Marketing Challenge 29:00 – AI's Role in Rebundling Marketing & Breaking Silos 31:00 – AI-Powered Consumer & Marketer Journeys Explained 33:00 – Inside L'Oréal's AI Tools: Creaitech & Content at Scale 35:00 – What's Next: The Future of Marketing in the AI Era 37:00 – Rapid Fire: Signal vs. Noise (AI, Influencers, Innovation) 40:00 – Final Takeaways: Fragmentation, Learning Systems & Dual Muscle 

Education researcher Susanna Loeb studies the broad spectrum of learning experience, including ways to recruit and retain expert teachers, how to optimize classrooms, and the impact of technology on learning. She says pandemic-inspired innovations in tutoring have led to greater student engagement and improved learning outcomes. And on the growing influence of AI in education, Loeb counts herself an optimist. She sees it as a tool for good, enhancing personalized learning and supporting teachers. These innovations that didn't exist a few years ago stand to help students to thrive, Loeb tells host Russ Altman on this episode of Stanford Engineering's The Future of Everything podcast. Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu. Episode Reference Links: Stanford Profile: Susanna Loeb Connect With Us: Episode Transcripts >>> The Future of Everything Website Connect with Russ >>> Threads / Bluesky / Mastodon Connect with School of Engineering >>> Twitter/X / Instagram / LinkedIn / Facebook Chapters: (00:00:00) Introduction Russ Altman introduces guest Susanna Loeb, a professor of education at Stanford University. (00:02:58) Path into Education Susanna's journey from engineering to education and her focus on impact at scale. (00:04:41) The Field of Learning Science The different approaches and challenges in education and its research. (00:07:06) Tutoring After the Pandemic How COVID exposed learning gaps and accelerated interest in tutoring. (00:10:14) What Makes Tutoring Effective The different factors that go into making tutoring effective. (00:12:16) Spreading Proven Practices Using proof points and partnerships to drive adoption across districts. (00:14:00) Building Education Networks The importance of trusted relationships and communication channels. (00:14:50) AI in the Classroom How schools are beginning to adopt AI tools and respond to demand. (00:16:00) AI & Education How teachers are leading AI adoption, with limited direct student use. (00:19:37) A Framework for Using AI The focus on improving student experiences and personalized learning. (00:21:23) Studying AI in Real Time Challenges of evaluating fast-changing tools and the need for rapid testing. (00:23:22) Partnering with AI Companies Collaborating with industry to test tools like ChatGPT in schools. (00:25:26) AI & Tutoring Blending human tutors with AI support to improve outcomes. (00:27:22) The Limits of AI Tutors Why human motivation and relationships remain essential. (00:28:54) The Future of Education Systems Balancing innovation with equitable access and student engagement. (00:30:51) Future In a Minute Rapid-fire Q&A: optimism, scaling education, and collaboration. (00:32:54) Conclusion Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Send us Fan MailLeader, this is where it all comes together.You've worked on how you lead yourself. You've started strengthening how your school operates.But now the question becomes:Is instruction actually improving?In this episode, you'll dive into the third system every school leader needs: Learning Systems—the structures that ensure teaching gets better and students achieve at higher levels.Because here's the reality: Instruction doesn't improve by chance. It improves through intentional systems.In this episode, you'll be coached through the key systems that drive instructional growth, including: Creating a clear instructional focus so your staff isn't pulled in too many directions  Using walkthroughs and coaching cycles to actually change classroom practice  Building data and PLC systems that turn conversations into action  Strengthening assessment and progress-monitoring to measure what's working  Developing intervention systems so all students receive the support they need  Aligning curriculum, instruction, and expectations across classrooms  Monitoring implementation so your initiatives don't lose momentum Because when Learning Systems are strong, you don't just manage a school…You lead one that grows.Support the showDownload Upside and use my code MELINDA35278 to get 15¢ per gallon extra cash back on your first gas fill-up and 10% extra cash on your first food purchase!Download Fetch app using this link, submit a receipt and we'll both score bonus points.Calling All Educators! I started a community with resources, courses, articles, networking, and more.I am looking for members to help me build it with the most valuable resources.I would really appreciate your input as a teacher, leader, administrator, or consultant.Join here: Empowered Educator CommunityBook: Educator to Entrepreneur: IGNITE Your Path to Freelance SuccessGrab a complimentary Power Surgeemail: melinda@empowereducator.com

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This edWeb podcast is hosted by SETDA.The edLeader Panel recording can be accessed here.SETDA, in partnership with ISTE+ASCD, Learning Forward, and FullScale, has developed Improving Professional Learning Systems to Better Support Today's Educators: How Title II, Part A Offers a Model for State and Local Leadership, a new guide on strengthening state and local systems for edtech and AI professional learning, that was released at the SETDA Leadership Forum on November 5, 2025. In this edWeb podcast, listeners learn about the research behind the guide, key recommendations for leaders, and strategies for building sustainable systems that expand educator capacity.This session emphasizes how Title II-A and braided funding can shift professional learning from compliance-driven training to educator-driven growth. By highlighting coaching models, PLC structures, and AI literacy building opportunities, the panelists show how systems can empower educators to set goals, lead peers, and personalize learning pathways. Listeners explore strategies that build capacity while ensuring professional learning is sustained and aligned to instructional vision.This edWeb podcast is of interest to K-12 school leaders, district leaders, education technology leaders, and state education leaders.SETDASETDA is the principal association representing U.S. state and territorial edtech leaders.Disclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Learn more about viewing live edWeb presentations and on-demand recordings, earning CE certificates, and using accessibility features.

Raviteja Yelamanchili shares how Scale AI transformed banking cycles from one year to real-time and why your most valuable enterprise data isn't being collected.Topics Include:Scale evolved from data annotations company to enterprise AI solutions providerHealthcare system transformed patient transcriptions into value using reinforcement learning researchBlank slate customer problems allow Scale to experiment with latest methodsMany customers propose solutions before explaining their actual underlying business problemsBiggest AI misconception: technology will replace jobs rather than augment productivityDon't wait for perfect AI—start learning through iteration and evolution nowBanking credit cycle transformed from one-year process to real-time strategic insightsScale deploys flexibly across EC2, EKS, or Bedrock based on customer requirementsEnterprises want business value generation more than academic research papers aloneNext 12-24 months focus: making data consumable and leveraging unused datasetsTribal knowledge from experienced SMEs represents most valuable yet uncollected dataAgent-based learning captures expertise through feedback loops on Scale's SGP platformParticipants:Raviteja Yelamanchili - Head of Solution Engineering, Scale AISee how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

In this conversation, Drs. Gaurav Suri and Jay Mcclelland delves into the intricate relationship between artificial intelligence and human cognition, exploring similarities and differences, the evolution of AI from rule-based systems to learning models, and the concept of emergence in both fields. The discussion also touches on the efficiency of human learning compared to AI, the role of consciousness, and the ethical implications of AI technology.Takeaways AI and human intelligence share similarities in neural network frameworks. Artificial systems lack the goal-directed nature inherent in humans. Humans learn more efficiently than current AI systems. Neural networks can adapt to language nuances better than rule-based systems. Emergence explains how collective intelligence arises from individual components. Memory in neural networks is represented through connections, not individual units. Mathematics is both invented and discovered, shaped by human needs. Understanding consciousness is crucial for AI development. Human misuse of AI poses significant risks. Recognizing ourselves as processes can foster empathy and morality.Chapters 00:00 Introduction and Backgrounds 01:00 AI vs Human Mind: Similarities and Differences 03:32 The Shift from Rule-Based AI to Learning Systems 09:07 Emergence in Cognition: Ant Colonies and Intelligence 15:25 Distributed Representations and Memory Storage 23:53 The Nature of Memory and Its Malleability 25:40 Emergence of Mathematical Concepts 29:50 The Invention vs. Discovery Debate in Mathematics 32:19 Learning Mechanisms: Brain vs. AI 36:48 Consciousness: Function and Implications 41:13 AI Risks: Human Misuse vs. AI Autonomy 43:45 Living with Emergence: Understanding Ourselves and Others 48:22 Exploring the Emergent MindFollow Gaurav Suri on LinkedIn. Follow Jay McClelland on Twitter and find their new book here.Subscribe to Breaking Math wherever you get your podcasts.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter, BlueSky, and InstagramBecome a guest hereemail: breakingmathpodcast@gmail.com

Understanding how humans learn language provides a blueprint for designing other intelligent learning systems. Jon Rawski, assistant professor in the department of linguistics and language development at San Jose State University, discusses how to do so. Jon Rawski is an Assistant Professor in the Department of Linguistics and Language Development at San José State University […]

Dr. Christie Vanorsdale, founder of Vanorsdale Learning Lab, a strategic learning consultancy that helps organizations at pivotal growth moments build smarter, more human-centered training systems.Through experience design rooted in cognitive science and thoughtful systems transformation, Christie empowers companies to create sustainable, scalable learning ecosystems that actually work.Now, Christie's journey of leaving secure but draining long-term roles to bet on herself again shows what's possible when you align your work with your values.And while she's teaching business leaders to forget what they think they know about learning and embrace systems that truly support people, she's also redefining what success looks like on her own terms.Here's where to find more:https://www.vanorsdalelearninglab.comhttps://www.linkedin.com/in/christiervanorsdalehttps://www.youtube.com/@VanorsdaleLearningLab________________________________________________Welcome to The Unforget Yourself Show where we use the power of woo and the proof of science to help you identify your blind spots, and get over your own bullshit so that you can do the fucking thing you ACTUALLY want to do!We're Mark and Katie, the founders of Unforget Yourself and the creators of the Unforget Yourself System and on this podcast, we're here to share REAL conversations about what goes on inside the heart and minds of those brave and crazy enough to start their own business. From the accidental entrepreneur to the laser-focused CEO, we find out how they got to where they are today, not by hearing the go-to story of their success, but talking about how we all have our own BS to deal with and it's through facing ourselves that we find a way to do the fucking thing.Along the way, we hope to show you that YOU are the most important asset in your business (and your life - duh!). Being a business owner is tough! With vulnerability and humor, we get to the real story behind their success and show you that you're not alone._____________________Find all our links to all the things like the socials, how to work with us and how to apply to be on the podcast here: https://linktr.ee/unforgetyourself

Josef George Kembel is an educator, entrepreneur, and advisor whose work sits at the intersection of creativity, leadership, and systems change. As the founding director of Stanford’s Design School (the d.school), Josef helped launch a global movement in design that has influenced education, business, and social innovation worldwide. Earlier in his career, his entrepreneurial work contributed to the foundations of today’s mobile app and app ecosystems. Josef’s global perspective was shaped by a six-month voyage to 30 countries, where he co-founded and co-led a ship-based social impact accelerator. Bringing together entrepreneurs, mentors, leaders, and students, the program explored how innovation can drive meaningful change across cultures and contexts. Today, Josef works with leaders and organizations around the world on aligning vision, values, and action. His focus is on building “living learning systems”, adaptive structures that enable individuals and organizations to learn continuously, innovate responsibly, and grow in ways that serve both people and planet. He has developed modular learning approaches that empower people to design self-guided projects, using their own lives and communities as laboratories for growth and impact. With a deep connection to the oceans and a commitment to collective flourishing, Josef brings a unique blend of practical innovation experience and inner consciousness work to the fields of philanthropy, leadership, and social change. His work centers on creating environments and practices that help people move more fluidly, act with clarity, and unlock value that goes beyond financial returns.See omnystudio.com/listener for privacy information.

Send us a textABA on Tap is proud to spend some time with Allyson Wharam (Part 2 of 2):Allyson Wharam is the founder of Sidekick Learning, a company dedicated to streamlining training and supervision systems for Applied Behavior Analysis (ABA) organizations. She brings a wealth of experience to her role, having worked hands-on in various clinical settings and served as a training coordinator for a large organization, gaining a deep understanding of the practicalities involved in creating effective systems in real-world scenarios. Her expertise also extends to instructional design, holding a Master's degree in Instructional Design and Technology from the University of Virginia and currently pursuing her doctorate in the same field at the same university. Wharam is also a Board Certified Behavior Analyst (BCBA), demonstrating her qualifications in the field of behavior analysis. This brew is refreshing and perfect for cerebration. It will make you smarter. Pour heavy, share with plenty of friends and always analyze responsibly.Support the show

Send us a textABA on Tap is proud to spend some time with Allyson Wharam (Part 1 of 2):Allyson Wharam is the founder of Sidekick Learning, a company dedicated to streamlining training and supervision systems for Applied Behavior Analysis (ABA) organizations. She brings a wealth of experience to her role, having worked hands-on in various clinical settings and served as a training coordinator for a large organization, gaining a deep understanding of the practicalities involved in creating effective systems in real-world scenarios. Her expertise also extends to instructional design, holding a Master's degree in Instructional Design and Technology from the University of Virginia and currently pursuing her doctorate in the same field at the same university. Wharam is also a Board Certified Behavior Analyst (BCBA), demonstrating her qualifications in the field of behavior analysis. This brew is refreshing and perfect for cerebration. It will make you smarter. Pour heavy, share with plenty of friends and always analyze responsibly.AND PLEASE CHECK OUT iLearn-ABA at learn.ilearn-aba.com for great CEUs at a very reasonable price. Use promo code ABAonTap for an additional 15% off already incredibly well priced CEUs.Support the show

Jeudi 12 juin, François Sorel a reçu Julien Billot, président de Scale Ai, Pablo Piantanida, directeur de l'ILLS (International Laboratory on Learning Systems), professeur associé à l'ÉTS à Montréal, et Jérémie Voix, professeur titulaire à l'ÉTS à Montréal. Ils ont parlé de la tech canadienne qui fait une entrée en force à VivaTech, d'une intelligence artificielle qui sert à diagnostiquer le cancer du sein, et des prothèses auditives révolutionnaires, dans l'émission Tech & Co, la quotidienne, sur BFM Business. Retrouvez l'émission du lundi au jeudi et réécoutez la en podcast.

Tired of feeling like your team is stuck in a cycle of frustration and miscommunication? What if the biggest blocker in your tech career isn't your code, but your thinking?That's the core premise of Systems Thinking, and in this episode, Diana Montalion (author of “Learning Systems Thinking”) shares the practical insights and mental models to help you make that essential shift.Key topics discussed:What systems thinking is and its core principlesThe difference between linear thinking (which we need) and systems thinking (which we're missing)Why building a metaphorical “car boat” is a failure of “conceptual integrity” and how to avoid itHow to break free from a “change-my-mind” culture and improve our collaborationThe critical skill of metacognition: why you must understand your own thinking before you can influence othersPractical ways to foster collective systems thinking and bridge the gap between Product and TechUsing modeling and visual tools to create alignment and solve the right problemsHow AI's inability to handle true inference makes human systems thinking more valuable than everWhether you're a software engineer, architect, team leader, or anyone tackling complex problems, learn why your technical skills alone are not enough and how a shift in your thinking can revolutionize your work and career.  Timestamps:(00:00:00) Trailer & Intro(00:02:23) Career Turning Points(00:04:35) Writing Learning Systems Thinking(00:08:53) Definition of Systems Thinking(00:13:39) Systems Thinking vs Linear Thinking(00:19:31) Definition of System(O0:24:13) Conceptual Integrity(00:30:02) Practices to Improve Our Systems Thinking(00:36:21) Metacognition and Self-Awareness(00:44:42) Practices to Improve Our Collective Systems Thinking(00:53:04) Collaboration with Consent(00:55:29) The Importance of Modeling(01:02:20) AI Usage and System Thinking(01:11:04) 3 Tech Lead Wisdom_____Diana Montalion's BioDiana Montalion is a systems architect, learning facilitator, and founder of Mentrix Group, with over 20 years of experience delivering transformative software initiatives for organizations like Stanford, The Gates Foundation, The Economist, and The Wikimedia Foundation. As the author of Learning Systems Thinking: Essential Nonlinear Skills & Practices for Software Professionals (O'Reilly), she empowers tech professionals to navigate complex systems through practices like systemic reasoning, metacognition, and collaborative modeling.Follow Diana:LinkedIn – linkedin.com/in/dianamontalionWebsite – montalion.comTwitter – @dianamontalionMastodon - @diana@hachyderm.ioBluesky - @mentrix.bsky.socialMentrix Group – https://mentrixgroup.com/SystemCrafters Collective – https://mentrix.systems/

Rafael Urquiza presents details on how Sylvan Learning Systems in Orange Park and North Jacksonville address academic needs for K-12 students.

In episode 181 with Robert Barnett, Rob and I were discussing the real constraints and difficult conditions teachers find themselves in as they try to prioritise the meaningful learning and growth of their young people. This week, we are taking a broader look at the kinds of institutional structures that might actually help rather than hinder these more generative ways of living and learning - the kinds of institutions suited to the transformative adaptations and systems change that we desperately need. So in this episode I'm really happy to be speaking with Thea Snow and Toby Lowe about taking a Human Learning Systems approach to management and governance of organisations. Thea and Toby in their work at Centre for Public Impact focus primarily on public sector management. However, these principles certainly apply more broadly to institutions in the private and third sectors. This is very exciting work as it feels much more authentically connected to the beautiful and complex realities that we know we live, learn and work in and that we want to prepare our young people to embrace. But we also know that the way we are held accountable for outcomes in our work often feels simplistic and naive and entirely dissociated from these complex realities. Thea is the Regional Director for Australia and Aotearoa New Zealand at Centre for Public Impact. Thea's experiences span the public, private and not-for-profit sectors. She has worked as a commercial lawyer, a public servant, and, prior to joining CPI, at the UK's innovation foundation, NestaToby Lowe is Professor of Public Management at Manchester Metropolitan University and action researcher at Centre for Public Impact. He has also done policy work addressing poverty in neighbourhoods for the Social Exclusion Unit, worked as a public management action researcher developing the Human Learning Systems approach and held the position as Chief Executive of a participatory arts charity in North East England.You can find links in the show notes to a lot of the documents and sources we talk about in the conversation, especially if you'd like to find out more about implementing a Human Learning Systems approach in your organisation. Some of Thea's work includes:“The (il)logic of legibility – Why governments should stop simplifying complex systems”https://blogs.lse.ac.uk/impactofsocialsciences/2021/02/12/the-illogic-of-legibility-why-governments-should-stop-simplifying-complex-systems/“Once upon a bureaucrat: exploring the role of stories in government“https://thepolicymaker.jmi.org.au/once-upon-a-bureaucrat-exploring-the-role-of-stories-in-government/“Why evidence should be the servant, not the master, of good policy”https://apolitical.co/solution-articles/en/Why-evidence-should-be-the-servant-not-the-master-of-good-policy“Public servants are tired of change-washing — not change”https://apolitical.co/solution-articles/en/public-servants-are-tired-of-change-washing-not-changeSome of Toby's work includes:Human Learning Systems: Public Service for the Real World: https://centreforpublicimpact.org/resource-hub/human-learning-systems-public-service-for-the-real-world/Harnessing Complexity for Better Outcomes in Public and Non-profit Services: https://policy.bristoluniversitypress.co.uk/harnessing-complexity-for-better-outcomes-in-public-and-non-profit-servicesHuman Learning Systems: A practical guide for the curious: https://www.centreforpublicimpact.org/assets/pdfs/hls-practical-guide.pdfVarious links from our discussion:https://www.humanlearning.systems/hls-insights-findings-from-our-research-2024/https://centreforpublicimpact.org/resource-hub/storytelling-for-systems-change/https://medium.com/centre-for-public-impact/embracing-ensembles-8e049c40b87fhttps://www.woodleigh.vic.edu.au/events-public-calendar/reimagined-conference

In this episode, I break down the key differences between content marketing videos and a complete soccer learning system. While content marketing videos are fantastic for quick tips and inspiration—I rely on them myself—they serve a different purpose than a step-by-step curriculum. A full learning system provides structure, progression, and a clear path to development, ensuring players build skills systematically. Tune in to hear why having both tools in your training arsenal can make all the difference! --- Support this podcast: https://podcasters.spotify.com/pod/show/anytime-soccer/support

This interview was recorded for the GOTO Book Club.http://gotopia.tech/bookclubRead the full transcription of the interview here:https://gotopia.tech/episodes/328Diana Montalion - Systems Architect, Mentrix Founder & Author of "Learning Systems Thinking"Charles Humble - Freelance Techie, Podcaster, Editor, Author & ConsultantRESOURCESDianahttps://hachyderm.io/@dianahttps://bsky.app/profile/mentrix.bsky.socialhttps://x.com/dianamontalionhttps://github.com/dianamontalionhttps://www.linkedin.com/in/dianamontalionhttps://blog.montalion.comhttps://learningsystemsthinking.comCharleshttps://twitter.com/charleshumblehttps://linkedin.com/in/charleshumblehttps://mastodon.social/@charleshumblehttps://conissaunce.comLinkshttps://xkcd.com/386DESCRIPTIONDiana Montalion and Charles Humble explore the complexities of systems thinking particularly in tech environments resistant to change. Diana shares insights on the frustrations of introducing new ideas in hierarchical organizations, where power dynamics and skepticism often block innovation.They discuss the importance of patience, community support, and accepting that recognition may not come when challenging ingrained structures. Diana also reflects on the personal growth she experienced while writing her book, including navigating her ADHD diagnosis and learning to embrace uncertainty. Together, they highlight the need for resilience and collaboration in driving meaningful, systemic change in tech.Struggling to make systems thinking work in rigid, hierarchical environments? You're not alone. Dive into Diana Montalion and Charles Humble's conversation on resilience, innovation, and driving real change in tech. Discover Diana Montalion's insights on systems thinking and overcoming hierarchical challenges in tech with Charles Humble. Essential read for anyone driving change in complex environments.RECOMMENDED BOOKSDiana Montalion • Learning Systems Thinking • https://amzn.to/3ZpycdJRobert M. Pirsig • Zen & the Art of Motorcycle Maintenance • https://amzn.to/4ekfJU0Donella H. Meadows • Thinking in Systems • https://amzn.to/3XtqYCVDonella H. Meadows • Limits to Growth • https://amzn.to/4d9sik4TwitterInstagramLinkedInFacebookLooking for a unique learning experience?Attend the next GOTO conference near you! Get your ticket: gotopia.techSUBSCRIBE TO OUR YOUTUBE CHANNEL - new videos posted daily!

Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems. Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI. - Episode notes: www.wellecks.com/thesisreview/episode48.html - Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter - Follow Tianqi Chen on Twitter (@tqchenml) - Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview

Yian Ma, an assistant professor in the Halıcıoğlu Data Science Institute at UC San Diego talks about his research using scalable inference methods for credible machine learning. This involves designing Bayesian inference methods to quantify uncertainty in the predictions of complex models; understanding computational and statistical guarantees of inference algorithms; and leveraging these scalable algorithms to learn from time series data and perform sequential decision making tasks. Series: "Science Like Me" [Science] [Show ID: 39710]

Yian Ma, an assistant professor in the Halıcıoğlu Data Science Institute at UC San Diego talks about his research using scalable inference methods for credible machine learning. This involves designing Bayesian inference methods to quantify uncertainty in the predictions of complex models; understanding computational and statistical guarantees of inference algorithms; and leveraging these scalable algorithms to learn from time series data and perform sequential decision making tasks. Series: "Science Like Me" [Science] [Show ID: 39710]

Yian Ma, an assistant professor in the Halıcıoğlu Data Science Institute at UC San Diego talks about his research using scalable inference methods for credible machine learning. This involves designing Bayesian inference methods to quantify uncertainty in the predictions of complex models; understanding computational and statistical guarantees of inference algorithms; and leveraging these scalable algorithms to learn from time series data and perform sequential decision making tasks. Series: "Science Like Me" [Science] [Show ID: 39710]

Yian Ma, an assistant professor in the Halıcıoğlu Data Science Institute at UC San Diego talks about his research using scalable inference methods for credible machine learning. This involves designing Bayesian inference methods to quantify uncertainty in the predictions of complex models; understanding computational and statistical guarantees of inference algorithms; and leveraging these scalable algorithms to learn from time series data and perform sequential decision making tasks. Series: "Science Like Me" [Science] [Show ID: 39710]

My guest today is Brittany Loney the founder and CEO of Elite Cognition. Brittany has almost 20 years of experience training high performing operators from communities as diverse as elite SOF warriors, professional and Olympic athletes, high-level coaches, and corporate executives. She also has over 14 years of experience training Special Operations Forces (SOF) and was the first cognitive performance coach embedded within a United States Special Operations Command (USASOC) Tactical Human Optimization and Rapid Rehabilitation and Reconditioning (THOR3) Program.Her work has been featured in the Harvard Business Review, peer reviewed academic journals, textbooks, SUCCESS Magazine, SOCOM's SOFcast, and various other programs. In addition, Brittany has been a panel member or guest speaker at Global SOF Week, Special Operations Medical Association (SOMA), SOCOM's Wellness Week, Air Force Air Education and Training Command (AETC) Learning Professional's Consortiums, Women in SOF Symposiums, and countless other professional conferences.Brittany has a Ph.D. in Educational Psychology and Learning Systems from The Florida State University, an M.A. in Kinesiology with an emphasis on Sport Psychology from California State University, Fresno, an M.S. in Exercise Science from Florida State University, and a B.S. in Criminal Justice from Texas State University where she was also a NCAA Division 1 basketball player. She lives her profession, spending much of her time working out, ultra-running, hiking, paddle boarding, and researching neuroscience, performance, and cognition.I was first introduced to Brittany by some of our nation's best tactical operators.  Her work with US SOF units is unique in its approach to improving operator performance through physical, cognitive, and emotional training. I am extremely excited to have her on the debrief, because the broad scope and clear structure of her work will lay a foundation for several episodes to come on improving operator performance. I hope you enjoy my chat with Brittan Loney. Book Recommendation:The Daily Stoic Boxed Set Hardcover - Ryan Holiday and Stephen Hanselman - ISBN-13:‎ 978-0593544891Warrior Mindset - Dr. Michael Asken, Loren W. Christensen, and Dave Grossman - ISBN-13: 978-0964920552Contact Info:Brittany Loney – www.elite-cognition.com

In the final episode of our 3-part miniseries on world-class learning systems, Jo Earp and Professor Geoff Masters discuss how schools and communities in British Columbia, Estonia, Finland, Hong Kong and South Korea are working together to best meet individual student learning and wellbeing needs. Host: Jo Earp Guest: Professor Geoff Masters Sponsor: Grok Academy (grokacademy.org)

Cynthia has her Master's in Social Work and her MBA. She is an independent health and wellness coach, corporate presenter, and trainer. Her corporate presentations cover a variety of wellness topics including sleep strategies, the impact of alcohol on the body, menopause, meditation, stress management, healthy eating, resilience, and more. She also is certified in Infinite Possibilities and is a presenter and a coach. For the past four years she has worked at Organizational Wellness & Learning Systems delivering trainings on stress management, resilience, burn out, and other mental health topics faced by employees. Cynthia is an IVF Support Group Peer Leader. She has been a volunteer for the Worksite Wellness Council of Massachusetts for the past four years helping to set up presentation on employee wellness. Cynthia has two children born through infertility and her second child was brought into the world with the help of a Gestational Surrogate. Listen as Cynthia discusses with Ellen and Jenn: • After her first pregnancy through IVF, becoming pregnant naturally, but experiencing an emergency hysterectomy. • While still in the hospital, her husband suggesting surrogacy. Not quite being ready for that conversation. • Just shy of a year from the surgery, being ready and starting the search. • Finding the perfect match! • How her son feels about being carried by a surrogate • Become active as an advocate for others suffering from infertility. Want to share your story or ask a question? Call and leave us a message on our hotline: 303-997-1903. Learn more about Health Coaching: www.cynthiahealthcoach.com Learn more about our podcast: https://iwanttoputababyinyou.com/ Learn more about our surrogacy agencies: https://www.brightfuturesfamilies.com/ Get your IWTPABIY merch here! https://iwanttoputababyinyou.com/merch Learn more about Ellen's law firm: http://trachmanlawcenter.com/

Our guest for this special miniseries is Professor Geoff Masters, CEO of the Australian Council for Educational Research. His new book, 'Building a World-Class Learning System, Insights from Some Top-Performing School Systems', explores what's happening in British Columbia, Estonia, Finland, Hong Kong, and South Korea. In the first episode, we talked about the big questions that school systems around the world are grappling with. We also looked at some of the reforms in these 5 jurisdictions, including the core characteristics of a world-class curriculum. Our topic for this episode is creating the conditions for all students to learn successfully. Host: Jo Earp Guest: Professor Geoff Masters

Welcome to a special edition of The Writing Glitch podcast, where we delve into the fascinating world of puppetry and its role in enhancing literacy skills. In this episode, we enjoyed hosting Carol Richards and Linnea Smith, the dynamic duo behind Richard's Learning Systems. This revolutionary literacy program incorporates puppets, animation, and multisensory learning to teach reading. Join us as we explore the magic behind their approach and how it's transforming how children learn to read.The Genesis of Richard's Learning SystemsCarol Richards, the founder of Richard's Learning Systems, shared her journey from starting a tutoring service to developing a comprehensive literacy program. With the challenge of making her science of reading program accessible and practical, Carol had a eureka moment that led to creating a unique video-based curriculum. These videos, devoid of adult presence, feature puppets and animation to engage children in learning sounds, blends, digraphs, and eventually syllables, culminating in the ability to read complex words like "antidisestablishmentarianism."The Puppets of LiteracyThe program boasts a cast of charming puppets, each with a specific role in teaching literacy concepts. Miss Alice teaches the short "a" sound, while Silly Ball, the syllable scientist, helps students break words into syllables. Chef Cookie teaches blends with her whisk and animated ingredients, and Sophie introduces non-phonetic "red words" through arm tapping.A Family AffairLinnea Smith, Carol's daughter, brings her creative expertise and personal experience as a struggling reader. She played a pivotal role in producing the video series and creating the puppets, transforming them from simple sock puppets to the engaging characters used today.ExpandRichard's Learning Systems is not just for young learners. The program has succeeded with older students, refugees, immigrants, and even adults in the workforce. Its simplicity and effectiveness make it a valuable tool for many learners, including non-verbal students who have shown remarkable progress.Incorporating Writing Skills:The program also addresses writing skills through tracing practice, spelling exercises, and gentle introductions to sentence structure. The focus is on making learning as multisensory as possible, with tactile letter cards and activities reinforcing the connection between reading and writing.Accessible and Affordable:Richard's Learning Systems is designed to be both accessible and affordable. With a subscription model, teachers and parents can access the materials and videos needed to implement the program effectively. The emphasis is on short, daily sessions that fit easily into any schedule.Conclusion:Richard's Learning Systems is a testament to the power of creativity and innovation in education. By harnessing the appeal of puppets and the principles of multisensory learning, Carol Richards and Linnea Smith have created a literacy program that teaches children how to read and instills a love for reading. As we explore the potential of puppetry in education, Richard's Learning Systems stands as a shining example of how thinking outside the box can lead to remarkable outcomes in literacy development.Visit Richard's Learning Systems for more information and to explore the magical world of literacy puppets.Contact Carol and LinneaContact CheriUpcoming Event: May 11, 2024Being RecordedTier 1,2,3 Non-Academic Interventions to enhance structured literacy and writing skills ★ Support this podcast ★

Professor Geoff Masters, CEO of the Australian Council for Educational Research, joins Teacher for a series on world-class learning systems. In Episode 1, we find out more about the 5 systems he's been exploring for a multi-year study commissioned by the National Centre on Education and the Economy in Washington DC. Host: Jo Earp Sponsor: MacKillop Seasons

Doug Wyatt brings an impressive level of energy and commitment to everything he does. That is demonstrated in his entrepreneurial endeavors, his personal and professional growth, and most recently in the development of Synergy Learning Systems. In this fascinating episode you will learn about: How Doug Wyatt's childhood of rural poverty fueled his ambition, work ethic, and values. His early entrepreneurial success in the world of pizza coupons. Doug's early and continuing commitment to personal growth and what that did for him. How to find time for personal development. The unexpected way Doug entered the HVAC Residential Service industry. The way Doug grew a company with no systems and processes to Lennox Partner of the Year in only 14 months. A great quote, "we overestimate what we can do in one day, but underestimate what we can do in a year" and what that means for you. Why Doug Wyatt is strategically incompetent, and why you should be strategically incompetent too. Can you afford to cut training in an economic downturn? The new learning paradigm from Synergy Learning Systems, measuring the personal growth of team members and what that can do for your company. How much training should you provide your team? Book recommendations. And more.... You will leave this podcast episode motivated and with ideas to do more for your company, your family, your team, and yourself.

Dr. Donna Vallese's entire career has been dedicated to improving outcomes for students by supporting educators in implementing game-changing and innovative practices. I have had the opportunity to work at all levels of education (state, university, district, school, and classroom) and those settings have been in urban, charter, sub-urban, and rural schools.

Transitioning a large company like Hewlett Packard Enterprise (HPE) to a skills-based organization could be a daunting task. That's why focusing on scope and purpose was an important place to start for Vandana Bhagtani and Kaye Slay. In this conversation, Vandana—The Director of Technical Talent Management—and Kaye—The User Experience and Adoption Lead for Talent and Learning Systems—share how they've worked together to develop a strategy for transitioning HPE to a skills-based organization. They also share why they chose to focus on a particular group and narrowed their scope further to talent acquisition and people development (all the while leveraging technology and AI). They're at the start of their journey and will evolve and develop as they transition to a skills-based organization. You will want to hear this episode if you are interested in...Learn more about Kaye Slay, Vandana Bhagtani, and HPE [4:19]Why they're trying to create a skills-based organization [7:42]The process of defining scope & purpose [9:13]The structure of their skills model [17:53]What sparked the transition to a skills-based organization [20:38]How they communicated scope & purpose to HPE [24:34]The lightning round [26:45]The role technology plays in enabling a skills-based organization [33:11]The technology that's necessary to become skills-based [36:29]Who supports the tech needs of the organization [39:02]A conversation about ethics in AI [41:13]Kaye's advice for someone starting in tech [46:21]Why Vandana and Kaye chose this work [48:33]Resources & People MentionedJosh BersinJohn MaxwellDon CliftonWorkday HCMSkillsoft PercipioPhenom Candidate Experience Connect with Vandana Bhagtani and Kaye SlayVandana Bhagtani on LinkedInKaye Slay on LinkedInConnect With Red Thread ResearchWebsite: Red Thread ResearchOn LinkedInOn FacebookOn TwitterSubscribe to WORKPLACE STORIES

Summary Software systems power much of the modern world. For applications that impact the safety and well-being of people there is an extra set of precautions that need to be addressed before deploying to production. If machine learning and AI are part of that application then there is a greater need to validate the proper functionality of the models. In this episode Erez Kaminski shares the work that he is doing at Ketryx to make that validation easier to implement and incorporate into the ongoing maintenance of software and machine learning products. Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Your host is Tobias Macey and today I'm interviewing Erez Kaminski about using machine learning in safety critical and highly regulated medical applications Interview Introduction How did you get involved in machine learning? Can you start by describing some of the regulatory burdens placed on ML teams who are building solutions for medical applications? How do these requirements impact the development and validation processes of model design and development? What are some examples of the procedural and record-keeping aspects of the machine learning workflow that are required for FDA compliance? What are the opportunities for automating pieces of that overhead? Can you describe what you are doing at Ketryx to streamline the development/training/deployment of ML/AI applications for medical use cases? What are the ideas/assumptions that you had at the start of Ketryx that have been challenged/updated as you work with customers? What are the most interesting, innovative, or unexpected ways that you have seen ML used in medical applications? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Ketryx? When is Ketryx the wrong choice? What do you have planned for the future of Ketryx? Contact Info Email (mailto:info@ketryx.com) LinkedIn (https://www.linkedin.com/in/erezkaminski/) Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast (https://www.dataengineeringpodcast.com) covers the latest on modern data management. Podcast.__init__ () covers the Python language, its community, and the innovative ways it is being used. Visit the site (https://www.themachinelearningpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com (mailto:hosts@themachinelearningpodcast.com)) with your story. To help other people find the show please leave a review on iTunes (https://podcasts.apple.com/us/podcast/the-machine-learning-podcast/id1626358243) and tell your friends and co-workers. Links Ketryx (https://www.ketryx.com/) Wolfram Alpha (https://www.wolframalpha.com/) Mathematica (https://www.wolfram.com/mathematica/) Tensorflow (https://www.tensorflow.org/) SBOM == Software Bill Of Materials (https://www.cisa.gov/sbom) Air-gapped Systems (https://en.wikipedia.org/wiki/Air_gap_(networking)) AlexNet (https://en.wikipedia.org/wiki/AlexNet) Shapley Values (https://c3.ai/glossary/data-science/shapley-values/) SHAP (https://github.com/shap/shap) Podcast.__init__ Episode (https://www.pythonpodcast.com/shap-explainable-machine-learning-episode-335/) Bayesian Statistics (https://en.wikipedia.org/wiki/Bayesian_inference) Causal Modeling (https://en.wikipedia.org/wiki/Causal_inference) Prophet (https://facebook.github.io/prophet/) FDA Principles Of Software Validation (https://www.fda.gov/regulatory-information/search-fda-guidance-documents/general-principles-software-validation) The intro and outro music is from Hitman's Lovesong feat. Paola Graziano (https://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Tales_Of_A_Dead_Fish/Hitmans_Lovesong/) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/)/CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/)

As the Senior Supervisor of Learning Systems & Development at Lucid Motors, Ryan Kruger has a mouthful of a job title—and a lot to say about electric luxury sports cars, heavy metal, and local libraries (see if yours has a 3D printer!). But his number one passion? Designing and delivering more effective learning solutions.It's worth tuning in, literally or figuratively, if you believe L&D has changed and is changing. If you're struggling to deliver effective training, curious about user experience design, and tired of bouncing between knowledge management tools. And if your personal success hinges on 1) understanding the efficacy of your work, and 2) driving behavioral change.In this episode, we discuss:• What L&D is and isn't• How time-starved teams consume content • The ADDIE framework—and why “A” and “E” need more focus• Evaluating L&D impact with the Kirkpatrick Model• How Lucid Motors minimizes siloed work and maximizes knowledge sharingWhere to find Ryan Kruger:• Lucid Motors: https://lucidmotors.com/• Tango's Community: https://www.tango.us/change-enablers-communityWhere to find your host, Ken: • LinkedIn: https://www.linkedin.com/in/kenbabcock/• Twitter/X: https://twitter.com/bigredbabzLike what you heard? Subscribe, leave us a review, and let us know who in Operations and Enablement should be our next guest.

In this live 55min group coaching call, Brian Cain, MPM is joined by Brittany Loney, cognitive performance coach to elite Warriors, to talk about the mindset, routines, and training of elite warriors.  Brittany has a Ph.D. in Educational Psychology and Learning Systems from The Florida State University, an M.A. in Kinesiology with an emphasis on performance psychology from California State University, Fresno, an M.S. in Exercise Science from Florida State University, and a B.S. in Criminal Justice from Texas State University where she was also a NCAA Division 1 basketball player.  Brittany is the director and creator of the Elite Cognition and Human Optimization (ECHO) program at Core One. She has over 18 years of experience training high performers from a vast array of communities, such as elite warriors, Olympic athletes, high-level coaches, Non-Governmental Organizations (NGOs), and C-Suite Executives.  For the past 13+ years, Brittany has been developing and implementing cognitive training programs within the national security and government sectors. She helped develop and taught curriculum for NATO's Inaugural Mental Performance and Resiliency Course.  Brittany focuses her efforts towards serving those who operate within dynamic high stakes environments where people are a critical capability and human error is a legitimate risk to self or mission.  Her specialty is building, refining, and implementing large-scale performance programs and thrives in environments where the concept of cognitive performance is novel. She routinely consults with an array of personnel, from military to sports to business, to bring about the effective assimilation of cognitive performance principles to advance both individual and organizational effectiveness.  Over her career, Brittany and her team were embedded within highly selective hiring processes and arduous training pipelines. During this time, they refined a 360 degree approach to developing adaptive experts across a multitude of domains. The team worked extensively with trainees, instructors, course planners, and leadership to assimilate deliberate practice principles, adaptability research, and growth cultivation throughout the entire developmental process.  Brittany will share some of the best practices and lessons learned garnered through their integration with some of the nation's most exceptional training. Maximum cohesive functioning is a prerequisite for any team to be greater than the sum of its parts. Over the past decade, Brittany and her team were immersed in organizations where their program was leveraged to facilitate desired cultural shifts and organizational end-states.  She will discuss interpersonal adaptability and adjusting communication styles, building unsung hero attributes, and refining team culture, values, systems, and processes to ensure optimal collective performance. Brittany looks forward to sharing with our community best practices and lessons learned related to training adaptive experts and building cultures that raise the tide. Learn more about your ad choices. Visit megaphone.fm/adchoices

Today we are joined by Rickard Brüel Gabrielsson, an artificial intelligence researcher and co-founder of Unbox AI. Rickard moved from Sweden to the US to attend Stanford and immediately dove into learning systems and artificial intelligence. Rickard breaks down unsupervised learning, text-based language models, revolutionizing retail, pricing your product, encoding semantics, and where companies will incorporate foundation models.Episode Chapters:Transitioning from Sweden to the US - 1:35Interest in Learning Systems & AI - 2:40Unsupervised Learning - 5:24Foundation Models - 7:14Unbox AI - 9:29Building Application Models - 11:41VC in the eyes of an AI founder - 14:26Fine-tuning and Vector Databases - 17:08Embedding Semantics - 19:50Protecting Domain Expertise - 24:40Are Smaller Players Ripe for AI Innovation? - 26:43Artificial General Intelligence (AGI) applicability - 28:52Ending Questions - 31:33As always, feel free to contact us at partnerpathpodcast@gmail.com. We would love to hear ideas for content, guests, and overall feedback.  

What does it take to support the complex training needs of franchise organizations? Find out on this Talented Learning Show podcast episode!

This episode is sponsored by Netsuite by Oracle, the number one cloud financial system, streamlining accounting, financial management, inventory, HR, and more. Download NetSuite's popular KPI Checklist, designed to give you consistently excellent performance - absolutely free, at NetSuite.com/EYEONAI. On episode #133 of the Eye on AI podcast, Craig Smith sits down with Michael Jordan. A revered scientist and distinguished professor at the University of California, Berkeley, Michael's expertise spans machine learning, statistics, and artificial intelligence. In this episode we explore the intricate landscape of deep learning, its statistical bedrock, and the myriad applications of machine learning methods. We dig deeper into the cloud computing revolution, ignited by deep learning, which has empowered behemoths like Amazon to streamline their logistics and commerce data. The dialogue continues as we uncover the trends in deep learning, its role in the grand scheme of AI, and the persisting challenges in the domain. We conclude by contemplating the repercussions of AI and optimization in complex systems. We examine its historical roots in the mid-20th century, its potential to replace jobs, and its application in various sectors such as financial markets, healthcare, and education. (00:00) Preview (01:00) Introduction (01:36) NetSuite by Oracle (03:53) Deep Learning Advancements in AI (12:56) AI Optimization in Complex Systems (28:53) Future of Machine Learning in Healthcare (39:45) Privacy and Value in Multi-Agent Learning (54:48) Learning Systems, Avatars, and Music Business (1:02:20) Single Source of Truth for Business Owners (1:04:28) NetSuite by Oracle Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI  

Meet Dr. Brittany Loney, the mastermind behind the Elite Cognition and Human Optimization (ECHO) program at Core One. As a skilled professional with over 12 years of experience training Special Operations Forces (SOF) personnel, Brittany was the first cognitive performance coach embedded within the USASOC Tactical Human Optimization and Rapid Rehabilitation (THOR3) Program. Since then, she has been dedicated to developing and implementing cognitive training programs across SOF, the U.S. national security community, and government sectors. Brittany frequently advises DoD and other U.S. government personnel on how to effectively incorporate cognitive performance principles into training and career pipelines. Brittany has an impressive educational background, including a Ph.D. in Educational Psychology and Learning Systems from Florida State University, an M.A. in Kinesiology with an emphasis on Performance Psychology from California State University, Fresno, an M.S. in Exercise Science from Florida State University, and a B.S. in Criminal Justice from Texas State University, where she also played NCAA Division 1 basketball. Her passion for her profession extends beyond the workplace as she enjoys exercising, ultra-running, hiking, paddle boarding, and researching neuroscience, performance, and cognition.This episode lays the groundwork for everything you need to start mentally preparing yourself for your journey ahead, and some really helpful tools to help you in the moment. Make sure to check out the ECHO program at www.elite-cognition.com and thank you to Dr. Loney for sitting down and sharing her considerable knowledge and experience. 00:00 The Intro 01:00 Dr. Loney's background08:30 Immersion into SOF11:15 Jump Master Training and Lessons Learned24:30 Creative Thinking with SOF33:00 Peaches Gets Mad at Hollywood for PTSD36:00 Peaches gets mad at the quiet professional stigma41:00 ECHO and where Core One started43:30 5 Pillars of ECHO45:30 The 5th Pillar - Culture 49:15 Assessment and Selection tools50:00 Great book recommendations- Ego is the Enemy and the Daily Stoic, Ryan Holiday52:56 Aaron blacks out and actually gives a passable answer for once01:01:30 Preparing for Selection#mentalhealth #podcast #onesready Collabs:18A Fitness - Promo Code: 1ReadyAlpha Brew Coffee Company - Promo Code: ONESREADYATAC Fitness - Promo Code: ONESREADY10CardoMax - Promo Code: ONESREADYEberlestock - Promo Code: OR10Hoist - Promo Code: ONESREADYStrike Force Energy - Promo Code: ONESREADYTrench Coffee Company - Promo Code: ONESREADYGrey Man Gear - Promo Code: ONESREADY The content provided is for informational purposes only and does not constitute legal advice. The host, guests, and affiliated entities do not guarantee the accuracy or completeness of the information provided. The use of this podcast does not create an attorney-client relationship, and the podcast is not liable for any damages resulting from its use. Any mention of products or individuals does not constitute an endorsement. All content is protected by intellectual property laws. By accessing or using this you agree to these terms and conditions.

Stacy and Brenda talk with Joel Bennett, author and President of Organizational Wellness & Learning Systems of what true spirituality is, and living it vs talking about it.We discuss: How we can build relationships and investigate together What is the relationship between time and intimacy? Tuning into synchronicities Opening up to different forms of timeWhy does the planet's future depend on having a revised language for time? Soulful Capacities: Acceptance, Presence, Flow, and SynchronicityCultivating our soulHow can we begin to shift the consciousness of our constructed idea of time? What role does time play with addiction?Patterns showing up in relationship and doing deep soul workHow his work is supporting the bigger picture of healing the world and what their Macrovision is for the work that he doesJoel Bennett, Ph.D., is President of Organizational Wellness & Learning Systems (OWLS), a consulting firm specializing in evidence-based wellness technologies to promote organizational health and employee well-being. Dr. Bennett first delivered stress management programming in 1985, and OWLS programs have since reached nearly 250,000 workers across the United States and abroad, including training over 1,000 facilitators and coaches. He is a primary developer of “Team Awareness” and “Team Resilience,” evidence-based culture of health programs recognized by the U.S. Dept. of Health and Surgeon General as effective in reducing employee behavioral risks. In 2022, Dr. Bennett was acknowledged with the "Lifetime Achievement Award" from the National Wellness Institute and, internationally, with the "Positive Leadership Award" from the Positive Leadership Institute. Dr. Bennett has authored/co-authored seven books, including "Raw Coping Power," "Heart-Centered Leadership," and "Your Best Self at Work," Joel Bennett's links:www.organizationalwellness.com https://presencequest.life/Be the Love Links:JOIN US IN COSTA RICA! Awaken Your Soul Women's Retreat, November 6-12th, 2023https://awakenyourempoweredsoul.com/be-the-love-costa-rica-retreatWebsite: https://www.bethelovepodcast.com/Facebook page: https://www.facebook.com/bethelovepodcastFacebook group: https://www.facebook.com/groups/bethelovepodcast Instagram: @bethelovepodcastPatreon Website: https://www.patreon.com/bethelovepodcastYour Empowered Soul: A Natural Pathway to Healing Anxiety and Depression https://smile.amazon.com/dp/0578401851/ref=cm_sw_r_cp_api_glt_i_Y764EDGHTVEKW7EV25H7--Free Journey to Abundant Energy video series with Brenda Carey. https://www.sacredpathyogaandreiki.com/journeyThis episode was sponsored by Miracle Tea from Dr. Varun's Love Abundance store. Check out this healing tea! https://www.drvarungandhi.com/product/miracle-tea/#.ZF2azezMKEsHeatherlyn's website: https://www.heatherlynmusic.com This episode was edited by Chelsea Weaver

What should learning professionals know about the latest AI trends? What matters now and how can you prepare for the future? Find out on this episode of The Talented Learning Show!

Summary The focus of machine learning projects has long been the model that is built in the process. As AI powered applications grow in popularity and power, the model is just the beginning. In this episode Josh Tobin shares his experience from his time as a machine learning researcher up to his current work as a founder at Gantry, and the shift in focus from model development to machine learning systems. Announcements Hello and welcome to the Machine Learning Podcast, the podcast about machine learning and how to bring it from idea to delivery. Your host is Tobias Macey and today I'm interviewing Josh Tobin about the state of industry best practices for designing and building ML models Interview Introduction How did you get involved in machine learning? Can you start by describing what a "traditional" process for building a model looks like? What are the forces that shaped those "best practices"? What are some of the practices that are still necessary/useful and what is becoming outdated? What are the changes in the ecosystem (tooling, research, communal knowledge, etc.) that are forcing teams to reconsider how they think about modeling? What are the most critical practices/capabilities for teams who are building services powered by ML/AI? What systems do they need to support them in those efforts? Can you describe what you are building at Gantry and how it aids in the process of developing/deploying/maintaining models with "modern" workflows? What are the most challenging aspects of building a platform that supports ML teams in their workflows? What are the most interesting, innovative, or unexpected ways that you have seen teams approach model development/validation? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Gantry? When is Gantry the wrong choice? What are some of the resources that you find most helpful to stay apprised of how modeling and ML practices are evolving? Contact Info LinkedIn (https://www.linkedin.com/in/josh-tobin-4b3b10a9/) Website (http://josh-tobin.com/) Parting Question From your perspective, what is the biggest barrier to adoption of machine learning today? Closing Announcements Thank you for listening! Don't forget to check out our other shows. The Data Engineering Podcast (https://www.dataengineeringpodcast.com) covers the latest on modern data management. Podcast.__init__ () covers the Python language, its community, and the innovative ways it is being used. Visit the site (https://www.themachinelearningpodcast.com) to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email hosts@themachinelearningpodcast.com (mailto:hosts@themachinelearningpodcast.com)) with your story. To help other people find the show please leave a review on iTunes (https://podcasts.apple.com/us/podcast/the-machine-learning-podcast/id1626358243) and tell your friends and co-workers Links Gantry (https://gantry.io/) Full Stack Deep Learning (https://fullstackdeeplearning.com/) OpenAI (https://openai.com/) Kaggle (https://www.kaggle.com/) NeurIPS == Neural Information Processing Systems Conference (https://nips.cc/) Caffe (https://caffe.berkeleyvision.org/) Theano (https://github.com/Theano/Theano) Deep Learning (https://en.wikipedia.org/wiki/Deep_learning) Regression Model (https://www.analyticsvidhya.com/blog/2022/01/different-types-of-regression-models/) scikit-learn (https://scikit-learn.org/) Large Language Model (https://en.wikipedia.org/wiki/Large_language_model) Foundation Models (https://en.wikipedia.org/wiki/Foundation_models) Cohere (https://cohere.com/) Federated Learning (https://en.wikipedia.org/wiki/Federated_learning) Feature Store (https://www.featurestore.org/) dbt (https://www.getdbt.com/) The intro and outro music is from Hitman's Lovesong feat. Paola Graziano (https://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/Tales_Of_A_Dead_Fish/Hitmans_Lovesong/) by The Freak Fandango Orchestra (http://freemusicarchive.org/music/The_Freak_Fandango_Orchestra/)/CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/)

We talked about: Arseny's background Working on machine learning in startups What is Machine Learning System Design? Constraints and requirements Known unknowns vs unknown unknowns (Design stage) Writing a design document Technical problems vs product-oriented problems The solution part of the Design Document What motivated Arseny to write a book on ML System Design Examples of a Design Document in the book The types of readers for ML System Design Working with the co-author Reacting to constraints and feedback when writing a book Arseny's favorite chapter of the book Other resources where you can learn about ML System Design Twitter Giveaway Links: Book: https://www.manning.com/books/machine-learning-system-design?utm_source=AGMLBookcamp&utm_medium=affiliate&utm_campaign=book_babushkin_machine_4_25_23&utm_content=twitter Discount: poddatatalks21 (35% off) Free data engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html

Chip Huyen, co-founder of Claypot AI and author of O'Reilly's best-selling "Designing Machine Learning Systems" is here to share her expertise on designing production-ready machine learning applications, the importance of iteration in real-world deployment, and the critical role of real-time machine learning in various applications. Technical listeners like data scientists and machine learning engineers will definitely enjoy this one! This episode is brought to you by Pathway, the reactive data processing framework (https://www.pathway.com/?from=superdatascience), and by epic LinkedIn Learning instructor Keith McCormick.(linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Why Chip wrote 'Designing Machine Learning Systems' [08:58] • How Chip ended up teaching at Stanford [13:18] • About Chip's book 'Designing Machine Learning Systems' [21:12] • What makes ML feel like magic [30:53] • How to align business intent, context, and metrics with ML [37:55] • The lessons Chip learned about training data [42:03] • Chip's secrets to engineering good features [53:19] • How Chip optimizes her productivity [1:07:48] Additional materials: www.superdatascience.com/661

    At the Learning Technologies France show in Paris this February, John talked to two of the industry's leading commentators, who both released significant pieces of research at the show. The L&D Global Sentiment Survey, run by Donald H Taylor, takes the pulse of the L&D community world-wide. The one-minute online poll asks L&D professionals internationally what they think will be hot in the following year. The Fosway 9-Grid™ report for Learning Systems plots the relative position of solutions and providers, predominantly within the UK and European market. Different solutions can be compared based on their Performance, Potential, Market Presence, Total Cost of Ownership and Future Trajectories across the market. Between them, these two surveys give a picture of where Learntech systems are in the post-pandemic world, and what is firing the expectations and imaginations of the learning community. 00:00 Intro 02:15 Don Taylor: What's changed since last year? 05:23 Is it unusual for a 'macro' issue like skills to dominate the survey? 07:21 AI 13:22 Metaverse 18:45 VR 21:07 Leading trends in the US 24:15 Is this a return to the pre-pandemic world? 26:45 David Wilson: The new 9-Grid for learning 28:05 Any surprises in the changes compared to last year? 33:43 'Ecosystemness' 42:40 Learning Systems market development Follow Donald H. Taylor LinkedIn: https://www.linkedin.com/in/donaldhtaylor Website: https://donaldhtaylor.co.uk/insight/gss2023-results/ Twitter: @DonaldHTaylor Follow David Wilson LinkedIn: https://www.linkedin.com/in/dwil23 Fosway website: https://www.fosway.com/ Twitter: @dwil23 Email: david.wilson@fosway.com Contact John Helmer Twitter: @johnhelmer LinkedIn: https://www.linkedin.com/in/johnhelmer/ Website: https://learninghackpodcast.com/ Patreon: https://www.patreon.com/LearningHack

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AI Safety in a World of Vulnerable Machine Learning Systems, published by AdamGleave on March 8, 2023 on The AI Alignment Forum. Even the most advanced contemporary machine learning systems are vulnerable to adversarial attack. The safety community has often assumed adversarial robustness to be a problem that will be solved naturally as machine learning (ML) systems grow more capable and general. However, recent work has shown that superhuman systems in a narrow domain such as AlphaZero are highly vulnerable to adversarial attack, as are general but less capable systems like large language models. This raises the possibility that adversarial (worst-case) robustness will continue to lag behind average-case capabilities. In other words, transformative AI systems are likely to be exploitable. Exploitability will cause a wide variety of current alignment proposals to fail. Most extant agendas seek to align the main ML system with the assistance of helper ML systems. The main ML system is the primary system that takes actions in the world (e.g. interacting with users), with the helper ML systems acting as scaffolding to train and/or verify the main ML system. These alignment schemes will fail if the helpers are exploited by the main system – and we expect helpers to be vulnerable to exploitation (see Contemporary ML systems are exploitable by default). In Table 1 we present a subjective risk matrix for a range of popular alignment agendas, evaluating the degree to which main ML systems have the ability and incentive to exploit the helper. We find many alignment agendas have a high risk of exploitation, with all having at least some risk. Alignment AgendaMain System's Ability to Exploit HelperMain System's Incentive to Exploit HelperRisk of ExploitRL on learned reward model (e.g. RLHF, IRL)MediumHighHighScalable oversight (e.g. recursive reward modeling,AI safety via debate)MediumHighHighImitation learning (e.g. behavioral cloning, supervised fine-tuning)MediumLowLow-MediumImitative Iterated Distillation and AmplificationHighLowMediumAuditing Tool (e.g. Adversarial Testing, Transparency)LowMediumLow-Medium Table 1: Subjective risk matrix for popular alignment agendas (see next section), using a helper ML system to assist with aligning the main ML system that will eventually be deployed. We are most concerned by vulnerabilities in the helpers as this can impact the alignment of the main system. By contrast, an aligned but adversarially exploitable main system would not necessarily pose a danger, especially if the main system can recursively self-improve to fix itself. However, there is a possibility that even superintelligent systems cannot attain adversarial robustness. This would be a volatile situation, which could conceivably collapse into chaos (systems frequently exploiting each other), an implicit equilibrium (e.g. mutually assured destruction), or an explicit agreement (e.g. all AI systems self-modify to commit to not exploiting one another). We see two possible approaches to fixing this: improving adversarial robustness, or developing fault tolerant alignment methods that can work even in the presence of vulnerable ML systems. We are most excited by fault tolerant alignment, as it is highly neglected and plausibly tractable, although further work is needed to solidify this approach. By contrast, adversarial robustness is an area that has received significant attention from the ML research community (low neglectedness)[1] but with only modest progress (low to medium tractability). In the remainder of this document, we will argue that systems are exploitable by default, explore the implications this has for alignment agendas in several different scenarios, and outline several research directions we are excited by. Alignment agendas need robustness Most alignment sche...

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: AI Safety in a World of Vulnerable Machine Learning Systems, published by AdamGleave on March 8, 2023 on LessWrong. Even the most advanced contemporary machine learning systems are vulnerable to adversarial attack. The safety community has often assumed adversarial robustness to be a problem that will be solved naturally as machine learning (ML) systems grow more capable and general. However, recent work has shown that superhuman systems in a narrow domain such as AlphaZero are highly vulnerable to adversarial attack, as are general but less capable systems like large language models. This raises the possibility that adversarial (worst-case) robustness will continue to lag behind average-case capabilities. In other words, transformative AI systems are likely to be exploitable. Exploitability will cause a wide variety of current alignment proposals to fail. Most extant agendas seek to align the main ML system with the assistance of helper ML systems. The main ML system is the primary system that takes actions in the world (e.g. interacting with users), with the helper ML systems acting as scaffolding to train and/or verify the main ML system. These alignment schemes will fail if the helpers are exploited by the main system – and we expect helpers to be vulnerable to exploitation (see Contemporary ML systems are exploitable by default). In Table 1 we present a subjective risk matrix for a range of popular alignment agendas, evaluating the degree to which main ML systems have the ability and incentive to exploit the helper. We find many alignment agendas have a high risk of exploitation, with all having at least some risk. Alignment AgendaMain System's Ability to Exploit HelperMain System's Incentive to Exploit HelperRisk of ExploitRL on learned reward model (e.g. RLHF, IRL)MediumHighHighScalable oversight (e.g. recursive reward modeling,AI safety via debate)MediumHighHighImitation learning (e.g. behavioral cloning, supervised fine-tuning)MediumLowLow-MediumImitative Iterated Distillation and AmplificationHighLowMediumAuditing Tool (e.g. Adversarial Testing, Transparency)LowMediumLow-Medium Table 1: Subjective risk matrix for popular alignment agendas (see next section), using a helper ML system to assist with aligning the main ML system that will eventually be deployed. We are most concerned by vulnerabilities in the helpers as this can impact the alignment of the main system. By contrast, an aligned but adversarially exploitable main system would not necessarily pose a danger, especially if the main system can recursively self-improve to fix itself. However, there is a possibility that even superintelligent systems cannot attain adversarial robustness. This would be a volatile situation, which could conceivably collapse into chaos (systems frequently exploiting each other), an implicit equilibrium (e.g. mutually assured destruction), or an explicit agreement (e.g. all AI systems self-modify to commit to not exploiting one another). We see two possible approaches to fixing this: improving adversarial robustness, or developing fault tolerant alignment methods that can work even in the presence of vulnerable ML systems. We are most excited by fault tolerant alignment, as it is highly neglected and plausibly tractable, although further work is needed to solidify this approach. By contrast, adversarial robustness is an area that has received significant attention from the ML research community (low neglectedness)[1] but with only modest progress (low to medium tractability). In the remainder of this document, we will argue that systems are exploitable by default, explore the implications this has for alignment agendas in several different scenarios, and outline several research directions we are excited by. Alignment agendas need robustness Most alignment schemes implicitl...

Head to Damn Good Conversations to find more about a limited number of Custom Communication Coaching opportunites.  Today's guest is a world class communicator. At 34, Kai Correa is one of the youngest coaches in all of Major League Baseball. He's ascended the ranks from small college baseball to the highest level in the world. Today he shares an inside look at his process like never before.  In our conversation, we discuss: Kai's philosophy of teaching  His definition of true preparation  How he thinks about being a MLB coach at 34 His personal systems for maximing his learning & teaching  How he communicates with some of the best athletes in the world  All this and much more. Email me Joe@onepercentbetterproject.com if I can be of help.  As always, thanks for listening! --Joe       

Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Trends in the dollar training cost of machine learning systems, published by Ben Cottier on February 1, 2023 on The Effective Altruism Forum. Thanks for listening. To help us out with The Nonlinear Library or to learn more, please visit nonlinear.org.

Asking for what you want doesn't have to be a difficult task. However, many mid-career professionals often struggle with asking for what they want, especially regarding their salary and compensation.  Christy Metcalf is an expert when it comes to asking for what you want in your career and life. She is the President and Founder of CEO Learning Systems, a company dedicated to helping women make more money without feeling like they need to work harder or sacrifice what's most important to them. And make no mistake; everyone will benefit from this episode.  In this episode, you'll learn the difference between feeling good and feeling usable or relevant, how to examine your thoughts about money and how they impact your life and career, as well as how to ask for what you want, negotiate a better salary, and get what you are worth.  Make sure to connect with Christy on LinkedIn at https://www.linkedin.com/in/christy-metcalf/.  Key Topics & Time Stamps: ·      Introduction (0:00)·      Get Your Free Guide (1:53)·      What Christy Wanted to Be Growing Up (3:40)·      Christy's Early Career (4:49)·      What Makes a Good Training? (6:25)·      Feeling Good vs. Feeling Usable (7:03)·      Your Money Thoughts & Values (8:55)·      Who Christy Works With (10:10)·      Where Fear Holds Us Back from Success (14:05)·      How Women Typically Negotiate Their First Starting Salary (17:15)·      Asking for Your Salary & Your Worth (20:40)·      Christy's Mid-Career GPS Advice (30:40)·      Connect with Christy Metcalf (31:25)·      Wrap-Up (32:10) List of Resources:·      Get Your Free Guide - 5 Mistakes Mid-Career Professionals Make (And Need to Stop Doing) ·      Your Mid-Career GPS – Four Steps to Figuring Out What's Next by John Neral·      SHOW UP - Six Strategies to Lead a More Energetic and Impactful Career by John Neral Thank you for listening to The Mid-Career GPS Podcast. Leave a rating and review on Apple Podcasts here. Visit https://johnneral.com to download your free guide, "5 Mistakes Mid-Career Professionals Make (And Need to Stop Doing) and more information about your leadership and career transition. Connect with John on LinkedIn here.Subscribe to John's YouTube Channel here. Follow John on Instagram @johnneralcoaching.