Podcasts about Coursera

"In this episode of the Aaron Werner Podcast on iCode Media, Aaron sits down with the dynamic and multifaceted Mikki Collins—a former surgical tech turned optical fashionista, ABO speaker, and industry insider. From the OR to the runway, Mikki shares her unique journey and dives into the evolving intersection of optical retail, fashion, patient experience, and practice growth. What You'll Learn:  • Mikki's journey from ophthalmology surgical tech to optical fashion leader  • Why opticians should know the story behind the frame—and how to tell it  • What bespoke acetate is and why it matters in premium eyewear (yes, even Kate Spade!)  • The real role of frame reps—and how to partner better with them  • How AI tools like ChatGPT can help forecast trends and understand local demographics  • Using social media trends and retail experiences (TJ Maxx vs. Gucci!) to design your optical  • How to elevate your team's communication, styling, and selling confidence  • Why “practice, not roleplay” can transform staff training  • Tips for masterclass binge-watching that actually helps your clinic  • Why it's okay to say “we're not for everyone”—and how to lean into your brand identity Resources & Shoutouts:  • Optical Women's Association (OWA)   • MasterClass picks: Salman Rushdie, Jocko Willink, Daniel Pink  • To Sell Is Human by Daniel Pink  • Extreme Ownership by Jocko Willink  • Building a StoryBrand by Donald Miller  • Vision Source (https://visionsource.com) FrameDream Program  • HubSpot Academy (https://academy.hubspot.com/) – Free sales & marketing courses  • Coursera (https://www.coursera.org) – Retail & psychology courses Whether you're an OD, optician, or part of the optical care team, this episode is packed with practical tips and inspiring insights on how to build a smarter, more stylish, and more strategic optical. Contact Mikki Collins: Mikki.Collins@safilo.com" ________________________ questions@eyecode-education.com Go to MacuHealth.com and use the coupon code PODCAST2024 at checkout for special discounts Let's Connect! Follow and join the conversation! Instagram: @aaron_werner_vision

In this episode, we sit down with Charlotte Evans, the Director of Global Customer Advocacy at Coursera for Business. Charlotte brings a wealth of expertise in the realm of talent development, focusing on how organizations can drive transformation through upskilling and reskilling initiatives. Together, they explore;The burgeoning trend of skills-based learningThe pivotal role of AI as both a disruptor and an enabler in the workplace. Charlotte's insights on the top skills in demand, derived from data on 5 million Coursera learners.How organizations like yours can align learning strategies with business outcomes. Dive into this episode to uncover the latest trends in AI, talent mobility, and more, as you gear up to stay ahead in the fast-evolving world of talent development.As Director, Global Customer Advocacy, Coursera for Business, Charlotte Evans collaborates with leading organizations to drive workforce transformation through upskilling and reskilling initiatives. Her focus is advising companies across industries on unlocking their potential by aligning learning strategies with measurable business outcomes. She is passionate about highlighting customer achievements to inspire action, build trust, and foster long-term partnerships.Her career began in student services in Asia, and her commitment to global education access was cemented while at Harvard Graduate School of Education where she received an Ed.M. in International Education Policy. Since joining Coursera in 2019, she has been proud to create meaningful opportunities for individuals to find opportunity and thrive in a rapidly evolving world.Connect with Andy Storch here:WebsiteLinkedInJoin us in the Talent Development Think Tank Community!Connect with Charlotte Evans here:LinkedInJob Skills Report 2025 / CourseraThis episode is sponsored by Learnit, the #1 place for live facilitated programs to elevate individual and organizational growth. Learn more. Mentioned in this episode:Learnit prerollVisit learnit.com/andy to start your free 45-day trial of their Team Pass which includes unlimited classes for up to 20 people. It's a no brainer!

En este episodio de Amigos TIC, Christian Hernandez, director de Coursera Enterprise en Latinoamerica, quien nos habla sobre los avances en la transformación digital de la educación. Nos cuenta cuáles son los intereses de los jóvenes a la hora de aprender y cómo las necesidades del mercado han ido evolucionando.Además, exploramos el papel de las plataformas de aprendizaje en el modelo educativo clásico, como universidades y colegios, y la posibilidad de integrar ambos mundos para potenciar el acceso al conocimiento. Descubre más sobre tecnologías del aprendizaje en este interesante episodio. ¡No te lo pierdas!00:00     Amigos Tic 02:51     Christian Hernandez, director de Coursera Enterprise en Latinoamerica05:00     ¿Qué es Coursera?06:27     ¿Cuántas personas latinoamericanas están aprendiendo  y en qué areas de estudio se enfocan?10:11     ¿Han notado una baja de interés por el aprendizaje de habilidades blandas?14:26     Pensando en voz alta, con Mauricio Jaramillo18:21     ¿Cómo puede impactar esta transformación digital y de aprendizaje en los colegios?22:43     ¿Cómo ven las universidades a Coursera?27:27     ¿Qué espacios hay por llenar en este mundo de la educación y qué tipo de profesionales se requieren?30:43     ¿Cómo es la oferta de Coursera frente a las empresas que requieren cursos personalizados?36:09     ¿Cómo ve el mercado frente a la aceptación de las microcredenciales?

Today, we are diving into an intriguing topic that is at the forefront of many minds in the talent development sphere: AI transformation in the workplace. Our episode features a keynote session by Charlotte Evans from Coursera, who serves as the Director of Global Customer Advocacy, specializing in workforce transformation through upskilling and reskilling.In this episode, originally recorded at the Talent Development Think Tank Conference back in November, Charlotte takes us through;A rapidly evolving landscape where AI is not just a buzzword, but a critical tool for future workforce readinessThe unprecedented speed at which AI tools like ChatGPT have reached global adoption Her insights on how talent development professionals can harness AI for productivity gains.The challenges of integrating AI smoothly into business models, emphasizing the importance of aligning L&D strategies with measurable outcomes, as well as maintaining a growth mindset in the face of rapid technological advancements.Join us as we explore these topics and prepare to elevate your understanding of AI's role in talent development. Whether you are part of L&D, HR, or another area keen on leveraging AI, this episode is packed with valuable insights that will help you navigate the AI transformation journey. Stay tuned for our full interview with Charlotte next week, where we will delve deeper into current skills trends and what they mean for the future of learning. Connect with Andy Storch here:WebsiteLinkedInJoin us in the Talent Development Think Tank Community!Connect with Charlotte Evans here:LinkedInCoursera 2025 Job Skills ReportThanks to our sponsor, Learnit, you can get a free 45-day trial to help your people build more skills that drive success Learn more. Mentioned in this episode:Learnit prerollVisit learnit.com/andy to start your free 45-day trial of their Team Pass which includes unlimited classes for up to 20 people. It's a no brainer!

Art school isn't the typical starting point for a tech industry leader, but for Jessica Neal, former Chief Talent Officer at Netflix, it was the first step in an extraordinary career. In this episode, Jessica shares how she transitioned from an aspiring artist to headhunter to leading Netflix's talent strategy during its explosive growth. Jessica emphasizes the critical importance of providing clear direction and context when it comes to leadership. “If you don't give the right context and your team isn't doing well, guess whose fault it is? Yours.” Jessica doesn't sugar coat the reality of what it takes to lead well and effectively today. Empower your teams? What does empower mean? How about let people do their work and get rid of bureaucracy? Jessica provides a masterclass in adaptability and strategic thinking. She reveals how Netflix's unique culture of “freedom and responsibility” shaped its success and how she implemented the “context, not control” philosophy to empower teams. As a current venture partner at TCV, board member for cutting-edge companies, and co-host of the TruthWorks podcast, Jessica offers invaluable insights on: Identifying and nurturing top talent in high-growth environments Creating a culture of clarity and context to drive business success Evolving HR practices to meet the demands of modern, global workforces Navigating the complexities of DEI initiatives in today's political climate The future of work and how leaders can prepare for ongoing changes Guest Resources: TCV TruthWorks Podcast LinkedIn Instagram About Jessica: Jessica Neal is a seasoned talent and human resources executive who has made significant contributions to some of the most innovative companies in the tech industry. Currently serving as a Venture Partner at TCV (Technology Crossover Ventures), a leading growth equity firm, Jessica brings her extensive experience in talent management and organizational culture to help scale high-growth companies. Jessica's career journey is as unconventional as it is impressive. She began her professional life as an artist, earning a BFA in Fine Arts from the School of Visual Arts in New York City. Her path took an unexpected turn when she discovered her talent for identifying and nurturing top- tier talent in the tech industry. Jessica is perhaps best known for her transformative work at Netflix, where she spent over 11 years across two tenures. As Chief Talent Officer (CHRO), she played a pivotal role in shaping Netflix's renowned culture during its explosive growth from a DVD-by-mail service to the world's leading streaming entertainment company. Under her leadership, Netflix's workforce expanded from 250 to over 10,000 employees globally. Between her stints at Netflix, Jessica held key leadership positions at other innovative companies. She served as Chief People Officer at Scopely, a mobile gaming company, and as Vice President of Talent at Coursera, an online education platform. These experiences further honed her skills in building and scaling teams in fast-paced, high-growth environments. Today, Jessica leverages her expertise as a board member for several companies, including JFrog, a DevOps platform, and Public.com, a social investing platform. Her board service allows her to share her insights on talent strategy, organizational culture, and scaling operations with the next generation of tech leaders. Jessica is also passionate about sharing her knowledge and experiences with a broader audience. She co-hosts the “TruthWorks” podcast with Patty McCord, where they explore pressing issues affecting the modern workplace, from AI and mental health to layoffs and toxic cultures. Known for her candid approach and deep understanding of what makes great companies tick, Jessica Neal continues to be a influential voice in reshaping how we think about work, talent, and organizational culture in the 21st century. Connect with Laurie McGraw – Inspiring Women: Podcast YouTube Instagram Linkedin

It's YOUR time to #EdUpIn this episode, recorded LIVE from the InsightsEDU 2025 Conference in New OrleansYOUR guest is Fritz Vandover, Distributed Learning Program Analyst, University of MinnesotaYOUR host is Dr. Joe SallustioHow is the University of Minnesota supporting online & hybrid program development?What role does Coursera play in the university's non-credit offerings?How are they helping students with "some credit, no credential" return to finish degrees?What impact does flexible program support have on enrollment growth?How are micro-credentials & alternative pathways being incorporated?Topics include:Online Program Support Services (OPSS)Coursera partnership & specializationsCredit for prior learning policiesRe-enrollment pilot for returning studentsSupporting program development across multiple campusesListen in to #EdUpDo YOU want to accelerate YOUR professional development?Do YOU want to get exclusive early access to ad-free episodes, extended episodes, bonus episodes, original content, invites to special events, & more?Then ⁠⁠⁠⁠⁠⁠BECOME AN #EdUp PREMIUM SUBSCRIBER TODAY⁠⁠ - $19.99/month or $199.99/year (Save 17%)!Want YOUR org to cover costs? Email: EdUp@edupexperience.comThank YOU so much for tuning in. Join us on the next episode for YOUR time to EdUp!Connect with YOUR EdUp Team - ⁠⁠⁠⁠⁠⁠⁠⁠⁠Elvin Freytes⁠⁠⁠⁠⁠⁠⁠⁠⁠ & ⁠⁠⁠⁠⁠⁠⁠⁠⁠Dr. Joe Sallustio⁠⁠⁠⁠● Join YOUR EdUp community at ⁠⁠⁠⁠⁠⁠⁠⁠⁠The EdUp Experience⁠⁠⁠⁠⁠⁠⁠⁠⁠!We make education YOUR business! 

In this episode you will hear:   Mark discusses new changes to the Common App, and then he gives he describes Forbes College Financial Grades, a tool you cn use to know which colleges are stable financially and which colleges are struggling financially? Mark interviews Kathleen deLaski, Founder of the Education Design Lab Preview of Part 4 ²  Kathleen and I discuss the correlation between parent involvement and high achievement ²  Kathleen tells our listeners what the Year Up program is ²  Kathleen tells us what a skills genome is ²  Kathleen tells us what the badging movement is ²  Kathleen talks about what she calls the edu-training ecosystem ²  Kathleen says colleges need to be re-imagined and she explains what she calls, “the great college reset” ²  Kathleen talks about students are strategically using Coursera to hack their way to a good job   Speakpipe.com/YCBK is our method if you want to ask a question and we will be prioritizing all questions sent in via Speakpipe. Unfortunately, we will NOT answer questions on the podcast anymore that are emailed in. If you want us to answer a question on the podcast, please use speakpipe.com/YCBK. We feel hearing from our listeners in their own voices adds to the community feel of our podcast.   You can also use this for many other purposes: 1) Send us constructive criticism about how we can improve our podcast 2) Share an encouraging word about something you like about an episode or the podcast in general 3) Share a topic or an article you would like us to address 4) Share a speaker you want us to interview 5) Leave positive feedback for one of our interviewees. We will send your verbal feedback directly to them and I can almost assure you, your positive feedback will make their day.   To sign up to receive Your College-Bound Kid PLUS, our new monthly admissions newsletter, delivered directly to your email once a month, just go to yourcollegeboundkid.com, and you will see the sign-up popup. We will include many of the hot topics being discussed on college campuses.   Check out our new blog. We write timely and insightful articles on college admissions:   Follow Mark Stucker on Twitter to get breaking college admission news, and updates about the podcast before they go live. You can ask questions on Twitter that he will answer on the podcast. Mark will also share additional hot topics in the news and breaking news on this Twitter feed. Twitter message is also the preferred way to ask questions for our podcast:   https://twitter.com/YCBKpodcast   1. To access our transcripts, click: https://yourcollegeboundkid.com/category/transcripts/ 2. Find the specific episode transcripts for the one you want to search and click the link 3. Find the magnifying glass icon in blue (search feature) and click it 4. Enter whatever word you want to search. I.e. Loans 5. Every word in that episode when the words loans are used, will be highlighted in yellow with a timestamps 6. Click the word highlighted in yellow and the player will play the episode from that starting point 7. You can also download the entire podcast as a transcript   We would be honored if you will pass this podcast episode on to others who you feel will benefit from the content in YCBK.   Please subscribe to our podcast. It really helps us move up in Apple's search feature so others can find our podcast.   If you enjoy our podcast, would you please do us a favor and share our podcast both verbally and on social media? We would be most grateful!   If you want to help more people find Your College-Bound Kid, please make sure you follow our podcast. You will also get instant notifications as soon as each episode goes live.   Check out the college admissions books Mark recommends:   Check out the college websites Mark recommends:   If you want to have some input about what you like and what you recommend, we change about our podcast, please complete our Podcast survey; here is the link:     If you want a college consultation with Mark or Lisa or Lynda, just text Mark at 404-664-4340 or email Lisa at or Lynda at Lynda@schoolmatch4u.com. All we ask is that you review their services and pricing on their website before the complimentary session; here is link to their services with transparent pricing: https://schoolmatch4u.com/services/compare-packages/

Episode Notes: My Support Initiative for Federal Workers in TransitionEpisode OverviewIn this episode, I announce a special initiative from Pragmatic AI Labs to support federal workers who are currently in career transitions by providing them with free access to our educational platform. I explain how our technical training can help workers upskill and find new positions.Key PointsAbout the InitiativeI'm offering free platform access to federal workers in transition through Pragmatic AI LabsTo apply, workers should email contact@paiml.com with:Their LinkedIn profileEmail addressPrevious government agencyAccess will be granted "no questions asked"I encourage listeners to share this opportunity with others in their networkAbout Pragmatic AI LabsOur mission: "Democratize education and teach people cutting-edge skills"We focus on teaching skills that are rapidly evolving and often too new for traditional university curriculaOur content has been featured at top universities including Duke, Northwestern, UC Davis, and UC BerkeleyAlso featured on major educational platforms like Coursera and edXWe've built a custom platform with interactive labs and exclusive contentTechnical Skills CoveredCloud Computing:Major providers: AWS, Azure, GCPOpen source solutions: Kubernetes, containerizationProgramming Languages:Strong focus on Rust (we have "potentially the most content on anywhere in the world")PythonEmerging languages like ZigWeb Technologies:WebAssemblyWebSocketsArtificial Intelligence:Practical approaches to generative AIIntegration of cloud-based solutions (e.g., Amazon Bedrock)Working with local open-source modelsMy Philosophy and ApproachOur platform is specifically designed to "help people get jobs"Content focused on practical skills for career advancementEmphasis on teaching cutting-edge material that moves "too fast" for traditional educationWe're committed to "helping humanity at scale"Contact InformationEmail: contact@paiml.comClosing MessageI conclude with a sincere offer to help as many transitioning federal workers as possible gain new skills and advance their careers.

SPECIAL GUEST! Dr. Laurie Santos, Yale professor and host of The Happiness Lab, gives us her sought-after advice for finding more joy in our lives. Parents will love her fresh take and practical insights for “finding the good” even in the most challenging parenting moments. Then in our Parenting Story of the Day, you will hear from a mom of two who was searching for happiness – until she realized it was right in front of her.  Special thanks to Walmart for sponsoring this episode! www.walmart.com  Dr. Laurie Santos / FB / IG / X / YT Dr. Santos is the Chandrika and Ranjan Tandon Professor of Psychology and Head of Silliman College at Yale University. Her course, Psychology and the Good Life, became Yale's most popular course in its over 300 year history, and the online version – The Science of Well-Being on Coursera.org – has attracted more than 4 million learners. A winner of numerous awards both for her science and teaching, Dr. Santos was recently voted as one of Popular Science Magazine's “Brilliant 10” young minds and Time Magazine named her a “Leading Campus Celebrity.” Her podcast, The Happiness Lab, is a top-3 Apple podcast with over 100 million downloads since its launch. Heather Osterman-Davis / FB / IG / X / LI   A mother of two and writer, Heather's work has appeared in various publications including, The New York Times, Washington Post, Time Magazine, Slate, Parents, Literary Mama, Brain Child, Filter Free Parents, and more. She is the author of an award winning short film titled Tell-By Date and winner of Austin Film Festival's Best Comedy TV Pilot for 2024.   StrollerCoaster: A Parenting Podcast is created by Munchkin Inc., the most loved baby lifestyle brand in the world.  You can find all your favorite Munchkin products at https://www.munchkin.com. Use the code STROLLERCOASTER15 for 15% off regular-price items! (expires 4/13/25)  Follow Munchkin on Instagram / Facebook / Pinterest / TikTok Trees for the Future https://trees.org/

Dans cet épisode, nous abordons un sujet qui passionne autant qu'il questionne, une type de pratique qui arrange autant qu'elle… dérange : la formation sur étagère. Nous vous emmenons donc dans le “supermarché” de la formation. Après avoir cadré ce type de pratique, nous passons en revue les questions suivantes, sur base de nos expériences personnelles : Quels sont nos usages de la formation “on-the-shelf” ? Quels en sont les avantages et les limites ? Quels conseils donnerions-nous pour une utilisation efficace ? Autant de questions pour autant de réponses dans cet épisode.Et, une fois n'est pas coutume, vous pouvez aussi y retrouver nos actualités en début d'épisode et nos recommandations pour clôturer cet épisode. Bonne écoute !Nous avons évoquéLes outils de conception pédagogique Genial.ly, Rise ou H5PLes plateformes de formation sur étagère Udemy, Skillshub, LinkedIn Learning, Coursera, Edx, Bookboon, …Les plateformes de formation Domestika,La plateforme de formation aux compétences transversales pour les ouvriers : SlalomNos recommandationsJérôme : L'article d'analyse sur l'utilisation de la gamification & de l'IA dans Duolinguo.Lio : Intégrer un rituel d'écriture

SPECIAL GUEST! Dr. Laurie Santos, Yale professor and host of The Happiness Lab, gives us her sought-after advice for finding more joy in our lives. Parents will love her fresh take and practical insights for “finding the good” even in the most challenging parenting moments. Then in our Parenting Story of the Day, you will hear from a mom of two who was searching for happiness – until she realized it was right in front of her.  Special thanks to Walmart for sponsoring this episode! www.walmart.com  Dr. Laurie Santos / FB / IG / X / YT Dr. Santos is the Chandrika and Ranjan Tandon Professor of Psychology and Head of Silliman College at Yale University. Her course, Psychology and the Good Life, became Yale's most popular course in its over 300 year history, and the online version – The Science of Well-Being on Coursera.org – has attracted more than 4 million learners. A winner of numerous awards both for her science and teaching, Dr. Santos was recently voted as one of Popular Science Magazine's “Brilliant 10” young minds and Time Magazine named her a “Leading Campus Celebrity.” Her podcast, The Happiness Lab, is a top-3 Apple podcast with over 100 million downloads since its launch. Heather Osterman-Davis / FB / IG / X / LI   A mother of two and writer, Heather's work has appeared in various publications including, The New York Times, Washington Post, Time Magazine, Slate, Parents, Literary Mama, Brain Child, Filter Free Parents, and more. She is the author of an award winning short film titled Tell-By Date and winner of Austin Film Festival's Best Comedy TV Pilot for 2024.   StrollerCoaster: A Parenting Podcast is created by Munchkin Inc., the most loved baby lifestyle brand in the world.  You can find all your favorite Munchkin products at https://www.munchkin.com. Use the code STROLLERCOASTER15 for 15% off regular-price items! (expires 4/13/25) Follow Munchkin on Instagram / Facebook / Pinterest / TikTok Trees for the Future 

The Power of Self-Improvement: A Journey Towards Personal GrowthSelf-improvement is a continuous journey that involves enhancing one's skills, knowledge, and mindset to reach their full potential. Here's why it's crucial and how to embark on this transformative path: Enhanced Self-Awareness: Self-improvement fosters a deeper understanding of your strengths, weaknesses, values, and beliefs, enabling informed decision-making and goal setting12. Improved Relationships: Developing better communication skills, empathy, and emotional intelligence through self-improvement can lead to more meaningful and harmonious relationships2. Increased Resilience: Personal growth equips you with the skills and mindset to cope with adversity, viewing challenges as opportunities for learning and growth2. Greater Clarity and Focus: By setting clear goals and priorities, self-improvement helps you direct your energy towards what truly matters, enhancing productivity and decision-making2. Enhanced Problem-Solving Skills: As you gain new knowledge and experiences, your ability to analyze situations, identify solutions, and make sound decisions improves2. Boosted Self-Confidence: Achieving goals and recognizing your capabilities through self-improvement builds self-worth and confidence, empowering you to take on new challenges2. Better Time Management: Developing organizational skills and prioritizing tasks leads to more efficient time management, reducing stress and increasing productivity2. Enhanced Creativity and Innovation: Personal growth encourages thinking outside the box, fostering creativity and innovation in both personal and professional contexts2. Improved Health and Well-Being: Self-improvement promotes positive habits and behaviors, enhancing physical, mental, and emotional health23. Set Clear Goals: Define what personal growth means to you, setting specific, measurable goals that act as beacons guiding your actions5. Embrace Continuous Learning: Never stop learning. Engage in formal education, self-directed study, or learn from mentors to expand your understanding5. Step Out of Your Comfort Zone: Challenge yourself by taking calculated risks and embracing uncertainty, fostering resilience and growth5. Practice Self-Reflection: Regularly introspect to evaluate your experiences, successes, and setbacks, gaining clarity and self-awareness5. Cultivate Positive Habits: Identify and replace negative habits with positive ones, reinforcing your commitment to personal growth5. Seek Feedback and Accountability: Solicit constructive criticism and have an accountability partner to stay motivated and focused5. Stay Flexible and Adapt: Embrace change as an opportunity for growth, maintaining a growth mindset that views failures as learning experiences5. Books: "Atomic Habits" by James Clear, "The 7 Habits of Highly Effective People" by Stephen Covey, and "Daring Greatly" by Brene Brown are among the top self-help books for personal growth71012. Apps: Tools like GoodLiife Score App, Trello, Headspace, Skillshare, Evernote, and MyFitnessPal can aid in tracking progress, managing tasks, and fostering well-being8. Online Courses: Platforms like Coursera, Udemy, and free courses by Dean Bokhari offer structured learning opportunities for personal development9. Websites and Blogs: Websites like joyamongchaos.com provide insights into personal growth, living joyfully, and self-improvement13.Self-improvement is not just about achieving goals but about becoming the best version of yourself. By embracing this journey, you unlock numerous benefits that enhance your professional and personal life. Remember, the path to self-improvement is ongoing, requiring patience, persistence, and a willingness to learn and grow. With the right mindset, tools, and strategies, you can navigate this journey with confidence, turning your dreams into reality and living a more fulfilling life.

Welcome to the What's Next! Podcast with Tiffani Bova.     This week I'm giving another listen to a conversation I shared with Professor Christian Terwiesch and I'm eager to share it with you! Christian is a Professor in Wharton's Operations and Information Management department, co-director of Penn's Mack Institute for Innovation Management, and also holds a faculty appointment at Penn's Perelman School of Medicine. He is the co-author of Matching Supply with Demand, a widely used textbook in Operations Management. He launched the first Massive Open Online Course (MOOC) in business on Coursera based on the book and since its inception, more than half a million students have enrolled. His first management book, Innovation Tournaments, details a new process-based approach to innovation and has inspired innovation tournaments around the world. His latest book, Connected Strategies, combines his expertise in the fields of operations, innovation, and strategy to help companies take advantage of digital technology leading to new business models. In addition to his teaching and his research, Professor Terwiesch is the host of “Work of Tomorrow,” a national radio show on Sirius XM 132.     THIS EPISODE IS PERFECT FOR… anyone wanting to become more innovative or bring a culture of innovation to their organization, as well as those wanting to get a pulse on new business models shaping how organizations interact with customers today.    TODAY'S MAIN MESSAGE… we have to find different ways of delighting our customers. How do we do that? Through innovation and continuous connection. Professor Terwiesch maintains that innovation is a cultural process that can be managed. That is the power of the Innovation Tournament, it leaves room for that magic spark to fly while giving it direction and structure. Beyond Innovation Tournaments, it's about becoming continuously connected. This connection enables new ways of delighting the customer and also allows organizations to provide more value to the customer, potentially at a lower cost. The purpose of a connected strategy and a continuous relationship is not only to get data but also to do a better job for the customer.    WHAT  I  LOVE  MOST… I love that Christian has identified these new business models that are fundamentally changing the way organizations interact with their customers.     Running Time: 30:47    Subscribe on iTunes     Find Tiffani Online: LinkedIn Facebook X    Find Christian Online: LinkedIn  Connected-Strategy Website Work of Tomorrow Podcast    Christian's Book:  Connected Strategy Book 

In this podcast episode, we talked with Alexander Guschin about launching a career off Kaggle.About the Speaker: Alexander Guschin is a Machine Learning Engineer with 10+ years of experience, a Kaggle Grandmaster ranked 5th globally, and a teacher to 100K+ students. He leads DS and SE teams and contributes to open-source ML tools.00:00 Starting with Machine Learning: Challenges and Early Steps 13:05 Community and Learning Through Kaggle Sessions 17:10 Broadening Skills Through Kaggle Participation 18:54 Early Competitions and Lessons Learned 21:10 Transitioning to Simpler Solutions Over Time 23:51 Benefits of Kaggle for Starting a Career in Machine Learning 29:08 Teamwork vs. Solo Participation in Competitions 31:14 Schoolchildren in AI Competitions42:33 Transition to Industry and MLOps50:13 Encouraging teamwork in student projects50:48 Designing competitive machine learning tasks52:22 Leaderboard types for tracking performance53:44 Managing small-scale university classes54:17 Experience with Coursera and online teaching59:40 Convincing managers about Kaggle's value61:38 Secrets of Kaggle competition success63:11 Generative AI's impact on competitive ML65:13 Evolution of automated ML solutions66:22 Reflecting on competitive data science experience

Book Club Podcast? Before we even got to the News and Research, this week we discussed the AI-related books we're currently reading: Dan's reading: Where Good Ideas Come From, by Steven Johnson (TED Talk) Why Data Science Projects Fail, by Douglas Gray and Evan Shellshear (An interview with Evan) Ray's reading  The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, by Kate Crawford (Wikipedia page) News Links Links to the reports and news we discuss in the episode: OpenAI's new Education newsletter https://openaiforeducation.substack.com/ Ethan Mollick's new "AI in Education: Leveraging ChatGPT for Teaching" course on Coursera https://www.coursera.org/learn/wharton-ai-in-education-leveraging-chatgpt-for-teaching World Economic Forum "Future of Jobs report" https://www.weforum.org/publications/the-future-of-jobs-report-2025/infographics-94b6214b36/ Student expelled and deported because they were accused of using ChatGPT by their professor. So they're suing their professor https://www.fox9.com/video/1574324 Digital Education Council Global AI Faculty Survey 2025 https://www.digitaleducationcouncil.com/post/digital-education-council-global-ai-faculty-survey We'll discuss this report with one of the authors in next week's episode UK government policy paper on "Generative artificial intelligence (AI) in education" https://www.gov.uk/government/publications/generative-artificial-intelligence-in-education/generative-artificial-intelligence-ai-in-education Year13 Case Study on AI use https://news.microsoft.com/en-au/2024/12/13/guiding-school-leavers-with-ai-support-year13s-mission-to-democratise-opportunities-for-young-people/ AI Use by industry employees - US, 2024 https://www.nber.org/papers/w32966 In the discussion of energy use by AI, Ray mentioned some stats from this research report: "The Carbon Emissions of Writing and Illustrating Are Lower for AI than for Humans"  https://arxiv.org/ftp/arxiv/papers/2303/2303.06219.pdf Research Papers And finally, links to the research papers we discussed this week ChatGPT and Its Educational Impact: Insights from a Software Development Competition https://arxiv.org/abs/2409.03779  How to Align Large Language Models for Teaching English? Designing and Developing LLM based-Chatbot for Teaching English Conversation in EFL, Findings and Limitations https://arxiv.org/abs/2409.04987  AI Meets the Classroom: When Does ChatGPT Harm Learning? https://arxiv.org/abs/2409.09047  Are Large Language Models Good Essay Graders? https://arxiv.org/abs/2409.13120  An Education Researcher's Guide to ChatGPT https://osf.io/spbz3  A Step Towards Adaptive Online Learning: Exploring the Role of GPT as Virtual Teaching Assistants in Online Education https://osf.io/preprints/edarxiv/rw45b  The AI Assessment Scale (AIAS) in action: A pilot implementation of GenAI-supported assessment https://ajet.org.au/index.php/AJET/article/view/9434     

In this episode of the Work in Progress podcast, we're talking about AI skills – there are more than you might think – and about the other must-have skills that employers are looking for today. I'm joined in conversation by Marni Baker Stein, chief content officer for Coursera, one of the largest online learning platform in the world. Through partnerships with more than 350 leading universities and companies – Google, IBM, Yale, and Duke, to name a few – Coursera has helped more than 168 million people learners build new skills. Stein says the rapid implementation of Chat-GPT and other AI products is having a "cascading effect across all sectors, all job roles, and all skills across disciplines. The Future of Jobs report [from the World Economic Forum] found that 50% of employers plan to reorient their business in response to AI. "And 85% of those employers say they plan to upskill their workforce in response to these skills gaps," says Stein. She adds that a large number of those employers are saying that they prefer job applicants that have verified AI skills. Coursera's own analysis of the fastest-growing skills for 2025 confirms that demand. "There is no doubt about it that if you don't already have AI skills, you absolutely need to develop them. (Additionally), you absolutely need to develop them very specifically for the job that you're in and the job tasks that you're doing," she emphatically points out. In the podcast, we go into depth about what those skills actually look like – what you need to learn how to do. We also discuss the top non-tech skills all employers want. Of course, we talk about how jobseekers and workers can get those skills. You can listen to the entire conversation here, or wherever you get your podcasts. You can also find our podcasts on the Work in Progress YouTube channel. Episode 351: Marni Baker Stein, chief content officer, CourseraHost & Executive Producer: Ramona Schindelheim, Editor-in-Chief, WorkingNationProducer: Larry BuhlTheme Music: Composed by Lee Rosevere and licensed under CC by 4Transcript: Download the transcript for this episode hereWork in Progress Podcast: Catch up on previous episodes here

Send us a textJeff Maggioncalda served as the CEO of Coursera from June 2017 to January 2025, leading the company through remarkable growth to over 160 million learners and 7,000+ institutions, delivering high-quality learning content from top universities and industry leaders. Under his leadership, Coursera expanded its reach, navigated the pandemic, embraced AI-driven learning, and became a publicly traded company.Since recording, Coursera announced that Jeff has retired from the role, and Greg Hart will succeed him as the CEO.

Join JJ as he delves into AI Agents with the CEO of Lutra.ai, Jiquan Ngiam. Discover how their no-code AI platform is revolutionizing business automation, enhancing workflow efficiency, and empowering users with AI-driven superpowers. Learn about Jiquan's journey from Coursera and Google Brain to founding Lutra.ai, and get insights into the future of AI, self-driving cars, and the dynamic tech industry. Tune in for a live demo and explore how Lutra.ai makes complex tasks simpler and more streamlined. Available on all platforms: Apple, Spotify, and YouTube.Lutra:Learn more about Lutra.ai:https://lutra.ai/Grab thisLutra playbookFollow Jiquan:https://www.linkedin.com/in/jngiam/View JJ'sAI Agent Course: 00:00 Introduction to Lutra.ai00:27 Founder's Journey: From Coursera to Google Brain02:04 The Evolution of AI: Key Milestones09:20 The Future of AI and Self-Driving Cars13:20 Introducing Lutra.ai: Vision and Challenges19:59 Lutra.ai Demo: Automating Email Management24:31 Navigating AI Downtime24:43 AI in Document Processing25:25 Step-by-Step AI Task Management26:15 Advanced AI Capabilities27:12 Creating and Using Playbooks28:23 Integrations and Practical Applications30:33 Complex Workflows and Hierarchical Playbooks31:34 AI in Social Listening32:42 Challenges and Future of AI Adoption43:32 Tips for Professionals Embracing AI45:57 Conclusion and How to Get Started with LutraWant to learnhow to build AI Agents?

Welcome to Sridhar's newsletter & Podcast (Click Play button for Audio version of the Post). Appreciate you being here, so we can connect weekly on interesting topics. Add your email id here to get this directly to your inbox.Do subscribe to show Minimalist Techie over Apple Or Spotify Or YouTube podcast (Click on Hyperlinks for Apple Or on Spotify Or on YouTube) or hear it over email you received through my subscription or on my website.This weekly newsletter is mostly about the article, books, videos etc. I read or watch or my views on different topics which revolves around my head during the week.Lets dive into todays topic.H1-B Life – Don't Hold Onto Stagnant JobsToday, we're going to talk about something that many H1-B professionals struggle with – staying in the same job for years, just to maintain visa status.It's a tricky situation. You move to the U.S. with strong technical skills, ready to grow, but over time, you find yourself stuck—working in outdated technologies, unable to switch jobs because of immigration processes, and ultimately risking your long-term career prospects.If this sounds like you or someone you know, stay tuned. We're going to break this down—why this happens, what risks it creates, and how to avoid getting trapped in a stagnant job. Let's get started!"#H1B #CareerGrowth #JobMarket #Upskilling #GreenCardBacklog #TechCareers #VisaChallenges #StayRelevant #WorkVisa #Immigration #CareerAdvice #TechJobs #ITCareer #AdaptAndGrowThe First 6 Years on H1-B: The Golden Phase* When professionals first arrive in the U.S. on an H1-B visa, they usually have solid technical skills. They are excited, ambitious, and eager to prove themselves.* Typically, these professionals work hard, upskill, and establish themselves within their companies.* Their employer and client see their value and realize that retaining them beyond the six-year H1-B limit is beneficial to the company.At this point, things are looking great. But then, a critical transition happens—one that many H1-B professionals don't think about early enough.The Green Card Backlog and Getting Stuck* After 6 years, if the employer wants to retain them, they begin the Green Card process.* For Indian nationals, the backlog is extreme. Right now, applications from 2011 are still being processed. That means many professionals could be waiting decades, even 100+ years, for their Green Card.* So, what happens? The employer files an I-140, which allows H1-B extensions beyond six years, effectively keeping the employee on an H1-B indefinitely.* This is where the real problem begins.The Trap: Why H1-B Professionals Stop GrowingOnce their Green Card is in process, many H1-B professionals start playing it safe:* They avoid switching jobs because restarting the Green Card process with a new employer feels risky.* If their client's technology is outdated, they don't push for learning new skills.* They prioritize job security over career growth.This comfort zone is what kills long-term career prospects.The Risk of Outdated SkillsLet's talk about why this is a dangerous trap:* Technology is moving fast.* What was in demand 10 years ago is obsolete today. If your skills are not updated, you will struggle to get a new job.* The longer you stay in outdated technologies, the harder it is to transition.* Employers look for people with hands-on experience in new tools. If you've been working on legacy systems for 10 years, moving to a modern tech stack will be very difficult.* What if you lose your job?* Imagine you lose your job today.* You're now competing with younger, more up-to-date professionals.* Your visa clock is ticking. If you don't find another job in 60 days, you must leave the U.S.* At that point, you realize how staying stagnant has put your career at risk.How to Avoid This Trap?The good news is—this situation is avoidable. Here's what you can do:* Upskill Regularly* Stay ahead of industry trends.* Take online courses, get certifications, and work on side projects.* Platforms like Coursera, Udemy, LinkedIn Learning, and EdX can help you stay competitive.* Be Open to New Opportunities* Don't be afraid to switch jobs.* Yes, your employer filed your Green Card, but you can port your priority date to a new employer and restart the process.* Network with Other Professionals* Join industry groups, attend meetups, and connect with hiring managers.* The best opportunities often come from networking, not job applications.* Have a Backup Plan* If you feel your current employer is limiting your growth, consider alternative options.* If the Green Card backlog is 100 years, it's worth considering returning to India or other countries where opportunities are growing fast.Final Thoughts: Your Career is Your ResponsibilityIf you're on an H1-B, remember:✅ You must take control of your career.✅ Don't stay in a job just for visa security.✅ Upskilling and staying relevant is non-negotiable.✅ Be strategic—look at your long-term career, not just short-term visa status.H1-B is an opportunity, not a trap. But only if you stay proactive.If you found this episode useful, share it with friends, colleagues, or anyone who might be stuck in this cycle. Let's help each other grow and succeed!That is all for this week. See you again.Do let me know in comments or reply me over email to share what is your view on this post. So, Share, Like, subscribe whatever these days' kids say :-)Stay Connected, Share Ideas, Spread Happiness. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit sridhargarikipati.substack.com

Welcome to another episode of The Coral Capital Podcast, a show where we bring on guests from tech, business, politics, and culture to talk about all things Japan. Today's guest is Andrew Schoen, Partner at NEA (New Enterprise Associates) . Established in 1977, NEA has served as a partner to the founders and teams behind some of the most transformational innovations in healthcare and technology over the past five decades including Cloudflare, Databricks, Coursera, Perplexity, Plaid, and Robinhood. The firm manages over $25B in AUM and invests across the early to post IPO stages. Andrew joined NEA in 2014 and invests in founders innovating in AI/ML, fintech, frontier tech, infrastructure software, technically differentiated SaaS and security. Prior to NEA, he was a member of Blackstone's M&A Group. Prior to Blackstone, he founded Flicstart. Andrew serves on the Cornell University Council, the Advisory Council for Entrepreneurship at Cornell, and is President Emeritus of the Cornell Venture Capital Club. He earned his master's degree as a Schwarzman Scholar and his bachelor's degree in economics and science of earth systems in engineering at Cornell. We've highlighted some insights from the conversation below: While NEA has had Japanese LPs for over 40 years, the firm only recently began actively investing in Japan. Talent is a leading indicator for the health of a startup ecosystem, and Japan has a high caliber of talent. Japan's startup ecosystem has key ingredients for success: A large GDP, strong technology base, quality education, and increasing enterprise demand for software and tech solutions. How Japanese founders pitch differently from US founders: Some Japanese founders are more modest about their vision, but overall, there's more similarity than difference in how founders pitch between Japan and the U.S. One major difference is that Japanese founders often set specific IPO dates early, whereas U.S. startups typically stay flexible based on market conditions. Japanese LPs often expect faster exits, but longer time horizons can lead to bigger and more successful outcomes. How to raise money from U.S. VCs: The first meeting is only about securing a second meeting — don't disqualify yourself early by making common mistakes like overstating valuation. Japanese startups should leverage local investors to get warm introductions. What NEA looks for in Japan: Mid to growth-stage, high-velocity, high-margin, software-driven businesses. Growth benchmarks also matter: $10M–$20M ARR → 100% growth $20M–$30M ARR → 50~100% growth $100M ARR → 30~40% growth Key metrics such as LTV/CAC, net revenue retention, and burn multiples are important—but potential future growth trumps past numbers. Longer term sheets = fewer surprises. Short-term sheets can leave room for bad terms later. ----- For founder's building Japan's next legendary companies, reach out to us here: https://coralcap.co/contact-startups/ If you're interested in joining a Coral startup join our talent network here: https://coralcap.co/coral-careers/

It had to happen eventually: this week The Studies Show is all about philosophy. As we look at science in general, how do we decide what those studies are actually showing? Tom and Stuart take a look at the Big Two of philosophy of science: Karl Popper and Thomas Kuhn, with their respective theories of falsificationism and paradigm shifts. Both are theories that almost everyone interested in science has heard of—but both make far more extreme claims than you might think.The Studies Show is sponsored by Works in Progress magazine, the best place to go online for fact-rich, data-dense articles on science and technology, and how they've made the world a better place—or how they might do so in the future. To find all their essays, all for free, go to worksinprogress.co.Show notes* Tom's new book, Everything is Predictable: How Bayes' Remarkable Theorem Explains the World* Wagenmakers's 2020 study asking scientists how they think about scientific claims* David Hume's 1748 Enquiry Concerning Human Understanding* Stanford Encyclopedia of Philosophy article on the problem of induction * Bertrand Russell's 1946 book History of Western Philosophy* Popper's 1959 book The Logic of Scientific Discovery* Stanford Encyclopedia of Philosophy article on Popper* Kuhn's 1962 book The Structure of Scientific Revolutions* Stanford Encyclopedia of Philosophy article on Kuhn* 2019 Scott Alexander review of the book* Michael Strevens's 2020 book The Knowledge Machine* Daniel Lakens's Coursera course on “improving your statistical inferences”CreditsThe Studies Show is produced by Julian Mayers at Yada Yada Productions. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.thestudiesshowpod.com/subscribe

In this episode of Web3 with Sam Kamani, I speak with Pauline Cohen, the visionary behind the Polkadot Blockchain Academy (PBA). With a career spanning giants like Coursera, Pauline brings her expertise in education to Web3, addressing the massive gap in blockchain talent. We dive deep into:✅ How PBA is creating world-class blockchain developers for Polkadot and beyond.✅ The challenges of online education and strategies to boost completion rates.✅ Why more women aren't entering Web3 development—and how to change that.✅ AI's role in personalized learning and the future of blockchain education.✅ The next big steps for Web3 education and PBA's vision for inclusivity and accessibility. Whether you're a developer, a lifelong learner, or simply curious about Web3 education, this episode is packed with valuable insights into the future of blockchain learning. Key Timestamps [00:00:00] Introduction: Sam introduces Pauline Cohen and the Polkadot Blockchain Academy. [00:01:00] The Origins of PBA: Why and how Polkadot Blockchain Academy was created. The need for high-quality blockchain education. [00:04:00] Lessons from Web2 Education: Pauline's experience at Coursera and how it shaped PBA. The importance of combining academic rigor with scalable solutions. [00:07:00] Addressing Completion Rates: Why online courses often struggle with low engagement. PBA's approach to fostering community and peer learning. [00:11:00] Challenges in Web3 Education: How to make blockchain more accessible for non-technical learners. Bridging the gender gap in Web3 development. [00:18:00] AI's Role in Education: How personalized AI tutors could revolutionize learning. Why human interaction remains key to effective education. [00:24:00] PBA's Future Vision: Expanding blockchain education across industries. Building learning pathways for diverse audiences, from developers to marketers. [00:30:00] Call to Action: Opportunities to join PBA online or in person. Collaborating with universities and communities to bring blockchain education worldwide. Connect https://polkadot.academy/ https://www.linkedin.com/school/polkadot-blockchain-academy/ https://x.com/academypolkadot https://www.linkedin.com/in/pauline-cohen-vorms-41710310/ https://x.com/PaulineVorms Disclaimer Nothing mentioned in this podcast is investment advice and please do your own research. Finally, it would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.Be a guest on the podcast or contact us - https://www.web3pod.xyz/

ABOUT ANDY KORTZAndy Kortz is currently the Chief Technology Officer at Integra Testing, where he leads technology transformation and drives operational efficiency in aggressive growth organizations. Andy also is a co-lead for the ELC Local Chapter initiative in Chicago. With over 20 years of experience in enterprise architecture and software development, Andy has consistently delivered innovative solutions while reducing IT expenses and improving application value. Drawing on his expertise in cloud technologies, data solutions, and integrations, Andy focuses on fostering a culture of continuous learning, building and empowering high-performing teams, and delivering customer-centric solutions in fast-paced environments.ABOUT JAMES TYACKJames is an engineering manager with a passion for people, technology, and learning. He's built and led distributed, diverse teams of engineers across locations and timezones for 10 years. James believes strongly in the value of diversity and championing a sense of belonging for everyone, from day 1. He's well versed in growth strategy, chaos engineering, major incident response, and blameless practice, and culture grounded by trust and psychological safety. He leads the Growth Acquisition team at Coursera where he's proud to be part of an organization that's transforming lives through learning. Previously, James enjoyed building and leading the Growth and Integrations engineering teams at PagerDuty.ABOUT JOHN ROSSJohn Ross is the Director of Infrastructure and Cloud at KUBRA, expertly navigating IT infrastructure and cloud solutions. Based in Toronto, John's career showcases a diverse range of experiences from large corporations to dynamic startups. He has a knack for aligning technology with business objectives, building robust teams, and managing platform migrations to the cloud. With experience in leading industry names like Ingram Micro and Symantec, as well as in the telecommunications sector, John combines strategic insight with a personable approach. His passion for sailing mirrors his love for innovation and precision in professional pursuits.SHOW NOTES:Scaling communication practices in parallel with scaling your org with Andy Kortz (1:18)Tools for bridging communication gaps between groups & building trust (2:49)Use humor strategically to break tension / build trust (5:16)Andy's introduction to ELC Chicago & the best parts of that community (8:57)Engineering challenges / conversations from ELC Chicago (10:24)What engineering leaders can learn from the best online courses - making a “Day One” commitment with James Tyack (12:28)Frameworks for putting the “Day One” commitment into practice (14:49)What making a “Day One” commitment looks like @ Coursera (17:59)Why the commitment needs to be made explicit (19:25)Practical exercises to encourage innovation & foster creativity (21:06)Strategies for getting hands-on with your learning (23:10)James's experience with ELC South Bay & connecting with leaders in a specific space (25:05)How to make the most out of attending your first ELC event (26:27)How to level up your teams through servant leadership with John Ross (27:52)Realizing you're the bottleneck & tips for stepping back / increasing team trust (30:49)John's experience with ELC Toronto & what ELC means to him (33:12)LINKS AND RESOURCESCheck out all of our local chapters & get involved here: elc.community/home/clubsThis episode wouldn't have been possible without the help of our incredible production team:Patrick Gallagher - Producer & Co-HostJerry Li - Co-HostNoah Olberding - Associate Producer, Audio & Video Editor https://www.linkedin.com/in/noah-olberding/Dan Overheim - Audio Engineer, Dan's also an avid 3D printer - https://www.bnd3d.com/Ellie Coggins Angus - Copywriter, Check out her other work at https://elliecoggins.com/about/

In this season premiere of The Data Chief podcast, your host Cindi Howson sits down with three industry visionaries to explore the trends, predictions, and must-take actions for data leaders in 2025. Get ready for a deep dive into: The generative AI revolution with Matt Turck, Partner at FirstMark CapitalThe future of data science and genAI with Steve Nouri, Founder of GenAI Works and AI for DiversityData Engineering in the Age of AI with Joe Reis, author of "Fundamentals of Data Engineering" and the upcoming "Mixed Model Arts."Plus: Hear their fun predictions for everything from sports to space travel!Key Moments:The generative AI revolution: Matt Turck, Partner at FirstMark Capital shares his insights on the evolving AI landscape, the rise of unstructured data, and why now is the time for enterprises to embrace AI. (1:40) The Future of Data Science: Steve Nouri, Founder of GenAI Works (an 8-million-strong community!) and AI for Diversity, discusses the impact of GenAI on data science roles, the ethical considerations of AI, and exciting trends like embodied AI and agentic AI. (29:36) Data Engineering in the Age of AI: Joe Reis, author of "Fundamentals of Data Engineering" and the upcoming "Mixed Model Arts," provides his expert perspective on the importance of data modeling, the need for upskilling in data teams, and the potential for a universal semantic layer. (1:00:00) Key Quotes:“I would predict that there's going to be a number of big acquisitions in our general space in 2025. This whole tension between the public markets doing very well, especially in tech, but the private markets still recovering - I think lends itself well to a wave of consolidation.”  - Matt Turck“Anything that requires democratization, I'm a big fan of. And certainly, the ability to query natural language databases and all things, making that available to everyone is a very powerful idea. You guys at ThoughtSpot know this better than anyone.” - Matt Turck“We are seeing people doing less coding, more relying on their co-pilots. It's going to evolve to become more and more robust. So we will be relying more on AI to do the coding.” - Steve Nouri“Well, that's what, you know, the tagline is, AI will do everything for you. It'll even do your laundry, the jobs that we don't like. And so you're actually saying you see a future where that actually is not too far off.” - Steve Nouri“I think that there's definitely a FOMO and a bit of a prisoner's dilemma problem with adopting AI in the organization because they're getting a lot of pressure from the top down, especially to do AI. Understanding what that means to your organization should be table stakes.” - Joe Reis“Learning never stops, investment never stops. And the best investment you can make is always improving yourself, no matter what that looks like.” Joe ReisMentions:FirstMark MAD Landscape 2024The MAD Podcast with Matt TurckAI4DiversityGenAI.WorksFundamentals of Data EngineeringJoe Reis Substack Guest Bios:Matt Turck is a Partner at FirstMark, where he focuses primarily on early-stage enterprise investing in the US and Europe. Matt is particularly active in the data, machine learning and AI space. For the last 10+ years, he has been organizing Data Driven NYC, the largest data/AI community in the US, and publishing the MAD Landscape, an annual analysis of the data/AI industry. He also hosts the weekly MAD (ML, AI, Data) Podcast. He can be followed on X/Twitter at @mattturck.Steve Nouri is the CEO and Co-founder of GenAI Works, the largest AI community. He is a renowned AI leader and Australia's ICT Professional of the Year, has revolutionized AI perspectives while championing Responsible and inclusive AI, founding a global non-profit initiative.Joe Reis, a "recovering data scientist" with 20 years in the data industry, is the co-author of the best-selling O'Reilly book, "Fundamentals of Data Engineering." He's also the instructor for the wildly popular Data Engineering Professional Certificate on Coursera, in partnership with DeepLearning.ai and AWS.Joe's extensive experience encompasses data engineering, data architecture, machine learning, and more. He regularly keynotes major data conferences globally, advises and invests in innovative data product companies, writes at Practical Data Modeling and his personal blog, and hosts the popular data podcasts "The Monday Morning Data Chat" and "The Joe Reis Show." In his free time, Joe is dedicated to writing new books and articles, and thinking of ways to advance the data industry. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Firefighters in the Los Angeles area struggle to contain deadly and destructive wildfires. President-elect Trump considers ways to fulfill his campaign promise of broad-based tariffs. Delta Air Lines CEO Ed Bastian discusses how his airline is embracing AI as it celebrates its centennial. And, the CEO of Coursera tells us about the surging interest in AI education. All that and more with Julia Chatterley. Learn more about your ad choices. Visit podcastchoices.com/adchoices

Change your life in 2025! You have access to fantastic training from the amazing Dr Chuck - no excuses!! // Python for Everybody // Python for Everybody: https://www.py4e.com/ Python for Everybody on Coursera: https://www.coursera.org/specializati... YouTube: • Python for Everybody - Full Universit... Free Python Book: http://do1.dr-chuck.com/pythonlearn/E... Dr Chuck's Website: https://www.dr-chuck.com/ Free Python Book options: https://www.py4e.com/book // C for Everybody Course // Free C Programming Course https://www.cc4e.com/ Free course on YouTube (freeCodeCamp): • Dr. Chuck reads C Programming (the cl... C Programming for Everybody on Coursera: https://www.coursera.org/specializati... // C book Audio by Dr Chuck // https://www.cc4e.com/podcast // Django for Everybody // Django for Everybody: https://www.dj4e.com/ Django for Everybody for on Coursera: https://www.coursera.org/specializati... YouTube: • Django For Everybody - Full Python Un... // PostgreSQL for Everybody // PostgreSQL for Everybody: https://www.pg4e.com/ PostgreSQL for Everybody on Coursera: https://www.coursera.org/specializati... YouTube: • Welcome to PostgreSQL for Everybody -... // Web Applications for Everybody // YouTube: • Web Applications for Everybody Course... Web Applications for Everybody: https://www.wa4e.com/ Web Applications for Everybody on Coursera: https://www.coursera.org/specializati... YouTube: • Welcome to Web Applications for Every... // Books // The C Programming Language by Brian Kernighan and Dennis Ritchie (the 1984 Second Ed and 1978 First Ed): https://amzn.to/3G0HSkU // MY STUFF // https://www.amazon.com/shop/davidbombal // SOCIAL // Discord: discord.com/invite/usKSyzb Twitter: www.twitter.com/davidbombal Instagram: www.instagram.com/davidbombal LinkedIn: www.linkedin.com/in/davidbombal Facebook: www.facebook.com/davidbombal.co TikTok: tiktok.com/@davidbombal // Dr Chuck Social // Website: https://www.dr-chuck.com/ Twitter: / drchuck YouTube: / csev Coursera: https://www.coursera.org/instructor/d... // MENU // 0:00 - Coming up 01:33 - How A.I. is affecting education 04:25 - Using A.I. to help students learn 08:11 - A.I. will fail you // Using A.I. to cheat in the real-world 19:40 - The Golden Age of A.I. and how it will get worse 24:51 - Is it worth it becoming a programmer in 2025 27:15 - Will A.I. replace programmers? 29:12 - Programming as a career choice 36:52 - A.I. is becoming a hardware problem 40:28 - Expectations of the younger generation 44:40 - The Master Programmer explained // Higher education is changing 52:03 - The Master Programmer courses and how to get started 56:23 - Learning JavaScript 01:09:37 - Conclusion Please note that links listed may be affiliate links and provide me with a small percentage/kickback should you use them to purchase any of the items listed or recommended. Thank you for supporting me and this channel!

In this episode of Grow a Small Business, host Troy Trewin interviews Jack Machado, founder of Staff X, shares how his business helps SMEs thrive by providing high-skilled offshore talent from the Philippines, South Africa, and Colombia. Growing from 3 to 22 team members and achieving $4M AUD in annual revenue within four years, Staff X stands out for its ethical recruitment practices and commitment to client solutions. Jack also discusses the journey toward B Corp certification and offers valuable insights on overcoming growth challenges and building a sustainable business. Other Resources: When should a growing small business have a Board of Directors or Advisors? Get a return from an effective Chairperson of a Board Why would you wait any longer to start living the lifestyle you signed up for? Balance your health, wealth, relationships and business growth. And focus your time and energy and make the most of this year. Let's get into it by clicking here.   Troy delves into our guest's startup journey, their perception of success, industry reconsideration, and the pivotal stress point during business expansion. They discuss the joys of small business growth, vital entrepreneurial habits, and strategies for team building, encompassing wins, blunders, and invaluable advice.   And a snapshot of the final five Grow A Small Business Questions:   What do you think is the hardest thing in growing a small business? According to Jack Machado, the hardest thing in growing a small business is finding the right people. He emphasizes that a business relies heavily on its people and processes, making it essential to hire trustworthy and dedicated team members who contribute to the company's success. What's your favourite business book that has helped you the most? Jack Machado's favorite business books are Good to Great by Jim Collins and Your Next Five Moves by Patrick Bet-David. These books provided him with valuable insights on strategy, leadership, and building a successful business. Are there any great podcasts or online learning resources you'd recommend to help grow a small business? Jack Machado recommends several great resources for small business growth. Among podcasts, he highlights the Grow Small Business Podcast by Troy Trewin, which delves into scaling businesses and overcoming challenges, and Built to Sell Radio by John Warrillow, focused on building scalable and valuable businesses. For online learning, Jack suggests using HubSpot Academy for free marketing and sales courses, Coursera and edX for university-level business topics, and LinkedIn Learning for quick, practical lessons on entrepreneurship and operational efficiency. He also emphasizes tools like HubSpot CRM for streamlining sales and marketing processes and recommends exploring tailored recruitment toolkits to attract and retain top talent effectively. What tool or resource would you recommend to grow a small business? Jack Machado highly recommends HubSpot CRM as a valuable tool for growing a small business. He highlights its ability to streamline sales and marketing processes, manage customer relationships effectively, and automate campaigns. According to Jack, the tool has significantly improved his business's lead management and overall sales efficiency, making it an essential resource for scaling operations. Additionally, he advises leveraging tailored recruitment toolkits to attract and retain top talent, ensuring the right people are in place to support growth. What advice would you give yourself on day one of starting out in business? Jack Machado's advice to his younger self on day one of starting a business is to go slower and focus on maintaining a better work-life balance. He emphasizes the importance of taking time to reassess decisions, digest outcomes, and ensure actions align with long-term goals. By pacing growth and allocating more time to family and personal life, he believes he could have achieved success while preserving meaningful moments with loved ones. Book a 20-minute Growth Chat with Troy Trewin to see if you qualify for our upcoming course. Don't miss out on this opportunity to take your small business to new heights! Enjoyed the podcast? Please leave a review on iTunes or your preferred platform. Your feedback helps more small business owners discover our podcast and embark on their business growth journey.       Quotable quotes from our special Grow A Small Business podcast guest: Success comes not from chasing money but from delivering genuine solutions — Jack Machado Sustainable success is built on continuous improvement and shared wins — Jack Machado A business thrives when its focus shifts from profit to quality and value — Jack Machado      

La Universidad de los Andes ofrece 95 cursos online gratuitos a través de la plataforma Coursera en 2025. Estos cursos, con temas que abarcan tecnología, finanzas y videojuegos, son MOOCs (Massive Open Online Courses), permitiendo a los estudiantes aprender a su propio ritmo y de forma remota. Los estudiantes reciben certificados al finalizar cada curso (con costo adicional) y pueden acceder a los cursos a través de un enlace proporcionado. Las evaluaciones miden el aprendizaje en cada etapa.

Today, we are joined by Dr. Barbara Oakley. Dr. Barbara Oakley is a distinguished professor, engineer, and globally recognized expert in the fields of learning and neuroscience. She is best known for her groundbreaking work on understanding how people learn and for developing practical strategies to improve learning effectiveness. She is also a NYT bestselling author of several books on learning science and learning how to learn. Dr. Oakley's Website: https://barbaraoakley.com/ Dr. Oakley on Coursera: https://www.coursera.org/learn/learning-how-to-learn Dr. Oakley's Books: https://www.amazon.com/stores/Barbara-Oakley-PhD/author/B000AP9ZR4 In this episode, Barbara shares her journey from struggling with math to becoming a distinguished professor of engineering. We also discuss the importance of updating learning strategies, embracing discomfort, and using techniques like active recall and dual-mode thinking (focused and diffuse modes) to enhance learning. Join us for this great discussion about the significance of self-awareness and self-monitoring in personal growth and learning efficiency. - Website and live online programs: http://ims-online.com Blog: https://blog.ims-online.com/ Podcast: https://ims-online.com/podcasts/ LinkedIn: https://www.linkedin.com/in/charlesagood/ Twitter: https://twitter.com/charlesgood99 Chapters: (00:00) Introduction (02:00) Barbaras's Journey Overcoming Math Struggles (05:03) Technique: Maintaining Motivation and Focus (07:37) Tool: The Concept of Mind Shift (10:50) Technique: Self-Monitoring and Overcoming Comparisons (14:04) Technique: Focused vs. Diffused Mode of Thinking (21:22) Tools: Understanding Memory and Effective Learning Strategies (27:58) Conclusion

Applications for the 2025 AI Engineer Summit are up, and you can save the date for AIE Singapore in April and AIE World's Fair 2025 in June.Happy new year, and thanks for 100 great episodes! Please let us know what you want to see/hear for the next 100!Full YouTube Episode with Slides/ChartsLike and subscribe and hit that bell to get notifs!Timestamps* 00:00 Welcome to the 100th Episode!* 00:19 Reflecting on the Journey* 00:47 AI Engineering: The Rise and Impact* 03:15 Latent Space Live and AI Conferences* 09:44 The Competitive AI Landscape* 21:45 Synthetic Data and Future Trends* 35:53 Creative Writing with AI* 36:12 Legal and Ethical Issues in AI* 38:18 The Data War: GPU Poor vs. GPU Rich* 39:12 The Rise of GPU Ultra Rich* 40:47 Emerging Trends in AI Models* 45:31 The Multi-Modality War* 01:05:31 The Future of AI Benchmarks* 01:13:17 Pionote and Frontier Models* 01:13:47 Niche Models and Base Models* 01:14:30 State Space Models and RWKB* 01:15:48 Inference Race and Price Wars* 01:22:16 Major AI Themes of the Year* 01:22:48 AI Rewind: January to March* 01:26:42 AI Rewind: April to June* 01:33:12 AI Rewind: July to September* 01:34:59 AI Rewind: October to December* 01:39:53 Year-End Reflections and PredictionsTranscript[00:00:00] Welcome to the 100th Episode![00:00:00] Alessio: Hey everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co host Swyx for the 100th time today.[00:00:12] swyx: Yay, um, and we're so glad that, yeah, you know, everyone has, uh, followed us in this journey. How do you feel about it? 100 episodes.[00:00:19] Alessio: Yeah, I know.[00:00:19] Reflecting on the Journey[00:00:19] Alessio: Almost two years that we've been doing this. We've had four different studios. Uh, we've had a lot of changes. You know, we used to do this lightning round. When we first started that we didn't like, and we tried to change the question. The answer[00:00:32] swyx: was cursor and perplexity.[00:00:34] Alessio: Yeah, I love mid journey. It's like, do you really not like anything else?[00:00:38] Alessio: Like what's, what's the unique thing? And I think, yeah, we, we've also had a lot more research driven content. You know, we had like 3DAO, we had, you know. Jeremy Howard, we had more folks like that.[00:00:47] AI Engineering: The Rise and Impact[00:00:47] Alessio: I think we want to do more of that too in the new year, like having, uh, some of the Gemini folks, both on the research and the applied side.[00:00:54] Alessio: Yeah, but it's been a ton of fun. I think we both started, I wouldn't say as a joke, we were kind of like, Oh, we [00:01:00] should do a podcast. And I think we kind of caught the right wave, obviously. And I think your rise of the AI engineer posts just kind of get people. Sombra to congregate, and then the AI engineer summit.[00:01:11] Alessio: And that's why when I look at our growth chart, it's kind of like a proxy for like the AI engineering industry as a whole, which is almost like, like, even if we don't do that much, we keep growing just because there's so many more AI engineers. So did you expect that growth or did you expect that would take longer for like the AI engineer thing to kind of like become, you know, everybody talks about it today.[00:01:32] swyx: So, the sign of that, that we have won is that Gartner puts it at the top of the hype curve right now. So Gartner has called the peak in AI engineering. I did not expect, um, to what level. I knew that I was correct when I called it because I did like two months of work going into that. But I didn't know, You know, how quickly it could happen, and obviously there's a chance that I could be wrong.[00:01:52] swyx: But I think, like, most people have come around to that concept. Hacker News hates it, which is a good sign. But there's enough people that have defined it, you know, GitHub, when [00:02:00] they launched GitHub Models, which is the Hugging Face clone, they put AI engineers in the banner, like, above the fold, like, in big So I think it's like kind of arrived as a meaningful and useful definition.[00:02:12] swyx: I think people are trying to figure out where the boundaries are. I think that was a lot of the quote unquote drama that happens behind the scenes at the World's Fair in June. Because I think there's a lot of doubt or questions about where ML engineering stops and AI engineering starts. That's a useful debate to be had.[00:02:29] swyx: In some sense, I actually anticipated that as well. So I intentionally did not. Put a firm definition there because most of the successful definitions are necessarily underspecified and it's actually useful to have different perspectives and you don't have to specify everything from the outset.[00:02:45] Alessio: Yeah, I was at um, AWS reInvent and the line to get into like the AI engineering talk, so to speak, which is, you know, applied AI and whatnot was like, there are like hundreds of people just in line to go in.[00:02:56] Alessio: I think that's kind of what enabled me. People, right? Which is what [00:03:00] you kind of talked about. It's like, Hey, look, you don't actually need a PhD, just, yeah, just use the model. And then maybe we'll talk about some of the blind spots that you get as an engineer with the earlier posts that we also had on on the sub stack.[00:03:11] Alessio: But yeah, it's been a heck of a heck of a two years.[00:03:14] swyx: Yeah.[00:03:15] Latent Space Live and AI Conferences[00:03:15] swyx: You know, I was, I was trying to view the conference as like, so NeurIPS is I think like 16, 17, 000 people. And the Latent Space Live event that we held there was 950 signups. I think. The AI world, the ML world is still very much research heavy. And that's as it should be because ML is very much in a research phase.[00:03:34] swyx: But as we move this entire field into production, I think that ratio inverts into becoming more engineering heavy. So at least I think engineering should be on the same level, even if it's never as prestigious, like it'll always be low status because at the end of the day, you're manipulating APIs or whatever.[00:03:51] swyx: But Yeah, wrapping GPTs, but there's going to be an increasing stack and an art to doing these, these things well. And I, you know, I [00:04:00] think that's what we're focusing on for the podcast, the conference and basically everything I do seems to make sense. And I think we'll, we'll talk about the trends here that apply.[00:04:09] swyx: It's, it's just very strange. So, like, there's a mix of, like, keeping on top of research while not being a researcher and then putting that research into production. So, like, people always ask me, like, why are you covering Neuralibs? Like, this is a ML research conference and I'm like, well, yeah, I mean, we're not going to, to like, understand everything Or reproduce every single paper, but the stuff that is being found here is going to make it through into production at some point, you hope.[00:04:32] swyx: And then actually like when I talk to the researchers, they actually get very excited because they're like, oh, you guys are actually caring about how this goes into production and that's what they really really want. The measure of success is previously just peer review, right? Getting 7s and 8s on their um, Academic review conferences and stuff like citations is one metric, but money is a better metric.[00:04:51] Alessio: Money is a better metric. Yeah, and there were about 2200 people on the live stream or something like that. Yeah, yeah. Hundred on the live stream. So [00:05:00] I try my best to moderate, but it was a lot spicier in person with Jonathan and, and Dylan. Yeah, that it was in the chat on YouTube.[00:05:06] swyx: I would say that I actually also created.[00:05:09] swyx: Layen Space Live in order to address flaws that are perceived in academic conferences. This is not NeurIPS specific, it's ICML, NeurIPS. Basically, it's very sort of oriented towards the PhD student, uh, market, job market, right? Like literally all, basically everyone's there to advertise their research and skills and get jobs.[00:05:28] swyx: And then obviously all the, the companies go there to hire them. And I think that's great for the individual researchers, but for people going there to get info is not great because you have to read between the lines, bring a ton of context in order to understand every single paper. So what is missing is effectively what I ended up doing, which is domain by domain, go through and recap the best of the year.[00:05:48] swyx: Survey the field. And there are, like NeurIPS had a, uh, I think ICML had a like a position paper track, NeurIPS added a benchmarks, uh, datasets track. These are ways in which to address that [00:06:00] issue. Uh, there's always workshops as well. Every, every conference has, you know, a last day of workshops and stuff that provide more of an overview.[00:06:06] swyx: But they're not specifically prompted to do so. And I think really, uh, Organizing a conference is just about getting good speakers and giving them the correct prompts. And then they will just go and do that thing and they do a very good job of it. So I think Sarah did a fantastic job with the startups prompt.[00:06:21] swyx: I can't list everybody, but we did best of 2024 in startups, vision, open models. Post transformers, synthetic data, small models, and agents. And then the last one was the, uh, and then we also did a quick one on reasoning with Nathan Lambert. And then the last one, obviously, was the debate that people were very hyped about.[00:06:39] swyx: It was very awkward. And I'm really, really thankful for John Franco, basically, who stepped up to challenge Dylan. Because Dylan was like, yeah, I'll do it. But He was pro scaling. And I think everyone who is like in AI is pro scaling, right? So you need somebody who's ready to publicly say, no, we've hit a wall.[00:06:57] swyx: So that means you're saying Sam Altman's wrong. [00:07:00] You're saying, um, you know, everyone else is wrong. It helps that this was the day before Ilya went on, went up on stage and then said pre training has hit a wall. And data has hit a wall. So actually Jonathan ended up winning, and then Ilya supported that statement, and then Noam Brown on the last day further supported that statement as well.[00:07:17] swyx: So it's kind of interesting that I think the consensus kind of going in was that we're not done scaling, like you should believe in a better lesson. And then, four straight days in a row, you had Sepp Hochreiter, who is the creator of the LSTM, along with everyone's favorite OG in AI, which is Juergen Schmidhuber.[00:07:34] swyx: He said that, um, we're pre trading inside a wall, or like, we've run into a different kind of wall. And then we have, you know John Frankel, Ilya, and then Noam Brown are all saying variations of the same thing, that we have hit some kind of wall in the status quo of what pre trained, scaling large pre trained models has looked like, and we need a new thing.[00:07:54] swyx: And obviously the new thing for people is some make, either people are calling it inference time compute or test time [00:08:00] compute. I think the collective terminology has been inference time, and I think that makes sense because test time, calling it test, meaning, has a very pre trained bias, meaning that the only reason for running inference at all is to test your model.[00:08:11] swyx: That is not true. Right. Yeah. So, so, I quite agree that. OpenAI seems to have adopted, or the community seems to have adopted this terminology of ITC instead of TTC. And that, that makes a lot of sense because like now we care about inference, even right down to compute optimality. Like I actually interviewed this author who recovered or reviewed the Chinchilla paper.[00:08:31] swyx: Chinchilla paper is compute optimal training, but what is not stated in there is it's pre trained compute optimal training. And once you start caring about inference, compute optimal training, you have a different scaling law. And in a way that we did not know last year.[00:08:45] Alessio: I wonder, because John is, he's also on the side of attention is all you need.[00:08:49] Alessio: Like he had the bet with Sasha. So I'm curious, like he doesn't believe in scaling, but he thinks the transformer, I wonder if he's still. So, so,[00:08:56] swyx: so he, obviously everything is nuanced and you know, I told him to play a character [00:09:00] for this debate, right? So he actually does. Yeah. He still, he still believes that we can scale more.[00:09:04] swyx: Uh, he just assumed the character to be very game for, for playing this debate. So even more kudos to him that he assumed a position that he didn't believe in and still won the debate.[00:09:16] Alessio: Get rekt, Dylan. Um, do you just want to quickly run through some of these things? Like, uh, Sarah's presentation, just the highlights.[00:09:24] swyx: Yeah, we can't go through everyone's slides, but I pulled out some things as a factor of, like, stuff that we were going to talk about. And we'll[00:09:30] Alessio: publish[00:09:31] swyx: the rest. Yeah, we'll publish on this feed the best of 2024 in those domains. And hopefully people can benefit from the work that our speakers have done.[00:09:39] swyx: But I think it's, uh, these are just good slides. And I've been, I've been looking for a sort of end of year recaps from, from people.[00:09:44] The Competitive AI Landscape[00:09:44] swyx: The field has progressed a lot. You know, I think the max ELO in 2023 on LMSys used to be 1200 for LMSys ELOs. And now everyone is at least at, uh, 1275 in their ELOs, and this is across Gemini, Chadjibuti, [00:10:00] Grok, O1.[00:10:01] swyx: ai, which with their E Large model, and Enthopic, of course. It's a very, very competitive race. There are multiple Frontier labs all racing, but there is a clear tier zero Frontier. And then there's like a tier one. It's like, I wish I had everything else. Tier zero is extremely competitive. It's effectively now three horse race between Gemini, uh, Anthropic and OpenAI.[00:10:21] swyx: I would say that people are still holding out a candle for XAI. XAI, I think, for some reason, because their API was very slow to roll out, is not included in these metrics. So it's actually quite hard to put on there. As someone who also does charts, XAI is continually snubbed because they don't work well with the benchmarking people.[00:10:42] swyx: Yeah, yeah, yeah. It's a little trivia for why XAI always gets ignored. The other thing is market share. So these are slides from Sarah. We have it up on the screen. It has gone from very heavily open AI. So we have some numbers and estimates. These are from RAMP. Estimates of open AI market share in [00:11:00] December 2023.[00:11:01] swyx: And this is basically, what is it, GPT being 95 percent of production traffic. And I think if you correlate that with stuff that we asked. Harrison Chase on the LangChain episode, it was true. And then CLAUD 3 launched mid middle of this year. I think CLAUD 3 launched in March, CLAUD 3. 5 Sonnet was in June ish.[00:11:23] swyx: And you can start seeing the market share shift towards opening, uh, towards that topic, uh, very, very aggressively. The more recent one is Gemini. So if I scroll down a little bit, this is an even more recent dataset. So RAM's dataset ends in September 2 2. 2024. Gemini has basically launched a price war at the low end, uh, with Gemini Flash, uh, being basically free for personal use.[00:11:44] swyx: Like, I think people don't understand the free tier. It's something like a billion tokens per day. Unless you're trying to abuse it, you cannot really exhaust your free tier on Gemini. They're really trying to get you to use it. They know they're in like third place, um, fourth place, depending how you, how you count.[00:11:58] swyx: And so they're going after [00:12:00] the Lower tier first, and then, you know, maybe the upper tier later, but yeah, Gemini Flash, according to OpenRouter, is now 50 percent of their OpenRouter requests. Obviously, these are the small requests. These are small, cheap requests that are mathematically going to be more.[00:12:15] swyx: The smart ones obviously are still going to OpenAI. But, you know, it's a very, very big shift in the market. Like basically 2023, 2022, To going into 2024 opening has gone from nine five market share to Yeah. Reasonably somewhere between 50 to 75 market share.[00:12:29] Alessio: Yeah. I'm really curious how ramped does the attribution to the model?[00:12:32] Alessio: If it's API, because I think it's all credit card spin. . Well, but it's all, the credit card doesn't say maybe. Maybe the, maybe when they do expenses, they upload the PDF, but yeah, the, the German I think makes sense. I think that was one of my main 2024 takeaways that like. The best small model companies are the large labs, which is not something I would have thought that the open source kind of like long tail would be like the small model.[00:12:53] swyx: Yeah, different sizes of small models we're talking about here, right? Like so small model here for Gemini is AB, [00:13:00] right? Uh, mini. We don't know what the small model size is, but yeah, it's probably in the double digits or maybe single digits, but probably double digits. The open source community has kind of focused on the one to three B size.[00:13:11] swyx: Mm-hmm . Yeah. Maybe[00:13:12] swyx: zero, maybe 0.5 B uh, that's moon dream and that is small for you then, then that's great. It makes sense that we, we have a range for small now, which is like, may, maybe one to five B. Yeah. I'll even put that at, at, at the high end. And so this includes Gemma from Gemini as well. But also includes the Apple Foundation models, which I think Apple Foundation is 3B.[00:13:32] Alessio: Yeah. No, that's great. I mean, I think in the start small just meant cheap. I think today small is actually a more nuanced discussion, you know, that people weren't really having before.[00:13:43] swyx: Yeah, we can keep going. This is a slide that I smiley disagree with Sarah. She's pointing to the scale SEAL leaderboard. I think the Researchers that I talked with at NeurIPS were kind of positive on this because basically you need private test [00:14:00] sets to prevent contamination.[00:14:02] swyx: And Scale is one of maybe three or four people this year that has really made an effort in doing a credible private test set leaderboard. Llama405B does well compared to Gemini and GPT 40. And I think that's good. I would say that. You know, it's good to have an open model that is that big, that does well on those metrics.[00:14:23] swyx: But anyone putting 405B in production will tell you, if you scroll down a little bit to the artificial analysis numbers, that it is very slow and very expensive to infer. Um, it doesn't even fit on like one node. of, uh, of H100s. Cerebras will be happy to tell you they can serve 4 or 5B on their super large chips.[00:14:42] swyx: But, um, you know, if you need to do anything custom to it, you're still kind of constrained. So, is 4 or 5B really that relevant? Like, I think most people are basically saying that they only use 4 or 5B as a teacher model to distill down to something. Even Meta is doing it. So with Lama 3. [00:15:00] 3 launched, they only launched the 70B because they use 4 or 5B to distill the 70B.[00:15:03] swyx: So I don't know if like open source is keeping up. I think they're the, the open source industrial complex is very invested in telling you that the, if the gap is narrowing, I kind of disagree. I think that the gap is widening with O1. I think there are very, very smart people trying to narrow that gap and they should.[00:15:22] swyx: I really wish them success, but you cannot use a chart that is nearing 100 in your saturation chart. And look, the distance between open source and closed source is narrowing. Of course it's going to narrow because you're near 100. This is stupid. But in metrics that matter, is open source narrowing?[00:15:38] swyx: Probably not for O1 for a while. And it's really up to the open source guys to figure out if they can match O1 or not.[00:15:46] Alessio: I think inference time compute is bad for open source just because, you know, Doc can donate the flops at training time, but he cannot donate the flops at inference time. So it's really hard to like actually keep up on that axis.[00:15:59] Alessio: Big, big business [00:16:00] model shift. So I don't know what that means for the GPU clouds. I don't know what that means for the hyperscalers, but obviously the big labs have a lot of advantage. Because, like, it's not a static artifact that you're putting the compute in. You're kind of doing that still, but then you're putting a lot of computed inference too.[00:16:17] swyx: Yeah, yeah, yeah. Um, I mean, Llama4 will be reasoning oriented. We talked with Thomas Shalom. Um, kudos for getting that episode together. That was really nice. Good, well timed. Actually, I connected with the AI meta guy, uh, at NeurIPS, and, um, yeah, we're going to coordinate something for Llama4. Yeah, yeah,[00:16:32] Alessio: and our friend, yeah.[00:16:33] Alessio: Clara Shi just joined to lead the business agent side. So I'm sure we'll have her on in the new year.[00:16:39] swyx: Yeah. So, um, my comment on, on the business model shift, this is super interesting. Apparently it is wide knowledge that OpenAI wanted more than 6. 6 billion dollars for their fundraise. They wanted to raise, you know, higher, and they did not.[00:16:51] swyx: And what that means is basically like, it's very convenient that we're not getting GPT 5, which would have been a larger pre train. We should have a lot of upfront money. And [00:17:00] instead we're, we're converting fixed costs into variable costs, right. And passing it on effectively to the customer. And it's so much easier to take margin there because you can directly attribute it to like, Oh, you're using this more.[00:17:12] swyx: Therefore you, you pay more of the cost and I'll just slap a margin in there. So like that lets you control your growth margin and like tie your. Your spend, or your sort of inference spend, accordingly. And it's just really interesting to, that this change in the sort of inference paradigm has arrived exactly at the same time that the funding environment for pre training is effectively drying up, kind of.[00:17:36] swyx: I feel like maybe the VCs are very in tune with research anyway, so like, they would have noticed this, but, um, it's just interesting.[00:17:43] Alessio: Yeah, and I was looking back at our yearly recap of last year. Yeah. And the big thing was like the mixed trial price fights, you know, and I think now it's almost like there's nowhere to go, like, you know, Gemini Flash is like basically giving it away for free.[00:17:55] Alessio: So I think this is a good way for the labs to generate more revenue and pass down [00:18:00] some of the compute to the customer. I think they're going to[00:18:02] swyx: keep going. I think that 2, will come.[00:18:05] Alessio: Yeah, I know. Totally. I mean, next year, the first thing I'm doing is signing up for Devin. Signing up for the pro chat GBT.[00:18:12] Alessio: Just to try. I just want to see what does it look like to spend a thousand dollars a month on AI?[00:18:17] swyx: Yes. Yes. I think if your, if your, your job is a, at least AI content creator or VC or, you know, someone who, whose job it is to stay on, stay on top of things, you should already be spending like a thousand dollars a month on, on stuff.[00:18:28] swyx: And then obviously easy to spend, hard to use. You have to actually use. The good thing is that actually Google lets you do a lot of stuff for free now. So like deep research. That they just launched. Uses a ton of inference and it's, it's free while it's in preview.[00:18:45] Alessio: Yeah. They need to put that in Lindy.[00:18:47] Alessio: I've been using Lindy lately. I've been a built a bunch of things once we had flow because I liked the new thing. It's pretty good. I even did a phone call assistant. Um, yeah, they just launched Lindy voice. Yeah, I think once [00:19:00] they get advanced voice mode like capability today, still like speech to text, you can kind of tell.[00:19:06] Alessio: Um, but it's good for like reservations and things like that. So I have a meeting prepper thing. And so[00:19:13] swyx: it's good. Okay. I feel like we've, we've covered a lot of stuff. Uh, I, yeah, I, you know, I think We will go over the individual, uh, talks in a separate episode. Uh, I don't want to take too much time with, uh, this stuff, but that suffice to say that there is a lot of progress in each field.[00:19:28] swyx: Uh, we covered vision. Basically this is all like the audience voting for what they wanted. And then I just invited the best people I could find in each audience, especially agents. Um, Graham, who I talked to at ICML in Vienna, he is currently still number one. It's very hard to stay on top of SweetBench.[00:19:45] swyx: OpenHand is currently still number one. switchbench full, which is the hardest one. He had very good thoughts on agents, which I, which I'll highlight for people. Everyone is saying 2025 is the year of agents, just like they said last year. And, uh, but he had [00:20:00] thoughts on like eight parts of what are the frontier problems to solve in agents.[00:20:03] swyx: And so I'll highlight that talk as well.[00:20:05] Alessio: Yeah. The number six, which is the Hacken agents learn more about the environment, has been a Super interesting to us as well, just to think through, because, yeah, how do you put an agent in an enterprise where most things in an enterprise have never been public, you know, a lot of the tooling, like the code bases and things like that.[00:20:23] Alessio: So, yeah, there's not indexing and reg. Well, yeah, but it's more like. You can't really rag things that are not documented. But people know them based on how they've been doing it. You know, so I think there's almost this like, you know, Oh, institutional knowledge. Yeah, the boring word is kind of like a business process extraction.[00:20:38] Alessio: Yeah yeah, I see. It's like, how do you actually understand how these things are done? I see. Um, and I think today the, the problem is that, Yeah, the agents are, that most people are building are good at following instruction, but are not as good as like extracting them from you. Um, so I think that will be a big unlock just to touch quickly on the Jeff Dean thing.[00:20:55] Alessio: I thought it was pretty, I mean, we'll link it in the, in the things, but. I think the main [00:21:00] focus was like, how do you use ML to optimize the systems instead of just focusing on ML to do something else? Yeah, I think speculative decoding, we had, you know, Eugene from RWKB on the podcast before, like he's doing a lot of that with Fetterless AI.[00:21:12] swyx: Everyone is. I would say it's the norm. I'm a little bit uncomfortable with how much it costs, because it does use more of the GPU per call. But because everyone is so keen on fast inference, then yeah, makes sense.[00:21:24] Alessio: Exactly. Um, yeah, but we'll link that. Obviously Jeff is great.[00:21:30] swyx: Jeff is, Jeff's talk was more, it wasn't focused on Gemini.[00:21:33] swyx: I think people got the wrong impression from my tweet. It's more about how Google approaches ML and uses ML to design systems and then systems feedback into ML. And I think this ties in with Lubna's talk.[00:21:45] Synthetic Data and Future Trends[00:21:45] swyx: on synthetic data where it's basically the story of bootstrapping of humans and AI in AI research or AI in production.[00:21:53] swyx: So her talk was on synthetic data, where like how much synthetic data has grown in 2024 in the pre training side, the post training side, [00:22:00] and the eval side. And I think Jeff then also extended it basically to chips, uh, to chip design. So he'd spend a lot of time talking about alpha chip. And most of us in the audience are like, we're not working on hardware, man.[00:22:11] swyx: Like you guys are great. TPU is great. Okay. We'll buy TPUs.[00:22:14] Alessio: And then there was the earlier talk. Yeah. But, and then we have, uh, I don't know if we're calling them essays. What are we calling these? But[00:22:23] swyx: for me, it's just like bonus for late in space supporters, because I feel like they haven't been getting anything.[00:22:29] swyx: And then I wanted a more high frequency way to write stuff. Like that one I wrote in an afternoon. I think basically we now have an answer to what Ilya saw. It's one year since. The blip. And we know what he saw in 2014. We know what he saw in 2024. We think we know what he sees in 2024. He gave some hints and then we have vague indications of what he saw in 2023.[00:22:54] swyx: So that was the Oh, and then 2016 as well, because of this lawsuit with Elon, OpenAI [00:23:00] is publishing emails from Sam's, like, his personal text messages to Siobhan, Zelis, or whatever. So, like, we have emails from Ilya saying, this is what we're seeing in OpenAI, and this is why we need to scale up GPUs. And I think it's very prescient in 2016 to write that.[00:23:16] swyx: And so, like, it is exactly, like, basically his insights. It's him and Greg, basically just kind of driving the scaling up of OpenAI, while they're still playing Dota. They're like, no, like, we see the path here.[00:23:30] Alessio: Yeah, and it's funny, yeah, they even mention, you know, we can only train on 1v1 Dota. We need to train on 5v5, and that takes too many GPUs.[00:23:37] Alessio: Yeah,[00:23:37] swyx: and at least for me, I can speak for myself, like, I didn't see the path from Dota to where we are today. I think even, maybe if you ask them, like, they wouldn't necessarily draw a straight line. Yeah,[00:23:47] Alessio: no, definitely. But I think like that was like the whole idea of almost like the RL and we talked about this with Nathan on his podcast.[00:23:55] Alessio: It's like with RL, you can get very good at specific things, but then you can't really like generalize as much. And I [00:24:00] think the language models are like the opposite, which is like, you're going to throw all this data at them and scale them up, but then you really need to drive them home on a specific task later on.[00:24:08] Alessio: And we'll talk about the open AI reinforcement, fine tuning, um, announcement too, and all of that. But yeah, I think like scale is all you need. That's kind of what Elia will be remembered for. And I think just maybe to clarify on like the pre training is over thing that people love to tweet. I think the point of the talk was like everybody, we're scaling these chips, we're scaling the compute, but like the second ingredient which is data is not scaling at the same rate.[00:24:35] Alessio: So it's not necessarily pre training is over. It's kind of like What got us here won't get us there. In his email, he predicted like 10x growth every two years or something like that. And I think maybe now it's like, you know, you can 10x the chips again, but[00:24:49] swyx: I think it's 10x per year. Was it? I don't know.[00:24:52] Alessio: Exactly. And Moore's law is like 2x. So it's like, you know, much faster than that. And yeah, I like the fossil fuel of AI [00:25:00] analogy. It's kind of like, you know, the little background tokens thing. So the OpenAI reinforcement fine tuning is basically like, instead of fine tuning on data, you fine tune on a reward model.[00:25:09] Alessio: So it's basically like, instead of being data driven, it's like task driven. And I think people have tasks to do, they don't really have a lot of data. So I'm curious to see how that changes, how many people fine tune, because I think this is what people run into. It's like, Oh, you can fine tune llama. And it's like, okay, where do I get the data?[00:25:27] Alessio: To fine tune it on, you know, so it's great that we're moving the thing. And then I really like he had this chart where like, you know, the brain mass and the body mass thing is basically like mammals that scaled linearly by brain and body size, and then humans kind of like broke off the slope. So it's almost like maybe the mammal slope is like the pre training slope.[00:25:46] Alessio: And then the post training slope is like the, the human one.[00:25:49] swyx: Yeah. I wonder what the. I mean, we'll know in 10 years, but I wonder what the y axis is for, for Ilya's SSI. We'll try to get them on.[00:25:57] Alessio: Ilya, if you're listening, you're [00:26:00] welcome here. Yeah, and then he had, you know, what comes next, like agent, synthetic data, inference, compute, I thought all of that was like that.[00:26:05] Alessio: I don't[00:26:05] swyx: think he was dropping any alpha there. Yeah, yeah, yeah.[00:26:07] Alessio: Yeah. Any other new reps? Highlights?[00:26:10] swyx: I think that there was comparatively a lot more work. Oh, by the way, I need to plug that, uh, my friend Yi made this, like, little nice paper. Yeah, that was really[00:26:20] swyx: nice.[00:26:20] swyx: Uh, of, uh, of, like, all the, he's, she called it must read papers of 2024.[00:26:26] swyx: So I laid out some of these at NeurIPS, and it was just gone. Like, everyone just picked it up. Because people are dying for, like, little guidance and visualizations And so, uh, I thought it was really super nice that we got there.[00:26:38] Alessio: Should we do a late in space book for each year? Uh, I thought about it. For each year we should.[00:26:42] Alessio: Coffee table book. Yeah. Yeah. Okay. Put it in the will. Hi, Will. By the way, we haven't introduced you. He's our new, you know, general organist, Jamie. You need to[00:26:52] swyx: pull up more things. One thing I saw that, uh, Okay, one fun one, and then one [00:27:00] more general one. So the fun one is this paper on agent collusion. This is a paper on steganography.[00:27:06] swyx: This is secret collusion among AI agents, multi agent deception via steganography. I tried to go to NeurIPS in order to find these kinds of papers because the real reason Like NeurIPS this year has a lottery system. A lot of people actually even go and don't buy tickets because they just go and attend the side events.[00:27:22] swyx: And then also the people who go and end up crowding around the most popular papers, which you already know and already read them before you showed up to NeurIPS. So the only reason you go there is to talk to the paper authors, but there's like something like 10, 000 other. All these papers out there that, you know, are just people's work that they, that they did on the air and they failed to get attention for one reason or another.[00:27:42] swyx: And this was one of them. Uh, it was like all the way at the back. And this is a deep mind paper that actually focuses on collusion between AI agents, uh, by hiding messages in the text that they generate. Uh, so that's what steganography is. So a very simple example would be the first letter of every word.[00:27:57] swyx: If you Pick that out, you know, and the code sends a [00:28:00] different message than that. But something I've always emphasized is to LLMs, we read left to right. LLMs can read up, down, sideways, you know, in random character order. And it's the same to them as it is to us. So if we were ever to get You know, self motivated, underlined LLMs that we're trying to collaborate to take over the planet.[00:28:19] swyx: This would be how they do it. They spread messages among us in the messages that we generate. And he developed a scaling law for that. So he marked, I'm showing it on screen right now, the emergence of this phenomenon. Basically, for example, for Cypher encoding, GPT 2, Lama 2, mixed trial, GPT 3. 5, zero capabilities, and sudden 4.[00:28:40] swyx: And this is the kind of Jason Wei type emergence properties that people kind of look for. I think what made this paper stand out as well, so he developed the benchmark for steganography collusion, and he also focused on shelling point collusion, which is very low coordination. For agreeing on a decoding encoding format, you kind of need to have some [00:29:00] agreement on that.[00:29:00] swyx: But, but shelling point means like very, very low or almost no coordination. So for example, if I, if I ask someone, if the only message I give you is meet me in New York and you're not aware. Or when you would probably meet me at Grand Central Station. That is the Grand Central Station is a shelling point.[00:29:16] swyx: And it's probably somewhere, somewhere during the day. That is the shelling point of New York is Grand Central. To that extent, shelling points for steganography are things like the, the, the common decoding methods that we talked about. It will be interesting at some point in the future when we are worried about alignment.[00:29:30] swyx: It is not interesting today, but it's interesting that DeepMind is already thinking about this.[00:29:36] Alessio: I think that's like one of the hardest things about NeurIPS. It's like the long tail. I[00:29:41] swyx: found a pricing guy. I'm going to feature him on the podcast. Basically, this guy from NVIDIA worked out the optimal pricing for language models.[00:29:51] swyx: It's basically an econometrics paper at NeurIPS, where everyone else is talking about GPUs. And the guy with the GPUs is[00:29:57] Alessio: talking[00:29:57] swyx: about economics instead. [00:30:00] That was the sort of fun one. So the focus I saw is that model papers at NeurIPS are kind of dead. No one really presents models anymore. It's just data sets.[00:30:12] swyx: This is all the grad students are working on. So like there was a data sets track and then I was looking around like, I was like, you don't need a data sets track because every paper is a data sets paper. And so data sets and benchmarks, they're kind of flip sides of the same thing. So Yeah. Cool. Yeah, if you're a grad student, you're a GPU boy, you kind of work on that.[00:30:30] swyx: And then the, the sort of big model that people walk around and pick the ones that they like, and then they use it in their models. And that's, that's kind of how it develops. I, I feel like, um, like, like you didn't last year, you had people like Hao Tian who worked on Lava, which is take Lama and add Vision.[00:30:47] swyx: And then obviously actually I hired him and he added Vision to Grok. Now he's the Vision Grok guy. This year, I don't think there was any of those.[00:30:55] Alessio: What were the most popular, like, orals? Last year it was like the [00:31:00] Mixed Monarch, I think, was like the most attended. Yeah, uh, I need to look it up. Yeah, I mean, if nothing comes to mind, that's also kind of like an answer in a way.[00:31:10] Alessio: But I think last year there was a lot of interest in, like, furthering models and, like, different architectures and all of that.[00:31:16] swyx: I will say that I felt the orals, oral picks this year were not very good. Either that or maybe it's just a So that's the highlight of how I have changed in terms of how I view papers.[00:31:29] swyx: So like, in my estimation, two of the best papers in this year for datasets or data comp and refined web or fine web. These are two actually industrially used papers, not highlighted for a while. I think DCLM got the spotlight, FineWeb didn't even get the spotlight. So like, it's just that the picks were different.[00:31:48] swyx: But one thing that does get a lot of play that a lot of people are debating is the role that's scheduled. This is the schedule free optimizer paper from Meta from Aaron DeFazio. And this [00:32:00] year in the ML community, there's been a lot of chat about shampoo, soap, all the bathroom amenities for optimizing your learning rates.[00:32:08] swyx: And, uh, most people at the big labs are. Who I asked about this, um, say that it's cute, but it's not something that matters. I don't know, but it's something that was discussed and very, very popular. 4Wars[00:32:19] Alessio: of AI recap maybe, just quickly. Um, where do you want to start? Data?[00:32:26] swyx: So to remind people, this is the 4Wars piece that we did as one of our earlier recaps of this year.[00:32:31] swyx: And the belligerents are on the left, journalists, writers, artists, anyone who owns IP basically, New York Times, Stack Overflow, Reddit, Getty, Sarah Silverman, George RR Martin. Yeah, and I think this year we can add Scarlett Johansson to that side of the fence. So anyone suing, open the eye, basically. I actually wanted to get a snapshot of all the lawsuits.[00:32:52] swyx: I'm sure some lawyer can do it. That's the data quality war. On the right hand side, we have the synthetic data people, and I think we talked about Lumna's talk, you know, [00:33:00] really showing how much synthetic data has come along this year. I think there was a bit of a fight between scale. ai and the synthetic data community, because scale.[00:33:09] swyx: ai published a paper saying that synthetic data doesn't work. Surprise, surprise, scale. ai is the leading vendor of non synthetic data. Only[00:33:17] Alessio: cage free annotated data is useful.[00:33:21] swyx: So I think there's some debate going on there, but I don't think it's much debate anymore that at least synthetic data, for the reasons that are blessed in Luna's talk, Makes sense.[00:33:32] swyx: I don't know if you have any perspectives there.[00:33:34] Alessio: I think, again, going back to the reinforcement fine tuning, I think that will change a little bit how people think about it. I think today people mostly use synthetic data, yeah, for distillation and kind of like fine tuning a smaller model from like a larger model.[00:33:46] Alessio: I'm not super aware of how the frontier labs use it outside of like the rephrase, the web thing that Apple also did. But yeah, I think it'll be. Useful. I think like whether or not that gets us the big [00:34:00] next step, I think that's maybe like TBD, you know, I think people love talking about data because it's like a GPU poor, you know, I think, uh, synthetic data is like something that people can do, you know, so they feel more opinionated about it compared to, yeah, the optimizers stuff, which is like,[00:34:17] swyx: they don't[00:34:17] Alessio: really work[00:34:18] swyx: on.[00:34:18] swyx: I think that there is an angle to the reasoning synthetic data. So this year, we covered in the paper club, the star series of papers. So that's star, Q star, V star. It basically helps you to synthesize reasoning steps, or at least distill reasoning steps from a verifier. And if you look at the OpenAI RFT, API that they released, or that they announced, basically they're asking you to submit graders, or they choose from a preset list of graders.[00:34:49] swyx: Basically It feels like a way to create valid synthetic data for them to fine tune their reasoning paths on. Um, so I think that is another angle where it starts to make sense. And [00:35:00] so like, it's very funny that basically all the data quality wars between Let's say the music industry or like the newspaper publishing industry or the textbooks industry on the big labs.[00:35:11] swyx: It's all of the pre training era. And then like the new era, like the reasoning era, like nobody has any problem with all the reasoning, especially because it's all like sort of math and science oriented with, with very reasonable graders. I think the more interesting next step is how does it generalize beyond STEM?[00:35:27] swyx: We've been using O1 for And I would say like for summarization and creative writing and instruction following, I think it's underrated. I started using O1 in our intro songs before we killed the intro songs, but it's very good at writing lyrics. You know, I can actually say like, I think one of the O1 pro demos.[00:35:46] swyx: All of these things that Noam was showing was that, you know, you can write an entire paragraph or three paragraphs without using the letter A, right?[00:35:53] Creative Writing with AI[00:35:53] swyx: So like, like literally just anything instead of token, like not even token level, character level manipulation and [00:36:00] counting and instruction following. It's, uh, it's very, very strong.[00:36:02] swyx: And so no surprises when I ask it to rhyme, uh, and to, to create song lyrics, it's going to do that very much better than in previous models. So I think it's underrated for creative writing.[00:36:11] Alessio: Yeah.[00:36:12] Legal and Ethical Issues in AI[00:36:12] Alessio: What do you think is the rationale that they're going to have in court when they don't show you the thinking traces of O1, but then they want us to, like, they're getting sued for using other publishers data, you know, but then on their end, they're like, well, you shouldn't be using my data to then train your model.[00:36:29] Alessio: So I'm curious to see how that kind of comes. Yeah, I mean, OPA has[00:36:32] swyx: many ways to publish, to punish people without bringing, taking them to court. Already banned ByteDance for distilling their, their info. And so anyone caught distilling the chain of thought will be just disallowed to continue on, on, on the API.[00:36:44] swyx: And it's fine. It's no big deal. Like, I don't even think that's an issue at all, just because the chain of thoughts are pretty well hidden. Like you have to work very, very hard to, to get it to leak. And then even when it leaks the chain of thought, you don't know if it's, if it's [00:37:00] The bigger concern is actually that there's not that much IP hiding behind it, that Cosign, which we talked about, we talked to him on Dev Day, can just fine tune 4.[00:37:13] swyx: 0 to beat 0. 1 Cloud SONET so far is beating O1 on coding tasks without, at least O1 preview, without being a reasoning model, same for Gemini Pro or Gemini 2. 0. So like, how much is reasoning important? How much of a moat is there in this, like, All of these are proprietary sort of training data that they've presumably accomplished.[00:37:34] swyx: Because even DeepSeek was able to do it. And they had, you know, two months notice to do this, to do R1. So, it's actually unclear how much moat there is. Obviously, you know, if you talk to the Strawberry team, they'll be like, yeah, I mean, we spent the last two years doing this. So, we don't know. And it's going to be Interesting because there'll be a lot of noise from people who say they have inference time compute and actually don't because they just have fancy chain of thought.[00:38:00][00:38:00] swyx: And then there's other people who actually do have very good chain of thought. And you will not see them on the same level as OpenAI because OpenAI has invested a lot in building up the mythology of their team. Um, which makes sense. Like the real answer is somewhere in between.[00:38:13] Alessio: Yeah, I think that's kind of like the main data war story developing.[00:38:18] The Data War: GPU Poor vs. GPU Rich[00:38:18] Alessio: GPU poor versus GPU rich. Yeah. Where do you think we are? I think there was, again, going back to like the small model thing, there was like a time in which the GPU poor were kind of like the rebel faction working on like these models that were like open and small and cheap. And I think today people don't really care as much about GPUs anymore.[00:38:37] Alessio: You also see it in the price of the GPUs. Like, you know, that market is kind of like plummeted because there's people don't want to be, they want to be GPU free. They don't even want to be poor. They just want to be, you know, completely without them. Yeah. How do you think about this war? You[00:38:52] swyx: can tell me about this, but like, I feel like the, the appetite for GPU rich startups, like the, you know, the, the funding plan is we will raise 60 million and [00:39:00] we'll give 50 of that to NVIDIA.[00:39:01] swyx: That is gone, right? Like, no one's, no one's pitching that. This was literally the plan, the exact plan of like, I can name like four or five startups, you know, this time last year. So yeah, GPU rich startups gone.[00:39:12] The Rise of GPU Ultra Rich[00:39:12] swyx: But I think like, The GPU ultra rich, the GPU ultra high net worth is still going. So, um, now we're, you know, we had Leopold's essay on the trillion dollar cluster.[00:39:23] swyx: We're not quite there yet. We have multiple labs, um, you know, XAI very famously, you know, Jensen Huang praising them for being. Best boy number one in spinning up 100, 000 GPU cluster in like 12 days or something. So likewise at Meta, likewise at OpenAI, likewise at the other labs as well. So like the GPU ultra rich are going to keep doing that because I think partially it's an article of faith now that you just need it.[00:39:46] swyx: Like you don't even know what it's going to, what you're going to use it for. You just, you just need it. And it makes sense that if, especially if we're going into. More researchy territory than we are. So let's say 2020 to 2023 was [00:40:00] let's scale big models territory because we had GPT 3 in 2020 and we were like, okay, we'll go from 1.[00:40:05] swyx: 75b to 1. 8b, 1. 8t. And that was GPT 3 to GPT 4. Okay, that's done. As far as everyone is concerned, Opus 3. 5 is not coming out, GPT 4. 5 is not coming out, and Gemini 2, we don't have Pro, whatever. We've hit that wall. Maybe I'll call it the 2 trillion perimeter wall. We're not going to 10 trillion. No one thinks it's a good idea, at least from training costs, from the amount of data, or at least the inference.[00:40:36] swyx: Would you pay 10x the price of GPT Probably not. Like, like you want something else that, that is at least more useful. So it makes sense that people are pivoting in terms of their inference paradigm.[00:40:47] Emerging Trends in AI Models[00:40:47] swyx: And so when it's more researchy, then you actually need more just general purpose compute to mess around with, uh, at the exact same time that production deployments of the old, the previous paradigm is still ramping up,[00:40:58] swyx: um,[00:40:58] swyx: uh, pretty aggressively.[00:40:59] swyx: So [00:41:00] it makes sense that the GPU rich are growing. We have now interviewed both together and fireworks and replicates. Uh, we haven't done any scale yet. But I think Amazon, maybe kind of a sleeper one, Amazon, in a sense of like they, at reInvent, I wasn't expecting them to do so well, but they are now a foundation model lab.[00:41:18] swyx: It's kind of interesting. Um, I think, uh, you know, David went over there and started just creating models.[00:41:25] Alessio: Yeah, I mean, that's the power of prepaid contracts. I think like a lot of AWS customers, you know, they do this big reserve instance contracts and now they got to use their money. That's why so many startups.[00:41:37] Alessio: Get bought through the AWS marketplace so they can kind of bundle them together and prefer pricing.[00:41:42] swyx: Okay, so maybe GPU super rich doing very well, GPU middle class dead, and then GPU[00:41:48] Alessio: poor. I mean, my thing is like, everybody should just be GPU rich. There shouldn't really be, even the GPU poorest, it's like, does it really make sense to be GPU poor?[00:41:57] Alessio: Like, if you're GPU poor, you should just use the [00:42:00] cloud. Yes, you know, and I think there might be a future once we kind of like figure out what the size and shape of these models is where like the tiny box and these things come to fruition where like you can be GPU poor at home. But I think today is like, why are you working so hard to like get these models to run on like very small clusters where it's like, It's so cheap to run them.[00:42:21] Alessio: Yeah, yeah,[00:42:22] swyx: yeah. I think mostly people think it's cool. People think it's a stepping stone to scaling up. So they aspire to be GPU rich one day and they're working on new methods. Like news research, like probably the most deep tech thing they've done this year is Distro or whatever the new name is.[00:42:38] swyx: There's a lot of interest in heterogeneous computing, distributed computing. I tend generally to de emphasize that historically, but it may be coming to a time where it is starting to be relevant. I don't know. You know, SF compute launched their compute marketplace this year, and like, who's really using that?[00:42:53] swyx: Like, it's a bunch of small clusters, disparate types of compute, and if you can make that [00:43:00] useful, then that will be very beneficial to the broader community, but maybe still not the source of frontier models. It's just going to be a second tier of compute that is unlocked for people, and that's fine. But yeah, I mean, I think this year, I would say a lot more on device, We are, I now have Apple intelligence on my phone.[00:43:19] swyx: Doesn't do anything apart from summarize my notifications. But still, not bad. Like, it's multi modal.[00:43:25] Alessio: Yeah, the notification summaries are so and so in my experience.[00:43:29] swyx: Yeah, but they add, they add juice to life. And then, um, Chrome Nano, uh, Gemini Nano is coming out in Chrome. Uh, they're still feature flagged, but you can, you can try it now if you, if you use the, uh, the alpha.[00:43:40] swyx: And so, like, I, I think, like, you know, We're getting the sort of GPU poor version of a lot of these things coming out, and I think it's like quite useful. Like Windows as well, rolling out RWKB in sort of every Windows department is super cool. And I think the last thing that I never put in this GPU poor war, that I think I should now, [00:44:00] is the number of startups that are GPU poor but still scaling very well, as sort of wrappers on top of either a foundation model lab, or GPU Cloud.[00:44:10] swyx: GPU Cloud, it would be Suno. Suno, Ramp has rated as one of the top ranked, fastest growing startups of the year. Um, I think the last public number is like zero to 20 million this year in ARR and Suno runs on Moto. So Suno itself is not GPU rich, but they're just doing the training on, on Moto, uh, who we've also talked to on, on the podcast.[00:44:31] swyx: The other one would be Bolt, straight cloud wrapper. And, and, um, Again, another, now they've announced 20 million ARR, which is another step up from our 8 million that we put on the title. So yeah, I mean, it's crazy that all these GPU pores are finding a way while the GPU riches are also finding a way. And then the only failures, I kind of call this the GPU smiling curve, where the edges do well, because you're either close to the machines, and you're like [00:45:00] number one on the machines, or you're like close to the customers, and you're number one on the customer side.[00:45:03] swyx: And the people who are in the middle. Inflection, um, character, didn't do that great. I think character did the best of all of them. Like, you have a note in here that we apparently said that character's price tag was[00:45:15] Alessio: 1B.[00:45:15] swyx: Did I say that?[00:45:16] Alessio: Yeah. You said Google should just buy them for 1B. I thought it was a crazy number.[00:45:20] Alessio: Then they paid 2. 7 billion. I mean, for like,[00:45:22] swyx: yeah.[00:45:22] Alessio: What do you pay for node? Like, I don't know what the game world was like. Maybe the starting price was 1B. I mean, whatever it was, it worked out for everybody involved.[00:45:31] The Multi-Modality War[00:45:31] Alessio: Multimodality war. And this one, we never had text to video in the first version, which now is the hottest.[00:45:37] swyx: Yeah, I would say it's a subset of image, but yes.[00:45:40] Alessio: Yeah, well, but I think at the time it wasn't really something people were doing, and now we had VO2 just came out yesterday. Uh, Sora was released last month, last week. I've not tried Sora, because the day that I tried, it wasn't, yeah. I[00:45:54] swyx: think it's generally available now, you can go to Sora.[00:45:56] swyx: com and try it. Yeah, they had[00:45:58] Alessio: the outage. Which I [00:46:00] think also played a part into it. Small things. Yeah. What's the other model that you posted today that was on Replicate? Video or OneLive?[00:46:08] swyx: Yeah. Very, very nondescript name, but it is from Minimax, which I think is a Chinese lab. The Chinese labs do surprisingly well at the video models.[00:46:20] swyx: I'm not sure it's actually Chinese. I don't know. Hold me up to that. Yep. China. It's good. Yeah, the Chinese love video. What can I say? They have a lot of training data for video. Or a more relaxed regulatory environment.[00:46:37] Alessio: Uh, well, sure, in some way. Yeah, I don't think there's much else there. I think like, you know, on the image side, I think it's still open.[00:46:45] Alessio: Yeah, I mean,[00:46:46] swyx: 11labs is now a unicorn. So basically, what is multi modality war? Multi modality war is, do you specialize in a single modality, right? Or do you have GodModel that does all the modalities? So this is [00:47:00] definitely still going, in a sense of 11 labs, you know, now Unicorn, PicoLabs doing well, they launched Pico 2.[00:47:06] swyx: 0 recently, HeyGen, I think has reached 100 million ARR, Assembly, I don't know, but they have billboards all over the place, so I assume they're doing very, very well. So these are all specialist models, specialist models and specialist startups. And then there's the big labs who are doing the sort of all in one play.[00:47:24] swyx: And then here I would highlight Gemini 2 for having native image output. Have you seen the demos? Um, yeah, it's, it's hard to keep up. Literally they launched this last week and a shout out to Paige Bailey, who came to the Latent Space event to demo on the day of launch. And she wasn't prepared. She was just like, I'm just going to show you.[00:47:43] swyx: So they have voice. They have, you know, obviously image input, and then they obviously can code gen and all that. But the new one that OpenAI and Meta both have but they haven't launched yet is image output. So you can literally, um, I think their demo video was that you put in an image of a [00:48:00] car, and you ask for minor modifications to that car.[00:48:02] swyx: They can generate you that modification exactly as you asked. So there's no need for the stable diffusion or comfy UI workflow of like mask here and then like infill there in paint there and all that, all that stuff. This is small model nonsense. Big model people are like, huh, we got you in as everything in the transformer.[00:48:21] swyx: This is the multimodality war, which is, do you, do you bet on the God model or do you string together a whole bunch of, uh, Small models like a, like a chump. Yeah,[00:48:29] Alessio: I don't know, man. Yeah, that would be interesting. I mean, obviously I use Midjourney for all of our thumbnails. Um, they've been doing a ton on the product, I would say.[00:48:38] Alessio: They launched a new Midjourney editor thing. They've been doing a ton. Because I think, yeah, the motto is kind of like, Maybe, you know, people say black forest, the black forest models are better than mid journey on a pixel by pixel basis. But I think when you put it, put it together, have you tried[00:48:53] swyx: the same problems on black forest?[00:48:55] Alessio: Yes. But the problem is just like, you know, on black forest, it generates one image. And then it's like, you got to [00:49:00] regenerate. You don't have all these like UI things. Like what I do, no, but it's like time issue, you know, it's like a mid[00:49:06] swyx: journey. Call the API four times.[00:49:08] Alessio: No, but then there's no like variate.[00:49:10] Alessio: Like the good thing about mid journey is like, you just go in there and you're cooking. There's a lot of stuff that just makes it really easy. And I think people underestimate that. Like, it's not really a skill issue, because I'm paying mid journey, so it's a Black Forest skill issue, because I'm not paying them, you know?[00:49:24] Alessio: Yeah,[00:49:25] swyx: so, okay, so, uh, this is a UX thing, right? Like, you, you, you understand that, at least, we think that Black Forest should be able to do all that stuff. I will also shout out, ReCraft has come out, uh, on top of the image arena that, uh, artificial analysis has done, has apparently, uh, Flux's place. Is this still true?[00:49:41] swyx: So, Artificial Analysis is now a company. I highlighted them I think in one of the early AI Newses of the year. And they have launched a whole bunch of arenas. So, they're trying to take on LM Arena, Anastasios and crew. And they have an image arena. Oh yeah, Recraft v3 is now beating Flux 1. 1. Which is very surprising [00:50:00] because Flux And Black Forest Labs are the old stable diffusion crew who left stability after, um, the management issues.[00:50:06] swyx: So Recurve has come from nowhere to be the top image model. Uh, very, very strange. I would also highlight that Grok has now launched Aurora, which is, it's very interesting dynamics between Grok and Black Forest Labs because Grok's images were originally launched, uh, in partnership with Black Forest Labs as a, as a thin wrapper.[00:50:24] swyx: And then Grok was like, no, we'll make our own. And so they've made their own. I don't know, there are no APIs or benchmarks about it. They just announced it. So yeah, that's the multi modality war. I would say that so far, the small model, the dedicated model people are winning, because they are just focused on their tasks.[00:50:42] swyx: But the big model, People are always catching up. And the moment I saw the Gemini 2 demo of image editing, where I can put in an image and just request it and it does, that's how AI should work. Not like a whole bunch of complicated steps. So it really is something. And I think one frontier that we haven't [00:51:00] seen this year, like obviously video has done very well, and it will continue to grow.[00:51:03] swyx: You know, we only have Sora Turbo today, but at some point we'll get full Sora. Oh, at least the Hollywood Labs will get Fulsora. We haven't seen video to audio, or video synced to audio. And so the researchers that I talked to are already starting to talk about that as the next frontier. But there's still maybe like five more years of video left to actually be Soda.[00:51:23] swyx: I would say that Gemini's approach Compared to OpenAI, Gemini seems, or DeepMind's approach to video seems a lot more fully fledged than OpenAI. Because if you look at the ICML recap that I published that so far nobody has listened to, um, that people have listened to it. It's just a different, definitely different audience.[00:51:43] swyx: It's only seven hours long. Why are people not listening? It's like everything in Uh, so, so DeepMind has, is working on Genie. They also launched Genie 2 and VideoPoet. So, like, they have maybe four years advantage on world modeling that OpenAI does not have. Because OpenAI basically only started [00:52:00] Diffusion Transformers last year, you know, when they hired, uh, Bill Peebles.[00:52:03] swyx: So, DeepMind has, has a bit of advantage here, I would say, in, in, in showing, like, the reason that VO2, while one, They cherry pick their videos. So obviously it looks better than Sora, but the reason I would believe that VO2, uh, when it's fully launched will do very well is because they have all this background work in video that they've done for years.[00:52:22] swyx: Like, like last year's NeurIPS, I already was interviewing some of their video people. I forget their model name, but for, for people who are dedicated fans, they can go to NeurIPS 2023 and see, see that paper.[00:52:32] Alessio: And then last but not least, the LLMOS. We renamed it to Ragops, formerly known as[00:52:39] swyx: Ragops War. I put the latest chart on the Braintrust episode.[00:52:43] swyx: I think I'm going to separate these essays from the episode notes. So the reason I used to do that, by the way, is because I wanted to show up on Hacker News. I wanted the podcast to show up on Hacker News. So I always put an essay inside of there because Hacker News people like to read and not listen.[00:52:58] Alessio: So episode essays,[00:52:59] swyx: I remember [00:53:00] purchasing them separately. You say Lanchain Llama Index is still growing.[00:53:03] Alessio: Yeah, so I looked at the PyPy stats, you know. I don't care about stars. On PyPy you see Do you want to share your screen? Yes. I prefer to look at actual downloads, not at stars on GitHub. So if you look at, you know, Lanchain still growing.[00:53:20] Alessio: These are the last six months. Llama Index still growing. What I've basically seen is like things that, One, obviously these things have A commercial product. So there's like people buying this and sticking with it versus kind of hopping in between things versus, you know, for example, crew AI, not really growing as much.[00:53:38] Alessio: The stars are growing. If you look on GitHub, like the stars are growing, but kind of like the usage is kind of like flat. In the last six months, have they done some[00:53:4

Today, we are joined by Dr. Barbara Oakley. Dr. Barbara Oakley is a distinguished professor, engineer, and globally recognized expert in the fields of learning and neuroscience. She is best known for her groundbreaking work on understanding how people learn and for developing practical strategies to improve learning effectiveness. She is also a NYT bestselling author of several books on learning science and learning how to learn. Dr. Oakley's Website: https://barbaraoakley.com/ Dr. Oakley on Coursera: https://www.coursera.org/learn/learning-how-to-learn Dr. Oakley's Books: https://www.amazon.com/stores/Barbara-Oakley-PhD/author/B000AP9ZR4 In this episode, Barbara shares her journey from struggling with math to becoming a distinguished professor of engineering. We also discuss the importance of updating learning strategies, embracing discomfort, and using techniques like active recall and dual-mode thinking (focused and diffuse modes) to enhance learning. Join us for this great discussion about the significance of self-awareness and self-monitoring in personal growth and learning efficiency. - Website and live online programs: http://ims-online.com Blog: https://blog.ims-online.com/ Podcast: https://ims-online.com/podcasts/ LinkedIn: https://www.linkedin.com/in/charlesagood/ Twitter: https://twitter.com/charlesgood99 Chapters: (00:00) Introduction (02:00) Barbaras's Journey Overcoming Math Struggles (05:03) Technique: Maintaining Motivation and Focus (07:37) Tool: The Concept of Mind Shift (10:50) Technique: Self-Monitoring and Overcoming Comparisons (14:04) Technique: Focused vs. Diffused Mode of Thinking (21:22) Tools: Understanding Memory and Effective Learning Strategies (27:58) Conclusion

Dr. Xenophon Papademetris, Professor of Biomedical Informatics & Data Science, and Radiology & Biomedical Imaging at Yale School of Medicine speaks with Pitt HexAI guest host Jamie Gramz, Senior Director of Digital Strategy and Business Development with Siemens Healthineers. Jamie and Dr. Papademetris discuss Xenophon's experience in medical image analysis, machine learning, and software development and his involvement in the development of medical image analysis software as well as his involvement in Yale's Certificate Program in Medical Software and Medical AI. Jamie and Dr. Papademetris also discuss Xenophon's textbook “Introduction to Medical Software: Foundations for Digital Health, Devices and Diagnostics” and his Coursera online class “Introduction to Medical Software”, the importance of medical software and AI education as well as the importance of interdisciplinary collaboration in AI for healthcare, and they discuss explainability in AI and clinical communications.

Welcome to the Financial Freedom & Wealth Trailblazers Podcast! In this episode, we'll share insights on financial literacy that can help you make informed decisions, create wealth, and gain financial independence. John Cousins (@jjcousins) is an investor, tech founder, and bestselling author of Understanding Corporate Finance and over 60 other books. John is the founder of MBA ASAP, which provides training to individuals and corporations including Adidas, Apple, General Mills, Kaiser Permanente, Lyft, PayPal, Pinterest, Mercedes-Benz, and Volkswagen. John has taught MBA students at universities worldwide. Currently General Partner at Tetraktys Global, a quantitative hedge fund, he is an early investor in many successful tech companies and crypto protocols, including Databricks, SpaceX, Anthropic, Discord, Udemy, Coursera, Fastly, UiPath, Palantir, Bitcoin, Chainlink, Ethereum, and Solana. John was the cofounder of Biomoda (IPO 2006), Advanced Optics Electronics (IPO 1999), FoodSentry (epic fail), MBA ASAP, and Tetraktys Global. He holds undergraduate degrees from MIT and Boston University and an MBA in finance from Wharton. Connect with John here:  MBA ASAP:  www.mba-asap.com YouTube: https://www.youtube.com/channel/UC6nmDenZkLv34n3FtkzRwgw X/Twitter:  https://x.com/jjcousins Facebook MBA ASAP: https://www.facebook.com/MBA.ASAP        Instagram: https://www.instagram.com/jjcousinsiii/ LinkedIn: https://www.linkedin.com/in/johncousinsiii/ Grab the freebie here: https://mba.myflodesk.com/finance =================================== If you enjoyed this episode, remember to hit the like button and subscribe. Then share this episode with your friends. Thanks for watching the Financial Freedom & Wealth Trailblazers Podcast. This podcast is part of the Digital Trailblazer family of podcasts. To learn more about Digital Trailblazer and what we do to help entrepreneurs, go to DigitalTrailblazer.com.Are you a coach, consultant, expert, or online course creator? Then we'd love to invite you to our FREE Facebook Group where you can learn the best strategies to land more high-ticket clients and customers.  QUICK LINKS:  APPLY TO BE FEATURED: https://app.digitaltrailblazer.com/podcast-guest-application DIGITAL TRAILBLAZER: https://digitaltrailblazer.com/

This week's episode of Don't Stop Us Now AI edition is with a fascinating guest who has a box seat in understanding what's going on with AI in businesses around the world. Helen Mayhew is a McKinsey & Company Partner and one of the leaders of its AI division, QuantumBlack. A Cambridge graduate, Helen has deep data analytics and AI expertise. Her day job is to guide leading organisations on their advanced analytics journeys and AI innovation and implementation. In this episode, Helen covers everything from the broad spectrum of initiatives and use cases different businesses are and will be trying, to detailing how radically different our roles are likely to be in future. Helpfully, she shares some of the key skills we'll all need to remain valuable and she reveals her belief that almost every workday process and every person's day will be reimagined and done differently thanks to AI.Helen also shares some incredible research predictions about the future in case you were in any doubt about AI's coming impact on us all. For example, between 30-40% of all tasks done at work today won't need to exist in the future. Yes you read that right, 30 to 40% of what we humans do today will be replaced by AI according to this research! Helen is really good at explaining things very clearly and bringing a variety of AI use cases to life. She also shares some of her favourite AI learning resources which you can see in the links below. This is an unmissable episode, so learn what's coming your way with the ever curious and super smart Helen Mayhew. Useful LinksHelen Mayhew LinkedInQuantumBlack websiteMckinsey websiteChat GPT GeminiStable Diffusion Microsoft AI Learning HubFast AI / AI for Everyone courseDeepLearning founder and Coursera co founder: Andrew Ng courses Practical AI podcastLex Fridman podcast Hosted on Acast. See acast.com/privacy for more information.

Welcome to Growthmates with Kate Syuma — Growth advisor, previously Head of Growth Design at Miro. I'm building Growthmates as a place to connect with inspiring leaders to help you grow yourself and your product. Here you can learn how companies like Dropbox, Adobe, Canva, Loom, and many more are building excellent products and growth culture. Get all episodes and a free playbook for Growth teams on our brand-new website — growthmates.club, and press follow to support us on your favorite platforms.Listen now and subscribe on your favorite platforms — Apple, Spotify, or watch on YouTube (new!).In this episode, Kate speaks with Chetana Deorah , a seasoned design leader who shares her journey across renowned companies like Yahoo!, Netflix, and Coursera, along with her transition to building a community-driven vegan pizza initiative. Chetana opens up about navigating the intersection of creativity, leadership, and self-reflection while balancing corporate and personal passions.—Brought to you by Command.ai — a user-focused platform offering an alternative to traditional popups or chatbots. Their AI “Copilot” answers questions, performs actions, and simplifies complex tasks. Use “Nudges” to guide users with timely, relevant messages, all within a no-code platform. Perfect for Product, Support, and Marketing teams to positively influence user behavior while respecting their needs:—Key highlights from this episode

Cybersecurity Today: Palo Alto Firewalls Breached, APT28's Wi-Fi Hack, Meta Fights Scams In today's episode, over 2,000 Palo Alto firewalls were hacked via patched zero-day vulnerabilities; a Russian group, APT28, exploited Wi-Fi networks in a novel 'Nearest Neighbor Attack' to breach a U.S. firm; Meta removed more than 2 million accounts linked to pig butchering scams; and Google launched a free cybersecurity certificate on Coursera to prepare students for entry-level jobs in six months. Host Jim Love provides in-depth analysis and the latest updates in the world of cybersecurity. 00:00 Introduction and Headlines 00:29 Palo Alto Firewalls Hacked 02:43 Nearest Neighbor Wi-Fi Attack 05:09 Meta's Crackdown on Pig Butchering Scams 07:10 Google's Free Cybersecurity Certificate 08:52 Conclusion and Resources

In this episode of Grow a Small Business, host Troy Trewin interviews Brad Riley, the founder of Infostatus, shares his incredible journey from starting with just one team member to now leading a thriving team of 15. He discusses the importance of perseverance through challenges and the invaluable lessons learned along the way. Brad emphasizes leveraging online resources and learning from the experiences of others in the industry. Tune in to discover how Infostatus achieved remarkable growth and generated $3 million in revenue over the past 11 years. Other Resources: NPS – An easy way to measure if your customers love you in 21 minutes – use the Net Promoter Score (NPS). And it's FREE. Productivity increases 7%-23%, team engagement up threefold and retention from 5.4 to 9.4 years – why wouldn't you consider an ESOP, Employee Share Ownership Plan. ESOP Subject Matter Expert talks other benefits, costs and time (Craig West) Why would you wait any longer to start living the lifestyle you signed up for? Balance your health, wealth, relationships and business growth. And focus your time and energy and make the most of this year. Let's get into it by clicking here. Troy delves into our guest's startup journey, their perception of success, industry reconsideration, and the pivotal stress point during business expansion. They discuss the joys of small business growth, vital entrepreneurial habits, and strategies for team building, encompassing wins, blunders, and invaluable advice. And a snapshot of the final five Grow A Small Business Questions: What do you think is the hardest thing in growing a small business? Brad Riley identifies that the hardest thing in growing a small business is navigating through tough times and maintaining perseverance. He emphasizes that challenges can take many forms, and what seems tough today may look different in the future. He believes that understanding and learning from both successes and failures, as well as leveraging resources and insights from others, is crucial to overcoming these hurdles and achieving sustainable growth. What's your favourite business book that has helped you the most? Brad Riley mentioned Annie Duke as a significant influence. Known for her work on decision-making under uncertainty, her insights have likely impacted Brad's approach to managing challenges and strategizing in his business. Annie Duke's books, such as Thinking in Bets, emphasize critical thinking and probabilistic decision-making, which are highly relevant for navigating complex business environments. Are there any great podcasts or online learning resources you'd recommend to help grow a small business? Brad Riley emphasized leveraging the internet to learn from others' journeys. While he didn't recommend specific resources, general suggestions include the podcasts "How I Built This," "The Tim Ferriss Show," and "Smart Passive Income," along with online courses from platforms like Coursera, LinkedIn Learning, and Udemy. You can also explore YouTube channels such as Gary Vaynerchuk and Stanford Graduate School of Business for valuable insights. What tool or resource would you recommend to grow a small business? Brad Riley recommends using online learning platforms to build skills, leveraging social media for networking and marketing, and utilizing project management tools like Trello or Asana to streamline team collaboration. Additionally, analytics tools such as Google Analytics can drive data-informed decisions. These resources collectively support efficient growth and operational scaling for small businesses. What advice would you give yourself on day one of starting out in business? Brad Riley advises his day-one self to stay resilient, reassuring that "it's okay, you'll be okay." He emphasizes the importance of perseverance, noting that tough times are part of the journey and that the challenges faced today will look different down the road. His key message: hang in there and trust that things will work out. Book a 20-minute Growth Chat with Troy Trewin to see if you qualify for our upcoming course. Don't miss out on this opportunity to take your small business to new heights! Enjoyed the podcast? Please leave a review on iTunes or your preferred platform. Your feedback helps more small business owners discover our podcast and embark on their business growth journey. Quotable quotes from our special Grow A Small Business podcast guest:   Perseverance is the secret ingredient that transforms tough times into success — Brad Riley Learning from others' experiences can fast-track your own growth — Brad Riley Hang in there; today's challenges are shaping tomorrow's victories — Brad Riley      

Laurie is a Professor of Psychology at Yale University.  In addition to her work on the evolutionary origins of human cognition, Laurie is an expert on the science of happiness and the ways in which our minds lie to us about what makes us happy. Her Yale course, Psychology and the Good Life, teaches students how the science of psychology can provide important hints about how to make wiser choices and live a life that's happier and more fulfilling. The class became Yale's most popular course in over 300 years.  The online version of the class—The Science of Well-Being on Coursera—has attracted more than 4 million students. She was recently voted as one of Popular Science Magazine's “Brilliant 10” young minds and was named in Time Magazine as a “Leading Campus Celebrity.” Her podcast, The Happiness Lab, has attracted over 100 million downloads since its launch.   Some interesting insights from this episode: ·       Our minds lie to us when it comes to happiness.  ·       There is the sense of being happy in your life and the sense of being happy with your life. ·       Investing in social relationships is the most important thing we can do to improve our happiness.  ·       If you force yourself to be more social, even if it's natural to you, you'll actually experience more positive emotions as a result. ·       Beyond social connections, practicing gratitude and helping others are also tools to increase your overall wellbeing.  ·       There's a disconnect between the things that we want and the things that we truly enjoy. ·       The arrival fallacy is thinking that you'll be happy once you achieve some goal but that happiness is often fleeting.  ·       The journey is ultimately much more rewarding than the destination.  Learn to enjoy it. ·       “Excellence is behaving and developing mindsets in a way that allows you to flourish.”   Show Notes: Personal website: Dr. Laurie Santos Podcast: The Happiness Lab Coursera class: The Science of Well-Being

In this episode of The Entrepreneurial You, we sit down with Marquel Russell, a multimillion-dollar revenue generator, best-selling author, Inc. 5000 CEO, and Rapid Business Growth Strategist.  From high school dropout to top business growth strategist, Marquel's journey is truly remarkable. He shares his blueprint for rapid business growth, emphasizing the importance of simple systems that make companies more profitable, scalable, and sustainable. Prepare to be inspired as Marquel reveals his secrets to achieving success and building a thriving business. COMMUNITY CONNECTION: Brought to you by 5-Minute Book-Keeper. In this segment, I invite you, our community, to share your reviews, questions, and feedback and engage with us. Today's feedback is a 5star review of Podcast Power from Aimee J:  Podcast Power Provides the Framework You Need to Launch Your Podcast - Heneka does a great job of taking a significant topic such as podcasting and presenting it in an easy-to-process manner. She showcases her knowledge of podcasting and provides actionable steps to help a beginner get started. Heneka lays the groundwork for why you should start a podcast so well that it's hard to find a reason not to. If you're interested in podcasting, this is a wonderful resource to help get you to press record and launch quickly. CONTACT MARQUEL RUSSELL: Facebook: https://www.facebook.com/ceomarquelrussell Instagram: https://instagram.com/marquelrussell Twitter: https://twitter.com/marquelrussell LinkedIn: https://www.linkedin.com/in/marquel-russell/  TRENDING NOW: Short-Form Videos One of the hottest trends in marketing right now is the rise of short-form video content. Platforms like TikTok, Instagram Reels, and YouTube Shorts are popular and driving significant engagement and business results. According to a recent report by HubSpot, 90% of marketers using short-form video will increase or maintain their investment in 2024, as these videos have the highest ROI of any social media marketing strategy (Coursera). Additionally, short-form videos are highly engaging, with a completion rate of around 68% (Coursera). This shift towards bite-sized content offers businesses a powerful way to connect with their audiences quickly and effectively. If you enjoyed this episode of The Entrepreneurial You, subscribe on Spotify and Apple Podcasts, leave a rating, and share it with your friends. Visit my website at ⁠henekawatkisporter.com⁠ for a free eBook on conducting podcast interviews like a pro. If you're an aspiring podcaster or a busy entrepreneur looking to start your own show, we've got you covered. Our podcast production services take the hassle out of creating your podcast, so all you have to do is show up and share your amazing content. From editing to distribution, we handle it all. Visit my website at henekawatkisporter.com to learn more. Remember to send me your feedback at heneka@henekawatkisporter.com   Affirm with me: I am a beacon of innovation and success, radiating my unique vision into the world. Stay inspired, stay driven, and until next time, keep shining brightly!

Director of SEO and Strategic Content at Coursera, Divya Hillier, discusses the critical role of humanization and empathy in SEO strategy. She emphasizes how understanding and integrating these elements can significantly enhance engagement and effectiveness in digital marketing. By focusing on the human aspects behind search behaviors, Divya provides insights on creating more meaningful and impactful SEO campaigns. Show NotesConnect With: Divya Hillier: Website // LinkedInThe Voices of Search Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

On the eve of the 2024 Election Day, Donna and Orlando sat down with the Executive Director of Building Community Value (BCV), Chase Cantrell.BCV is a Detroit-based non-profit organization dedicated to equipping residents with tools to shape their neighborhoods.They recently announced the launch of their first-ever online course, “Real Estate Development: Building Value in Your Community.” Hosted on Coursera, the course aims to teach aspiring real estate developers the fundamentals of real estate development, including development stages, team building, project feasibility, social impact, and financial modeling. This innovative online course, developed in close collaboration with the University of Michigan Center for Academic Innovation (CAI), marks a significant shift for BCV. Traditionally focused on in-person training for residents of Detroit, Hamtramck, and Highland Park, the online course is now accessible to learners worldwide, fostering real estate and community development skills on a scale far beyond SE Michigan. To learn more about Building Community Values' online course, click here!FOR HOT TAKES:DETROIT STRENGTHENS SECURITY AT SITES WHERE BALLOTS ARE COUNTED LATE RESULTS, VOTING MACHINES, AND MORE: DEBUNKING MICHIGAN'S ELECTION MISINFORMATION Support the showFollow us on Instagram, Facebook and Twitter.

Divya Hillier, the SEO Lead at Coursera, discusses leading SEO teams and programs during uncertain times. She explores the challenges and strategies involved in maintaining team efficiency and morale when external conditions are unpredictable. Divya shares insights on adapting SEO practices to stay ahead in a rapidly changing digital landscape. Show NotesConnect With: Divya Hillier: Website // LinkedInThe Voices of Search Podcast: Email // LinkedIn // TwitterBenjamin Shapiro: Website // LinkedIn // TwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Description: Marni Baker Stein, Chief Content Officer at Coursera, joins host, Cindi Howson, and dives into  the impact of Generative AI on skills, diversity in tech, and the future of upskilling.Key Moments: The impact GenAI and the surge of learning demand (05:45)Why employers must prioritize AI literacy (10.32)The gender gap in AI learning and why it matters (19:40)Leveraging data to drive personalization and learner success (24:00)Predictions for the future of AI in the labor market (29.53)Key Quotes:“Generative AI is going to require us to all be a lot more emotionally intelligent because it's going to create such disruption and change. And we're all going to have to navigate the complexities of this change. We're going to have to bring our organizations through this change. That's going to take emotional intelligence as the one thing this technology isn't, is human. Understanding and human empathy is going to remain paramount.”“In terms of data and AI skills, what is extraordinary is that the demand for these skills in the last year has grown over a thousand percent. We now have seven individuals a minute enroll in GenAI content.”“Millions of people globally are deciding that it's time to upskill and reskill in these AI, regardless of whether their employer is telling them to or not. People see it happening. They're reading about it. They're hearing about it. And they're actively going out and chasing down those skills.”Mentions:  Caste: The Origins of Our Discontent by Isabel WilkersonFrom Academia to EdTech: The Path to an Equitable Education in the Digital Age Girls Who CodeMarni Baker Stein Bio: Marni Baker Stein is Coursera's Chief Content Officer, where she oversees the company's content and credential strategy and partner relationships. Marni has more than 25 years of experience in producing and scaling online and hybrid education programs. Prior to joining Coursera, she was Chief Academic Officer and Provost at Western Governors University, where she led its four colleges serving more than 135,000 students with programs that improved access and affordability without compromising academic quality. Before that, Marni held several leadership positions focused on access, student success, and program design at institutions such as the University of Texas, Columbia University, and the University of Pennsylvania. She earned her PhD in Educational Leadership from the University of Pennsylvania.  Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Weiterbildung mit KI – Chancen für Unternehmer – Shownotes In dieser Episode von TomsTalkTime geht es um die Rolle der Künstlichen Intelligenz in der Weiterbildung speziell für Unternehmer. In der modernen Geschäftswelt, in der sich alles schnell verändert, wird es immer wichtiger, neue Fähigkeiten zu erlernen und Wissen kontinuierlich zu aktualisieren. KI-gestützte Lernplattformen bieten genau dafür eine Lösung: Sie ermöglichen eine effiziente, flexible und personalisierte Weiterbildung, die sich an deine individuellen Lernziele und Bedürfnisse anpasst. Tom zeigt dir in dieser Episode, wie du KI in deinen Weiterbildungsprozess einbinden kannst, um dich und dein Unternehmen fit für die Zukunft zu machen. Zusammenfassung und Stichpunkte: Möglichkeiten, die KI in der Weiterbildung bietet: Wie Weiterbildung mit KI persönlicher und relevanter für Unternehmer gestaltet. Beispiele für KI-gestützte Lernplattformen: Einblicke in Plattformen wie Coursera und Udacity und ihre spezifischen Vorteile bei Weiterbildung mit KI. Wichtige Skills für Unternehmer: Die Vielzahl an Hard und Soft Skills, die dank KI effizient und flexibel erlernt werden können durch Weiterbildung mit KI. Vorteile gegenüber klassischen Methoden: Flexibilität, Zeitersparnis und individuelle Lernwege mit KI, die sowohl den Lernprozess als auch die Qualität der Inhalte verbessern. Shownotes und Episodendetails In dieser Folge erfährst du, wie du Künstliche Intelligenz gezielt für deine Weiterbildung einsetzen kannst. Kurz: Weiterbildung mit KI. Unternehmer müssen heute mehr denn je am Puls der Zeit bleiben, und genau hier kann KI als „persönlicher Coach“ einen entscheidenden Unterschied machen. KI-Tools können dir helfen, gezielte Lernstrategien zu entwickeln und deine Fortschritte ständig zu überprüfen, sodass du dich konsequent weiterentwickelst und deine Ziele erreichst. Hier sind die wichtigsten Themen, die in dieser Episode behandelt werden: Welche Möglichkeiten bietet Weiterbildung mit KI? Künstliche Intelligenz ermöglicht es dir, nicht nur Wissen zu erlangen, sondern es auch effizient und gezielt auf dich zugeschnitten zu konsumieren. Durch personalisierte Vorschläge, die an deinen Wissensstand, deine beruflichen Ziele und sogar deine bevorzugte Lernweise angepasst sind, bekommst du das Wissen, das für dich wirklich relevant ist. So sparst du Zeit und gewinnst die Flexibilität, die Weiterbildung dann zu machen, wenn es dir passt. Diese Effizienz bietet dir den Vorteil, dass du stets nur das lernst, was du wirklich für dein Business und deine Weiterentwicklung benötigst, ohne von allgemeinem Wissen überfordert zu werden. Beispiele für KI-gestützte Lernplattformen: Plattformen wie Coursera, Udacity und LinkedIn Learning nutzen KI, um den Lernprozess gezielt zu optimieren und deine persönlichen Fortschritte sichtbar zu machen. Diese Plattformen analysieren deine Lerngewohnheiten und Vorlieben und bieten dir Inhalte an, die genau auf dich zugeschnitten sind. Das bedeutet, ob du visuell, textbasiert oder interaktiv lernst – die Plattformen passen sich dynamisch an. Sie fordern dich heraus, gehen auf deine Schwächen ein und helfen dir dabei, deine Fähigkeiten kontinuierlich zu verbessern. Der Lernerfolg wird messbar, da du stets aufbauende und passende Inhalte bekommst, die dir beim Erreichen deiner individuellen Ziele helfen. Wichtige Skills, die Unternehmer durch Weiterbildung mit KI lernen können: KI ist ein „digitaler Trainer“, der dir ermöglicht, eine breite Palette an neuen Skills zu entwickeln – von technischen Grundlagen wie Datenanalyse und Programmieren bis hin zu essentiellen Soft Skills. Entscheidungsfindung und Führungsqualitäten lassen sich mit KI-gesteuerten Programmen ebenfalls simulieren und üben. Diese Programme bieten interaktive Szenarien, in denen du Entscheidungen treffen und in einer sicheren Umgebung Fehler machen kannst. Die KI analysiert dein Verhalten und gibt dir direkt Feedback, sodass du nach und nach strategisch denkst und agierst. Das ermöglicht dir, im Alltag souveräner und erfolgreicher aufzutreten und in deinem unternehmerischen Umfeld fundierte Entscheidungen zu treffen. Vorteile und Herausforderungen von Weiterbildung mit KI gegenüber klassischen Methoden: Die Flexibilität, die KI-Weiterbildung bietet, ist kaum zu übertreffen. Anstatt an feste Zeiten und Orte gebunden zu sein, entscheidest du selbst, wann und wo du lernen möchtest. Das macht es ideal für Unternehmer, die oft wenig Zeit haben, sich aber dennoch kontinuierlich weiterentwickeln möchten. Gleichzeitig bringt der Umgang mit KI gewisse Herausforderungen mit sich. Ein technisches Grundverständnis und Offenheit gegenüber neuen Methoden sind oft gefragt. Doch wenn du dich darauf einlässt, eröffnen sich dir neue Lernwege, die nicht nur effizient, sondern auch auf deine individuellen Ziele zugeschnitten sind. Der große Vorteil gegenüber klassischen Methoden liegt also in der Kombination aus Flexibilität, Effizienz und Personalisierung, die es dir ermöglicht, in deinem eigenen Tempo und genau an den für dich relevanten Themen zu arbeiten. Zusammenfassung: KI-Tools bieten eine personalisierte, zielgerichtete Form der Weiterbildung, die speziell für Unternehmer große Vorteile bringt. KI-gestützte Lernplattformen passen Inhalte auf dich an und optimieren so deinen Lernprozess durch gezieltes Feedback. Unternehmer können sowohl technische Skills als auch Soft Skills mithilfe von KI-gestützten Programmen weiterentwickeln und ihre Entscheidungsfähigkeit in simulationsbasierten Umgebungen trainieren. Die Flexibilität und die Möglichkeit des selbstbestimmten Lernens machen KI-Weiterbildung zu einem Vorteil gegenüber klassischen Methoden. Und denk immer daran: Wer will, findet Wege. Wer nicht will, findet Gründe. Tschüss, mach's gut. Dein Tom.   Hol Dir jetzt Dein Hörbuch "Selfmade Millionäre packen aus" und klicke auf das Bild!     Buchempfehlung bei Amazon: Denken Sie wie Ihre Kunden   +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Mehr Freiheit, mehr Geld und mehr Spaß mit DEINEM eigenen Podcast. Erfahre jetzt, warum es auch für Dich Sinn macht, Deinen eigenen Podcast zu starten. Jetzt hier zum kostenlosen Podcast-Workshop anmelden: https://Podcastkurs.com +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++   So fing alles an. Hier geht´s zur allerersten Episode von TomsTalkTime.com – DER Erfolgspodcast. Und ja, der Qualitätsunterschied sollte zu hören sein. Aber hey, das war 2012…

Join host Geoffrey Rubin, MD, MBA, FACR, as he engages in an inspiring conversation with Matthew P. Lungren, MD, MPH, Chief Data Science Officer for Microsoft Health & Life Sciences. Dr. Lungren, an academic pediatric interventional radiologist with a strong interest in global healthcare, literature, and competitive swimming, discusses his transition from medicine to focusing on AI in healthcare. As the co-founder of the Stanford Center for AI in Medicine and Imaging, Dr. Lungren played a key role in establishing the center as a prime driver of innovation in the development and assessment of artificial intelligence and medical imaging in healthcare. Dr. Lungren grew up in Arizona, obtained his undergraduate degree in English and Biology from Arizona State University, and went on to earn his MPH from the University of North Carolina and his medical degree from the University of Michigan. He completed fellowships at both Cincinnati's Children's Hospital and Duke University. His defining moment came when he volunteered in Albania during a humanitarian crisis, which motivated him to pursue a career in medicine and become involved in global health initiatives and research, ultimately specializing in radiology. A talented and passionate educator, he has catalyzed the education of countless physicians, scientists, and laypeople, including being the top-rated instructor in the wildly successful Coursera course, Fundamentals in AI in Healthcare, completed by 25,000 students to date. Don't miss this special episode to learn more about Dr. Lungren's unique career journey and his definition of a perfect Saturday afternoon—hint: it would include the latest issue of Harper's Magazine, an Xbox, and a trip to the pool.

Listen on: Apple Podcasts Spotify Do you enjoy the podcast? Please leave a review!  Having trouble letting go? Deiadora Blanche (Airbnb, Coursera) can help.  In this episode, we dive deep into the idea of ego detachment — letting go of personal attachment to the work we do. Deiadora shares her journey from business consulting to content strategy, and how she's learned to balance personal growth with professional success.  We also chat about thinking like a CEO, even when you're not in leadership, and how content professionals can create their own success by setting metrics and driving results. Plus, Deiadora shares some incredible insights about AI content strategy — why we need to engage with it, not fear it. If you're curious about how to stay grounded in your work, navigate high-pressure environments, or just want to hear some practical advice on building a successful content strategy career, this episode is a must-listen. What we talked about: Deiadora's path from business consulting to content design Why detaching from your ego can make you a better content designer How to set metrics for your team and think like a CEO Using mindfulness to step back and make better decisions How content professionals can lead without a formal title Practical tips for using AI in content strategy Why letting go of attachment to outcomes helps you succeed Notable quotes: “Stop being so attached to the work—it's not about you. It's about what the user needs.” “When you step away and detach from the ego, you can make better decisions.” “Thinking like a CEO is essential, even when you're an individual contributor. Own the work, don't wait for direction.” Where to find Deiadora: Deadorable Life The Quantum CEO Podcast LinkedIn Listeners get 20% off podcasts and workshops at UX Content Collective! Just use PODCAST20 at checkout

It's not only ADHD Awareness Month, it is also Dyslexia Awareness Month! So today, let's revisit a conversation with Dr. Sally Shaywitz about overcoming dyslexia and addressing the reading crisis, which is still relevant and a huge concern. We are in the midst of a reading crisis in the United States. This problem has existed for a long time, but it was exacerbated by the COVID-19 pandemic. It has been said that the pandemic has caused the loss of 2 decades worth of progress made in reading. We have the knowledge, research, and science to address this issue, but we are lacking action. Today's guest is Dr. Sally Shaywitz, one of the world's preeminent experts on reading and dyslexia and author of Overcoming Dyslexia. Dyslexia is the most common learning disorder on the planet, affecting about one in five individuals, regardless of age or gender. In today's episode, Dr. Shaywitz shares what is known about dyslexia, the 40 years of data to show what works in overcoming dyslexia, and the sad reality that there is little action being taken to improve screening students and providing the appropriate interventions. There is so much we can do and it all starts with understanding.  Show Notes: [3:31] - Regardless of decades of research, there are still a lot of misconceptions. [4:44] - Dyslexia is a very specific learning disability, but the term “learning disability” is very vague. [6:21] - Through brain imaging, Dr. Shaywitz was able to determine the neuro signature of dyslexia. [8:21] - Educators, parents, and the individual with dyslexia need to know that they are intelligent and have the intelligence to read, but dyslexia makes it a struggle. [9:58] - Dyslexia is common in all areas of the world. The consequences are similar in all cultures. [11:06] - Those with dyslexia can be good readers while still reading slowly. [12:02] - The most important step is for the student to be identified as dyslexic. [13:34] - Through her studies, Dr. Shaywitz has nearly 40 years worth of data for both typical readers and dyslexic readers from childhood to adulthood. [14:50] - Indicators of dyslexia can be seen as early as first grade. Identifying those at risk for developing dyslexia and intervening early can accelerate reading growth. [16:06] - Screening can take place later, but by then, the window of time for the most reading growth has passed. [18:03] - Currently, we are scoring worse in previous years in identifying dyslexia in young students. [19:09] - Dr. Shaywitz describes the screener used to determine the risk of dyslexia. [21:08] - A universal screener is a solution to this reading crisis. [22:13] - Given that we know a great deal about dyslexia, it is disgraceful that more isn't being done to support students. [23:14] - ADHD and anxiety often co-occur with dyslexia. [24:36] - We often hyperfocus on the struggles, but what are the common strengths for those with dyslexia? [25:42] - School policies and teacher training surrounding dyslexia need to be changed. [26:46] - There is also research on individuals incarcerated who are also dyslexic. [28:06] - Dr. Shaywitz offers a course on Coursera that can be found here. [30:36] - We need screening, intervention, and education for parents, teachers, and students. About Our Guest: Sally E. Shaywitz, M.D. is the Audrey G. Ratner Professor in Learning Development at Yale University and Co-Founder and Co-Director of the Yale Center for Dyslexia & Creativity. She is a world renowned scientist and dedicated, compassionate physician who is devoted to bringing ground-breaking scientific advances to benefit dyslexic children and adults. Connect with Dr. Shaywitz: Overcoming Dyslexia by Sally Shaywitz, MD Overcoming Dyslexia Online Course with Sally Shaywitz, MD Links and Related Resources: What is Dyslexia? 6 Quick Questions for Parents Concerned About Dyslexia ChildNEXUS Dyslexia Mini Course for Parents Join our email list so that you can receive information about upcoming webinars - ChildNEXUS.com The Diverse Thinking Different Learning podcast is intended for informational purposes only and is not a substitute for medical or legal advice, diagnosis, or treatment. Additionally, the views and opinions expressed by the host and guests are not considered treatment and do not necessarily reflect those of ChildNEXUS, Inc or the host, Dr. Karen Wilson.  

This week's guest on The CMO Podcast is one of the foremost experts in the world of Artificial Intelligence and marketing, Professor Jim Lecinski. Jim is the Clinical Associate Professor of Marketing at Northwestern Kellogg. We use the term “Renaissance man or woman” too loosely these days, but in this case it's an appropriate moniker. Consider these highlights from Professor Lecinski's curriculum vitae:Studied German and Government at Notre Dame, MBA from Illinois.Teaches seminars and blogs about Jazz for newcomers.Has written for The Journal of the International Association of Jazz Record Collectors.Twelve years at Google, left as a VP.Literally wrote the book on marketing and AI, back in 2021 before it was the “in thing.”Awarded Professor of the Year at Northwestern Kellogg in 2022.It's a double-Jim conversation, as the two dive into the hottest topic in marketing...AI.---Learn more about AI:Marketing AI Institute: https://www.marketingaiinstitute.com/Andrew Ng's Courses on Coursera: https://www.coursera.org/instructor/andrewngKeynotes to Watch:Agentforce Keynote: Build the Future with AI Agents: https://www.salesforce.com/plus/experience/dreamforce_2024/series/agentforce_&_data_cloud_at_dreamforce_2024/episode/episode-s1e27Google Cloud CEO Thomas Kurian'a Keynote: https://cloud.withgoogle.com/nextAnd pickup Jim and Raj Venkatesan's book - The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing: https://a.co/d/9osop0BSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

We discussed a few things including:1. Jordan's career journey2.  Historical progress3. Latest AI developments4. How we can leverage AI5. Trends, challenges and opportunities re AIJordan is an AI strategist and founder and host of Everyday AI. Everyday AI is a fast-growing media company helping everyday professionals grow their companies and careers with Generative AI through its daily livestream, podcast and newsletter.Everyday AI is a Top 10 tech podcast on Spotify, and Jordan has taught prompt engineering basics to thousands of people, from entrepreneurs and small business owners to software engineers and Fortune 100 execs. He's been a featured keynote speaker on GenAI, as well as a Coursera instructor for GenAI.Previously, Jordan was an award-winning multimedia journalist and also worked with companies like Nike and Jordan Brand before starting his own Chicago-based digital strategy company called Accelerant Agency.#podcast #AFewThingsPodcast

Dr. Andrew Ng is a globally recognized AI leader, founder of DeepLearning.AI and Landing AI, General Partner at AI Fund, Chairman and Co-Founder of Coursera, and Adjunct Professor at Stanford University. Subscribe to the Gradient Flow Newsletter:  https://gradientflow.substack.com/Subscribe: Apple • Spotify • Overcast • Pocket Casts • AntennaPod • Podcast Addict • Amazon •  RSS.Detailed show notes - with links to many references - can be found on The Data Exchange web site.