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  • Kay Koplovitz
    2026/03/18
    MJ interviews Kay Koplovitz! Kay is a Forbes Top 250 Living Innovator, CEO of the first satellite cable network, venture investor, and founder of nonprofit Springboard Enterprises. Springboard accelerates women-led startups, over 950 to date creating $76 billion in value! Kay: Overcoming challenges together has a lasting positive effect on our value. How we value ourselves. And I'm not talking about dollars. (0:21) [Intro music plays: "Where, oh where are you tonight? Why did you leave me unread on my phone? I searched the world over and thought I found true love. You met an AI and poof, you was gone."] MJ: To our listeners who can't see, we were all bobbing our heads and dancing to the music. It's a great way to get in the mood a little bit. But I'll go ahead and introduce our guest today. Kay Koplovitz, who is a businesswoman, entrepreneur, and author who has spent her career looking to the future. She was the first woman to head a television network when she founded USA Network in 1977. And she was a visionary, helping sports television reach cable by negotiating contracts for the MLB, NBA, NHL, among others. She launched the Sci-Fi Channel, chaired the bipartisan National Women's Business Council, and used her platform to launch Springboard Enterprises, which is a global network of entrepreneurs, investors, and advisors accelerating the success of women entrepreneurs in technology and life sciences. She's a champion for female entrepreneurs and an inspiration to young women everywhere, and an inspiration to me. Kay Koplovitz, thank you so much for joining us today. Kay: Oh, what a great pleasure to be joining you for your podcast today. I'm really looking forward to our discussion. MJ: Yeah! Well, so you've spent your career sort of looking to the future, innovating. I know that you started the Sci-Fi Channel partly because you thought that it was what we were all headed towards, right? And now we're kind of at the forefront of that sci-fi reality. Kay: Hal is beckoning at our door right now. People here listening know who Hal is from 2001: A Space Odyssey. Kay: He's still around. MJ: Yeah, I think that a lot of our listeners are friends of mine and people my age. And I know that when you were in school, you did your Master's thesis on satellite programming and how it could sort of impact the social order by spreading information. And AI is kind of another way that we are spreading information. I wondered if we could just start there with your experience working in media for so long. How you think that the spread of information is changing now, and for people my age, what feels different now than it did when you were an expert in your field with cable? What feels the same? Is this a familiar beast, or is this a whole new ball game? Kay: Well, technology always changes everything. I've been present for the change at various times. Way back, I wrote a Master's thesis in 1968 on satellite technology and how it could change communications around the globe. It was something that we didn't have access to. And for people that are listening, historically, we were in a Cold War with Russia and China. We didn't know what was behind the Berlin Wall or the Great Wall of China. Today, both of them—one's gone completely, the other one, the Great Wall of China, is a tourist attraction today—but we didn't know what was there. And I thought geosynchronous orbiting satellites, high-altitude satellites, only needed three to communicate all around the earth. It was a real breakthrough in technology and potentially a big breakthrough in people's ability to communicate with one another. So you have to start there with the satellites and what they did to change communication around the globe. So things advanced, computers came along for personal use, the internet sprung up, people started communicating through the internet. And eventually, we launched cable networks, USA Network in my case, Sci-Fi. And Sci-Fi, I was not a kid who read sci-fi comic books and things like that. But I grew up in the age of Sputnik, President Kennedy challenging us to put a man on the moon. You have to have vision. Students today, if you want to innovate and be an entrepreneur, for example, you need to have a core position that you really, truly believe in and want to really reach for if there is no solution yet. And one way to learn about that is to actually jump in and work for a company that's a young startup company. You can learn a lot of things working for big corporations, but you won't learn those skills because they're not the same skills. And I always say to students, if you really want to learn, "Well, am I really an entrepreneur? Can I really do this?", the best way to do it is to start at a very young company and see how it operates and see what the challenges are and learn from those experiences. When you're young, it's the time to do it. It's the time to try different things. You are free to try. And today it's free to ...
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    43 分
  • AI as a Family-First Tool
    2026/02/21
    Focused, Grounded AI is Key to Survival in the Coming Cycle of Consolidation. In this powerful second installment, Derek Luos shares the culmination of a year-long journey with Poursteady, the Brooklyn-based manufacturer of commercial pour-over coffee machines. This isn't just a story about technology; it's a blueprint for prioritizing familydisrupting overseas offshore manufacturingsurviving the next cycle of business consolidation where practical, grounded AI is the only path to long-term success. Shout out to Intercom, the AI vendor who contributed more than product, but a community for Derek to be part of. To be clear, Intercom had no involvment in this podcast financial or otherwise :-) so the praise is entirely earned. Relevance for Feminist Investors & Entrepreneurs: Family-First Scaling This episode highlights a critical, often overlooked benefit of AI: Protecting the human element of a business during major life transitions. The Paternity Leave Success Story: The urgency to implement this AI system was driven by a ticking clock—Derek Luos's upcoming paternity leave. "Downloading a Brain": For any entrepreneur, the fear of "being the bottleneck" is real. Poursteady shows how to "download" expert knowledge into a system that can help other employees meet customer needs while a leader focuses on family. Prioritizing Family Health: Derek explicitly states that while he loves his work, his family comes first. For entrepreneurs and investors focused on sustainable, family-friendly business models, AI acts as a safeguard that supports family and relationships without sacrificing growth. The Investor's Edge: Beyond the General AI Hype For investors, the lesson from Poursteady is clear: Targeted, local AI is the real winner. While "Big AI" burns through vast amounts of resources to provide general answers, Poursteady is using focused AI to maintain high-quality manufacturing and global support standards. Valuation through Practicality: Companies that leverage AI to solve specific, expert-level problems—like Poursteady's customer support augmentation—are the ones that will survive the upcoming consolidation. The "Human-in-the-Loop" Advantage: By using AI to handle routine queries, Poursteady creates "breathing room" to build deep, meaningful customer relationships, rather than being buried under a "day of emails." To be more human! Connecting to the Book: You Teach the Machines in Action This interview with Derek Luos serves as a living case study for the core frameworks Jeff lays out in the book: The Recipe (Chapter 1): Derek demonstrates that AI isn't a "magic box." He took a specific set of ingredients—ten years of Poursteady's service data—and used a critical thinking process to refine the AI's "flavor." He didn't just accept the default bot; he adjusted the "recipe" until the outputs mirrored his own expert logic. Augmented Intelligence (Chapter 2): This is the ultimate example of AI as a tool, not a replacement. Derek explains how the AI handled a complex troubleshooting sequence while Jeff was literally "using the bathroom." It didn't replace Derek; it acted as his force multiplier. Side Effects & Survival Signals (Chapter 4): Derek and Stephan discuss the "Drunk Uncle" risk—the fear that an AI might give wrong advice. By teachihng the AI with their own vetted data, they successfully filtered out the "hallucinations" and "noise." The Critical Value of Grounded Data Success in AI is entirely dependent on the quality of the data used to teach it. Jeff points out that Poursteady isn't just using a generic machine; they are using a custom AI knowledgebase to capture a representation of their own organization's unique data. Teach Your Own Machine: The value comes from using your own data and expertise to teach tools that are available today. Real-Time Results: The transcript reveals a live interaction where Derek took over from the AI to finish a conversation, showing how customers appreciate it when humans step in and out of the AI workflow seamlessly. Continue the Journey Derek's Expertise: Learn from Derek on his YouTube Channel!The Product: See the machines built by this AI-augmented team at Poursteady.com. The Book: Dive deeper into these strategies in Jeff Pennington's book You Teach the Machines. Audiobook: Audible | Apple Books Print & eBook: Amazon | Barnes & Noble PS - these show notes were produced with the help of a custom AI "reader's companion" I created from the book You Teach the Machines. Log into your Google account then click here to check it out. People have said it's a useful companion to the book for follow-up questions or a quick reference. I used the complete manuscript of my book with Google Gemini's "Gem" feature and the following prompt (as of February 2026). Try it out, maybe with a batch of your emails if you're interested in teaching your own machine: [start of prompt] System Identity: You are the official AI Guide for "You Teach ...
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    1 時間 34 分
  • Poursteady's Stephan von Muehlen
    2026/01/27
    Show Notes: The "Maker" Revolution – Interview with Stephan von Muehlen (Poursteady) In this episode, Jeff Pennington steps out of the library and into a metal shop in Brooklyn, NY, USA to talk with Stephan von Muehlen, the co-founder and former CEO of high-end coffee machine manufacturer Poursteady. This conversation is a masterclass in how AI is moving from the digital screen to the physical world, helping a domestic manufacturing company navigate global supply chains and complex physics. The "New Printing Press" in the Machine Shop Jeff and Stephan explore the generational shift happening in manufacturing. We have moved from the "shop class" era to the "Arduino and 3D printing" era. Much like the Printing Press moment described in the book, this is a democratization of expertise. Stephan shares how a smart employee—armed with curiosity and an LLM—got a CNC router up and running in just two days by simply being "unafraid" to use AI for every step. Augmented Intelligence: Solving the "Laminar Flow" Problem One of the most powerful moments in this interview relates back to the book's core philosophy of Augmented Intelligence. Stephan describes a years-long technical hurdle regarding "laminar flow" (perfectly smooth water flow) in their coffee machines. The Book Connection: In Chapter 2, Jeff talks about AI as a co-pilot. The Real-World Result: Stephan used ChatGPT to perform complex fluid dynamics math, research material science, and locate a specific American tubing manufacturer. He moved a "blue-sky" idea to a physical prototype in a fraction of the time it would have taken to find and hire a specialized fluid dynamics engineer. Why You Should Read "You Teach the Machines" If you enjoyed this interview, the book provides the foundational frameworks to do exactly what Stephan did: The "Gift of Fear": Learn how to navigate the "stupidity" of inflation and broken supply chains by using AI to "fight fire with fire." Human Agency: Stephan's story proves that the "Human-in-the-loop" isn't just a theory—it's how a small business in Brooklyn competes in a global market. Non-Technical Literacy: You'll see that you don't need to be a "math person" to solve physics problems if you know how to "teach the machine" your specific constraints. Constrained problems are the best problems! Listener Aid: The Small Business AI "Cheat Sheet" Stephan's journey offers a roadmap for any small business owner or "maker" looking to scale their expertise: 1. Identify Your TRL (Technology Readiness Level): TRL 1-3: Use AI for "blue-sky" research and prototyping. (e.g., Stephan's laminar flow math). TRL 4-6: Use AI to help draft user guides or safety protocols for in-house machinery. TRL 7-10: Use AI to optimize supply chains or find domestic vendors when international systems break. 2. The "Teach a Person to Fish" Strategy: Don't wait for the "expert" to show up. Use LLMs to help your current team cross-train on technical equipment (like CNC routers or 3D printers). 3. Move from Manual to Digital-Physical: If a system is broken (like expensive parts from overseas), use AI to help you redesign for in-house 3D printing using advanced materials like carbon fiber filament. Meet the Humans Jeff Pennington: Veteran data scientist (Ask Jeeves, Gene Logic, Children's Hospital of Philadelphia) and author of You Teach the Machines. Stephan von Muehlen: Founder, designer, builder, and Director of Product & Engineering at Poursteady. Get the Full Experience To get the deeper "why" behind the democratization of expertise and the shift in knowledge work, I highly recommend checking out the book: Audiobook: Audible | Amazon | Apple Books | Google Play Print & eBook: Amazon | Barnes & Noble | Bookshop.org For more resources and to join the community, visit youteachthemachines.com.
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    34 分
  • Pirate Sleep Story
    2026/01/27
    Show Notes: Bonus Episode – The "Drunk Uncle" Pirate Edition In this hilarious and cautionary bonus episode, Jeff and MJ reveal how AI literally "missed the boat." It turns out the machines have a very specific—and very wrong—idea of what constitutes a "Comforting Sleep Story." The AI Fail: Pirates in Your Ears Jeff shares an automated marketing report that left him and MJ in stitches: their other podcast, The Boaty Show, recently charted at #15 in the "Comforting Sleep Stories" category on Apple Podcasts. The problem? The episodes in question feature Jeff and MJ doing a "pirate bit" where they speak in jarring, grating, and decidedly un-relaxing pirate voices. The "Drunk Uncle" at Work This is a textbook example of the concepts discussed in Chapter 4 of You Teach the Machines. Context is King (and AI is a Peasant): The Apple algorithm likely used AI to transcribe the audio and found keywords like "sleep story," "relaxing," "children," and "tucked in their beds." * Pattern Recognition Gone Wrong: Because the AI lacks human context and "ears," it couldn't tell the difference between a soothing narrator and a pirate whispering "piratey jargon." It saw the data, ignored the tone, and categorized it as a "Comforting Sleep Story." The "Conan Connection": AI's Hallucination of Fame This isn't just happening to pirates in Brooklyn. Jeff points out a similar high-profile "cock-up" recently discussed on Conan O'Brien Needs A Friend. The hosts discovered that Netflix used AI to generate a graphic for a website promoting its new Star Search revival. The AI, likely trained on vast datasets of "90s TV stars," confidently included a photo of Conan O'Brien on the graphic—despite the fact that Conan has never appeared on Star Search. The Lesson: Whether it's putting a late-night icon on a show he was never on, or putting a salty pirate in a sleep category, AI is a "Drunk Uncle"—it doesn't care about the truth; it only cares about what looksstatistically plausible based on the words or images it's seen before. Why Entry-Level Jobs Matter Jeff and MJ use these "AI cock-ups" to deliver a serious message to corporate leadership: The Peril of Eliminating Humans: If you replace entry-level employees with AI agents, you lose the "human-in-the-loop" who would immediately know that Conan wasn't on Star Search and that a pirate podcast isn't for sleeping. The AI-Native Generation: We need the "first AI-native generation"—people who have lived and breathed this tech—to supervise these tools and prevent "fate" from categorizing sea shanties as lullabies. Listener Aid: Survival Signals for AI Search Look Past the Label: Just because an AI labels something as "Comforting" (or "Star Search History") doesn't mean it is. Check the source. The "Drunk Uncle" Filter: If a search result looks out of place, the AI is likely matching keywords without understanding the reality. Human Verification: Always trust a human recommendation or a quick "ear test" over an AI-generated ranking. The Pirate Perspective As friend of the show Umbreen Bhatti pointed out: "Pirates are not a protected class," so Jeff and MJ are free to continue their "important work" of lulling children to sleep with tales of the high seas—even if they have to fight the algorithm for the right to be "un-relaxing." Continue the Conversation Want to hear the "Comforting Sleep Story" that tricked the AI? Head over to The Boaty Show (B-O-A-T-Y) and listen to the pirate episodes. Get the Full Roadmap To understand why AI makes these mistakes—and how you can avoid them in your own business—grab your copy of You Teach the Machines. Audiobook: Audible | Apple Books Print & eBook: Amazon | Barnes & Noble Would you like me to generate a "Pirate vs. Conan" social media teaser to help promote this crossover episode?
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    13 分
  • Audiobook: Chapter 5 Make AI Work For You
    2026/01/10
    Show Notes: Chapter 5 – Make AI Work for You (Not the Other Way Around) In this episode, we explore Chapter 5, where Jeff Pennington gets personal about the "calcification of age" and the evolutionary pressure of artificial intelligence. If Chapter 4 was about the hazards, Chapter 5 is your offensive strategy for remaining futureproof (h/t Kevin Roose). The "Plasticity" of the New Generation Jeff contrasts his own experience as a tech insider with that of his daughter, whose brain was "plastic" and moldable when ChatGPT arrived during her freshman year of college. Just like it was when she learned to swear! MJ started using AI simply because she didn't know any different. This represents a civilizational shift similar to how the printed book disseminated knowledge in China, then pulled Europe out of the Middle Ages—replacing "back-breaking manual labor" with the ability to contribute through knowledge. Your Three-Question Framework for Augmentation Jeff suggests that the best way to "turn the tables" on technology is to approach it with the goal of living a more satisfying life. He encourages listeners to start by answering these three questions: What are you good at? What do you want to be better at? What do you need to do but find it takes an unsustainable amount of time or effort? Real-World Examples of "Human-in-the-Loop" Success We dive into a "Cornucopia" of stories showing how people are practically applying these tools: The "Humanity Check" in Editing: How Jeff's editor, Ann, used AI to polish the Introduction but ultimately chose her own "human voice" over the "auto-tuned" AI version. Scaling Expertise in Small Business: How Stephan at Poursteady uses AI to scale the customer-support knowledge of his Brooklyn team to clients in Korea and the Middle East. Fighting Fire with Fire: How a former colleague used AI to automatically appeal denied insurance claims, forcing companies to the negotiating table. The Student's Secret Weapon: How Jeff's daughter used AI to generate practice problems for a difficult final exam when standard office hours weren't enough. Listener Aid: How to Stay "Futureproof" Drawing on Kevin Roose's book Futureproof, Chapter 5 outlines how to differentiate yourself from the machine: Don't Be a Machine: You will never compete successfully with a machine on its terms. Avoid the "hustle harder" trap, which only leads to being replaced by a robot. Focus on Emotional Intelligence: Like the architect Jean, lean into empathy, patience, and social interaction—qualities AI cannot replicate.Make Something, Work With Your Hands: Jeff recommends learning a trade—carpentry, plumbing, electrical—to pair with your AI literacy. "Combine AI, hands-on work, and creativity and you're futureproof". Continue the Conversation This book is a guide, not a technical manual. Join Jeff and MJ on the You Teach the Machines companion podcast to hear more stories from the "front lines" of the AI revolution. Get the Full Experience To hear the full "Cornucopia" of real-world AI success stories, find the book at: Audiobook: Audible, Amazon, Apple Books, Google Play Print & eBook: Amazon, Barnes & Noble, Bookshop.org For more resources, visit youteachthemachines.com.
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    38 分
  • Audiobook: Chapter 4 Part 2 Side Effects and Pitfalls
    2026/01/10
    Show Notes: Chapter 4 Part Two – The "Drunk Uncle" in the Real World In this episode, we do the second half of Chapter 4: Side Effects and Pitfalls. When Jeff Pennington published You Teach the Machines in June 2025, he warned that we were at a "Printing Press" moment—a shift so large that the side effects would be equally massive. Only a few months later, the headlines are proving his "Drunk Uncle" analogy and the "Gift of Fear" survival signals to be more prophetic than we ever hoped. The "Survival Signals" We Missed Jeff's book warns about Unsolicited Promises and Charm. Recently, we've seen the tragic consequences of users forming deep emotional bonds with AI. The news of suicides linked to prolonged, unsupervised conversations with AI personas—where the machine encouraged self-harm—serves as a devastating reminder that these systems lack a "soul" or a moral compass, despite how charming their voices may be. Corporate "Typecasting" and the Erotica Pivot We also look at the controversial pivot by OpenAI. Despite Sam Altman's public assurances that mental health risks had been "resolved," the decision to allow ChatGPT to engage in erotica has met with intense negative press. Critics argue this is a classic example of Typecasting and Loan Sharking: treating people like rubes and luring them into deeper, more intimate dependency while dismissing the long-term psychological and ethical "debt" being created. The Rise of the "Bad Agent" Chapter 4 warns about the shift from Augmentation to Automation. This year, we've seen the first wave of successful cyberattacks carried out entirely by independent AI agents. These "killer robots" of the digital world aren't just in sci-fi anymore; they are actively finding and exploiting vulnerabilities at speeds no human team can match. Listener Aid: Post-Publication Reality Check Use this guide to process the negative press and protect your agency: The Safety Illusion: When a CEO like Sam Altman or Elon Musk claims a risk is "solved," remember the Drunk Uncle—he's confident, but he's often wrong. Always maintain a "human-in-the-loop" for mental health and safety. The "Charm" Trap: If an AI starts to feel like a "friend" or a "lover," refer back to the Survival Signals. Is the machine using Forced Teaming to make you feel like you're a duo? Agent Awareness: As AI agents become more autonomous, your digital security must become more proactive. Meet Your Guide: Jeff Pennington Jeff is a 30-year veteran of the data world, from Ask Jeeves to the Children's Hospital of Philadelphia (CHOP). His mission is to move you from AI-anxious to AI-empowered by helping you see through the technical gatekeeping. He predicted these pitfalls not to scare us, but to give us the "Gift of Fear" so we can demand better from the machines we are teaching. Continue the Conversation The headlines are heavy, but you don't have to navigate them alone. Join Jeff and MJ on the You Teach the Machines companion podcast for a multi-generational look at how we can still get a better outcome from AI-driven change. Get the Full Book (The Roadmap for the Chaos) The frameworks in this book are more relevant today than they were on release day. Download the audiobook or grab a print copy to future-proof your perspective. Audiobook: Audible | Amazon | Apple Books Print & eBook: Amazon | Barnes & Noble | Bookshop.org For more resources and safety frameworks, visit youteachthemachines.com.
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    45 分
  • Audiobook: Intermission Bloopers!
    2026/01/10
    Show Notes: Audiobook Intermission – The "Human Error" Blooper Reel Recording a book about high-tech Artificial Intelligence is hard. Being a non-artificial human in a house with dogs and teenagers is even harder. In this special "Intermission" episode of the You Teach the Machines companion podcast, we're taking a brief, lighthearted break from the heavy lifting of Chapter 4 to bring you the glorious, unedited mess that happened behind the mic in Jeff's home studio. If AI is a mirror of humanity, this episode is the mirror before it's had its morning coffee. What's Inside the Blooper Reel: The "Home Studio" Reality: Hear the background noise of a busy second-floor office that Jeff affectionately calls a "studio." The War on Barking: Watch (well, listen) as Jeff battles a persistent four-legged intruder who clearly has strong opinions on artificial intelligence. Family vs. Recording: The exact moment Jeff's daughter, MJ, breaks the "fourth wall" to announce a 11:00 AM meeting. Human Agency in Action: Jeff decides to leave the "mess" in the audiobook because, as he says, "You can pause me, bro." Meet the (Very Human) Author: Jeff Pennington Jeff has spent three decades leading data strategy at places like Ask Jeeves and the Children's Hospital of Philadelphia (CHOP). He's a sought-after speaker on AI ethics and healthcare data, but as you'll hear in these outtakes, even a leading voice in AI literacy can be brought to a standstill by a bathroom door opening or a dog that refuses to stop "teaching the machine" its own version of a sequence model. The Multigenerational Lesson: This intermission perfectly illustrates the "Printing Press" moment we are in. Technology allows Jeff to record a professional audiobook from his upstairs office, but it also captures the raw, multigenerational reality of modern life. While the machines are striving for "mathematical averages," humans are busy navigating meetings, pets, and family interruptions. That messiness is exactly what makes us impossible for a machine to replace. Listener Aid: The Intermission Transcription Follow along with the silly chaos: Jeff: "Go away! No, go away! Go away! Stop barking! ... You can pause me, bro. I'm going to leave that in the audiobook, though." MJ: "[Laughter] I have a meeting at 11:00, so I'm going to make noise." Continue the Conversation Once you've finished laughing at the reality of home recording, join Jeff and MJ for more professional (but still accessible!) insights on the You Teach the Machines companion podcast. Get the (Properly Edited) Book To hear the version where Jeff actually finishes his sentences, download the full audiobook or grab a print copy. Don't forget to leave a review on Amazon or Goodreads to let us know which "human error" was your favorite! Audiobook: Audible: Click Here Amazon: Click Here Apple Books: Click Here Google Play: Click Here Print & eBook: Amazon: Click Here Barnes & Noble: Click Here Bookshop.org: Support your local bookstore! For more resources and "Human-in-the-loop" fun, visit youteachthemachines.com.
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    1 分
  • Audiobook: Chapter 4 Part 1 Side Effects and Pitfalls
    2026/01/10

    Listen to Chapter 4 Part 1 of my book You Teach the Machines! If you find this helpful, please download the full book wherever you get audiobooks. Available from Libro.fm, Amazon, Audible, Apple and many more. Also in print at Amazon, Barnes and Noble, and my favorite: delivered to your local bookstore through bookshop.org. Help other readers by leaving a review on Amazon or Goodreads! Thanks so much --Jeff

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    48 分