『You Teach The Machines』のカバーアート

You Teach The Machines

You Teach The Machines

著者: Jeff Pennington and MJ Pennington
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概要

Hot takes on living with AI from the first generation who has no choice: today's college students.2025 政治・政府 社会科学
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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
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