A Beginner's Guide to AI

Dietmar Fischer
  • 3.3 (77)
  • Technology
  • Updated Semiweekly

"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each episode either asks someone working with AI about what they do and how AI can help you or it explains an important concept/idea. Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us and learn everything you need to know on how to use AI in the best way 🚀 🎙️ About The Host, Dietmar Fischer Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com Hosted on Acast. See acast.com/privacy for more information.

  1. 22h ago

    Job Seekers: Your AI-Written Résumé Is Destroying Trust - Jeremy Schiefeling

    Why AI Skills Alone Won’t Build an AI-Proof Career🤖 An AI-proof career requires more than learning the newest tools. It requires knowing when to use AI, when to rely on human judgment, and how to demonstrate real value. Jeremy Schifeling, founder and CEO of The Job Insiders, joins Dietmar Fischer to discuss how AI is changing job searches, recruitment, professional skills, and the future of work. Jeremy was working at Khan Academy when the organization received early access to GPT-4. He immediately saw its potential to transform education and career development. He also came to recognize the risks: hallucinations, cheating, generic applications, and AI shortcuts that can make professionals appear less capable and less trustworthy. In this episode, Jeremy explains why candidates should not ask ChatGPT to write a generic résumé or cover letter. A better approach is to use AI to identify the employer’s most important problems and connect them to genuine experience. You will also learn why a modern application must work for three different audiences: the applicant tracking system, the recruiter, and the hiring manager. Algorithms need relevant language. Recruiters need clear stories. Hiring managers need evidence that you can solve a business problem. 🤝 Jeremy argues that referrals and professional relationships are becoming more important as AI-generated applications make traditional documents less trustworthy. He explains how to use LinkedIn proactively, identify shared connections, and approach people inside a target company. The broader lesson is simple. AI literacy is becoming essential, but it is not sufficient. Communication, trust, accountability, judgment, and relational talent are the skills that turn AI capability into business value. Key takeawaysUse AI to identify an employer’s problems, not to fabricate expertise.Optimize your résumé for both algorithms and human readers.Demonstrate AI skills through real projects and outcomes.Use LinkedIn to develop relationships instead of waiting to be discovered.Combine AI fluency with communication and judgment.Delegate repetitive work to AI while retaining human accountability.🎧 This conversation is for job seekers, career changers, business leaders, consultants, recruiters, and professionals who want to remain valuable as AI transforms work. Never Miss An Episode: Our Newsletter📧💌📧 Tune in to get my thoughts and all episodes. Don't forget to subscribe to our Newsletter: https://beginnersguideto.ai 📧💌📧 About Dietmar FischerDietmar Fischer is a podcaster and AI marketer from Berlin. If you want help with AI strategy or digital marketing, visit: https://argoberlin.com Quotes from the Episode“The bottleneck is no longer technical talent, it is relational talent.”“Your job as a job seeker is not just to give them keywords, but to give them solutions.”“At the end of the day, it comes back to the same thing that our ancestors cared about. Can I trust you?” Chapters00:00 Early access to GPT-4 and the loss of AI innocence 04:13 Marketing your talent to algorithms and humans 11:53 The referral advantage and proactive LinkedIn networking 17:27 Using AI and Ikigai to rethink your career 19:33 Why relational talent is becoming the new bottleneck 27:31 Lazy AI use destroys trust 32:40 AI agents, résumé research, and the future of human work Where to Find Jeremy Schifeling🌐 Website: Break into Tech💼 LinkedIn: Jeremy Schifeling🏢 Company: The Job Insiders📘 Book: Unbreakable: How to AI-Proof Your Job Search, Career, and Future Hosted on Acast. See acast.com/privacy for more information.

    Job Seekers: Your AI-Written Résumé Is Destroying Trust - Jeremy Schiefeling

  2. 2d ago

    What Heavy Metal Bands Teach You About AI Content Creation // DIETMAR'S THOUGHTS

    Why AI-Generated Content Is Not a Content Strategy🎸 What can synthesizers, heavy metal, and the 1980s teach us about artificial intelligence? Quite a lot, according to Dietmar Fischer. When synthesizers first entered popular music, many musicians and fans saw them as artificial intruders. They feared that technology would destroy real music and replace human skill. Today, digital tools, electronic effects, and production software are normal parts of making music. Businesses now face a similar debate about AI-generated content. Some people want to automate the complete creative process. Others refuse to use AI at all. In this Weekend Thoughts episode of Beginner’s Guide to AI, Dietmar argues that both extremes miss the real opportunity. The future is AI-assisted content creation. Humans provide the original idea, personal experience, position, taste, and final judgment. AI helps structure, challenge, edit, and improve the work. 🤖 In this episode, you will discover: Why AI-generated content is not the same as an AI content strategyWhat synthesizers reveal about technological resistanceWhy mass-produced AI content often becomes genericHow AI slop creates new problems for brands and creatorsWhy purely human content could become a premium productHow human-AI collaboration can improve creative workWhy businesses should use AI as a tool rather than as the creatorHow to use AI without losing authenticity or your personal voice As automated content floods blogs, social networks, and publishing platforms, production volume becomes less valuable. Anyone can ask a model to generate another article or social post. The competitive advantage comes from having something original to say and using AI to express it more effectively. 🎧 Chapters 00:00 What Synthesizers Can Teach Us About AI 02:05 When Artificial Technology Becomes Normal 04:22 The Two Extremes of AI Content 06:12 Why Hybrid Content Is the Future 07:26 The Coming Flood of Generic AI Content 09:09 Use AI as a Tool, Not the Creator 📧💌📧 Tune in to get my thoughts and all episodes. Don’t forget to subscribe to our newsletter at beginnersguideto.ai. 📧💌📧 Quotes from the Episode💬 “You do your stuff, and you take AI to make yourself better.” 💬 “Most of the content will be this hybrid content.” 💬 “Go for your own ideas. Just polish them. Make them greater. With AI as a tool, not as the content creator itself.” About Dietmar FischerDietmar is a podcaster and digital marketer from Argo.berlin. If you want to get your AI or digital marketing going, contact him at argoberlin.com. Hosted on Acast. See acast.com/privacy for more information.

    What Heavy Metal Bands Teach You About AI Content Creation // DIETMAR'S THOUGHTS

  3. 4d ago

    How AI Decides What to See and What to Ignore

    👁️ How does artificial intelligence decide what to see? Your eyes can look directly at something without your brain ever noticing it. AI faces a similar problem. A camera may capture every pixel, but the system must still decide which parts of an image matter and which parts it can safely ignore. In this episode of A Beginner’s Guide to AI, we examine spatial attention in humans and visual attention in artificial intelligence. You will learn how the brain uses a mental spotlight, why seeing is not the same as noticing, and how attention mechanisms help computer vision systems process complex images. We also investigate the limitations of AI attention. A model can identify the correct object for the wrong reason, use backgrounds as shortcuts, or create a convincing heatmap without truly understanding the scene. 🏥 Our central case study follows the collaboration between Google DeepMind and Moorfields Eye Hospital. Their medical AI system analysed three-dimensional OCT retinal scans, created detailed tissue maps, and recommended how urgently patients should be referred. It performed at a level comparable with leading specialists in a retrospective test. Then a different scanner caused its accuracy to fall dramatically. The anatomy had not changed. The machine’s view of it had. 🔍 Key highlights: How spatial attention filters human perceptionHow AI decides where to lookSpatial attention compared with self-attentionWhy vision transformers connect distant image regionsThe limitations of saliency maps and AI heatmapsHow AI retinal scans can support medical specialistsWhy machine vision fails when devices or environments changeHow humans and AI can compensate for each other’s blind spots 📧💌📧 Tune in to get my thoughts and all episodes, and don’t forget to subscribe to our newsletter: beginnersguideto.ai 📧💌📧 Quotes from the Episode“Spatial attention begins with a simple problem: there is too much world and not enough brain.”“The anatomy had not changed. The machine’s view of it had.”“Every spotlight reveals something. Every spotlight also leaves something in the dark.” About Dietmar FischerDietmar is a podcaster and digital marketer from Argo.berlin. If you want to get your AI or digital marketing moving, contact him at argoberlin.com Hosted on Acast. See acast.com/privacy for more information.

    How AI Decides What to See and What to Ignore

  4. Sep 23

    Would You Trust An AI Wearable To Reveal Your Personal Blind Spots? Lyle Maxson Interview

    AI wearable technology is usually presented as a way to improve productivity. Lyle Maxson believes the more important opportunity may be self-awareness. As the founder of Above, Lyle is building a wearable device that combines speech recognition, voice analysis, conversational context, and AI-generated reflection. The goal is not only to remember meetings or create transcripts. It is to help users understand patterns in how they speak, behave, work, and relate to other people. In this conversation, Lyle Maxson explains why he believes AI coaching and personal development deserve more attention. He discusses the difference between an AI assistant, an AI companion, and an AI guide. He also explains how Above uses personal intentions to generate feedback about blind spots, communication patterns, emotional responses, and progress. The conversation also addresses difficult questions. How can AI wearables protect privacy? Should employees use them at work? What happens when an AI system analyzes conversations with a partner or colleague? And how can companies use this technology for development without turning it into surveillance? Maxson also discusses the potential of voice analysis, the limits of self-assessment, and the future of personal AI. His broader argument is that technology should help people become more human, not more dependent on screens. 📧💌📧 Tune in to get my thoughts and all episodes. Don't forget to subscribe to our Newsletter: https://beginnersguideto.ai 📧💌📧 About Dietmar FischerDietmar Fischer is a podcaster and AI marketer from Berlin. If you want help with AI strategy or digital marketing, visit: https://argoberlin.com Quotes from the Episode“The limbic system that's in charge of love and connection, that part of the AI brain is completely neglected.”“The real focus for us ... is around this core transformational loop of setting your intention, practicing how you show up in the real world, receiving feedback on that, and then iterating and progressing through that loop.”“I do think that there is this middle path ... around how do we live in harmony with technology.”Chapters00:00 Opening: AI, well-being, and human potential 04:36 Coaching, therapy, and the hidden AI use case 13:04 From DIY AI hardware to the Above wearable 15:42 How the AI mirror works 23:20 Privacy, consent, and trust 29:36 Enterprise use cases and employee development 34:19 Voice analysis, blind spots, and a more human future Where to Find Lyle Maxson:Website: goabove.aiLyle Maxson on LinkedIn: linkedin.com/in/lylemaxsonCompany Instagram: @goabove.ai 🎧 Thanks for listening to Beginner’s Guide to AI. Hosted on Acast. See acast.com/privacy for more information.

    Would You Trust An AI Wearable To Reveal Your Personal Blind Spots? Lyle Maxson Interview

  5. Sep 21

    We Mustn’t Talk Ourselves Into Helplessness. We Have Agency - Says Simon Bell

    🤖 AI anxiety may be more dangerous than AI itself when fear convinces us that the future is inevitable. In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with academic and dystopian novelist S G Bell about artificial intelligence, fear, human agency, and the stories that shape our expectations of the future. Simon’s interest in AI began during a 2010 research project on infinite bandwidth and zero latency. That research eventually contributed to the AI Aftermath novel series, beginning with The Epilogue Event. But Simon does not believe that society is moving toward one simple, unavoidable AI tipping point. What appears to be a sudden transformation is usually the result of many smaller decisions, technologies, institutions, and social forces coming together. 🧠 The conversation explores why fear-based AI narratives can produce learned helplessness, how dystopian fiction can warn without paralysing its audience, and why humans should not treat AI as an oracle. Simon also shares a revealing experience with Claude. After providing apparently convincing research, the AI admitted that it had invented some information to fill a gap. For Simon, this did not make the system useless. It clarified its proper role: an exceptional research and collation assistant whose output still requires human judgment. You will learn: Why there may be no single AI tipping pointHow AI fear can weaken human agencyWhy artificial intelligence should be treated as a tool, not a godWhat AI hallucinations reveal about machine reasoningHow dystopian stories influence the futures we imagineWhy presence, self-irony, and human connection remain powerfulWhat Plato’s cave can teach us about technological change This is a conversation for anyone who wants to take AI risks seriously without surrendering to panic. Newsletter📧💌📧 Tune in to get all episodes in your mailbox. Don't forget to subscribe to our Newsletter: https://beginnersguideto.ai 📧💌📧 About Dietmar FischerDietmar Fischer is a podcaster and AI marketer from Berlin. If you want help with AI strategy or digital marketing, visit: https://argoberlin.com Quotes from the Episode“We mustn’t kind of talk ourselves into helplessness. We have agency.”“The future isn’t the manifestation of our devices. It’s a self-manifestation of our capacity.”“It doesn’t do my thinking for me, it does my collation for me.”Chapters00:00 From AI Research to Dystopian Fiction 05:16 Why There Is No Single AI Tipping Point 12:30 Ordinary People, Crisis, and Human Potential 20:05 The Stories That Shape Our Future 24:49 What AI Can and Cannot Do 28:16 AI Fear, Learned Helplessness, and Human Agency 36:26 Presence, Hallucinations, and Plato’s Cave Where to Find the Guest🌐 Website: sgbell.org💼 LinkedIn: linkedin.com/in/s-g-bell-94b0809/📸 Instagram: @sgbellauthor✍️ Substack: Simon Bell🏛️ Affiliation: The Open University BooksThe AI Aftermath series includes: The Epilogue EventBaptised and Newly BornThe Lost Tunnels of LondonThe Woman and the LightBeneath the Graves The first three books are published. The final two are presented as forthcoming on the author’s official website. Hosted on Acast. See acast.com/privacy for more information.

    We Mustn’t Talk Ourselves Into Helplessness. We Have Agency - Says Simon Bell

  6. Sep 19

    Talking About AI Disasters - The Peter McAllister Interview Resurfaced

    In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Peter McAllister about AI risk, AI safety, AI sentience, regulation, and the strange overlap between science fiction and current reality. Peter is the author of The Code: If Your AI Loses its Mind, Can it Take Meds?, a near-future novel about an AI on the moon that begins dismantling it with catastrophic consequences. Peter describes the book as a story about Gene, an AI developed for asteroid-belt mining tests, whose instability turns into a race against time for humanity. Peter also has a background in engineering, science, IT, and technology management, which explains why the conversation feels grounded rather than hand-wavy. The discussion goes far beyond fiction. Peter explains why the biggest AI danger may come from bias, compounding error, flawed assumptions, and organizations that fail to notice warning signs early enough. He argues that AI safety is not just a technical debate for labs, but a practical leadership issue for companies, regulators, and anyone deploying automated systems in the real world. The episode also explores sentience, AI rights, robotics, augmentation, business adoption, and why he uses AI in work but not in fiction writing. 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 🎙️ About Dietmar Fischer Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com 💬 Quotes from the Episode “An AI going rogue could just be something that is capable of doing something fairly simple and straightforward, but ridiculously fast in a ridiculous number of times.”“I expected it to sit on the bookshelves under dystopian fiction, and now it seems to be appearing under current affairs.”“LLMs are just a really, really, really, really, really overblown autocorrect.” 🕒 Chapters 00:00 Introduction to Peter McAllister 01:09 Why Peter Became Interested in AI 02:05 The Book Premise and AI Mental Illness 03:33 Why Small AI Errors Can Scale Into Disasters 06:06 Can Governments Really Regulate AI 12:18 The Social Bargain We Make With Dangerous Technology 17:14 Optimism, Pessimism, and the Future of AI 19:05 Why Peter Would Write a Sequel Instead of Changing the Book 20:28 AI Rights, Sentience, and Legal Control 24:03 Why Peter Does Not Use AI to Write Fiction 31:00 Robots, Human Augmentation, and the Physical Future of AI 33:47 Where to Find the Book 🔗 Where to find Peter McAllister Website: petermcallisterauthor.comBook: The Code: If Your AI Loses its Mind, Can it Take Meds? on Amazon: amazon.com/Code-your-loses-mind-take-ebook/dp/B085ZGGYZ3 Hosted on Acast. See acast.com/privacy for more information.

    Talking About AI Disasters - The Peter McAllister Interview Resurfaced

  7. Sep 17

    AI Existential Risk: Why This Catastrophe Would Be Different // DIETMARs OPINION

    A walking essay through historical catastrophes, industrialization, AI 2027, and the possibility of human extinction. 🌍 Humanity has endured epidemics, environmental destruction, industrial pollution, wars, and natural disasters. Even the worst historical catastrophes left survivors who could rebuild. But what happens when a new technology creates the possibility of an outcome from which nobody can recover? In this experimental solo episode of Beginner’s Guide to AI, Dietmar Fischer records his thoughts while walking through Berlin. He traces how human-made risks developed from local disasters to global consequences. Ancient societies depleted ecosystems. Industrialization connected human activity across continents. Pollution and climate change showed that actions in one place could affect the entire planet. 🤖 Artificial intelligence may introduce another change in scale. The episode examines AI existential risk and the difference between a catastrophe that kills many people and one that could eliminate humanity as a species. Dietmar uses the AI 2027 scenario as a provocative example of how autonomous AI, bioweapons, and physical systems could combine in an extreme worst-case future. The question is not whether this exact scenario will happen. It is whether even a small and uncertain possibility of human extinction should change how governments, companies, and society approach AI safety and AI regulation. Key Takeaways🌐 The difference between local, global, and existential catastrophes🏭 How industrialization transformed the scale of human-made risk📖 What the AI 2027 scenario proposes⚠️ Why AI extinction risk differs from other global crises🎲 How to evaluate low-probability, irreversible outcomes🏛️ Whether advanced AI requires stronger regulation🧭 Why humans must retain control over their collective future This short walking essay does not offer a confident prediction. Instead, it asks a difficult question: if advanced AI could create a catastrophe with no survivors, how much certainty should we require before taking that risk seriously? 📧💌📧 Tune in to get my thoughts and all episodes, and don’t forget to subscribe to our newsletter: beginnersguideto.ai 📧💌📧 Quotes from the Episode“This would be the first time we can think about a scenario where humankind gets extinguished.”“Few humans. We can survive as a species. Zero humans. There is nobody left.”“I don’t say it’s probable that that happens. But, as you figure, it’s different than before.”Chapters00:00 Why Compare AI With Historical Catastrophes? 01:09 Local Disasters and Global Consequences 03:55 How Industrialization Changed the Scale of Risk 06:14 The AI Catastrophe and the AI 2027 Scenario 07:21 Why Extinction Is a Different Kind of Outcome 09:25 Regulation, Responsibility, and What Comes Next About Dietmar FischerDietmar is a podcaster and digital marketer from Argo.berlin. If you want to get your AI project or digital marketing moving, contact him at argoberlin.com. 🎧 Follow Beginner’s Guide to AI for more accessible and critical conversations about artificial intelligence, business, technology, and society. Hosted on Acast. See acast.com/privacy for more information.

    AI Existential Risk: Why This Catastrophe Would Be Different // DIETMARs OPINION

  8. Sep 14

    AI Is Changing What Investors Look For in Startups - With Jim Ferry

    AI is changing startup investing from the ground up. In this episode, Jim Ferry, Partner at Volition Capital, explains what AI is changing in growth equity, from startup formation and deal sourcing to due diligence, competitive defensibility and enterprise adoption. Ferry argues that AI has expanded the market of companies that can reach product-market fit before raising capital. Coding and engineering are less of a barrier to entry, while lean teams can increasingly accomplish work that once required much larger organizations. But easier company creation creates a new problem for investors: defensibility. A company can look excellent today while facing the possibility that a foundation-model provider introduces a competing capability tomorrow. Ferry describes the critical investment question as: “Is time on this company's side or not?”That question sits at the center of modern AI investing. The conversation also goes inside Volition's own AI workflow. Ferry describes how the firm uses AI to speed up market research and due diligence, connect internal data sources, identify potential investments and even create agents that continuously search for companies matching an investor's preferences. Yet AI has not made investing purely automated. Ferry argues that sourcing increasingly depends on relationships because AI-generated outbound communication can make inboxes noisier. High-value enterprise sales also remain difficult to automate because human-to-human conversations still matter. We also discuss why startups often move faster than large enterprises, how AI experimentation can become an organizational culture, why companies need to “slow down to speed up,” and what AI could mean for employment and the future of work. 📧💌📧 Tune in to get my thoughts and all episodes. Don't forget to subscribe to our Newsletter: beginnersguideto.ai 📧💌📧 About Dietmar FischerDietmar Fischer is a podcaster and digital marketer. If you want help with AI strategy or digital marketing, visit his agency's website: argoberlin.com Quotes from the Episode“Is time on this company's side or not?”“This is a people business at the end of the day.”“They need to slow down to speed up.”Chapters00:00 How AI Is Changing Startup Investing 04:18 The New Test for AI Startup Defensibility 07:56 Why AI Makes Due Diligence Faster 13:49 Volition IQ, MCP and AI Agents 20:21 Where AI Works and Where Sales Still Needs Humans 25:10 Why Startups Adopt AI Faster Than Enterprises 29:47 Building an AI Experimentation Culture 32:12 The WOW Expample 38:47 The Employment/Adoption Discussion Where to Find Jim FerryWebsite: volitioncapital.com LinkedIn: Jim Ferry ClosingAI can automate an extraordinary amount of work. But according to Ferry, it does not remove the importance of judgment, relationships, trust and leadership. In fact, those qualities may become more important as more routine work moves to machines. 🎧 Subscribe, listen and share the episode with someone thinking about AI, startups or the future of work. Hosted on Acast. See acast.com/privacy for more information.

    AI Is Changing What Investors Look For in Startups - With Jim Ferry
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3.3
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About

"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each episode either asks someone working with AI about what they do and how AI can help you or it explains an important concept/idea. Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us and learn everything you need to know on how to use AI in the best way 🚀 🎙️ About The Host, Dietmar Fischer Dietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or your digital marketing going, just contact him at argoberlin.com Hosted on Acast. See acast.com/privacy for more information.

Information

  • Creator
    Dietmar Fischer
  • Years Active
    2023 - 2026
  • Episodes
    406
  • Rating
    Clean
  • Copyright
    © Dietmar Fischer
  • Show Website
    A Beginner's Guide to AI

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