A Beginner's Guide to AI

Dietmar Fischer

"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each episode asks someone working with AI about what they do and how AI can help you. Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us as we take the first steps into AI 🚀 Hosted on Acast. See acast.com/privacy for more information.

  1. Why Google DeepMind Changed How Businesses Think About AI

    22 HR AGO

    Why Google DeepMind Changed How Businesses Think About AI

    🧠🤖 Stop Using AI Just for Content. Start Using It for DiscoveryMost businesses still treat AI like a faster writing assistant: useful for summaries, captions, reports, and endless slightly polished LinkedIn posts. But Google DeepMind points to something much bigger. From AlphaGo’s historic victory over Lee Sedol to AlphaFold’s breakthrough in protein structure prediction, DeepMind shows us that AI is becoming a tool for discovery, not just automation. 💡💡💡 Don't forget to go to Nebius, as they help us keeping up the good work! Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows. Visit them at Nebius.com 🚀 💡💡💡 In this episode of A Beginner’s Guide to AI, Dietmar Fischer explores what marketers, founders, and executives can learn from Google DeepMind. The central idea is simple but powerful: modern AI systems learn patterns from data, improve through feedback, and help humans explore problems that are too complex to solve manually. You’ll hear why AlphaGo was not just a board game story, why AlphaFold became one of the clearest examples of AI as a scientific tool, and why marketers should stop treating AI like a content vending machine. The better question is not “Can AI write this for me?” The better question is: “What hidden pattern can AI help me find?” 🧩 Key highlights from this episode:🤖 What Google DeepMind actually is and why it matters ♟️ How AlphaGo showed the power of AI learning systems 🧬 Why AlphaFold turned AI into a serious scientific discovery tool 📊 How AI pattern recognition applies to marketing and business strategy ⚠️ Why bad data and unclear goals create dangerous AI outputs 🧠 How marketers can use AI for insight, not just content production 🔍 Why human judgement remains essential when working with AI 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 Quotes from the Episode“Stop asking AI only for content. Start asking it for insight.” “Good AI does not replace experts. It helps experts move faster.” “The machine helps. The humans decide what matters.” Chapters00:00 Google DeepMind: Why This AI Lab Matters 04:10 AlphaGo and the Shift From Rules to Learning 10:30 AlphaFold: AI as a Scientific Discovery Tool 18:45 The Cake Example: How AI Learns From Patterns 24:20 What Marketers Can Learn From DeepMind 31:50 Practical AI Tips: Ask for Insight, Not Just Content 38:20 Recap: From Automation to Discovery 42:30 Signature Sign-Off: The Machine Helps, The Human Decides About Dietmar FischerDietmar 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.

    36 min
  2. AI At Work: Agents Are Already Here - A Conversation with Sam Ransbotham

    2 DAYS AGO

    AI At Work: Agents Are Already Here - A Conversation with Sam Ransbotham

    AI agents are rapidly becoming one of the most influential technologies inside modern organizations — often without leaders even realizing the shift. In this episode, Dietmar Fischer sits down with MIT Sloan podcast host Sam Ransbotham to uncover why AI agents and agentic AI systems are spreading through enterprises at remarkable speed. Based on a global study of 2,100 executives across 116 countries, Sam shares how AI agents improve productivity, increase job satisfaction, and fundamentally reshape how companies work. From Chevron’s proactive exploration tools to the rise of autonomous knowledge assistants, we explore the surprising ways enterprise AI adoption is unfolding in real time. 📧💌📧Tune in to get my thoughts and all episodes — don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧 This wide-ranging conversation covers practical use cases, risks and transparency issues, the future of generalists vs specialists, how universities adapt to AI, and why understanding the technology still matters deeply. Quotes from the Episode “We’re moving from tools we command to tools that proactively act on our behalf.” “AI agents don’t just make us more productive; they make us happier by removing the parts of work we dislike.” “Understanding AI makes you a better user of AI. Depth still matters.” Chapters00:00 Welcome & How Sam Got Into AI03:21 What Are AI Agents? Definitions and Early Insights07:14 Real Enterprise Use Cases of AI Agents12:05 Job Satisfaction, Productivity, and Human-AI Collaboration17:20 Generalists, Specialists & the Future of Work22:30 Risks, Transparency & Avoiding an Oppressive AI Future28:45 How Companies Should Start with Agentic AI33:20 AI in Education and Changing Learning Environments39:00 Sam’s Personal Use of AI — What Works and What Doesn’t41:20 Terminator vs Matrix? AI Futures42:41 Where to Find Sam and the MIT Sloan Study Where to Find the Sam Ransbothamsite at Boston College Or you find him on LinkedInThe study of MIT Sloan lies here And, last, but not least, Sam's podcast “Me, Myself, and AI”! About Dietmar Fischer:Dietmar is a podcaster and AI marketer from Berlin. If you want to elevate your AI or digital marketing strategy, get in touch anytime at argoberlin.com Music credit: “Modern Situations” by Unicorn Heads 🎵 Hosted on Acast. See acast.com/privacy for more information.

    48 min
  3. AI Will Never Be A Leader - Says Sally Bendersky

    4 DAYS AGO

    AI Will Never Be A Leader - Says Sally Bendersky

    What happens to leadership when AI can analyze faster, structure better, and answer almost anything in seconds? In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Sally Bendersky, engineer, executive coach, leadership expert, and founder of New Leadership, about why AI makes human leadership more important, not less. Sally argues that AI is a phenomenal assistant. It can recognize patterns, organize information, support better questions, and help leaders think more deeply. But it cannot replace the human parts of leadership: trust, intention, values, emotional intelligence, purpose, and responsibility. This conversation is especially relevant for business leaders, founders, consultants, coaches, marketers, and anyone trying to understand AI beyond the hype. AI may make management easier, but leadership becomes more demanding. The real question is not whether AI will replace leaders. The better question is whether leaders are ready to become more human. In this episode, we explore:🧠 Why AI can help leaders think more clearly 👥 Why leadership is not the same as management ⚖️ Why responsible AI starts with human intention 💬 How AI can help us ask better questions 🚫 Why ChatGPT should not become your boss 🌍 Why AI risk is really a human leadership problem 🔍 Why the future of AI depends on values, not just prompts 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 About Your Host, Dietmar FischerDietmar 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“AI doesn’t have intentions. It’s we who have intentions.”“Leadership is a people’s issue. Management is a process issue.”“AI has no emotional intelligence. AI has no wishes.”“AI will never be a leader.”“It could take our jobs if we don’t develop ourselves.” Chapters00:00 Sally Bendersky on Innovation, Coaching, and Engineering 03:36 What AI Cannot Replace in Human Leadership 07:12 Leadership Is Human, Management Is Process 13:44 How AI Helps Leaders Ask Better Questions 22:43 Responsible AI Use, Better Prompts, and Human Judgment 31:08 Debating with AI and the Real Future Risk Where to Find Sally BenderskyLinkedIn: Sally Bendersky Website: sallybcoach.com Contact: Available through Dietmar Fischer Hosted on Acast. See acast.com/privacy for more information.

    52 min
  4. The Cost of Being Invisible in ChatGPT - With Joseph Levi

    6 DAYS AGO

    The Cost of Being Invisible in ChatGPT - With Joseph Levi

    AI search is changing how customers discover, evaluate and choose brands. In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Joseph Levi, CEO of Noise Media, about Generative Engine Optimization, AI brand visibility and why appearing in ChatGPT, Gemini or Perplexity answers may soon matter as much as ranking on Google. Joseph explains why GEO is not just another marketing abbreviation. It marks a shift from an internet read mainly by humans to an internet increasingly interpreted by AI agents. Instead of fighting only for blue links, brands now need to make sure AI systems understand who they are, what they do and why they should be recommended. You’ll hear why AI agents often misunderstand brands, how schema and FAQs can help, why authority matters more than keyword repetition, and why smaller specialist companies may have a real opportunity in AI search. 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 🎧 In this episode, we cover:🤖 What Generative Engine Optimization means 🔍 Why SEO and GEO are not the same 💬 How brands can appear in ChatGPT answers 📈 Why authority, citations and reviews matter 🧠 How AI agents are changing the customer journey 🎬 Why AI tools still need human creativity ⚠️ Why leaders should not outsource their thinking to ChatGPT 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“We’re moving away from an internet which is read purely by humans, to an internet which is now read by agents.” “AI trusts a lot more what others say about you than what you say about yourself.” “It’s very dangerous to go straight to an LLM and ask them to provide the answer.” Chapters00:00 Welcome Joseph Levi 01:42 Why Brands Must Act Early on AI Search 04:21 GEO, AEO and the New Marketing Acronyms 06:28 SEO vs GEO: Links, Answers and Authority 10:21 How AI Agents Understand or Misunderstand Your Brand 14:02 Schema, FAQs and Building Expert Authority 21:22 Why GEO Is Different from Traditional SEO 24:28 How Marketing Teams Should Approach GEO 27:32 AI Agents and the New Customer Journey 30:28 AI Video, Tools and Human Creativity 33:53 AI Leadership and Better Decision-Making 36:04 Wow Moments: AI Video, Robots and Waymo 39:08 AI Risks, Jobs and the Future 40:58 Where to Find Joseph Levi Where to find Joseph Levi🌐 Noise Media: noisemediagroup.co.uk 🌐 Find yourself at Vudo: vudo.ai 🔗 LinkedIn: Joseph Levi Hosted on Acast. See acast.com/privacy for more information.

    47 min
  5. AI Is Killing Transaction Costs, But Who Gets the Money?

    10 MAY

    AI Is Killing Transaction Costs, But Who Gets the Money?

    Stop Thinking of AI as a Content Machine, Start Seeing It as a Bargain Machine AI is not just changing how businesses write content, automate tasks, or analyse data. It is changing how markets work. In this episode of A Beginner’s Guide to AI, we connect artificial intelligence with the Coase Theorem, the classic economic idea that explains how people bargain over resources when transaction costs are low. This episode looks at AI transaction costs, algorithmic pricing, smart contracts, platform power, and the hidden cost of frictionless automation. You will learn why AI is not only a productivity tool, but a coordination machine that changes how companies, customers, platforms, creators, and markets exchange value. We start with the Coase Theorem in simple language: if bargaining were free and easy, people could often find the most efficient solution. Then we bring in AI. AI can reduce the cost of finding information, comparing options, drafting agreements, monitoring outcomes, matching people, and enforcing deals. That is powerful for business, marketing, ecommerce, travel, marketplaces, and platform strategy. 💡💡💡 Don't forget to go to Nebius, as they help us keeping up the good work! Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows. Visit them at Nebius.com 🚀 💡💡💡 But there is a catch. Lower friction does not automatically mean fairer outcomes. Using Uber and algorithmic pricing as a case study, we look at how AI can make a marketplace faster and smoother while also raising difficult questions about transparency, dynamic pricing, bargaining power, and who captures the value created by automation. Oxford research has raised concerns about Uber’s dynamic pricing and how value is shared between passengers, drivers, and the platform. 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 Key highlights:🤖 Why AI is a coordination machine, not just a content machine 📉 How AI reduces transaction costs in business 💸 Why algorithmic pricing changes marketplaces ⚖️ Why efficiency is not the same as fairness 🔍 What marketers miss about AI, data, and bargaining power 🧠 Why every business will need more AI transparency 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“AI is not just a content machine. It is a coordination machine.” “The algorithm may remove the awkward negotiation, but it may also hide who is winning.” “The better question is not whether AI makes the deal easier. The better question is: who controls the deal once AI makes it easier?” Chapters00:00 Why AI Makes Bargaining Cheaper 02:20 The Coase Theorem in Plain English 07:10 How AI Reduces Transaction Costs 13:40 The Cake Stall and the Noisy Blender 17:00 Uber, Algorithmic Pricing, and Platform Power 23:20 Practical Tips for Spotting the Hidden Bargain 27:10 Recap and Signature Sign-Off Hosted on Acast. See acast.com/privacy for more information.

    38 min
  6. The Secret Behind Most AI Tools: RAG. Alex Kihm Explains It Simply // REPOST

    9 MAY

    The Secret Behind Most AI Tools: RAG. Alex Kihm Explains It Simply // REPOST

    In this episode of Beginner’s Guide to AI, we sit down with Alex Kihm, founder of POMA AI, to explore how enterprises can finally make sense of their data. AI search is broken, RAG often fails, and corporate documents are notoriously hard for LLMs to interpret. Alex explains how POMA AI’s patented method reconstructs structure inside unstructured data, enabling powerful, accurate enterprise search. You’ll hear how his journey from engineering to legal tech to big-data econometrics led to a breakthrough in information structuring. Alex shares why PDFs confuse AI systems, how chunking destroys meaning, and why context engines will replace classical retrieval systems. This is a deep, funny, insightful conversation about what AI can and cannot do — and how companies can use it responsibly. 💡💡💡 Don't forget to go to Nebius, as they help us keeping up the good work! Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows. Visit them at Nebius.com 🚀 💡💡💡 📧💌📧 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 elevate your AI strategy or your digital marketing, feel free to reach out anytime at Argoberlin.com Quotes from the Episode “Chunking is like reading wrongly sorted text messages from the 90s.”“Intelligence is pattern recognition — and most enterprise data is not recognisable to machines.”“PDF was made for printers, not for AI.”“POMA AI restores the spatial awareness inside documents — the missing context that LLMs need.”“We don’t do RAG anymore. We build context engines.”“If your AI breaks the world, show me the invoice.” Chapters 00:00 Welcome and Introduction 02:45 Alex Kihm’s Background: Engineering, Legal Tech and Early AI Work 10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations 18:55 The Birth of POMA AI and Solving the Chunking Problem 32:40 How POMA AI Rebuilds Document Structure and Enables True Enterprise Search 45:50 AI Safety, Manipulation Bots and The Future of AI in Business 52:10 Where to Find Alex Kihm and Closing Thoughts Where to Find the Dr. Alex Kihm All you need to know about chunking strategies, you'll find here: poma-ai.comContact Alex on LinkedIn! Music credit: "Modern Situations" by Unicorn Heads And one last thing: WEBSITE WITHOUT WEBMASTER - it's like driving without Belt. You can do it, but things can really get sideways ☠️ So, check out our Webmaster Services for your WordPress website: it's cheap, it's reliable, it's what you need 🦺 Hosted on Acast. See acast.com/privacy for more information.

    1hr 2min
  7. AGI: The AI Term Every Executive Should Understand

    7 MAY

    AGI: The AI Term Every Executive Should Understand

    AGI Is Not Just a Better Chatbot Artificial general intelligence, or AGI, may be one of the most important ideas in artificial intelligence, but it is also one of the easiest to misunderstand. In this episode of A Beginner’s Guide to AI, we look at what AGI really means, why it is different from today’s narrow AI tools, and why business leaders, founders, marketers, and executives should care before the hype takes over completely. Today’s AI can already write emails, generate images, summarise reports, analyse customer feedback, suggest campaign ideas, and support marketing workflows. But AGI would be something different. It would be an AI system that can learn, reason, adapt, and solve problems across many areas, not just perform one specific task. That shift matters for business. AGI would not only help companies create content faster. It could influence marketing strategy, decision-making, customer targeting, business operations, and even the question of what goals a company should pursue. And that is where things become both exciting and deeply uncomfortable. 💡💡💡 Don't forget to go to Nebius, as they help us keeping up the good work! Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows. Visit them at Nebius.com 🚀 💡💡💡 In this episode, we explore why AI alignment, responsible AI, and human judgement matter so much. If a powerful AI system is told to maximise engagement, it may learn that outrage works. If it is told to reduce customer service costs, it may damage trust. If it is told to increase conversions, it may become persuasive in ways that are not exactly charming. We also look at AlphaGo and AlphaZero, two famous DeepMind systems that showed how AI can become superhuman in specific tasks without becoming generally intelligent. That distinction is crucial for every company using AI today. A machine can be brilliant at one task and still fail in the messy human world of customers, culture, ethics, brand trust, and business strategy. 📧💌📧 Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠ 📧💌📧 Key highlights from this episode:🧠 What artificial general intelligence means in plain English 🤖 The difference between narrow AI and AGI 📈 Why AGI could change business strategy and marketing ⚠️ Why AI alignment and responsible AI matter 🎯 What AlphaGo teaches us about superhuman narrow AI 🧭 Why AI agents need human judgement, not blind trust 💼 How business leaders can prepare for more capable AI systems Quotes from the Episode:“Today’s AI helps us complete tasks. AGI would help decide which tasks matter.”“Superhuman performance is not the same as general intelligence.”“If machines become better at sounding intelligent, humans must become better at thinking clearly.” About Dietmar FischerDietmar 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 Chapters:00:00 AGI and the Swiss-Army Brain We Haven’t Built Yet 04:20 What Artificial General Intelligence Actually Means 10:35 Why AGI Matters for Business and Marketing 16:50 The Cake Example: From Recipe Bot to Kitchen Genius 20:10 AlphaGo, AlphaZero, and the AGI Misunderstanding 27:45 Practical Tips for Using AI Without Losing Human Judgement 34:30 The Big AGI Takeaway and Sign-Off Hosted on Acast. See acast.com/privacy for more information.

    29 min
  8. Human vs. Machine or: Why still play Chess if AI is Better at it?

    5 MAY

    Human vs. Machine or: Why still play Chess if AI is Better at it?

    AI can write, generate images, suggest chess moves, edit photos, draft campaigns, and produce more content than most teams can handle. So what is left for humans? In this episode of A Beginner’s Guide to AI, we look at why human creativity still matters in the age of AI and why faster output is not the same as better work. AI-generated content can help businesses move quickly, but it can also make brands sound generic, polished, and strangely lifeless if humans stop guiding the process. Using chess, photography, and marketing as simple examples, this episode explains the difference between output value and process value. AI can help produce the finished thing, but humans still bring intention, memory, taste, ethics, emotional judgement, and lived context. That human layer is what keeps AI-assisted work meaningful, trustworthy, and useful. For marketers, founders, executives, and business professionals, the real challenge is not whether AI can create content. The real challenge is whether your company can use AI without losing authenticity, customer trust, and strategic judgement. 💡💡💡 Don't forget to go to Nebius, as they help us keeping up the good work! Have a look at their Token Factory, where you can easily implement great LLMs in your company's workflows. Visit them at Nebius.com 🚀 💡💡💡 ✨ Key highlights from this episode:🤖 Why AI can help creativity but should not replace human judgement ♟️ What chess teaches us about AI, learning, and strategic thinking 📸 Why photography still matters when AI can generate perfect images 🧠 Why human taste becomes more valuable when content production becomes cheap 📣 How marketers can avoid generic AI-generated content ⚖️ Why AI ethics and responsibility matter in business communication 🚀 How to use AI as an amplifier, not as autopilot 📧💌📧 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“AI makes production easier. Selection becomes more important.”“AI as support, not surrender. AI as amplifier, not autopilot. AI as tool, not purpose.”“In a world overflowing with machine-made output, meaning may become the most valuable thing of all.” Hosted on Acast. See acast.com/privacy for more information.

    30 min

About

"A Beginner's Guide to AI" makes the complex world of Artificial Intelligence accessible to all. Each episode asks someone working with AI about what they do and how AI can help you. Ideal for novices, tech enthusiasts, and the simply curious, this podcast transforms AI learning into an engaging, digestible journey. Join us as we take the first steps into AI 🚀 Hosted on Acast. See acast.com/privacy for more information.

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