A Beginner's Guide to AI

What can a silent film from 1927 teach us about artificial intelligence, deepfakes, and the future of business trust? In this episode of A Beginner’s Guide to AI, we look at Fritz Lang’s legendary film Metropolis and use it as a surprisingly sharp lens for understanding modern AI. The robot Maria is not dangerous because she is made of metal. She is dangerous because she borrows a trusted human face.And that is exactly why today’s AI-generated voices, synthetic avatars, and deepfake videos matter.This episode explores how AI can imitate human communication, why that creates new risks for businesses, and why the real question is not whether machines will become human. The better question is who controls the machine, what it is being used for, and whether people can still verify what is real.We connect Metropolis to modern deepfake scams, including the real Arup case in Hong Kong, where a finance employee was tricked into transferring around 25 million dollars after joining what appeared to be a video meeting with senior colleagues. It is the fake Maria problem in business clothing.💡💡💡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 🚀💡💡💡You will learn:🤖 Why Metropolis is still relevant for AI ethics🎭 Why deepfakes are not only a technology problem, but a trust problem🏢 How AI impersonation can become a real business risk📢 Why marketers must not use AI to counterfeit authenticity🔍 How to use the “Fake Maria Test” to verify what looks and sounds real🧠 Why AI literacy means keeping your judgement awakeThe big lesson: AI can help us think, create, and work better. But it becomes dangerous when it is used to make people easier to manipulate.📧💌📧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.comQuotes from the Episode“AI does not need to be conscious to manipulate us. It only needs to be convincing.”“The danger is not just fake content, but fake trust.”“Use AI to support trust, not counterfeit it.”Chapters00:00 Why Metropolis Still Matters for AI08:30 The Robot Maria and the Human Mask Problem16:45 AI, Trust, Deepfakes, and Business Risk24:30 The Cake Example: When the Fake Baker Sells the Cake29:00 The Arup Deepfake Scam Case Study38:30 Practical Tips: The Fake Maria Test45:00 Recap: Use AI, But Keep Your Judgement Awake49:00 Final Thought and Sign-Off

Humayun Sheikh on the Agentic Web, Trust, and the Agentic EconomyHumayun Sheikh joins Dietmar Fischer to explain what happens when AI stops recommending and starts doing. We explore the Agentic Web, a new layer where personal AI agents and verified brand agents collaborate to complete tasks like booking travel, coordinating meetings, and shopping with trust built in.You will learn what makes a real AI agent, why autonomy matters, and how multi-agent systems unlock an agentic economy. We also tackle the marketer’s question: what happens to SEO when the buyer becomes an assistant agent choosing on your behalf? Humayun breaks down how identity, verification, and trusted lists can reduce scams and make agentic commerce safe and usable.📧💌📧Tune in to get my thoughts and all episodes, don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧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.comChapters00:00 Welcome and Humayun’s journey from gaming to DeepMind03:01 What is an AI agent: autonomy and decision-making08:20 The Agentic Web: discoverability, connectivity, trust and commerce rails23:47 Personal agents in practice: preferences, handles and onboarding in minutes29:53 Verified brand agents and trust: domains, identity and safe agentic buying48:12 Risks, AGI fears, corporations vs countries and what comes nextQuotes from the Episode“There has to be a hint of autonomy within an agent.”“We have provided the rails of discoverability, connectivity, communication, trust. And commerce.”“Your aggregator is your own agent. It holds your preferences. It doesn’t pass it to anybody.”“Anybody who has a website should have an agent, or will have an agent.”“I was the first investor in DeepMind.”“We will not have countries, we will have corporations.”Where to find Humayun SheikhFetch.ai - your personal AIASI1.ai - the LLMFollow Humayun on LinkedIn!Music credit: "Modern Situations" by Unicorn Heads

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 StudyWhere to Find the Sam Ransbothamsite at Boston CollegeOr you find him on LinkedInThe study of MIT Sloan lies hereAnd, 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.comMusic credit: “Modern Situations” by Unicorn Heads 🎵

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.comQuotes 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 Engineering03:36 What AI Cannot Replace in Human Leadership07:12 Leadership Is Human, Management Is Process13:44 How AI Helps Leaders Ask Better Questions22:43 Responsible AI Use, Better Prompts, and Human Judgment31:08 Debating with AI and the Real Future RiskWhere to Find Sally BenderskyLinkedIn: Sally BenderskyWebsite: sallybcoach.comContact: Available through Dietmar Fischer

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 ChatGPTAbout 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.comQuotes 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 Levi01:42 Why Brands Must Act Early on AI Search04:21 GEO, AEO and the New Marketing Acronyms06:28 SEO vs GEO: Links, Answers and Authority10:21 How AI Agents Understand or Misunderstand Your Brand14:02 Schema, FAQs and Building Expert Authority21:22 Why GEO Is Different from Traditional SEO24:28 How Marketing Teams Should Approach GEO27:32 AI Agents and the New Customer Journey30:28 AI Video, Tools and Human Creativity33:53 AI Leadership and Better Decision-Making36:04 Wow Moments: AI Video, Robots and Waymo39:08 AI Risks, Jobs and the Future40:58 Where to Find Joseph LeviWhere to find Joseph Levi🌐 Noise Media: noisemediagroup.co.uk🌐 Find yourself at Vudo: vudo.ai🔗 LinkedIn: Joseph Levi

Stop Thinking of AI as a Content Machine, Start Seeing It as a Bargain MachineAI 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 transparencyAbout 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.comQuotes 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 Cheaper02:20 The Coase Theorem in Plain English07:10 How AI Reduces Transaction Costs13:40 The Cake Stall and the Noisy Blender17:00 Uber, Algorithmic Pricing, and Platform Power23:20 Practical Tips for Spotting the Hidden Bargain27:10 Recap and Signature Sign-Off

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 FischerDietmar 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.comQuotes 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.”Chapters00:00 Welcome and Introduction02:45 Alex Kihm’s Background: Engineering, Legal Tech and Early AI Work10:32 The Problem with RAG, Training, Fine-Tuning and Hallucinations18:55 The Birth of POMA AI and Solving the Chunking Problem32:40 How POMA AI Rebuilds Document Structure and Enables True Enterprise Search45:50 AI Safety, Manipulation Bots and The Future of AI in Business52:10 Where to Find Alex Kihm and Closing ThoughtsWhere to Find the Dr. Alex KihmAll you need to know about chunking strategies, you'll find here: poma-ai.comContact Alex on LinkedIn! Music credit: "Modern Situations" by Unicorn HeadsAnd 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 🦺

AGI Is Not Just a Better ChatbotArtificial 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 systemsQuotes 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.comChapters:00:00 AGI and the Swiss-Army Brain We Haven’t Built Yet04:20 What Artificial General Intelligence Actually Means10:35 Why AGI Matters for Business and Marketing16:50 The Cake Example: From Recipe Bot to Kitchen Genius20:10 AlphaGo, AlphaZero, and the AGI Misunderstanding27:45 Practical Tips for Using AI Without Losing Human Judgement34:30 The Big AGI Takeaway and Sign-Off