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    Technology

    A Beginner’s Guide to AI

    “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.

    Advertise

    Copyright: © Dietmar Fischer

    • Apple Podcasts
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    Latest Episodes:
    Why Every Business Will Need An AI Agent - Inside the Agentic Economy with Humayun Sheikh // REPOST May 19, 2026
    Show notes

    Humayun Sheikh on the Agentic Web, Trust, and the Agentic Economy


    Humayun 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 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



    Chapters

    00:00 Welcome and Humayun’s journey from gaming to DeepMind

    03:01 What is an AI agent: autonomy and decision-making

    08:20 The Agentic Web: discoverability, connectivity, trust and commerce rails

    23:47 Personal agents in practice: preferences, handles and onboarding in minutes

    29:53 Verified brand agents and trust: domains, identity and safe agentic buying

    48:12 Risks, AGI fears, corporations vs countries and what comes next




    Quotes 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 Sheikh

    • Fetch.ai - your personal AI
    • ASI1.ai - the LLM
    • Follow Humayun on LinkedIn!




    Music credit: "Modern Situations" by Unicorn Heads

    Hosted on Acast. See acast.com/privacy for more information.


    Why Google DeepMind Changed How Businesses Think About AI May 17, 2026
    Show notes

    🧠🤖 Stop Using AI Just for Content. Start Using It for Discovery

    Most 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 🚀

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    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.”




    Chapters

    00:00 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 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.


    AI At Work: Agents Are Already Here - A Conversation with Sam Ransbotham // REPOST May 15, 2026
    Show notes

    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.”


    Chapters
    00:00 Welcome & How Sam Got Into AI
    03:21 What Are AI Agents? Definitions and Early Insights
    07:14 Real Enterprise Use Cases of AI Agents
    12:05 Job Satisfaction, Productivity, and Human-AI Collaboration
    17:20 Generalists, Specialists & the Future of Work
    22:30 Risks, Transparency & Avoiding an Oppressive AI Future
    28:45 How Companies Should Start with Agentic AI
    33:20 AI in Education and Changing Learning Environments
    39:00 Sam’s Personal Use of AI — What Works and What Doesn’t
    41:20 Terminator vs Matrix? AI Futures
    42:41 Where to Find Sam and the MIT Sloan Study


    Where to Find the Sam Ransbotham
    site at Boston College

    Or you find him on LinkedIn
    The 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.


    AI Will Never Be A Leader - Says Sally Bendersky May 13, 2026
    Show notes

    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 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 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.”



    Chapters

    00:00 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 Bendersky

    LinkedIn: Sally Bendersky

    Website: sallybcoach.com

    Contact: Available through Dietmar Fischer

    Hosted on Acast. See acast.com/privacy for more information.


    The Cost of Being Invisible in ChatGPT - With Joseph Levi May 11, 2026
    Show notes

    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.”




    Chapters

    00:00 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.


    AI Is Killing Transaction Costs, But Who Gets the Money? May 10, 2026
    Show notes


    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?”



    Chapters

    00:00 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.


    The Secret Behind Most AI Tools: RAG. Alex Kihm Explains It Simply // REPOST May 09, 2026
    Show notes

    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.com
    • Contact 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.


    AGI: The AI Term Every Executive Should Understand May 07, 2026
    Show notes

    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 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




    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.


    Human vs. Machine or: Why still play Chess if AI is Better at it? May 05, 2026
    Show notes

    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.


    Why AI Feels Human (And Why That’s a Problem) May 03, 2026
    Show notes

    AI feels human. That’s the problem.


    In this episode of A Beginner’s Guide to AI, Dietmar Fischer breaks down one of the most misunderstood aspects of artificial intelligence: why we treat AI like a person and why that creates real business risks.


    You’ll discover how anthropomorphism shapes the way we interact with AI, why human-like responses increase trust, and how companies unintentionally push users into overestimating AI capabilities.


    This episode goes beyond the hype and focuses on what really matters: using AI without losing control.


    💡💡💡

    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 🚀

    💡💡💡



    🔥 What you’ll learn:

    • Why AI sounds smart but isn’t
    • The psychology behind AI trust
    • Emotional attachment to chatbots
    • The business risks of human-like AI
    • How to think critically when using AI



    📧💌📧

    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

    • “Fluency is not proof of truth.”
    • “The more human AI feels, the more we overtrust it.”
    • “You’re not talking to a mind. You’re reacting to a pattern.”




    ⏱ Chapters

    00:00 The Moment AI Feels Human

    06:30 What Anthropomorphism Really Means

    18:20 Why Your Brain Trusts AI

    32:10 The Business Risk of Human-Like AI

    48:45 Emotional Attachment and Real Cases

    01:05:00 How to Use AI Without Losing Control

    Hosted on Acast. See acast.com/privacy for more information.


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