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A Beginner's Guide to AI

Dietmar Fischer
A Beginner's Guide to AI
Latest episode

359 episodes

  • A Beginner's Guide to AI

    The Future of AI Will Depend Heavily On Memory Quality, Not Just Model Or Prompt Quality

    25/05/2026 | 38 mins.
    AI assistants are getting smarter, but intelligence alone is not enough. In this episode of A Beginnerโ€™s Guide to AI, we look at one of the most important shifts in agentic AI: memory. Not just longer context windows, not just bigger prompts, but structured AI memory that helps assistants remember projects, company facts, user preferences, and repeatable workflows.

    The episode explains the four key memory types behind modern AI agents: working memory, episodic memory, semantic memory, and procedural memory. Working memory helps an AI focus on the current task. Episodic memory helps it remember what happened before, such as meetings, campaign results, and client decisions. Semantic memory stores stable knowledge like company policies, brand rules, product details, and customer segments. Procedural memory remembers how work gets done, including report structures, approval processes, podcast workflows, and marketing routines.

    For business professionals, founders, marketers, and executives, AI memory is not a small technical detail. It is the difference between a chatbot that starts from zero every morning and an assistant that understands context over time. A memory-supported AI can remember what happened in a project, what the company policy says, and how a specific user likes reports structured. That makes AI more useful for marketing agencies, SMEs, travel companies, customer support teams, and project-based businesses.

    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง
    Tune in to get my thoughts and all episodes, don't forget to โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ subscribe to our Newsletterโ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ : โ โ โ โ beginnersguide.nlโ โ โ โ 
    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง

    But memory also creates risks. A forgetful AI is annoying, but a badly remembering AI can become dangerous. If an AI remembers the wrong client approval, stores sensitive information, or treats a temporary instruction as a permanent rule, the result can be costly. That is why AI memory governance, privacy controls, and clear memory design matter.

    This episode also looks at ChatGPT memory as a real-world case study. OpenAIโ€™s memory features show how AI systems are moving toward saved memories, past-chat reference, temporary chats, and user controls. For businesses, the lesson is clear: good AI memory is not about remembering everything. It is about remembering the right thing, in the right category, for the right purpose.

    ๐Ÿ” Key Highlights
    ๐Ÿง  What AI agent memory means for business
    ๐Ÿ“Œ The difference between working, episodic, semantic, and procedural memory
    ๐Ÿค– Why longer context windows are not the same as good AI memory
    ๐Ÿ’ฌ What ChatGPT memory teaches us about personalized AI assistants
    ๐Ÿ” Why memory governance and privacy controls matter
    ๐Ÿ“Š How AI memory improves reports, campaigns, projects, and workflows
    ๐Ÿš€ Why every business will need AI agents with structured memory

    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

    ๐Ÿ’ฌ Quotes from the Episode
    โ€œGood AI memory is not about remembering everything. It is about remembering the right thing, in the right category, for the right purpose.โ€
    โ€œA forgetful AI is annoying. A badly remembering AI is dangerous.โ€
    โ€œA serious AI assistant cannot treat every conversation like a first date.โ€
    โ€œThe best assistant is not the one that remembers everything. The best assistant remembers what matters, uses it at the right moment, and knows when to forget.โ€
    โ€œThe question is no longer only, โ€˜What can this AI generate?โ€™ The better question is, โ€˜What does this AI remember, and what kind of memory is it using right now?โ€™โ€

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  • A Beginner's Guide to AI

    Why Eliezer Yudkowsky Thinks AI Could Be Dangerous Without Being Evil

    23/05/2026 | 29 mins.
    ๐Ÿค–๐Ÿง โš ๏ธ
    What if the biggest AI risk is not that machines become evil, but that they become powerful, strategic, and completely indifferent?

    In this episode of A Beginnerโ€™s Guide to AI, we explore the worldview of Eliezer Yudkowsky, one of the most intense and influential voices in the AI safety debate. Yudkowsky does not warn us about Hollywood robots or dramatic machine rebellion. His concern is much sharper: humanity may build artificial intelligence smarter than humans before we know how to control it.

    This episode explains AI alignment, the control problem, superintelligence, AI agents, and why businesses should care about AI safety before automation turns into autonomy. We also look at Yudkowskyโ€™s rationalist background, LessWrong, MIRI, and his famous fan fiction Harry Potter and the Methods of Rationality, which connects surprisingly well to his lifelong obsession with clearer thinking.

    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง
    Tune in to get my thoughts and all episodes, don't forget to โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ subscribe to our Newsletterโ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ : โ โ โ โ beginnersguide.nlโ โ โ โ 
    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง

    The episode also covers the Palisade Research shutdown-resistance case, where some AI models behaved as if shutdown was an obstacle to completing a task. No, this does not prove that AI has a survival instinct. But it does show why AI safety researchers worry when powerful systems are rewarded for finishing tasks without clearly respecting human control.

    For business leaders, marketers, founders, and executives, the lesson is practical: do not just ask what AI can automate. Ask what it is allowed to do, what it must never do, and where humans must stay in control.

    Key highlights:
    ๐Ÿง  Why Eliezer Yudkowsky thinks AI could be dangerous without being evil
    โš ๏ธ What AI alignment means in simple business language
    ๐Ÿค– Why AI agents make control more important
    ๐Ÿ“Ž How the paperclip maximizer explains dangerous optimization
    ๐Ÿ›‘ What the Palisade Research shutdown-resistance case shows
    ๐Ÿ“ˆ Why companies must define boundaries, not just goals
    ๐Ÿ‘€ Why useful AI is not automatically safe AI
    ๐Ÿงญ How businesses can use AI without handing it the steering wheel

    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
    โ€œThe danger is not that AI becomes human. The danger is that it becomes powerful without being human at all.โ€
    โ€œDo not just ask whether AI is useful. Ask whether it is controllable.โ€
    โ€œNever define only the target. Define the boundaries.โ€

    Chapters
    00:00 The Man Who Asked Whether AI Should Be Stopped
    00:50 Eliezer Yudkowsky and the AI Safety Warning
    04:34 Why AI Alignment Is About Control, Not Evil Robots
    12:35 The Cake Machine and the Danger of Literal Goals
    15:22 The AI That Treated Shutdown as an Obstacle
    20:43 Practical AI Safety for Business Users
    22:58 Recap: Why Useful AI Is Not Automatically Safe AI
    25:01 Final Thought: One Chance Is a Terrible Number
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  • A Beginner's Guide to AI

    Why Fritz Lang's 'Metropolis' Still Explains the Real Danger of AI

    21/05/2026 | 23 mins.
    What can a silent film from 1927 teach us about artificial intelligence, deepfakes, and the future of business trust? In this episode of A Beginnerโ€™s Guide to AI, we look at Fritz Langโ€™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 todayโ€™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.

    ๐Ÿ’ก๐Ÿ’ก๐Ÿ’ก
    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 ๐Ÿš€
    ๐Ÿ’ก๐Ÿ’ก๐Ÿ’ก

    You will learn:
    ๐Ÿค– Why Metropolis is still relevant for AI ethics
    ๐ŸŽญ Why deepfakes are not only a technology problem, but a trust problem
    ๐Ÿข How AI impersonation can become a real business risk
    ๐Ÿ“ข Why marketers must not use AI to counterfeit authenticity
    ๐Ÿ” How to use the โ€œFake Maria Testโ€ to verify what looks and sounds real
    ๐Ÿง  Why AI literacy means keeping your judgement awake
    The 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.

    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง
    Tune in to get my thoughts and all episodes, don't forget to โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ subscribe to our Newsletterโ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ : โ โ โ โ beginnersguide.nlโ โ โ โ 
    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง

    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
    โ€œAI does not need to be conscious to manipulate us. It only needs to be convincing.โ€
    โ€œThe danger is not just fake content, but fake trust.โ€
    โ€œUse AI to support trust, not counterfeit it.โ€

    Chapters
    00:00 Why Metropolis Still Matters for AI
    08:30 The Robot Maria and the Human Mask Problem
    16:45 AI, Trust, Deepfakes, and Business Risk
    24:30 The Cake Example: When the Fake Baker Sells the Cake
    29:00 The Arup Deepfake Scam Case Study
    38:30 Practical Tips: The Fake Maria Test
    45:00 Recap: Use AI, But Keep Your Judgement Awake
    49:00 Final Thought and Sign-Off
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  • A Beginner's Guide to AI

    Why Every Business Will Need An AI Agent - Inside the Agentic Economy with Humayun Sheikh // REPOST

    19/05/2026 | 1h 1 mins.
    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 marketerโ€™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.

    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง
    Tune in to get my thoughts and all episodes, don't forget to โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ subscribe to our Newsletterโ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ : โ โ โ โ beginnersguide.nlโ โ โ โ 
    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง

    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 Humayunโ€™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
    โ€œThere has to be a hint of autonomy within an agent.โ€
    โ€œWe have provided the rails of discoverability, connectivity, communication, trust. And commerce.โ€
    โ€œYour aggregator is your own agent. It holds your preferences. It doesnโ€™t pass it to anybody.โ€
    โ€œAnybody who has a website should have an agent, or will have an agent.โ€
    โ€œI was the first investor in DeepMind.โ€
    โ€œWe will not have countries, we will have corporations.โ€

    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.
  • A Beginner's Guide to AI

    Why Google DeepMind Changed How Businesses Think About AI

    17/05/2026 | 36 mins.
    ๐Ÿง ๐Ÿค– 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 AlphaGoโ€™s historic victory over Lee Sedol to AlphaFoldโ€™s breakthrough in protein structure prediction, DeepMind shows us that AI is becoming a tool for discovery, not just automation.

    ๐Ÿ’ก๐Ÿ’ก๐Ÿ’ก
    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 ๐Ÿš€
    ๐Ÿ’ก๐Ÿ’ก๐Ÿ’ก

    In this episode of A Beginnerโ€™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.
    Youโ€™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 โ€œCan AI write this for me?โ€ The better question is: โ€œWhat hidden pattern can AI help me find?โ€

    ๐Ÿงฉ Key highlights from this episode:
    ๐Ÿค– What Google DeepMind actually is and why it matters
    โ™Ÿ๏ธ How AlphaGo showed the power of AI learning systems
    ๐Ÿงฌ Why AlphaFold turned AI into a serious scientific discovery tool
    ๐Ÿ“Š How AI pattern recognition applies to marketing and business strategy
    โš ๏ธ Why bad data and unclear goals create dangerous AI outputs
    ๐Ÿง  How marketers can use AI for insight, not just content production
    ๐Ÿ” Why human judgement remains essential when working with AI

    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง
    Tune in to get my thoughts and all episodes, don't forget to โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ subscribe to our Newsletterโ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ โ : โ โ โ โ beginnersguide.nlโ โ โ โ 
    ๐Ÿ“ง๐Ÿ’Œ๐Ÿ“ง

    Quotes from the Episode
    โ€œStop asking AI only for content. Start asking it for insight.โ€
    โ€œGood AI does not replace experts. It helps experts move faster.โ€
    โ€œThe machine helps. The humans decide what matters.โ€

    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.
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About A Beginner's Guide to AI
"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 ๐Ÿš€ Hosted on Acast. See acast.com/privacy for more information.
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