A Beginner's Guide to AI

In this episode of A Beginner’s Guide to AI, Professor GePhardT takes The Cluetrain Manifesto’s famous idea markets are conversations and stress tests it in the age of generative AI. In 1999, Cluetrain demanded that brands stop sounding like machines and start speaking with a human voice. Today, AI can generate that human sounding voice on demand, which creates a new problem: it becomes easy to sound authentic while becoming less trustworthy.You will learn why conversational marketing is not about posting more, replying faster, or writing prettier copy. It is about credibility in public. This episode breaks down the difference between tone and truth, why AI customer service chatbots can create brand risk when they guess, and how to use human in the loop design so your AI supports real accountability instead of manufacturing polite noise.We also unpack a real cautionary case: Moffatt v Air Canada. A website chatbot provided incorrect guidance about bereavement fares, the customer relied on it, and compensation was ordered. It is a sharp reminder that when AI speaks on your website, customers experience it as the company speaking.📧💌📧Tune in to get my thoughts and all episodes, don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧💬 Quotes from the Episode“AI makes language cheap, and when language is cheap, trust becomes the scarce ingredient.”“Responsiveness can masquerade as empathy.”“When AI speaks in your name, its answers become part of your promises, not just part of your tone.”“You can talk beautifully about cake while still serving bad cake.”“A chatbot is not a neutral tool. It is a brand voice.”“In 1999 the challenge was speaking human. Now the challenge is acting human.” 🎧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🕒 Chapters00:00 Why Cluetrain matters again in the AI era04:10 Markets are conversations and why the human voice cannot be faked10:05 AI makes language cheap and trust expensive18:30 The authenticity trap: tone without accountability27:40 Case study: Air Canada chatbot and the cost of confident wrong answers36:20 Practical framework: human in the loop and conversation design✅ Key topics and keywordsCluetrain Manifesto and AIMarkets are conversations AIConversational marketing AIAI brand voice authenticityAI trust and accountabilityChatbot hallucinations customer supportChatbot legal liabilityHuman in the loop chatbot designMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

How is artificial intelligence transforming the way we approach marketing? In this episode, we dive deep with Kasper Sierslev, founder of Zite, to uncover the real-world opportunities and challenges of AI in marketing.Discover how forward-thinking brands are leveraging AI tools to spark creativity, streamline campaigns, and stay ahead in a rapidly evolving digital landscape.📧💌📧Ready to take your business to the next level? Subscribe for more AI strategies, share your questions in the comments, and visit our website for free resources. Don’t miss exclusive content in our newsletter—sign up today: ⁠⁠⁠beginnersguide.nl⁠⁠⁠📧💌📧💡 Key Highlights:Kasper Sierslev shares his journey and unique perspective on embedding AI into marketing strategiesTop AI tools for marketers and how to use them for impactful resultsThe importance of a human-centric approach to AI in marketingInsights on the future of AI and how brands can stay aheadActionable advice for marketers looking to adopt AI today🧾 Quotes from the Episode:“It’s not super easy sitting on the other side doing creative work and just saying, ‘We made this great film, look how funny it is.’ That’s gut feeling, it’s opinions. For almost 20 years now, creativity and branding has lost a lot.” - Kasper Sierslev“I think it’s super easy to do something now, but we don’t really have the big AI tech companies here yet. Maybe that’s because of copyright laws or the lawsuits happening at the moment. Still, we can build on top of the bigger models and protect what we’re doing as it goes back into the loop.”Kasper Sierslev📂 Chapters (experimental feature):00:00 Introduction & Kasper Sierslev's Background04:00 AI Tools for Marketers08:00 Creativity, Branding & AI15:00 Human-Centric AI in Marketing25:00 Real-World AI Marketing Case Studies33:00 Challenges & Cultural Shifts in Advertising41:00 The Future of AI in Marketing50:00 Practical Advice for Marketers🔗 Where to find Kasper Sierslev:LinkedInZite Website, where you also find the In-house Barometer!---Tune in to get my thoughts, and don’t forget to subscribe to our Newsletter!Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

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

The Rising Cost of Intelligence: What Expensive AI Means for the WorldArtificial intelligence is reshaping how we work, learn, and create. But as frontier AI models become more capable, their costs are rising faster than ever. This episode of A Beginner’s Guide to AI dives into the global AI divide, exploring how price, compute, infrastructure, and access are quietly determining who benefits from AI and who risks falling behind.Listeners will discover why advanced AI models cost so much to train and run, how high prices can concentrate innovation in wealthy institutions, and why access to strong models is becoming a new form of economic and educational inequality. Through vivid examples and clear explanations, Professor Gephardt guides listeners through the real-world consequences of expensive AI and what can still be done to ensure a more inclusive future.📧💌📧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:“When intelligence becomes expensive, opportunity becomes exclusive.”“A great model is useless if only a handful of people can afford to use it.”“If AI becomes a privilege, innovation shrinks to the size of the elite who control it.”Chapters00:00 The Hidden Price of Intelligence04:12 Why Cutting-Edge AI Is So Expensive12:47 How AI Costs Create a Global Divide21:30 Real-World Case Studies on AI Access32:18 Practical Ways to Narrow the AI Gap39:42 Final Thoughts and Key LessonsMusic credit: "Modern Situations" by Unicorn Heads 🎧✨ Hosted on Acast. See acast.com/privacy for more information.

Context rot is one of the most underestimated risks in artificial intelligence today. In this episode of A Beginner’s Guide to AI, we explore how AI systems trained on static data slowly drift away from reality while continuing to sound confident, helpful, and persuasive.You’ll learn why large language models struggle with time, why feeding more information into AI can backfire, and how outdated knowledge quietly sabotages decisions in marketing and business. This episode explains the difference between timeless principles and perishable insights, and why trusting AI without checking freshness can cost credibility and money.Key topics include context rot in AI, outdated training data, long context window limitations, AI decision-making risks, and practical strategies like retrieval-augmented generation and smarter context engineering.📧💌📧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“Fluency is not accuracy, even though our brains desperately want it to be.”“More context doesn’t make AI smarter, it often makes it confused.”“AI confidence is cheap. Verification is expensive.”Chapters00:00 Context Rot and the Illusion of Smart AI05:42 Why AI Knowledge Freezes in Time12:18 When More Context Makes AI Worse19:47 Business and Marketing Risks of Context Rot27:05 How to Reduce Context Rot in Practice34:40 What Humans Must Do Better Than AIMusic credit: "Modern Situations" by Unicorn Heads 🎧 Hosted on Acast. See acast.com/privacy for more information.

Machine learning is everywhere, yet rarely understood. In this episode of A Beginner’s Guide to AI, we strip away the hype and explain how machine learning actually works, why it’s so powerful, and where it quietly goes wrong.You’ll learn how machines are trained on data rather than rules, why predictions are not understanding, and how real-world systems can produce unfair outcomes even when they look accurate. A real healthcare case shows how a cost-based algorithm systematically underestimated medical need, revealing the hidden dangers of proxy metrics.This episode covers machine learning basics, ethical AI, algorithmic bias, fairness, and transparency in a way that is accessible to beginners and useful for professionals.📧💌📧Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Quotes from the Episode“Machine learning gives you what you measure, not what you value.”“The algorithm didn’t invent bias. It learned it efficiently.”“A perfect prediction of the wrong thing is still failure.”Chapters00:00 Machine Learning Without the Myth04:12 How Machines Learn From Data10:45 Types of Machine Learning18:30 The Cake Example26:05 Healthcare Case Study36:40 Ethics, Bias, and Proxies45:50 Final TakeawaysAbout 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.Music credit: Modern Situations by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

REPOST due to low podcast listener activity - if you listen now, you are the exception 😉Ever wondered how Netflix knows exactly what you'll binge next or how big brands like Delta Air Lines turn multimillion-dollar sponsorships into concrete sales?Welcome back to A Beginner's Guide to AI, where today we're uncovering the fascinating world of AI inference—the secret sauce behind machine-made predictions.--- --- ---A word from our Sponsor:Sensay creates AI-powered digital replicas to preserve and share individual and organizational knowledge, turning it into scalable, sustainable, and autonomous wisdom.Visit Sensay at ⁠⁠⁠⁠⁠⁠⁠Sensay.io⁠⁠⁠⁠⁠⁠⁠And listen to Dan, Sensay's CEO and founder, ⁠⁠⁠⁠⁠⁠⁠in this episode⁠⁠⁠⁠⁠⁠⁠!--- --- ---Professor Gephardt, with his usual charm and wit, breaks down precisely how AI learns from past data to tackle new, unseen scenarios, turning educated guesses into powerful, profitable insights.Expect engaging analogies—from fruit-loving robots to cake-tasting mysteries—and real-life case studies, like Delta’s remarkable $30 million Olympic success story powered by AI. Plus, practical tips on how to spot AI inference in your daily digital life and even how to experiment with your own AI models!Tune in to get my thoughts, and don't forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠!This podcast was generated with the help of ChatGPT and Mistral. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

REPOST DUE TO WRONG AUDIO TRACK. Changed it, but many may have missed the right episode.Is intelligence something we’re born with, or do we learn everything from scratch? That’s not just a question for philosophers - it’s at the core of artificial intelligence today.In this episode ofA Beginner’s Guide to AI, we explore the great debate between nativism and deep learning.Nativism suggests that some knowledge is built-in, like the way babies instinctively pick up language. Deep learning, on the other hand, argues that intelligence comes purely from experience - AI models don’t start with any understanding; they learn everything from massive amounts of data.We break down how this plays out in real AI systems, from AlphaZero teaching itself to play chess to ChatGPTGPT mimicking human language without actually understanding it. And, of course, we use cake to make it all crystal clear.Tune in to get my thoughts, and don’t forget tosubscribe to our Newsletter at beginnersguide.nlThis podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it’s read by an AI voice.Music credit:"Modern Situations" by Unicorn Heads. Hosted on Acast. See acast.com/privacy for more information.

AI vs. Automation: Why Repetitive Marketing is FailingREPOST due to low podcast listener activity - if you listen now, you are the exception 😉Ever received the same email twice—word for word, from two different people? That’s not AI, that’s bad automation. And it happens way more often than it should.In this episode, we break down the key difference between automation and artificial intelligence—why one just follows rules while the other actually thinks. With a real-world case study straight from my inbox, we’ll expose how businesses are unknowingly damaging their credibility with mindless automation and what they could do differently with AI.If you’re running digital marketing, email campaigns, or even PR outreach, this is a must-listen. Stop the spam, start thinking smarter.Tune in to get my thoughts, and don’t forget to subscribe to our Newsletter!This podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice.Music credit: "Modern Situations" by Unicorn Heads. Hosted on Acast. See acast.com/privacy for more information.

Ever wonder how Netflix knows your next binge-watch, or why your bank spots fraud before you do? In this lively episode of A Beginner’s Guide to AI, Professor GePhardT lifts the lid on predictive AI—the hidden tech wizard quietly shaping our daily lives.From forecasting retail trends at Target to critical healthcare interventions, predictive AI isn't just predicting the future; it's already shaping it. But there’s a catch: with great power comes the thorny challenge of bias and ethics.Join the fun as we untangle how predictive AI differs from generative AI, explore its surprising influence in everyday situations (cakes included!), and sharpen our own predictive skills through hands-on activities with Google Trends. Plus, a reality check from AI pioneer Pedro Domingos reminds us why understanding this tech matters—because computers might already run more than we'd like to admit.Tune in to get my thoughts and all the episodes: don't forget to ⁠subscribe to our Newsletter⁠ 💌Want to get in contact? Write me an email: podcast@argo.berlinThis podcast was generated with the help of ChatGPT, Mistral, and Claude 3. We do fact-check with human eyes, but there still might be hallucinations in the output. And, by the way, it's read by an AI voice from ElevenLabs.Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence has become incredibly convincing. It talks smoothly, reacts instantly, and often feels surprisingly human. In this episode of A Beginner’s Guide to AI, Prof. GepHardT explores why that feeling can be misleading — and why it matters.Drawing on literature, psychology, and real-world AI design, the episode explains how modern AI systems simulate intelligence without understanding, why humans instinctively project emotions onto machines, and where ethical risks begin when appearance replaces clarity. This is an accessible, practical episode for anyone who wants to understand AI without getting lost in jargon or hype.📧💌📧Tune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Chapters00:00 When AI Feels Alive04:12 The Olympia Effect and Human Projection10:05 What AI Actually Does and What It Doesn’t18:40 Why Humans Trust Machines26:30 Ethical Risks of Emotional AI34:10 How to Stay Clear-Headed Around AIQuotes from the Episode“AI doesn’t understand you — it performs understanding.”“The danger isn’t smart machines, it’s trusting fluent ones.”“When intelligence looks alive, that’s when it needs the most scrutiny.”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🎧 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

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

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.📧💌📧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 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 KihmAll you need to know about chunking strategies, you'll find here: poma-ai.comContact Alex on LinkedIn! Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial intelligence breakthroughs might appear magical from the outside, but underneath lies a predictable and surprisingly elegant structure. This episode of A Beginner’s Guide to AI takes listeners on a clear and engaging journey into the three scaling laws of AI, exploring how model size, dataset size, and compute power work together to shape the intelligence of modern systems. Through practical explanations, entertaining analogies, and detailed real-world case studies, this episode demystifies the rules that drive every meaningful AI advancement.Listeners will learn why bigger models often perform better, how data becomes the lifeblood of learning, and why compute power is the critical engine behind every training run. The episode includes a memorable cake analogy, a breakdown of how scaling laws led to the rise of state-of-the-art large language models, and practical tips for evaluating AI tools using these principles.This deep yet accessible explanation is designed for beginners, creators, and curious minds who want to understand what truly makes AI work.📧💌📧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 doesn’t just grow; it scales, and scaling changes everything.”“Compute isn’t the cherry on top; it is the oven that makes the entire AI cake possible.”“Scaling laws show us that AI progress isn’t magic; it’s engineered.”Chapters00:00 Introduction to AI Scaling03:24 The Three Scaling Laws Explained11:02 The Cake Analogy for AI Models17:40 Case Study: How Scaling Transformed Large Language Models23:58 Practical Tips for Understanding and Applying Scaling Laws28:45 Final Recap and Key TakeawaysMusic credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🚀 Matt Weaver, Solutions Engineering Leader at OpenAI, takes us inside the launch of GPT-5, the rise of AI agents, and how these tools are transforming industries. From practical business adoption tips to exploring advanced features like Deep Research and Custom GPTs, this episode is packed with actionable insights.📧 Tune in to get my thoughts, tips and tricks and all the episode in your mailbox: beginnersguide.nl💡 What you’ll learn in this episode:How GPT-5 chooses the right reasoning model automatically for better answersWhy AI literacy is the foundation for business adoptionIndustry examples from banking (BBVA) to travel (Virgin Atlantic)How AI agents like Deep Research work – and why they’re a game changerCreating your own Custom GPTs without codingAddressing AI objections: security, hallucinations, and cost concernsQuotes from the Episode:💬 “AI is such a transformative technology — now is the time to reimagine your processes, not just bolt it onto old ones.” – Matt Weaver💬 “Your first AGI moment changes how you see every problem — you start thinking, ‘How can ChatGPT help me with this?’” – Matt Weaver🧾 Chapters (experimental):00:00 Welcome & Introduction to Matt Weaver01:18 Matt’s Journey into AI and Joining OpenAI03:58 GPT-5 Launch – What’s New and Why It Matters08:28 How Businesses Should Start with ChatGPT10:45 AI Adoption Strategies & Avoiding Common Mistakes12:14 Industry Examples – Banking, Travel, and Professional Services14:06 Deep Research: AI Agents Explained18:06 Study Mode & AI in Education19:56 Overcoming Objections: Security, Hallucinations & Costs24:06 ROI of ChatGPT in Business28:22 The “AGI Moment” & Personal Uses of ChatGPT32:03 The Future of AI: Agents, Coding, and New Businesses35:48 Custom GPTs – Building Your Own AI Apps39:06 AI Safety & Optimism for the Future41:16 Where to Find Matt Weaver & ClosingWant to know more?🔗 ChatGPT is now also at Chat.com🔗 OpenAI's learning resources are at: academy.openai.com🎵 Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Ever wished you could clone yourself to get more done? Julian Goldie actually did it — and built a content empire out of it. In this episode of A Beginner’s Guide to AI, host Dietmar Fischer talks with Julian about how he uses AI to create five videos a day, automate workflows, and still keep a personal, human touch that builds real trust with his audience.Julian reveals how he turned his initial fear of AI into a full-scale growth engine for his business, transforming his SEO agency into a modern AI-powered content studio. He shares the systems, tools, and mindset that helped him automate marketing, scale his team, and reach millions — all while avoiding the “AI slop” that floods the internet.📧💌📧Tune in to get my thoughts and all episodes — don’t forget to ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠subscribe to our Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: ⁠⁠⁠⁠beginnersguide.nl⁠⁠⁠⁠📧💌📧💡 Key HighlightsHow Julian scaled from one YouTube channel to nine using AIThe tools behind his workflow: Descript, Claude, and HeyGenWhy AI videos sometimes outperform human ones (and when they don’t)The importance of quality control and the “human in the loop”How AI can make leadership more human — through reflection and empathyWhy it’s not humans vs AI, but humans with AI vs everyone else🧠 Quotes from the Episode“I thought AI would destroy my agency — instead, it became my best employee.”“It’s not humans versus AI — it’s humans with AI versus everyone else.”“My AI avatar never gets tired, never mispronounces a word, and somehow gets better watch time than me.”🕒 Chapters00:00 Julian’s AI Origin StoryHow the fear of losing his SEO agency pushed him into AI — and why his first ChatGPT video went viral.06:12 Scaling Content: From Livestreams to 5 Videos a DayJulian explains his full workflow, the role of AI avatars, repurposing, and why human connection still matters.14:40 AI Tools That Power the SystemA practical look at Descript, HeyGen, Claude, and how his team uses them to automate editing, clipping, and content creation.22:18 Leadership, Teams & the Human in the LoopHow AI supports decision-making, reflection, communication, and empowers team members instead of replacing them.30:44 The Future of AI Content & Final ThoughtsQuality control, the fight against “AI slop,” the risks ahead — and whether the Terminator is coming.🌐 Where to Find the Julian Goldie:Julian Goldie's Agency: goldie.agencyAI Profit Boardroom: aiprofitboardroom.comYouTube: @JulianGoldieTwitter/X: @JulianGoldieSEOAnd Julian's Website: juliangoldie.com👤 About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to know how to get your AI or digital marketing going, just reach out at argoberlin.com 🚀🎵 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Step into the future of artificial intelligence with Fred Jordan as he introduces “Biocomputing”—the next evolutionary leap for AI. In this episode, Fred unpacks how biocomputing uses nature’s own design principles to build more adaptive, resilient, and intelligent systems.📧💌📧Tune in to get my thoughts, and don’t forget to ⁠subscribe to our Newsletter⁠! 📧💌📧Highlights from the episode:What “Biocomputing” is, and why it matters for the future of AIHow biocomputing fundamentally differs from traditional approachesFred Jordan’s personal journey and vision for next-generation intelligenceReal-world examples and the untapped potential of biocomputingQuotes from the Episode:“Biocomputing is about harnessing the principles of life itself to create intelligence that adapts and evolves, just like nature intended.”“We’re not just building smarter machines; with biocomputing, we’re taking inspiration from biology to leap forward in how AI thinks and grows.”Chapters (experimental):00:00 Introduction and Fred Jordan’s Background04:15 What Is Biocomputing? The Big Idea15:30 Biocomputing vs. Traditional AI: Key Differences28:50 Real-World Applications and the Future of Biocomputing41:10 Closing Thoughts and Next StepsWhere to find Fred Jordan and FinalSpark:Discord: discord.com/invite/edPetHUYtxWebsite: finalspark.comApply to join: finalspark.com/neuroplatform/Music credit: "Modern Situations" by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

🎙️ He Taught AI How to Have Manners — Meet David Petrou of Continua AIWhat if your next group chat had an extra participant — one that listens, understands the social context, remembers what you said last week, and even knows when to stay quiet? In today’s episode, host Dietmar Fischer sits down with David Petrou, founder and CEO of Continua AI, to explore the emerging world of Social AI — intelligent agents designed not just to talk, but to collaborate inside group chats.David, formerly at Google and part of the original Google Glasses team, has spent decades thinking about how humans and machines interact. With Continua, he’s building the world’s first truly human-aware AI that can join your Discord, iMessage, or Google Message conversations and behave like a socially intelligent teammate. This isn’t a chatbot — it’s an AI that understands when to talk, when to listen, and when to help.📧💌📧 Get my NewsletterTune in to get my thoughts and all episodes, don’t forget to subscribe to our Newsletter: 👉 https://beginnersguide.nl📧💌📧Get ready for a deep dive into social intelligence, etiquette in AI systems, agentic actions, and the future of communication where AI participates naturally alongside humans.💡 What You’ll Learn in This EpisodeWhy Social AI is the next big evolution beyond traditional chatbotsHow Continua trains AI to understand timing, tone, context, and social cuesWhy David believes text messaging with AI will reach a billion usersThe engineering challenge behind teaching AI “manners” and “machine etiquette”How AI group chat agents improve communication, planning, and collaborationThe real use cases: debugging code, planning trips, updating documents, running games, and summarizing informationHow Continua’s multi-model architecture orchestrates LLMs, fine-tunes, and intent classifiersWhy Social AI is surprisingly safe — and why today’s fears don’t match the technical realityThe leadership perspective: how to integrate AI thoughtfully without overwhelming teamsWhere Social AI is heading next: meetings, real-time participation, contextual computing, and agentic actions like shoppingThis episode is packed with insights for anyone interested in AI agents, human–AI collaboration, team communication, or the future of intelligent digital assistants.📌 Quotes from the Episode“We had to break the LLM’s brain and teach it social etiquette: when to talk, when to listen, and when to stay quiet.”“Traditional chatbots operate in single-player mode — Continua is built for multiplayer conversation.”“There are problems beyond our ability to solve directly — the real ingenuity is creating something that can learn how to solve them.”“Introducing a foreign intelligence into human group dynamics is one of the most fascinating problems in AI.”“Text messaging with AI will be the next form factor to hit a billion users.”“Language itself is the interface. You don’t need menus. You just tell the AI how you want it to behave.”⏱️ Chapters00:00 David Petrou’s Origin Story & Early Fascination with AI04:51 Why Social AI Matters: From APIs to Human-Aware Group Agents09:12 Teaching AI Social Etiquette: When to Talk, Listen, or Stay Quiet16:11 Inside Continuum: Multi-Model Architecture, Fine-Tuning & Real Use Cases24:05 Social AI in the Real World: Planning Trips, Debugging, Collaboration & Automation35:01 The Future of Social AI: Meetings, Agentic Actions, Leadership & Ethical Considerations🧑‍💼 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🔗 Where to Find the Guest: David PetrouWebsite: continua.aiLinkedIn: David PetrouInstagram: David Petrou🎵 Closing CreditsMusic credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

Artificial Intelligence isn’t just reshaping technology — it is reshaping leadership.In this episode, former Google strategist Louisa Loran joins Dietmar Fischer to explore how leaders can adapt, evolve, and thrive in an age defined by rapid AI acceleration.Louisa shares her journey across Moët Hennessy, Maersk, and Google, revealing why the biggest barrier to meaningful AI adoption isn’t technology but leadership behavior, culture, and the willingness to unlearn. She explains why strategy must come before tools, how organizations waste months chasing the wrong use cases, and why AI doesn’t challenge culture — it scales it.---Newsletter:Tune in to get deeper insights and all episodes. Subscribe at beginnersguide.nl---This conversation offers a clear and practical blueprint for anyone leading teams, shaping strategy, or trying to stay relevant in an AI-enabled world.In this episode you will learn:How leaders can build an effective AI leadership mindsetWhy organizations waste time on “AI use-case lists”How generative AI distorted expectations across industriesHow to build a culture of curiosity rather than controlWhy middle management often resists AI transformationThe four elements of Louisa’s Leadership Anatomy frameworkHow Louisa uses three AIs as strategic thought partnersWhat AI literacy really means for modern organizationsHow Europe’s AI culture compares to the U.S.Quotes from the Episode:“AI doesn’t challenge culture. It scales it.”“If you don’t unlearn, you can’t lead.”“AI won’t replace you — but bad leadership will.”Chapters:00:00 Welcome & Introduction — Meet Louisa Loran00:37 How curiosity led Louisa from Moët Hennessy to AI and Google02:21 Early digital transformation and the roots of AI in logistics04:46 Why strategy comes before tools — the real AI leadership lesson07:15 The global “AI panic” and how leaders wasted 18 months on use-case lists09:42 Rediscovering critical thinking in the AI era11:56 Learning to lead through uncertainty and data discovery14:33 Building a culture of curiosity instead of control17:28 The leadership challenge: unlearning the habits of success20:14 Lessons from Google — when inefficiency is actually innovation23:01 How AI puts pressure on leaders and middle management25:47 The anatomy of leadership: eyes, lungs, arms, and spine29:42 Using three AIs as thought partners while writing a book33:11 What AI literacy really means in organizations36:18 Education, ethics, and the future of learning with AI39:22 The European AI mindset vs. U.S. drive42:15 Final insights: leading with clarity, courage, and curiosity43:37 Where to find Louisa Loran and her bookWhere to find the Guest:Website: LouisaLoran.comLinkedIn: Louisa LoranBook: Leadership Anatomy in Motion (wherever you buy your books)About Dietmar Fischer:Dietmar is a podcaster and AI marketer based in Berlin. If you want to get your AI or digital marketing moving, visit Argo.berlin.Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.

📖 AI-Created Books: Chance or Threat?In this eye-opening episode of A Beginner’s Guide to AI, Professor GePhardT unpacks the fascinating, chaotic and sometimes alarming rise of AI-generated books. From Amazon’s restrictions on AI content to the ethics of machine-written storytelling, this episode dives deep into the future of publishing and what it means for readers, writers and creators.We explore how AI-written books are made, why platforms are overwhelmed and how readers can distinguish human creativity from machine-made text. You’ll hear surprising real-world cases, including the Clarkesworld shutdown and the now-infamous “82% AI-written” herbal remedy category on Amazon.📌 What you’ll learn:How AI book generation actually worksWhy AI is both a creative partner and a creative threatThe risks of misinformation in AI-written booksHow to spot an AI-generated bookWhy platforms like Amazon are tightening their rulesThe future of authorship in an AI-saturated world📧💌📧Tune in to get my thoughts and all episodes — don't forget to subscribe to our Newsletter: beginnersguide.nl📧💌📧Quotes from the Episode“A book is more than content; it’s a relationship between the mind that wrote it and the mind that reads it.”“AI doesn’t dream, doubt or desire — it just predicts what comes next.”“AI can help creativity bloom, but it can also bury real voices under mountains of machine-written noise.”🧑🏻 About Dietmar FischerDietmar is a podcaster and AI marketer from Berlin. If you want to kickstart your AI or digital marketing journey, he’s your guy!You can find him at Argoberlin.com🎧 Music credit: “Modern Situations” by Unicorn Heads Hosted on Acast. See acast.com/privacy for more information.