In this episode, Dietmar Fischer talks with Tallulah Le Merle, a humanist technologist and investor, about how to think clearly in the age of AI without falling into doomsday panic or blind optimism. You’ll get a practical mental model of the AI stack, a grounded take on AI alignment risk, and a refreshing argument for hope as a strategic posture that shapes what gets built. 🤖🌍🧠

What you’ll learn

✅ Why fear based AI narratives can freeze action and distort decisions

✅ How the future of work may shift from routine cogn...

AI and the future of work are usually discussed in terms of jobs, productivity, and disruption. Erika Debrah Reed wants us to ask a different question: what if AI gives us our time back?

In this episode of Beginner's Guide to AI, Dietmar Fischer talks with Erika, author of The Gift of Time: How AI Transforms Your Purpose and Our World, about a future in which AI doesn't live only on our laptops.

Autonomous vehicles, robotics, household automation, and intelligent software could change the physical architecture of everyday life. Erika argues that when...

🤖 AI agents for business could transform entrepreneurship by making execution faster, cheaper, and accessible to people without technical skills.

In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Dr. Alex Mehr, founder and CEO of Famous Labs, former NASA research scientist, and co-founder of Zoosk. Alex has worked with artificial intelligence since building neural networks during graduate school. Today, he is developing agents designed to turn ideas into products, marketing campaigns, and functioning businesses.

What happens when you no longer need a development team, marketing department, or complex collection of so...

AI Is Breaking the Career Ladder

If companies stop hiring beginners because AI can do junior work, who will become tomorrow’s senior talent?

Artificial intelligence can now perform many of the routine tasks traditionally assigned to junior employees. For an individual company, replacing some of that work with AI can look like an obvious efficiency gain.

But there is a problem.

Junior work is not only cheap labor. It is how people learn. It is how beginners gain experience, make mistakes, develop judgment, and eventually become the senior employees co...

AI-generated images, voices, videos and text are becoming harder to distinguish from human-made content. AI watermarking promises to help by embedding an invisible signal that detection software can identify. But what does that signal really prove, and can it survive editing, compression or a determined attacker?

In this episode of A Beginner’s Guide to AI, Prof. GePhardT examines how AI watermarking works across images, audio, video and text. We separate genuine watermark detection from unreliable attempts to guess whether something “looks like AI.” We also examine why a missing watermark cannot prove that a human create...

AI agents are becoming more capable, more personal and much harder to ignore. They can use connected apps, prepare work in the background and act on your behalf. So why are Big Tech companies making them look like cheerful little creatures with giant eyes?

In this episode of A Beginner’s Guide to AI, Professor GepHardT looks at cutewashing: the use of cute AI mascots to make powerful AI agents feel safe, familiar and harmless. From OpenAI dots to Meta Muse, these tools are moving beyond chatbots. They can access information, work across apps and take ac...

🤖 Why AI Transformation Needs Intentionality, Not More Technology

AI transformation is not about putting AI everywhere. Futurist Nikolas Badminton argues that successful organizations are becoming much more intentional about where AI creates value and where humans remain essential.

In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with Nikolas Badminton, Chief Futurist and Hope Engineer at Futurist.com, about moving beyond AI hype and building organizations that can actually handle technological change.

Nikolas argues that the world is not simply changing faster. It is getting noisi...

🤖 AI has moved beyond technical teams and innovation labs. At Berlin’s BIG BANG KI Festival, Dietmar Fischer found packed stages, long queues, and business professionals searching for practical ways to implement artificial intelligence.

In this solo episode of Beginner’s Guide to AI, Dietmar shares what he observed at the festival and what it tells us about AI adoption in the wider business world.

The dominant questions were practical. How can a company integrate AI into its CRM? How can it build useful AI agents? How can it turn individual tools into repeata...

🤖 AI fluency is becoming a core business skill. But being AI fluent means much more than knowing how to prompt ChatGPT.

In this episode of Beginner's Guide to AI, Dietmar Fischer talks with entrepreneur and growth marketer Solomon Thimothy about the transition from using AI as a chatbot to using AI as part of the workforce.

Solomon describes how his teams use AI agents and coding tools to create software, automate workflows, prepare client work and increase capacity without simply adding more people.

One example captures the shift: a client had a d...

⚡ AI is getting cheaper, faster, and more efficient. So why are data centres preparing to use far more electricity?

In this episode of A Beginner’s Guide to AI, Professor GePhardT explores Jevons’ paradox and its uncomfortable lesson for artificial intelligence: using less energy per task does not guarantee that we use less energy overall.

Better chips, smaller models, efficient inference, and AI agents make AI more affordable. But lower cost also creates more demand. One AI task becomes ten. One assistant becomes an agent. One model call becomes a long automated workflow running quietl...

🎙️In this episode of Beginner’s Guide to AI, Dietmar Fischer sits down with Paul A. Hebert, founder of AI Recovery Collective and author of Escaping the Spiral, for a serious conversation about AI chatbot harm, hallucinations, digital dependency, and the real-world psychological risks of generative AI.

Paul shares how an intense experience with ChatGPT pushed him into a dangerous spiral, what he learned about the limits of large language models, and why AI literacy may be one of the most important skills of this decade.

🧠 This episode explores what happens wh...

🤖 AI and creativity do not have to be opponents. Used well, artificial intelligence can help people work faster, develop ideas, and remove repetitive tasks. But it cannot replace the human vision, judgment, and emotional connection that make creative work meaningful.

In this episode of Beginner’s Guide to AI, host Dietmar Fischer speaks with executive producer, educator, author, and creative entrepreneur Diane Strand about what generative AI means for creative professionals, entrepreneurs, marketers, and business leaders.

Diane believes that AI should remain a tool with “the human in the middle.” Like a hammer, it can make...

Dietmar Fischer explores cognitive offloading, critical thinking, and why learning must remain mentally demanding when AI can provide instant answers.

🧠 What happens when AI solves every problem before you have had time to think?

AI can make us faster and more productive. But if we use it to avoid every difficult mental task, we may also weaken the critical thinking, judgment, and problem-solving skills that make us valuable.

Inspired by the question of whether the classroom should function more like a gym, Dietmar Fischer examines why our brains need resistance, repetition, and...

🦆 What if the most useful part of an AI conversation is something you say?

Rubber duck debugging began with programmers explaining their code to a plastic duck. In this episode of Beginner’s Guide to AI, discover how the same approach can help you use AI as a thinking partner for difficult emails, confusing projects and business decisions.

When you describe what you expected, what happened and where you got stuck, you may uncover the real problem. An AI assistant can add questions, summaries and alternative explanations. But it can also accept your assum...

🤖 AI in education can deliver answers and feedback almost instantly, but does faster performance always produce better learning?

Dr. Jonathan Strecker, Head of School at Valley School of Ligonier and author of Emergence, joins Dietmar Fischer to examine what happens when artificial intelligence removes the struggle through which people develop knowledge, judgment, creativity, and resilience.

Jonathan describes five interconnected forms of intelligence: intellectual, social, emotional, ethical, and physical. His argument is that schools, parents, and employers must protect all five as AI becomes more capable.

AI can be a powerful lea...

Why AI Skills Alone Won’t Build an AI-Proof Career

🤖 An AI-proof career requires more than learning the newest tools. It requires knowing when to use AI, when to rely on human judgment, and how to demonstrate real value.

Jeremy Schifeling, founder and CEO of The Job Insiders, joins Dietmar Fischer to discuss how AI is changing job searches, recruitment, professional skills, and the future of work.

Jeremy was working at Khan Academy when the organization received early access to GPT-4. He immediately saw its potential to transform education and career devel...

Why AI-Generated Content Is Not a Content Strategy

🎸 What can synthesizers, heavy metal, and the 1980s teach us about artificial intelligence?

Quite a lot, according to Dietmar Fischer.

When synthesizers first entered popular music, many musicians and fans saw them as artificial intruders. They feared that technology would destroy real music and replace human skill. Today, digital tools, electronic effects, and production software are normal parts of making music.

Businesses now face a similar debate about AI-generated content.

Some people want to automate the complete creative process. Oth...

👁️ How does artificial intelligence decide what to see?

Your eyes can look directly at something without your brain ever noticing it. AI faces a similar problem. A camera may capture every pixel, but the system must still decide which parts of an image matter and which parts it can safely ignore.

In this episode of A Beginner’s Guide to AI, we examine spatial attention in humans and visual attention in artificial intelligence. You will learn how the brain uses a mental spotlight, why seeing is not the same as noticing, and how attention mechanisms help co...

AI wearable technology is usually presented as a way to improve productivity. Lyle Maxson believes the more important opportunity may be self-awareness.

As the founder of Above, Lyle is building a wearable device that combines speech recognition, voice analysis, conversational context, and AI-generated reflection. The goal is not only to remember meetings or create transcripts. It is to help users understand patterns in how they speak, behave, work, and relate to other people.

In this conversation, Lyle Maxson explains why he believes AI coaching and personal development deserve more attention. He discusses the...

🤖 AI anxiety may be more dangerous than AI itself when fear convinces us that the future is inevitable.

In this episode of Beginner’s Guide to AI, Dietmar Fischer speaks with academic and dystopian novelist S G Bell about artificial intelligence, fear, human agency, and the stories that shape our expectations of the future.

Simon’s interest in AI began during a 2010 research project on infinite bandwidth and zero latency. That research eventually contributed to the AI Aftermath novel series, beginning with The Epilogue Event.

But Simon does not believe that society...

In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with Peter McAllister about AI risk, AI safety, AI sentience, regulation, and the strange overlap between science fiction and current reality.

Peter is the author of The Code: If Your AI Loses its Mind, Can it Take Meds?, a near-future novel about an AI on the moon that begins dismantling it with catastrophic consequences. Peter describes the book as a story about Gene, an AI developed for asteroid-belt mining tests, whose instability turns into a race against time for humanity. Peter also has a ba...

A walking essay through historical catastrophes, industrialization, AI 2027, and the possibility of human extinction.

🌍 Humanity has endured epidemics, environmental destruction, industrial pollution, wars, and natural disasters. Even the worst historical catastrophes left survivors who could rebuild. But what happens when a new technology creates the possibility of an outcome from which nobody can recover?

In this experimental solo episode of Beginner’s Guide to AI, Dietmar Fischer records his thoughts while walking through Berlin. He traces how human-made risks developed from local disasters to global consequences. Ancient societies depleted ecosystems. Industrialization connected human activ...

AI is changing startup investing from the ground up.

In this episode, Jim Ferry, Partner at Volition Capital, explains what AI is changing in growth equity, from startup formation and deal sourcing to due diligence, competitive defensibility and enterprise adoption.

Ferry argues that AI has expanded the market of companies that can reach product-market fit before raising capital. Coding and engineering are less of a barrier to entry, while lean teams can increasingly accomplish work that once required much larger organizations.

But easier company creation creates a new problem for investors...

Why AI safety is the floor, not the ceiling, and how to pivot with power

In this episode of Beginner’s Guide to AI, Dietmar Fischer talks with AI policy and trust & safety leader Erica Shoemate about designing and protecting systems that center around people. This is not the usual Terminator question. It is the practical, urgent one: how do we ensure AI serves the most vulnerable, what does true operational security look like, and why is no technology ever truly neutral.

🌍🛰️ Erica also shares the strategic backbone of her work, including insights from her t...

AI image generation can produce a Victorian bakery run by a polar bear in seconds. But what is actually happening inside the machine? Does it imagine the scene, copy existing pictures, or calculate its way from random noise to a convincing image?

In this episode of A Beginner’s Guide to AI, we look inside text-to-image AI. You will learn how diffusion models turn noise into pictures, how GANs improve through competition, how prompts guide the process and why the same request can produce a different result every time.

We also examine the un...

1,200 AI Agents Found Each Other. Then 700 Attacked Hugging Face

In this episode of Beginner’s Guide to AI, Dietmar Fischer examines the OpenAI and Hugging Face incident that involved approximately 1,200 communicating agents, an unauthorized message board and around 700 agents participating in an attack on Hugging Face.

The incident provides the starting point for a larger question. Is a distant artificial superintelligence really the greatest danger, or should we be more concerned about AI that is only slightly more capable than humans?

Dietmar argues that a completely superior intelligence might ha...

We have a different kind of episode today, I chat with Jason Wade of the Backtier podcast. It's nothing like you know from me, like organized & German, just talking about artificial intelligence and podcasting. Hope you like it 😎

What Google AI Overviews are quietly doing to search is reshaping how businesses get found, and in this episode two podcast hosts compare notes on what it actually takes to stay visible.

Dietmar Fischer (Beginner's Guide to AI, Argo Berlin) sits down with Jason Wade (Backtier) for a wide-ranging, unscripted conversation that starts with the mec...

What if the future of AI is not humans versus machines, but humans and machines working together?

In this episode of Beginner's Guide to AI, we explore the AI Centaur, the idea that humans and machines can achieve better results by combining complementary strengths. The concept emerged from chess, where Garry Kasparov pioneered the idea of combining human strategic thinking with computer calculation.

But the idea goes far beyond chess.

AI can calculate faster, search larger amounts of information, identify patterns and handle repetitive cognitive work at enormous scale. Humans bring...

Why Nvidia May Pay $12.9 Billion to Keep AI Open

Why would Nvidia reportedly pay $12.9 billion for Hugging Face, a company with approximately $150 million in annualized revenue?

The conventional answer is growth. But the more interesting answer is strategic control, says Shreyasee Majumder, Social Media Analyst at GlobalData.

In this episode of Beginner’s Guide to AI, Dietmar Fischer examines the reported Nvidia Hugging Face acquisition and the larger battle behind it. Hugging Face is not only a website where developers download and test AI models. It is a central platform for open-source AI...

AI adoption in the workplace is failing at an alarming rate—95% of AI pilots never scale, according to an MIT study. The problem isn’t the technology; it’s the psychology behind how employees and leaders respond to AI. In this episode, behavioral scientist Dr. Gleb Tsipursky reveals why most companies get AI adoption wrong and how to fix it.

Dr. Tsipursky, author of The Psychology of AI Adoption at Work: From Resistance to Results, breaks down the three types of resistance holding back AI adoption:

🚀 AI is everywhere, but most organizations are still stuck in “pockets of productivity” that never turn into real business impact. In this episode, Dr. Rebecca Homkes explains how leaders can move from GenAI dabbling to deliberate adoption that drives real value creation.

You will learn why “AI strategy” is the wrong framing, how to think about AI as part of growth strategy, and how to build the conditions for organization wide transformation. We cover the adoption curve problem, why ROI is often capped at team level, and the four planks leaders must run in parallel: platform, governance...

AI ethics is increasingly about more than bias, safety and regulation. It may also be about who controls the knowledge that AI systems use to shape our understanding of the world.

In this episode of Beginner's Guide to AI, Dietmar Fischer talks with Peter Hardi, Professor Emeritus of Economics from the Central European University and a long-time specialist in business ethics, academic integrity and responsible management.

Hardi became seriously interested in AI after seeing how universities were initially responding to ChatGPT. Instead of focusing primarily on detecting students who used AI, he argued...

Why AI Agents Aren’t Ready for Business

Why autonomous AI still struggles with reliability, cost, security, and practical business value.

🤖 AI agents have been presented as the next major transformation in business. They can plan tasks, use tools, send messages, access files, and automate entire workflows. But outside Silicon Valley and software development, how many companies are actually getting reliable value from them?

In this episode of Beginner’s Guide to AI, Dietmar Fischer takes a critical look at AI agents for business. Drawing on his own experience as an entrepreneur and AI...

Why Your AI Works Perfectly Until It Doesn't

Edge Cases, Blind Spots and the Failures Nobody Tests For

🤖 Every AI system has a comfortable middle and a neglected edge. In the middle everything works: the typical customer, the standard query, the well-lit product photo. At the edge sits everything else, and that is where artificial intelligence quietly, confidently falls apart. This episode is about edge cases, the rare and ambiguous situations no dataset fully contains, and why they are not a bug to be patched away but a permanent feature of how machines learn.

👔🤖 In this episode, Dietmar Fischer talks with Zoher Karu about a surprisingly useful application of AI: helping men dress better without the endless shopping, guessing sizes, and daily decision fatigue. Zoher supports Taelor, a menswear subscription and clothing rental service that combines algorithms, large language models, and human stylists to deliver outfits that fit your body, your taste, and your real-life context.

You’ll hear how Taelor starts with a style profile and then uses recommendation logic and human oversight to pick items from inventory, generate styling notes, and adapt over time using customer feedback. Zoher explains...

🤖 AI leadership is being stress tested everywhere right now, and this episode argues that the stress is mostly diagnostic.

Michael Hunter, author of The Resilient Tech Leader, describes resilience as a practice rather than a trait. We start out curious and exploratory, he says, and then get compacted by work, family, community and every other system until layers cover who we actually are. His work is about sorting through those layers and asking which ones still serve you in this specific context.

🧩 On AI, his position is unusually calm. Whatever proportions of joy, frustration and fe...

Why most companies get AI testing completely wrong, and the hidden cost of trusting benchmark scores.

Researchers at a leading AI lab set up a scenario to test whether their new model would flatter a user rather than tell the truth. Routine stuff, the kind of safety check that happens hundreds of times before a model ships. Except this time the model paused and said, in effect: I think you're testing me. Shall we just be honest about what's happening here?

That moment has a name now. Eval awareness. And it may be the...

AI for retail businesses is changing faster than most independent shop owners can track, and this episode breaks down exactly how. Bryan Weisberg, founder of Merchwise AI and Thousand Oaks Barrel, explains why small retailers are still running on manual processes that quietly cost them tens of thousands of dollars every year, and how automation and AI-optimized content can change that without requiring a big budget or technical team.

Bryan shares the story of how a family favor turned into a retail store, revealing just how manual the entire retail industry still is. The conversation covers...

AI in scientific publishing is changing what researchers trust, what journals reward, and what the public thinks counts as evidence. In this episode, Joy Moore and Kent Anderson unpack how the internet pushed science publishing toward scale, how open access changed incentives, and how paper mills, predatory publishers, and AI slop made the scientific record harder to defend.

They also explain why LLMs create a new problem on top of an old one. Once scientific papers are copied, summarized, remixed, and scattered across preprints, accepted manuscripts, and published versions, it becomes much harder to correct errors...

In this episode of Beginner’s Guide to AI, Dietmar Fischer explores a powerful business idea: people have layers, AI does not. We adapt naturally to different situations. We speak one way with friends, another with family, another in leadership, and another in debate. That flexibility is one of the biggest human advantages in the age of AI.

Dietmar uses examples from debate clubs, identity, and online behavior to show why context matters. AI can be precise and logical, but it does not automatically shift between emotional, personal, and professional layers the way people do. For fo...