Throughout history, information networks have shaped not only what we know, but also who we are. Now artificial intelligence is building the most powerful information networks in human history. But how do we shape these networks?

Inspired by Yuval Noah Harari's book Nexus, in this episode, we talk about why knowledge ecosystems need diversity, how AI can make decision-making processes more transparent, and how human-machine collaboration can create a new balance.

Links:

• https://fbildirici.github.io
• https://www.ynharari.com/book/nexus/
• https://www.nytimes.com/2024/09/10/books/review/nexus-yuval-noah-harari.html
• https://www.theguardian.com/books/article/2024/sep/10/nexus-a-brief-history-of-information-networks-from-the-stone-age-to-ai-by-yuval-noah-harari-review-rage-against-the-machine

Join us for a groundbreaking episode of Explain the Explainables by your favorite podcast host, Fatih Bildirici PhD(c), unbound where we explore the fascinating world of Large Language Models, starting with the revolutionary 2017 paper "Attention Is All You Need." From its Beatles-inspired title to becoming the foundation of modern AI with over 160,000 citations, we'll uncover how this breakthrough transformed machine learning forever.

In this episode, we dive deep into the history, philosophy and architecture that powers tools like ChatGPT and modern AI systems. Through engaging storytelling and clear examples, we'll explore how machines learned to understand human language, the significance of the Transformer architecture, and what it means for our future.

Whether you're a tech enthusiast or simply curious about AI, this episode offers an accessible journey into one of the most transformative technologies of our time. We'll also feature insights from explainability side.

Don't miss this illuminating exploration of how a single paper revolutionized artificial intelligence and set the stage for the AI revolution we're experiencing today.

Recommended resources:

• Mywebsite: https://fbildirici.github.io
• Andrej Karpathy's Intro to LLMs: https://www.youtube.com/watch?v=zjkBMFhNj_g
• Attention is All You Need: https://arxiv.org/abs/1706.03762
• Explainability of LLMs: https://dl.acm.org/doi/10.1145/3639372

In this episode, we delve deeper into the foundations, history, and current importance of Good Old-Fashioned Artificial Intelligence (GOFAI) and Symbolic AI. Discover the adventure of researchers taking the first steps of artificial intelligence from the 1950s onwards, designing systems based on logic, rules, and symbols to mimic human intelligence.

What Are We Talking About?

• History and Foundations: The birth of GOFAI, the role of the Dartmouth Conference, and the visions of pioneers such as Allen Newell, Herbert Simon, and Marvin Minsky.

• Rise of Expert Systems: The achievements and limitations of landmark projects such as MYCIN (medical diagnostics), DENDRAL (chemical analysis), SHRDLU (natural language processing).

Challenges and AI Winters: Frame Problem (unexpected situations), knowledge representation issues, and disappointments caused by overly optimistic predictions.

• Modern Connections: How GOFAI-inspired Explainable Artificial Intelligence (XAI) and neuro-symbolic systems (deep learning + logic) are creating more transparent and reliable AI.

About Me: https://fbildirici.github.io

Are you ready for the incredible story of,Reinforcement Learning - one of AI's most fascinating fields? In this episode, we're taking you on an extraordinary journey from simple animal experiments tomodern artificial intelligence.

How did a story that began with Pavlov's dogs and Thorndike's curious cats transform into systems that can beatGo champions, drive cars autonomously, and know what you'll want to watch next on Netflix?How did machines learn to learn through trial and error, just like humans do?

We'll discover how video games became the perfect testing ground for AI, explore AlphaGo's creative moves that stunned world champions, and see how this technology is changing our daily lives. From self-driving cars to smart home devices, you'll learn how reinforcement learning is quietly revolutionizing the world around us.

Whether you're an AI enthusiast or simply curious about how machines learn, this episode tells the universal story of learning and growth through an entertaining and thought-provoking journey. If you've ever wondered how the learning machines we've seen in science fiction movies became reality, this episode is for you!

Join us for a fascinating exploration of how simple ideas about reward and punishment evolved into one of the most powerful tools in machine learning & artificial intelligence. Get ready to be amazed by the power of learning through trial and error!

🖖 Vulcan salute from the second episode of Explain the Explainables! Today, we’re taking a deep dive into Mustafa Suleyman’s The Coming Wave, a book that challenges us to think about how rapid advancements in AI and biotechnology are reshaping our world. We’ll explore why it’s becoming harder to explain how these systems work, the risks of their unchecked growth, and what practical steps we can take to ensure that technology remains a force for good.

In this episode, we break down key topics like the “black box” problem in AI, the need for robust safety measures, and the importance of clear, coordinated policies—from technical safety initiatives to international treaties. We’ll also chat about the human side of this revolution: why public understanding and movements are essential to keeping these powerful technologies in check.

Whether you’re a tech leader, a policymaker, or just curious about what the future holds, this podcast offers an engaging and accessible roadmap for riding this incredible, sometimes daunting, wave of innovation. So, sit back, relax, and join us as we explore how we can shape a safe and exciting future together. ☕

Link of the Book: https://the-coming-wave.com

Ever wonder how Ned Ludd and his followers—iconic “machine breakers” of the early nineteenth century—connect to our modern struggles with AI-driven automation? In this episode, we spotlight the thundering events captured in Brian Merchant’s Blood in the Machine, unearthing how the Industrial Revolution’s winners and losers mirror today’s battles over technology’s impact on labor. Then, we examine how Explainable AI (XAI) could prevent us from repeating the mistakes of the past—allowing us to harness cutting-edge tech in ways that genuinely benefit everyone. From factories of 1811 to algorithmic workplaces of now, join us as we unravel who truly gains from these transformations—and how we can ensure it’s all of us.

Genesis—every story has one, and ours begins right here. I’m Fatih, your host for Explain The Explainables, where we trace the arc of innovation from its earliest sparks to today’s AI revolution. Join me as we uncover the myths, the machines, and the minds behind our most transformative technologies—and discover how explainability can light the way forward. Welcome to our genesis—let’s shape the future together.