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PODCAST

pplpod

pplpod is a podcast about people, places and lots of other stuff. Each episode takes a deep dive into the lives, choices, and legacies of fascinating figures from history, culture, music, and beyond. From icons who shaped entire generations to hidden stories that deserve the spotlight, pplpod brings you closer to the people behind the headlines and the legends.Thoughtful, engaging, and story-driven, pplpod explores what makes these lives extraordinary—and what we can learn from them today.

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All Episodes

22:42

How AI designs its own brain

pplpod ·

2026/04/03

The concept of neural architecture search deconstructs the transition from human-designed intelligence to systems that can design themselves, revealing how artificial intelligence is beginning to automate its own evolution. This episode of pplpod analyzes the rise of NAS, exploring the shift away from human intuition, the mechanics of automated design, and the profound implications of machines building better machines. We begin our investigation by stripping away the assumption that engineers

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21:59

How AI Finds the Global Minimum

pplpod ·

2026/04/03

The concept of gradient descent deconstructs the transition from abstract mathematics to the invisible engine powering nearly every modern AI system, revealing how machines learn by repeatedly moving from error toward accuracy. This episode of pplpod analyzes the evolution of gradient descent, exploring the geometry of optimization, the tradeoffs between speed and precision, and the profound idea that intelligence can emerge from simple, repeated adjustments. We begin our investigation by stripping

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20:29

How AI identifies objects never seen before

pplpod ·

2026/04/03

The concept of zero-shot learning deconstructs the transition from experience-bound intelligence to a radically more flexible system—one that can recognize what it has never seen. This episode of pplpod analyzes the evolution of zero-shot learning, exploring how machines bridge knowledge gaps, the role of language as a computational shortcut, and the deeper implication that intelligence may be less about memory and more about inference. We begin our investigation by stripping away the assumption

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21:18

How AI Learns By Questioning Humans

pplpod ·

2026/04/03

The concept of active learning deconstructs the transition from brute-force data consumption to a far more strategic and human-aligned model of intelligence, where machines don’t just absorb information—they decide what is worth learning. This episode of pplpod analyzes the evolution of active learning, exploring the economics of human expertise, the mathematics of uncertainty, and the unsettling reality that intelligence may depend more on asking the right questions than having the right answers

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20:05

How AI learns how to learn

pplpod ·

2026/04/03

An AI system can crush the world's greatest chess grandmasters, processing millions of positions per second with superhuman precision. But show that same system a simple card game it's never seen before, and it's completely helpless — no better than random guessing. The gap between narrow expertise and genuine adaptability is the central challenge of modern AI, and meta-learning is the field trying to close it.This episode explores meta-learning in computer science — the paradigm shift from AI that

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22:42

How AI learns without human labels

pplpod ·

2026/04/03

A toddler doesn't need someone constantly whispering "this is a dog, this is not a dog" to learn about the world. Babies observe, interact, and discover structural patterns entirely on their own — using the raw environment as their curriculum. Yet for decades, AI couldn't do this at all. Every training dataset required painstaking human labeling, creating a bottleneck that limited what machine learning could accomplish. This episode explains how that bottleneck was finally broken.We explore

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24:22

How AI learns without seeing your data

pplpod ·

2026/04/03

To build a brilliant AI, the conventional wisdom has been simple: feed it an ocean of personal data. Your text messages, health records, location history, browsing habits — all sucked into a massive centralized server farm where algorithms chew through it to get smarter. For years, surrendering your privacy was the assumed price of machine intelligence. But what if that assumption is wrong?This episode explores federated learning, a privacy-preserving approach to machine learning that trains AI

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24:06

How AI Masters Unpredictable Reality

pplpod ·

2026/04/03

Traditional software follows a recipe: if this condition is met, execute this command. The boundaries are rigid, predictable, and entirely defined by the human engineer who wrote the code. But when AI has to navigate messy, unpredictable reality — environments where the rules change, the terrain shifts, and the right answer isn't known in advance — that recipe book becomes useless.This episode explores reinforcement learning (RL), the branch of AI that teaches machines to master unpredictable

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21:48

How AI models recycle knowledge

pplpod ·

2026/04/03

Imagine waking up every morning with total amnesia — relearning the concept of gravity before you can get out of bed, relearning friction before you can turn a doorknob. By the time you've rebuilt the basic rules of reality, the day is over and you've accomplished nothing. For a long time, that was the reality of artificial intelligence: every new task required training a model from absolute zero.Transfer learning changed everything, and this episode explains how. We break down the technique that

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20:46

How AI Navigates Infinite Decision Trees

pplpod ·

2026/04/03

Imagine mapping every possible route for a cross-country road trip — not just the highways, but every dirt road, wrong turn, scenic bypass, and gas station stop. The number of possible paths would dwarf the number of atoms in the observable universe. You'd never leave the driveway. Yet AI systems navigate decision spaces this vast every day, and this episode explains how.We explore Monte Carlo tree search (MCTS) and related algorithms that allow AI to make intelligent decisions in impossibly large

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26:36

How AI Outgrew The Prompt Engineer

pplpod ·

2026/04/03

Everyone who has used ChatGPT, Claude, or any generative AI tool knows the frustration: you sit at your computer, stare at a blinking cursor, and try to find the exact magic words that will make the AI do what you actually want. Misphrasing a single sentence can produce wildly different results. It feels less like using software and more like casting a volatile spell. This episode explores why — and where prompt engineering is headed.We trace the rapid rise and evolution of prompt engineering, the

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16:00

How AI turns static into images

pplpod ·

2026/04/03

Those hyper-realistic AI-generated images flooding your social media feed — the surreal digital paintings, the photorealistic deepfakes, the absurd mash-ups of astronaut cats on Mars — all start from the same place: pure random noise. Static. And somehow, through a process that feels like magic, a neural network sculpts that chaos into coherent, detailed imagery. This episode explains exactly how.We break down diffusion models, the AI architecture behind tools like Stable Diffusion, DALL-E, and

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18:46

How AI Understands the World

pplpod ·

2026/04/03

When you save a photo of your dog to your phone, the computer stores ones and zeros. It has no idea what a golden retriever is. Teaching machines to actually understand the world — not just file data about it — is arguably the defining challenge of artificial intelligence, and this episode explains how researchers have been tackling it for decades.We take a deep dive into knowledge representation and reasoning (KRR), the branch of AI concerned with encoding real-world knowledge in formats that

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25:53

How algorithms automate human prejudice

pplpod ·

2026/04/03

In the early 1980s, a computer at St. George's Hospital Medical School in London was automatically rejecting qualified applicants — not because they lacked credentials, but because their names sounded foreign. The algorithm had learned to discriminate by studying years of human admissions decisions, and nobody caught it for years. This episode examines how automated systems don't just reflect human prejudice — they industrialize it.We start with the St. George's case as a concrete entry point into

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22:43

How algorithms inherit human bias

pplpod ·

2026/04/03

The math equation deciding whether you get a mortgage, a job interview, or adequate medical care might be actively prejudiced against you — and nobody programmed it to be. This episode explores one of the most urgent problems in modern technology: how algorithms trained on historical data systematically inherit and amplify the biases of the humans who created that data.We break down the mechanics of algorithmic bias from the ground up, starting with a counterintuitive truth: computers aren't

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21:26

How Alpha-beta pruning accelerates complex decisions

pplpod ·

2026/04/03

There are more possible chess games than atoms in the observable universe. If a computer tried to calculate every single move by brute force, the universe would go cold and dark before it made its first decision. Yet a chess app on your phone can checkmate you in three seconds. The secret isn't raw computing power — it's a brilliantly simple algorithm called alpha-beta pruning.This episode explains how alpha-beta pruning works and why it represents a fundamental philosophical shift in how machines

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21:13

How Archie Leach invented Cary Grant

pplpod ·

2026/04/03

The man who taught Hollywood how romance should look on screen grew up believing his mother was dead. He only discovered, more than two decades later, that she had been locked in an asylum by his own father. This episode isn't a celebrity biography — it's the deconstruction of what might be the most extraordinary act of psychological self-invention in entertainment history.Born Archibald Alexander Leach in Bristol, England in 1904, the future Cary Grant endured a childhood defined by poverty,

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20:37

How ASA built the student loan system

pplpod ·

2026/04/03

The story of American Student Assistance deconstructs the transition from community-driven access to higher education to a multi-billion-dollar system that reshaped how Americans pay for opportunity. This episode of pplpod analyzes the evolution of ASA, exploring the hidden architecture of student loans, the shifting balance between public and private power, and the radical transformation from debt guarantor to workforce investor. We begin our investigation by stripping away the assumption that

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21:11

How ASA reshaped the student loan industry

pplpod ·

2026/04/03

The story of American Student Assistance deconstructs the transition from community-driven access to higher education to a multi-billion-dollar system that reshaped how Americans pay for opportunity. This episode of pplpod analyzes the evolution of ASA, exploring the hidden architecture of student loans, the shifting balance between public and private power, and the radical transformation from debt guarantor to workforce investor. We begin our investigation by stripping away the assumption that

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22:47

How Autoencoders Turn Compression Into Creation

pplpod ·

2026/04/03

Right now, one AI is designing cancer-fighting drug molecules no human chemist has ever imagined. Another is generating a photorealistic image of a cat riding a skateboard. These outputs seem worlds apart, but the core engine driving both is the same: an autoencoder, a neural network architecture that learns by compressing information down to its absolute essence and then rebuilding it from scratch.This episode takes you behind the curtain of one of deep learning's most versatile building blocks. We

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7,536 results

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