エピソード

  • EP25 - The Alignment Problem: Ensuring a Safe and Beneficial Future

    EP25 - The Alignment Problem: Ensuring a Safe and Beneficial Future
    2025/10/30
    In our series finale, we tackle the most critical challenge in artificial intelligence: the alignment problem. As AI systems surpass human capabilities, how do we ensure their goals, values, and objectives remain aligned with our own? This episode explores the profound difference between what we tell an AI to do and what we actually mean, and why solving this is the final, essential step in building a safe and beneficial AI future.
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    43 分
  • EP24 - AI Ethics: Decoding Algorithmic Bias, Fairness, and Accountability

    EP24 - AI Ethics: Decoding Algorithmic Bias, Fairness, and Accountability
    2025/10/25
    AI systems are not neutral. This episode moves from technical mechanisms to societal impact, exploring how algorithmic bias arises from human data and design. We will deconstruct real-world cases of AI-driven discrimination in hiring, justice, and healthcare, and then establish the core principles of fairness, transparency, and accountability required to build responsible and ethical AI.
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    34 分
  • EP23 - Generative AI (Part 2): Diffusion Models and the Art of Denoising

    EP23 - Generative AI (Part 2): Diffusion Models and the Art of Denoising
    2025/10/18
    We deconstruct the generative AI revolution behind DALL-E, Midjourney, and Stable Diffusion. This episode explores Diffusion Models, explaining the elegant, two-part process of destroying an image with noise and training a network to meticulously reverse the damage, sculpting order from chaos. This is the engine of modern AI image generation.
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    39 分
  • EP22 - Generative AI Part 1: GAN and VAE Creative Architectures

    EP22 - Generative AI Part 1: GAN and VAE Creative Architectures
    2025/10/11
    We move beyond AI that analyzes and into AI that *creates*. This episode deconstructs the two foundational models of generative AI: Generative Adversarial Networks (GANs), which learn through a "forger and detective" game, and Variational Autoencoders (VAEs), which learn to create by mastering compression.
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    22 分
  • EP21 - Large Language Models and The Power of Scale

    EP21 - Large Language Models and The Power of Scale
    2025/10/04
    This episode moves from the Transformer architecture to the models that define our era: Large Language Models (LLMs). We explore how the simple act of "next-word prediction," when combined with internet-scale data and massive compute, leads to the surprising "emergent abilities" of models like GPT-4, and we break down the crucial training paradigm of pre-training and fine-tuning.
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    32 分
  • EP20 - The Transformer Architecture: Attention is All You Need

    EP20 - The Transformer Architecture: Attention is All You Need
    2025/09/27
    This episode deconstructs the 2017 paper that revolutionized AI. We go "under the hood" of the Transformer architecture, moving beyond the sequential bottleneck of RNNs to understand its parallel processing and the core mechanism of self-attention. Learn how Queries, Keys, and Values enable the powerful contextual understanding that powers all modern Large Language Models.
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    28 分
  • EP19 - Robotics and Embodied AI: Giving AI a Body

    EP19 - Robotics and Embodied AI: Giving AI a Body
    2025/09/20
    We move AI from the abstract world of data to the physical world of matter. This episode deconstructs Embodied AI, exploring the deep connection between intelligence, a physical body, and real-world interaction. Discover how robots use perception, planning, control, and learning to bridge the gap between digital code and physical action.
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    40 分
  • EP18 - LSTMs and the Vanishing Gradient: Solving AI's Long-Term Memory Problem

    EP18 - LSTMs and the Vanishing Gradient: Solving AI's Long-Term Memory Problem
    2025/09/13
    Simple RNNs are fatally flawed; they have the memory of a goldfish. This episode dives "under the hood" to diagnose the "vanishing gradient problem" that causes this amnesia and systematically deconstructs its solution: the Long Short-Term Memory (LSTM) network. You will learn how the LSTM's brilliant "gate" system acts as a managed memory controller, enabling AI to finally learn and connect ideas across long sequences.
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    33 分