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    AI Revolution: Promise, Peril, and Human Wisdom

    17 min
    |
    |
    10 de dez. de 2025
    AIPhilosophyTechnology

    Nia and Eli explore the transformative world of AI and machine learning, from neural networks to algorithmic bias. They reveal how these powerful systems learn, where they fail, and why human wisdom remains essential in our AI-driven future.

    AI Revolution: Promise, Peril, and Human Wisdom

    Melhor citação de AI Revolution: Promise, Peril, and Human Wisdom

    “

    The alignment problem isn't just about making machines safe; it's about understanding ourselves clearly enough to build technology that amplifies our best qualities rather than our worst.

    ”

    Esta aula em áudio foi criada por um membro da comunidade BeFreed

    Pergunta de entrada

    AI and ML

    Vozes dos apresentadores
    Niaplay
    Eliplay
    Fontes de conhecimento
    Hands-on Machine Learning With Scikit-learn And Tensorflow
    Make your own neural network
    Keras Reinforcement Learning Projects
    The Alignment Problem
    Weapons of Math Destruction
    AI Snake Oil

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    "Perfect balance between learning and entertainment. Finished ‘Thinking, Fast and Slow’ on my commute this week."

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    Pontos-chave

    1

    Opening and Welcome

    0:00
    0:18
    0:41
    2

    Setting the Stage: The AI Revolution Unfolding

    1:01
    1:29
    1:50
    2:08
    3

    Understanding the Learning Landscape

    2:30
    2:52
    2:59
    3:19
    1:50
    3:59
    4

    The Foundation: Data Quality and Real-World Challenges

    4:13
    4:34
    4:49
    5:12
    5:33
    0:41
    5

    When Algorithms Make Life-Changing Decisions

    6:09
    6:29
    6:34
    6:53
    7:13
    7:33
    7:47
    6

    The Neural Network Revolution: Promise and Peril

    8:07
    8:25
    8:48
    8:58
    9:15
    9:30
    7

    Beyond Prediction: The Rise of Curious Machines

    9:51
    10:08
    10:31
    7:47
    11:00
    8

    The Wisdom of Uncertainty and Human Values

    11:20
    11:43
    7:47
    12:02
    12:58
    13:18
    9

    Separating Hype from Reality: Practical Applications

    1:50
    14:02
    7:47
    14:36
    8:58
    10

    Charting Our Path Forward

    15:07
    12:58
    15:53
    16:10
    16:27
    16:48

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