Towards Data Science

Un pódcast de The TDS team

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131 Episodo

  1. 71. Ben Garfinkel - Superhuman AI and the future of democracy and government

    Publicado: 17/2/2021
  2. 70. Sarah Williams - What does ethical AI even mean?

    Publicado: 10/2/2021
  3. 69. Anders Sandberg - Answering the Fermi Question: Is AI our Great Filter?

    Publicado: 3/2/2021
  4. 68. Silvia Milano - Ethical problems with recommender systems

    Publicado: 27/1/2021
  5. 67. Joaquin Quiñonero-Candela - Responsible AI at Facebook

    Publicado: 20/1/2021
  6. 66. Owain Evans - Predicting the future of AI

    Publicado: 13/1/2021
  7. 65. Helen Toner - The strategic and security implications of AI

    Publicado: 6/1/2021
  8. 64. David Krueger - Managing the incentives of AI

    Publicado: 30/12/2020
  9. 63. Geordie Rose - Will AGI need to be embodied?

    Publicado: 23/12/2020
  10. 62. Nicolai Baldin - AI meets the law: Bias, fairness, privacy and regulation

    Publicado: 16/12/2020
  11. 61. Ben Goertzel - The unorthodox path to AGI

    Publicado: 9/12/2020
  12. 60. Rob Miles - Why should I care about AI safety?

    Publicado: 2/12/2020
  13. 59. Matthew Stewart - Tiny ML and the future of on-device AI

    Publicado: 25/11/2020
  14. 58. David Duvenaud - Using generative models for explainable AI

    Publicado: 18/11/2020
  15. 57. Dylan Hadfield-Menell - Humans in the loop

    Publicado: 11/11/2020
  16. 56. Annette Zimmermann - The ethics of AI

    Publicado: 4/11/2020
  17. 55. Rohin Shah - Effective altruism, AI safety, and learning human preferences from the state of the world

    Publicado: 28/10/2020
  18. 54. Tim Rocktäschel - Deep reinforcement learning, symbolic learning and the road to AGI

    Publicado: 15/10/2020
  19. 53. Edouard Harris - Emerging problems in machine learning: making AI "good"

    Publicado: 8/10/2020
  20. 52. Sanyam Bhutani - Networking like a pro in data science

    Publicado: 23/9/2020

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Note: The TDS podcast's current run has ended. Researchers and business leaders at the forefront of the field unpack the most pressing questions around data science and AI.

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