#74 – Michael I. Jordan: Machine Learning, Recommender Systems, and the Future of AI

Michael I. Jordan is a professor at Berkeley, and one of the most
influential people in the history of machine learning, statistics,
and artificial intelligence. He has been cited over 170,000 times
and has mentored many of the world-class researchers defining the
field of AI today, including Andrew Ng, Zoubin Ghahramani, Ben
Taskar, and Yoshua Bengio. EPISODE LINKS: (Blog post) Artificial
Intelligence—The Revolution Hasn’t Happened Yet This conversation
is part of the Artificial Intelligence podcast. If you would
like to get more information about this podcast go to
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Here's the outline of the episode. On some podcast players you
should be able to click the timestamp to jump to that time.
OUTLINE: 00:00 - Introduction 03:02 - How far are we in development
of AI? 08:25 - Neuralink and brain-computer interfaces 14:49 - The
term "artificial intelligence" 19:00 - Does science progress by
ideas or personalities? 19:55 - Disagreement with Yann LeCun 23:53
- Recommender systems and distributed decision-making at scale
43:34 - Facebook, privacy, and trust 1:01:11 - Are human beings
fundamentally good? 1:02:32 - Can a human life and society be
modeled as an optimization problem? 1:04:27 - Is the world
deterministic? 1:04:59 - Role of optimization in multi-agent
systems 1:09:52 - Optimization of neural networks 1:16:08 -
Beautiful idea in optimization: Nesterov acceleration 1:19:02 -
What is statistics? 1:29:21 - What is intelligence? 1:37:01 -
Advice for students 1:39:57 - Which language is more beautiful:
English or French?