Big Technology Podcast Getting AI To Think And Learn Like Humans — With Daniel Kahneman and Yann LeCun
Dec 8, 2021
Join Nobel laureate Daniel Kahneman, a master of human decision-making, and Yann LeCun, the visionary chief AI scientist at Meta, as they explore the fascinating intersection of AI and human cognition. They delve into how machines can learn, the challenges of aligning AI with human reasoning, and the role of predictive coding in both realms. Discover the implications of deep learning on facial recognition and the hurdles AI faces in understanding context, showcasing a compelling dialogue about intelligence's future.
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Learning-Based Intelligence
- Yann LeCun believes that building intelligent machines requires a learning-based approach.
- He emphasizes the importance of learning, particularly self-supervised learning, as crucial for AI development.
Predictive Representation
- Daniel Kahneman highlights that humans possess a representation of the world that enables prediction.
- This representation, formed through System 1 thinking, allows us to make sense of events and often feel unsurprised.
Humans vs. AI Learning
- LeCun points out the brittleness of specialized AI systems compared to humans' ability to learn quickly.
- He emphasizes the role of background knowledge and intuitive physics in human learning.
