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Sutton’s “dead end” argument for LLMs
In this episode of "AI in 5,4,3,2,1," Dominic, founder of 'Leaders of AI,' shines a light on an intriguing controversy in the world of Artificial Intelligence: Are large language models the right path or merely imitators of human knowledge? This discussion leads us into new horizons for learning in AI.
- Richard Sutton, a pioneer of reinforcement learning, questions the scaling of large language models.
- Comparison with a chef: Theory vs. practical experience in reality.
- Introduction of a new approach called "Oak," an autonomous, self-learning agent.
- Paradigm shift: From rigid models to dynamic, continuously learning systems.
More info can be found at: https://www.youtube.com/live/XqYTQfQeMrE?t=22620s
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By Dominic von ProeckIn this episode of "AI in 5,4,3,2,1," Dominic, founder of 'Leaders of AI,' shines a light on an intriguing controversy in the world of Artificial Intelligence: Are large language models the right path or merely imitators of human knowledge? This discussion leads us into new horizons for learning in AI.
- Richard Sutton, a pioneer of reinforcement learning, questions the scaling of large language models.
- Comparison with a chef: Theory vs. practical experience in reality.
- Introduction of a new approach called "Oak," an autonomous, self-learning agent.
- Paradigm shift: From rigid models to dynamic, continuously learning systems.
More info can be found at: https://www.youtube.com/live/XqYTQfQeMrE?t=22620s