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Scaling Knowledge
The Myth of Artificial Intelligence with Erik J. Larson
Jul 22, 2023
Author Erik J. Larson discusses the unpredictability of invention, limits of deep learning progress, abduction in hypothesis generation, creativity and serendipity, the myth of self-improving machines, combining deep learning and symbolic approaches in AI knowledge.
34:01
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Quick takeaways
- Predicting future technological advancements is flawed due to practical limitations.
- The concept of self-improving machines in artificial intelligence lacks a solid foundation.
Deep dives
The Limitations of Predicting Technological Advancements
In a highly technocratic society, there is a common illusion that people can accurately predict future technological advancements. However, the idea of extrapolating progress is flawed, as it fails to take into account practical limitations. For example, Sam Alman, the head of Opening AI, warned about the practical limitations of training advanced language models like GPT-4 due to the availability of data and computing resources. This highlights the need to be cautious about making future predictions based solely on technological advancements.
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