François Chollet: Scientific Progress is Not Exponential | AI Podcast Clips | Summary and Q&A

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October 9, 2019
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Lex Fridman
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François Chollet: Scientific Progress is Not Exponential | AI Podcast Clips

TL;DR

Intelligence explosion, the belief that AI will exponentially increase its capabilities, is unlikely due to the inherent limitations and exponential friction in problem-solving systems like science, where resource consumption increases exponentially while progress remains linear.

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Questions & Answers

Q: What is the correlation between resource consumption and scientific progress?

Resource consumption in science, such as the number of papers published and patents filed, is increasing exponentially, but the progress in terms of the significance of discoveries remains linear, indicating that resource consumption is not directly linked to the advancement of knowledge.

Q: How does scientific progress compare to technological progress?

Scientific progress, which feeds into technological progress, has not shown exponential growth over time. While technology has enabled faster communication and networking among scientists, the overall progress remains linear, as measured by the temporal density of significant discoveries.

Q: Why does progress become exponentially more difficult in a given field?

As a field or system makes progress, low-hanging fruit and easier discoveries are already made, requiring subsequent researchers to dig deeper and work harder to achieve smaller discoveries. This results in the need for a greater number of researchers and resources to maintain the same level of impact.

Q: Is the exponential increase in AI research papers indicative of exponential progress?

No, the exponential increase in AI research papers does not necessarily correspond to exponential progress. Significance in deep learning ideas may even be decreasing, indicating that the overall progress in the field remains linear when considering the importance of discoveries.

Q: How does the concept of exponential friction apply to AI systems?

Like any problem-solving system, AI systems will also encounter exponential friction. As progress is made, it becomes exponentially more difficult to develop new ideas, requiring exponential amounts of resources and expertise. This friction prevents an intelligence explosion, as the system adjusts to maintain linear progress.

Summary & Key Takeaways

  • Intelligence explosion is not possible due to the inherent limitations and exponential friction in problem-solving systems, such as science.

  • While resource consumption in science is exponentially increasing, scientific progress remains linear, as measured by the significance of discoveries.

  • As a system makes progress, it becomes exponentially more difficult to make further progress, requiring a larger number of researchers and resources.

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