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Most people in AI, particularly the younger ones, now believe that if you want a system that has a lot of knowledge in, like an amount of knowledge that would take millions of bits to quantify, the only way to get a good system with all that knowledge in it is to make it learn it. You are not going to be able to put it in by hand.
Geoffrey Hinton
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Interpretation

What this quote means

Knowledge in AI systems is best acquired through learning rather than manual input.

Geoffrey Hinton emphasizes that modern artificial intelligence, especially in its more advanced forms, relies on learning from vast amounts of data rather than being manually programmed with information. This perspective reflects a significant shift in how knowledge is integrated into systems, showcasing the necessity of machine learning to achieve the complexity of understanding required for sophisticated AI applications.

Themes

Artificial IntelligenceMachine LearningKnowledgeDataAutomation

In practice

Example use cases

In a talk about the future of technology, this quote illustrates the necessity of learning algorithms in AI.

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In the long run, curiosity-driven research just works better... Real breakthroughs come from people focusing on what they're excited about.
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In science, you can say things that seem crazy, but in the long run, they can turn out to be right. We can get really good evidence, and in the end, the community will come around.
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I have always been convinced that the only way to get artificial intelligence to work is to do the computation in a way similar to the human brain. That is the goal I have been pursuing. We are making progress, though we still have lots to learn about how the brain actually works.
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In a sensibly organised society, if you improve productivity, there is room for everybody to benefit.
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