The role of radiologists will evolve from doing perceptual things that could probably be done by a highly trained pigeon to doing far more cognitive things.
Geoffrey HintonRead
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.
Interpretation
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.
In practice
In a talk about the future of technology, this quote illustrates the necessity of learning algorithms in AI.
The role of radiologists will evolve from doing perceptual things that could probably be done by a highly trained pigeon to doing far more cognitive things.
Everybody right now, they look at the current technology, and they think, 'OK, that's what artificial neural nets are.' And they don't realize how arbitrary it is. We just made it up! And there's no reason why we shouldn't make up something else.
In the long run, curiosity-driven research just works better... Real breakthroughs come from people focusing on what they're excited about.
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.
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.
In a sensibly organised society, if you improve productivity, there is room for everybody to benefit.
I get hired by companies to hack into their systems and break into their physical facilities to find security holes. Our success rate is 100%; we've always found a hole.
I love what the Valley does. I love company building. I love startups. I love technology companies. I love new technology. I love this process of invention. Being able to participate in that as a founder and a product creator, or as an investor or a board member, I just find that hugely satisfying.
Revolutionary products don't fail because they are shipped too early. They fail because they aren't revised fast enough.
The greatest single programming language ever designed
The speed of communications is wondrous to behold. It is also true that speed can multiply the distribution of information that we know to be untrue.
We're all vulnerable to social approval. The need to belong, to be approved or appreciated by our peers is among the highest human motivations. But now our social approval is in the hands of tech companies.
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