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.
The goal of Tesla is to accelerate sustainable energy, so we're going to take a step back and think about what's most likely to achieve that goal.
Software is eating the world, but AI is going to eat software.
If, at any moment, reality gets dull or boring, our phone offers something more pleasurable, more productive and even more educational than whatever reality gives us.
With the development of the Internet...we are in the middle of the most transforming technological event since the capture of fire. I used to think that it was just the biggest thing since Gutenberg, but now I think you have to go back farther.
By 2010 computers will disappear. They'll be so small, they'll be embedded in our clothing, in our environment. Images will be written directly to our retina, providing full-immersion virtual reality, augmented real reality. We'll be interacting with virtual personalities.
By his very success in inventing labor-saving devices, modern man has manufactured an abyss of boredom that only the privileged classes in earlier civilizations have ever fathomed.
Subscribe for the occasional hand-picked quote. No noise.