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
I had a stormy graduate career, where every week we would have a shouting match. I kept doing deals where I would say, 'Okay, let me do neural nets for another six months, and I will prove to you they work.' At the end of the six months, I would say, 'Yeah, but I am almost there. Give me another six months.'
Interpretation
This quote reflects the challenges faced during a graduate career and the persistence required in research.
Geoffrey Hinton describes the tumultuous nature of his graduate studies, characterized by conflicts and the need to continually advocate for the potential of neural networks. Despite facing skepticism, he demonstrates determination, negotiating additional time to prove the validity of his work, which highlights the resilience and commitment often necessary in academic and scientific endeavors.
In practice
During a conference on artificial intelligence, one might use this quote to illustrate the persistence required in research.
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.
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.
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.
By asking a novel question that you don't know the answer to, you discover whether you can formulate a way of finding the answer, and you stretch your own mind, and very often you learn something new.
Books wrote our life story, and as they accumulated on our shelves (and on our windowsills, and underneath our sofa, and on top of our refrigerator), they became chapters in it themselves.
Sure, it's simple, writing for kids... Just as simple as bringing them up.
There is something so deeply visceral about libraries for me-rooms and rooms full of people dreaming and remembering.
Further Education should be about the ability to learn, not the ability to pay - everyone who is able should have the opportunity, regardless of their family background. I don't want to see students struggling with huge debts or frightened off even going to university in the first place.
A writer should get as much education as possible, but just going to school is not enough; if it were, all owners of doctorates would be inspired writers.
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