David Sarnoff Quotes

By 2020, most home computers will have the computing power of a human brain. That doesn't mean that they are brains, but it means that in terms of raw processing, they can process bits as fast as a brain can. So the question is, how far behind that is the development of a machine that's as smart as we are?

The human brain has an amazing ability for pattern recognition, sometimes even better than a computer.

Twenty-five years ago, the notion was you could create a general problem-solver software that could solve problems in many different domains. That just turned out to be totally wrong.

There is a real danger that computers will develop intelligence and take over. We urgently need to develop direct connections to the brain so that computers can add to human intelligence rather than be in opposition.

The human brain is an incredible pattern-matching machine.

Mimicking the intricacies of the human brain, a neuro-inspired computer would work in a fashion similar to the way neurons and synapses communicate. It could potentially learn or develop memory.

It seems like everything that we see perceived in the brain before we actually use our own eyes, that everything we see is coming through computers or machines and then is being input in our brain cells. So that really worries me.

We could construct a machine that is more intelligent than we can understand. It's possible Google is that kind of thing already. It scales so fast.

Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.

The key to artificial intelligence has always been the representation.

Is artificial intelligence less than our intelligence?

This is a magical time for computer programming. We are moving towards the artifical intelligence holy grail of programming the computer to simulate the human brain.

The degree of intelligence that a man or a machine can show depends on many qualities of the ways that knowledge, goals, and problem-solving techniques are represented and put together, and not so much on the fine details.

In order to be truly intelligent, computers must understand - that is probably the critical word.

It struck me deep in my mind. Some day, the chip is going to surpass mankind's brain.

One of the interesting applications of symbolic systems is artificial intelligence, and I spent some time thinking about how to create a brain that operates the way ours does.

The brain has about ten thousand parameters for every second of experience. We do not really have much experience about how systems like that work or how to make them be so good at finding structure in data.

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.

I think that what the machines can do, of course, is wonderful, but it's not the same as what the brain can do.

If you just have a single problem to solve, then fine, go ahead and use a neural network. But if you want to do science and understand how to choose architectures, or how to go to a new problem, you have to understand what different architectures can and cannot do.

I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.

The real goal of AI is to understand and build devices that can perceive, reason, act, and learn at least as well as we can.

I think what's really amazing is that given the scale of the web and getting the compute power we have today, we're starting to see things that appear intelligent but actually aren't semantically intelligent.

Supercomputers will achieve one human brain capacity by 2010, and personal computers will do so by about 2020.

Because I believe that humans are computers, I conjectured that computers, like people, can have left- and right-handed versions.