Douglas Rushkoff Quotes

The computer is not, in our opinion, a good model of the mind, but it is as the trumpet is to the orchestra - you really need it. And so, we have very massive simulations in computers because the problem is, of course, very complex.

Machine learning is the science of getting computers to learn without being explicitly programmed.

If you want to solve very complex problems, you will have to end up letting machines work out a lot of the details for themselves, and in ways that we don't understand what they are doing.

Eventually, I believe, current attempts to understand the mind by analogy with man-made computers that can perform superbly some of the same external tasks as conscious beings will be recognized as a gigantic waste of time.

I don't think there's anything unique about human intelligence.

So the thing I realized rather gradually - I must say starting about 20 years ago now that we know about computers and things - there's a possibility of a more general basis for rules to describe nature.

Moore's Law-based technology is so much easier than neuroscience. The brain works in such a different way from the way a computer does.

Machine learning allows us to build software solutions that exceed human understanding and shows us how AI can innervate every industry.

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'm fascinated by artificial intelligence.

Nobody phrases it this way, but I think that artificial intelligence is almost a humanities discipline. It's really an attempt to understand human intelligence and human cognition.

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.

Interactive computers and software will, I think, provide a less costly method of doing some kinds of inquiry, in knowledge acquisition and even reasoning and interaction.

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

I do two things. I design mobile computers and I study brains.

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

In fact, there was general agreement that minds can exist on nonbiological substrates and that algorithms are of central importance to the existence of minds.

If computers remain far worse than us at image recognition, a certain over-confident combination of man and machine can elsewhere take inaccuracy to a whole new level.

Graphics has lately made a great shift towards machine learning, which itself is about understanding data.

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?

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.

I'm working on artificial intelligence. Actually, natural language understanding, which is to get computers to understand the meaning of documents.

Computers have proved to be formidable chess players. In fact, they've beaten our top human chess champions.

The big question society will have to answer is whether it wants computers thinking like humans.

There will always be plenty of things to compute in the detailed affairs of millions of people doing complicated things.