Howard Rheingold Quotes

We often attribute 'understanding' and other cognitive predicates by metaphor and analogy to cars, adding machines, and other artifacts, but nothing is proved by such attributions.

I've come to a view that humans will continue to do what we do well, and that computers will continue to do what they do very well, and the two will coexist, but in different spaces.

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

Some claim that computers will, by 2050, achieve human capabilities. Of course, in some respects they already have.

People assume that computers will do everything that humans do. Not good. People are different from each other and they are all really different from computers.

Even though chess isn't the toughest thing that computers will tackle for centuries, it stood as a handy symbol for human intelligence. No matter what human-like feat computers perform in the future, the Deep Blue match demands an indelible dot on all timelines of AI progress.

Understanding of natural language is what sometimes is called 'AI complete,' meaning if you can really do that, you can probably solve artificial intelligence.

Things that are so hard for people, like playing championship-level Go and poker, have turned out to be relatively easy for the machines. Yet at the same time, the things that are easiest for a person - like making sense of what they see in front of them, speaking in their mother tongue - the machines really struggle with.

A computer can have so much more in its brain that a human can.

Effective translation of natural languages comes awfully close to requiring a sentient translator program.

The brain can be seen as a complex machine, like a gooey computer.

The largest and most powerful computers are still no match for the smallest and weakest humans.

Until computers and robots make quantum advances, they basically remain adding machines: capable only of doing things in which all the variables are controlled and predictable.

The problem with Google is you have 360 degrees of omnidirectional information on a linear basis, but the algorithms for irony and ambiguity are not there. And those are the algorithms of wisdom.

We think of computers as smart and powerful machines. But your goldfish is smarter.

I think a lot of jobs, with that additional artificial intelligence, we can augment human capabilities and impact.

There's a lot that machine learning can't do that humans can do very, very well.

Computers will understand sarcasm before Americans do.

Humans are still much better than computers at recognizing speech.

Early AI was mainly based on logic. You're trying to make computers that reason like people. The second route is from biology: You're trying to make computers that can perceive and act and adapt like animals.

The only path to build intelligent machines is to enable it with powerful visual intelligence, just like what animals did in evolution.

Once you acknowledge that human brains are basically made of atoms and acknowledge that atoms are governed by simple laws of physics, then there is no reasoning principle why computers couldn't do anything that people are doing, and we don't really see any evidence that this is not the case.

Artificial intelligence is the science of making machines do things that would require intelligence if done by men.