Noreena Hertz Quotes

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

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

Making AI more sensitive to the full scope of human thought is no simple task. The solutions are likely to require insights derived from fields beyond computer science, which means programmers will have to learn to collaborate more often with experts in other domains.

Computers ought to help people find their own best path through lots of textual information.

We've seen computers play chess and beat grand masters. We've seen computers drive a car across a desert. But interestingly, playing chess is easy, but having a conversation about nothing is really difficult for a computer.

My mission at Google is to develop natural language understanding with a team and in collaboration with other researchers at Google.

Everyone talks about how much data's in the world. Except, actually, 80% of it is pretty blind to computers. I mean, it can store it. But if it's a movie, a poem, a song, it doesn't know what it's actually saying or doing.

I believe this artificial intelligence is going to be our partner. If we misuse it, it will be a risk. If we use it right, it can be our partner.

Artificial intelligence is one of 50 things that Watson does. There is also machine learning, text-to-speech, speech-to-text, and different analytical engines - they're like little Lego bricks. You can put intelligence in any product or any process you have.

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.

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

Computers will understand sarcasm before Americans do.

One of our big goals in search is to make search that really understands exactly what you want, understands everything in the world. As computer scientists, we call that 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.

The sad thing about artificial intelligence is that it lacks artifice and therefore intelligence.

Continuing on my theme of backing inclusive innovations, I am optimistic of the success of Uniphore. Man-machine communication is one of the more complex problems to solve. Uniphore's vision lends possibility of finding a solution to this very difficult problem, and the company has already made substantial progress.

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.

By 2029, computers will have emotional intelligence and be convincing as people.

It would help if human experts agreed on the meaning of such basic terms as intelligence, consciousness, or awareness. They don't. It's hard to build something that's incompletely defined.

I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence.

Search is an unsolved problem.

My car and my adding machine understand nothing: they are not in that line of business.

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

With the headset and motion tracker and all kinds of different future tracking technologies that we are R&Ding, there is just a huge amount of intelligence that has to be created. So we are looking at hiring some of the brightest minds out there to tackle some of those challenges and deliver the very best experience possible for the consumer.

The thing that's going to make artificial intelligence so powerful is its ability to learn, and the way AI learns is to look at human culture.