Geoffrey Hinton Quotes

I'm very interested in voice synthesis and vocoders in general.

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.

When I was building robots in the early 1990s, the problems of voice recognition, image understanding, VOIP, even touchscreen technologies - these were robotics problems.

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?

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

Why did Google, for example, recently decide to offer free 411 service? I haven't talked to people at Google, but it's pretty clear to me why. It's because of speech recognition. It has nothing to do with 411 service: it has to do with getting a database of voices, so they don't have to license speech technology from Nuance or someone else.

Google, as usual, is one step ahead of everyone and provided the means where all videos on YouTube can be automatically captioned through voice-recognition technology without having to be told that it's the responsible thing to do.

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.

I want to be able to speak with errors in my wording, errors in my grammar. When you type things into Google search, it corrects your words. With speech, I want it to be general enough, smart enough, to know 'No, he couldn't have meant these words that I think he said. He must have really meant something similar.'

In real life, I'm the kind of person that if I use Siri, I thank her afterwards.

Imagine if we can just talk to our computers and have it understand, 'Please schedule a meeting with Bob for next week.' Or if each child could have a personalized tutor. Or if self-driving cars could save all of us hours of driving.

The two things I'm most excited about are self-driving cars and speech. Speech doesn't sound like that much, but it's one of those technologies with the potential to change everything. Steve Jobs didn't invent the touch screen. He just made it work very well, and that's changed everything.

Around my neighborhood, I'm known as the American who talks to her computer while she types.

When you go to a voice-based interaction, you can't tell people, 'Ask me this question and structure it in this way.' And if they ask a question, and you have a bad answer, first time, maybe they'll be okay with it. Third time, they're going to say, 'This is a complete waste of time. I'm going away.'

Computers will understand sarcasm before Americans do.

After an afternoon of interviewing Siri it turns out there are millions of questions that it can't or won't answer: How did you get my phone number? How many Siris are there? Did you have a Christmas party? Who is playing the tiny xylophone before and after each interaction? Are you spying on us, plotting the downfall of our species?

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.

Computers are getting smarter all the time. Scientists tell us that soon they will be able to talk to us. (And by 'they', I mean 'computers'. I doubt scientists will ever be able to talk to us.)

AI - not so some kind of far-off thing. It's part of our lives now, from your phone to everything you do. It makes our lives easier in a lot of ways.

To make real progress in A.I., we have to overcome the big challenges in the area of common sense.

Most of the value of deep learning today is in narrow domains where you can get a lot of data. Here's one example of something it cannot do: have a meaningful conversation.

The future of Windows is to let the computer see, listen and even learn.

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.

We're making progress, but getting machines to replicate our ability to perceive and manipulate the world remains incredibly hard.

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.