Fei-Fei Li Quotes

One thing that humans still do better than computers is recognize images.

I think the way we're doing computer vision is just wrong.

Computer vision and machine learning have really started to take off, but for most people, the whole idea of what is a computer seeing when it's looking at an image is relatively obscure.

Understanding vision and building visual systems is really understanding intelligence.

In the past, Google has used teams of humans to 'read' its street address images - in essence, to render images into actionable data. But using neural network technology, the company has trained computers to extract that data automatically - and with a level of accuracy that meets or beats human operators.

As commentators like the American psychologist Gary Marcus have noted, it's extremely difficult to teach a computer to recognise cats. And that's not for want of trying.

A lot of the future of search is going to be about pictures instead of keywords. Computer vision technology is going to be a big deal.

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

My system uses the speed of components in cameras and cell phones to get four inches of depth through the brain.

My Ph.D. is in computer vision and machine learning. I developed software that can read your emotions from your face as part of my doctorate work.

Yes, iD is a machine vision and sensor browser for the physical world. That's what we have been working on with Coca-Cola, Verizon, Bank of America and Disney to launch content when an image is recognised.

People are good at figuring out what's attractive, and computers are good at quickly searching and finding. You put them together, and bang!

When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.

The idea [of the Quantum Computer] is to create a machine that is as intelligence as humans, and probably much more so.

In Silicon Valley, there are a lot of startups using computer vision for agriculture or shopping - there are a lot for clothes shopping. At Baidu, for example, if you find a picture of a movie star, we actually use facial recognition to identify that movie star and then tell you things like their age and hobbies.

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.

There is great potential to use computer vision technology in a constructive and benevolent way.

Deep learning is already working in Google search and in image search; it allows you to image-search a term like 'hug.' It's used to getting you Smart Replies to your Gmail. It's in speech and vision. It will soon be used in machine translation, I believe.

I think the automation of vision is a much bigger deal than the invention of perspective.

The research on vision machines was mainly conducted at the Stanford Research Institute in the US. So, we can say that the events that took place in the Kosovo War were a total confirmation of the thesis of The Vision Machine.

I want to build the next CNN with 'VICE' - it's within my grasp.

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 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.

Computer science is no more about computers than astronomy is about telescopes.