Om Malik Quotes

The computer can do a much better job than the human eye, as it is much more systematic in analysing tissues.

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

Take a picture of this so Isaac can see it when they invent robot eyes.

Digital imaging is as much about chemistry as it is about semiconductors.

There are a lot of companies - not just Sony and Kodak - that have spent a lot of money trying to make the quality of the digital images comparable with film. But when you're sending these things over the Internet, they don't have to be high quality.

Light-field photography is a transformational technology that needs a transformational product to introduce it. For the first time, we have a light-field camera that's going to be for everyone - not something in a huge room in a research facility.

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.

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.

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

Some Google employees have their self-driving vehicles take them to work. These car robots don't look like something from 'The Jetsons'; the driverless features on these cars are a bunch of sensors, wires, and software. This technology 'works.'

In 1976, Kodak's first digital camera shot at 0.1 megapixels, weighed 3.75 pounds, and cost over $10,000.

As a photographer, I'm interested in how dramatically photography has changed. Most images are not real or are composites, and most of us don't even know it anymore.

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.

There are an endless number of things to discover about robotics. A lot of it is just too fantastic for people to believe.

I like to think of Photography 1.0 as the invention of photography. Photography 2.0 is digital technology and the move from film and paper to everything on a chip. Photography 3.0 is the use of the camera, space, and color and to capture an object in the third dimension.

Whatever you are studying right now, if you are not getting up to speed on deep learning, neural networks, etc., you lose. We are going through the process where software will automate software, automation will automate automation.

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.

Did you notice what happened when digital photography arrived? Suddenly there were four times as many people on set for a shoot! It used to be a photographer, a couple of photo assistants, stylist and a fashion assistant, hair and make-up and that was about it.

When I was a graduate student in computer science in the early 2000s, computers were barely able to detect sharp edges in photographs, let alone recognize something as loosely defined as a human face.

Understanding vision and building visual systems is really understanding intelligence.

Traditionally, images have functioned as representations of something in the world, but we are quickly approaching the point where vast majority of images are produced for other machines, and no human being will ever see them.

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

To make a vehicle autonomous, you need to gather massive streams of data from loads of sensors and cameras and process that data on the fly so that the car can 'see' what's around it.

Yes, we have prototyped cars that can drive by themselves, but without smart vision, they cannot really tell the difference between a crumpled paper bag on the road, which can be run over, and a rock that size, which should be avoided.

The digital camera takes photographs in practically no light: it will dig out the least bit of light available. I was amazed to see the results of photographs that I wouldn't take ordinarily. That's the advantage of digital photography.