Ben Sasse Quotes

There is huge demand for artificial intelligence technologies.

Artificial intelligence is growing up fast, as are robots whose facial expressions can elicit empathy and make your mirror neurons quiver.

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.

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.

Emotion AI uses massive amounts of data. In fact, Affectiva has built the world's largest emotion data repository.

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.

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

More than 500 million years ago, vision became the primary driving force of evolution's 'big bang', the Cambrian Explosion, which resulted in explosive speciation of the animal kingdom. 500 million years later, AI technology is at the verge of changing the landscape of how humans live, work, communicate, and shape our environment.

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.

I have always been convinced that the only way to get artificial intelligence to work is to do the computation in a way similar to the human brain. That is the goal I have been pursuing. We are making progress, though we still have lots to learn about how the brain actually works.

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

Deep learning is a subfield of machine learning, which is a vibrant research area in artificial intelligence, or AI.

The human brain has an amazing ability for pattern recognition, sometimes even better than a computer.

Algorithms learn by being fed certain images, often chosen by engineers, and the system builds a model of the world based on those images. If a system is trained on photos of people who are overwhelmingly white, it will have a harder time recognizing nonwhite faces.

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.

All you need is lots and lots of data and lots of information about what the right answer is, and you'll be able to train a big neural net to do what you want.

I see that our emotional AI technology can be a core component of online learning systems - health wearables, even.

I became interested in AI in high school because I read 'Goedel, Escher, Bach,' a book by Douglas Hofstader. He showed how all their work in some ways fit together, and he talked about artificial intelligence. I thought 'Wow, this is what I want to be doing.'

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

To determine if you're human. Be silent.

Artificial Intelligence (AI) is the science of how to get machines to do the things they do in the movies.

Artificial intelligence is a tool, not a threat

I don't think there's anything unique about human intellience. All the nuerons in the brain that make up perceptions and emotions operate in a binary fashion.

Pretend I asked, now answer the question.

Sometimes it seems as though each new step towards AI, rather than producing something which everyone agrees is real intelligence, merely reveals what real intelligence is not.