Naveen Tewari Quotes

I think, in the future, we'll assume that every device just knows how to read your emotions.

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

Our aim is to develop affectionate robots that can make people smile.

Emotion AI will be ingrained in the technologies we use every day, running in the background, making our tech interactions more personalized, relevant, authentic, and interactive.

I remember, once I was stressed, with an upcoming paper deadline. That little Microsoft Word clippy guy would show up in my face, jumping around and asking if I needed help. It had no understanding of my emotions and had zero empathy. That got me interested in this idea of tech being responsive to our emotions.

You won't remember what it was like when your technology didn't recognize when you are sad or angry.

My own work falls into a subset of AI that is about building artificial emotional intelligence, or Emotion AI for short.

I spent many, many hours with my computer, and it really bugged me that it was very oblivious to my emotional state. And that kind of inspired and motivated me to build an emotionally intelligent computer.

With Emotion AI, we can inject humanity back into our connections, enabling not only our devices to better understand us, but fostering a stronger connection between us as individuals.

Facebook is studying emotional reaction to things and bringing you fewer of things you don't engage with and more of what you do.

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

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.

Now with our Software Developer Kit (SDK), any developer can embed Emotion AI into the apps, games, devices, and digital experiences they are building, so that these can sense human emotion and adapt. This approach is rapidly driving more ubiquitous use of Emotion AI across a number of different industries.

We believe that one day Emotion AI will be ubiquitous, embedded on chips in our devices, ingrained into technology we use every day at home and at work.

Computers will understand sarcasm before Americans do.

Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the Web. It would understand exactly what you wanted, and it would give you the right thing. We're nowhere near doing that now. However, we can get incrementally closer to that, and that is basically what we work on.

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

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.

If you want to solve very complex problems, you will have to end up letting machines work out a lot of the details for themselves, and in ways that we don't understand what they are doing.

A graphic representation of data abstracted from the banks of every computer in the human system. Unthinkable complexity. Lines of light ranged in the nonspace of the mind, clusters and constellations of data. Like city lights, receding.

I've always been interested in technology, but specifically how we can use machines to engage the imagination. I started using computers when I was young and was fascinated by creating rules and instructions that allow a computer to engage in a dialogue with humans. The stories found in the data all around us can do just that.

Graphics has lately made a great shift towards machine learning, which itself is about understanding data.

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

I was really interested to see whether we could make predictions or forecasts by listening in on what people were saying on social media.

Social media has given companies access to unprecedented amounts of information on client behavior and preferences - so-called Big Data. But making sense of it all and turning it into actionable policy has been elusive.