Robin Sloan Quotes

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

Computers will understand sarcasm before Americans do.

I am a brain, Watson. The rest of me is a mere appendix.

My mission at Google is to develop natural language understanding with a team and in collaboration with other researchers at Google.

Understanding of natural language is what sometimes is called 'AI complete,' meaning if you can really do that, you can probably solve artificial intelligence.

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.

One of our big goals in search is to make search that really understands exactly what you want, understands everything in the world. As computer scientists, we call that artificial intelligence.

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.

Now that neural nets work, industry and government have started calling neural nets AI. And the people in AI who spent all their life mocking neural nets and saying they'd never do anything are now happy to call them AI and try and get some of the money.

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

I am often asked what the future holds for Emotion AI, and my answer is simple: it will be ubiquitous, engrained in the technologies we use every day, running in the background, making our tech interactions more personalized, relevant, authentic and interactive.

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

We have a good sense of the pulse of the industry. We know what's going on out there. We know that deep learning adoption is broad. It's going into production at scale.

If you step back a little and say we want to do A.I., then you will realize that A.I. needs knowledge, reasoning, and explanation.

A lot of what people are calling 'artificial intelligence' is really data analytics - in other words, business as usual. If the hype leaves you asking 'What is A.I., really?,' don't worry, you're not alone.

I'd like to make a fundamental impact on one of the most exciting, intelligent questions of all time. Can we use software and hardware to build intelligence into a machine? Can that machine help us solve cancer? Can that machine help us solve climate change?

We now think of internal representation as great big vectors, and we do not think of logic as the paradigm for how to get things to work. We just think you can have these great big neural nets that learn, and so, instead of programming, you are just going to get them to learn everything.

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

The only path to build intelligent machines is to enable it with powerful visual intelligence, just like what animals did in evolution.

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

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.

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.

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

AI cloud is just very, very nascent.

Google created the intent graph. Facebook created the social graph. We are creating the emotional graph.