Steve Jurvetson Quotes

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.

Today, there are industries employing hundreds of thousands of engineers creating artificial intelligence.

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.

The deep learning techniques, while relatively easy to learn, are quite foreign to traditional engineering modalities. It takes a different mindset and a relaxation of the presumption of control. The practitioners are like magi, sequestered from the rest of a typical engineering process.

I think a lot of people don't understand how deep AI already is in so many things.

Deep learning allows you to create predictive models at a level of quality and sophistication that was previously out of reach. And so deep learning also enhances the product function of data science because it can generate new product opportunities.

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.

You may not realize it, but artificial intelligence is all around us.

I'm fascinated by artificial intelligence.

AI does not keep me up at night. Almost no one is working on conscious machines. Deep learning algorithms, or Google search, or Facebook personalization, or Siri or self driving cars or Watson, those have the same relationship to conscious machines as a toaster does to a chess-playing computer.

I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.

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.

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

By 2020, most home computers will have the computing power of a human brain. That doesn't mean that they are brains, but it means that in terms of raw processing, they can process bits as fast as a brain can. So the question is, how far behind that is the development of a machine that's as smart as we are?

I am suggesting that we recognize that in network and interface research there is something as profound (and potential wild) as Artificial Intelligence.

Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.

The big question society will have to answer is whether it wants computers thinking like humans.

This is a magical time for computer programming. We are moving towards the artifical intelligence holy grail of programming the computer to simulate the human brain.

The revolution in AI [artifical intelligence] has been profound. It surprised me, even though I was sitting right there.

The thing that's going to make artificial intelligence so powerful is its ability to learn, and the way AI learns is to look at human culture.

There's a very long tail of all sorts of creative products - beyond our core web search, image search and advertising businesses - that are powered by deep learning.

Data is going to be dynamic... and, combined with the performance of computing that allows for artificial intelligence to be applied, is going to bring all kinds of insights and additives to enhance everyday life.

Because Facebook can't exist without AI, it needs all its engineers to build with it.

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