Robert Scoble Quotes

I want Facebook to pick the best 20 items to show me every single time I refresh that screen.

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

My hope for AI and Facebook in the next decade is you can sit down and tell Facebook, 'This is what I want to hear about today.' Like, I'm having a bad day; I want to hear some good news. If we make our products better, more people will use it - people use it more. It's fairly easy to understand.

If I'm reading my Facebook feed, it's using algorithms, procedures, and methods to give me what I want, or what it thinks that I want, or what suits its business plan.

Facebook and Twitter have a ton of information they're trying to make sense of.

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

Ideally, Facebook would take all our clicks and information and would magically give us everything we want, without us even knowing we want it.

YouTube's algorithm doesn't know what's going on in the world.

It is probable that Facebook boasts the broadest, deepest, and most comprehensive dataset of human information, interests, and activity ever collected.

We need to build systems that can automatically figure out what's high quality and what's not, and encourage users to contribute high-quality content. There's a lot of technical challenges in that.

Facebook is at the forefront. It's the company that can fundamentally change the way information is being exchanged and processed. It can be the basis for artificial intelligence to develop over time.

All sorts of factors contribute to what Facebook or Twitter present in a feed, or what Google or Bing show us in search results. Our expectation is that those intermediaries will provide open conduits to others' content and that the variables in their processes just help yield the information we find most relevant.

Facebook can be an accumulation of different intelligences.

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.

With this emergence of big data and social mobility, you will, in fact, see the death of 'average,' Instead, you will see the era of you.

Once upon a time, if you were going to get a loan from me, I would have had to look at your file, and I would have to make a decision about whether youre going to get a loan. Maybe we would meet and talk about it. There would be some level of human involvement and human interaction. Now, a lot of this is determined by an algorithm.

People are building apps that are doing super-crazy things, and there's a lot of talk about modeling and microtargeting. Facebook can predict when people are going to break up, and Target is able to predict if a woman is pregnant before she knows just based on the type of lotion she bought.

I was interested in data mining, which means analyzing large amounts of data, discovering patterns and trends. At the same time, Larry started downloading the Web, which turns out to be the most interesting data you can possibly mine.

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

A new, a vast, and a powerful language is developed for the future use of analysis, in which to wield its truths so that these may become of more speedy and accurate practical application for the purposes of mankind than the means hitherto in our possession have rendered possible.

I discover real-time news far more often on Facebook than on Google News or a regular Google search.

We obviously try to be in tune with what our users want.

We are going to completely change what it means to do advanced analytics with our data solutions. We have machine-learning stuff that is about really bringing advanced analytics and statistical machine learning into data-science departments everywhere.

Watson augments human decision-making because it isn't governed by human boundaries. It draws together all this information and forms hypotheses, millions of them, and then tests them with all the data it can find. It learns over time what data is reliable, and that's part of its learning process.

I came in as an engineer and worked on artificial intelligence at Google. I worked on related sites and matching advertising to queries with some of our earliest ads.