How Facebook is using machine learning to create targeted ads

An engineer at Facebook’s research lab is trying to develop algorithms that will be able to make Facebooks advertising decisions more efficiently, in part by understanding how people are interacting with its products.

The idea is to make personalized ads that don’t need to appeal to every user, as opposed to what is usually done by Facebook in its current model, where users are presented with a list of features and ads based on their preferences.

The company has been experimenting with machine learning techniques to better understand how users interact with its online properties in an attempt to make its online advertising more efficient, and the new research is the latest step in that process.

For example, Facebook has a dedicated algorithm that can be used to determine what people want to see on a news feed, and if that same content is available on the company’s own news site, it can then tailor the ads accordingly.

In the same vein, Facebook can tell users that they have to check out its “Community” section before they can use the site.

Facebook is also experimenting with automated targeting, which is a way to tailor ads based not only on the content that a user is interested in, but also on the behavior of the user, in order to get them to click on an ad or buy something.

But in this case, the automated targeting is not done with the intention of getting users to click the ad, but with the intent of getting them to buy something that the company sells.

In a recent research paper, Facebook researchers from the lab of Professor Nick Oram, showed that using machine-learning techniques to understand how people interact with their online products, and then trying to understand the types of behaviors people are using to click through ads, can help Facebook develop better algorithms for targeting ads that are more relevant to people’s behavior and interests.

“We are very excited about this work because we want to take the same technology to new worlds of relevance,” Oram said in a statement.

“We are going to build a whole new way of analyzing the behavior, and building the algorithms that we need to understand that behavior, that is going to help us better target ads to people that are most likely to click.”

Oram and his colleagues also are exploring ways to use machine learning algorithms to make decisions about whether or not to display ads on the pages of its News Feed, or whether or no ads should be displayed at all.

Facebook also is working on using machine vision techniques to develop personalized ads tailored to specific users, such as those that are interested in a specific subject.

The research is not just about improving the algorithms for Facebook’s algorithms, however.

It is also a way for Facebook to get more people to see its ads.

According to a Facebook spokesperson, the company has spent the last several months working with publishers to make their ads more relevant and to develop ways to make the ads more personal to their users.

The new work is a big step forward for Facebook, and it shows that the tech giant is actively working to improve its algorithms for delivering ads, and to improve the quality of the ads that people see.