Facebook looking for meaning in user posts with 'deep learning' algorithms

Sep 23, 2013 by Bob Yirka weblog

(Phys.org) —Officials at Facebook have apparently decided to get serious about making sense of posts by its vast user base—according to MIT's Technology Review, officials with the company (specifically Chief Technical Officer Mike Schroepfer) have announced that they have put together a team of eight professionals with the mission of developing what the software industry has begun calling "deep learning." Deep learning is a type of software programming where algorithms are created that allow for building simulated neural networks. Such neural networks are capable of "learning" by analyzing patterns over time. Facebook, TR reports, is hoping to use its algorithms to better target ads, and also to improve its newsfeed.

As anyone who uses Facebook knows, friending people means adding their posts to your personal newsfeed. As the number of friends grows, so too does the number of newsfeed entries. Eventually, a point is reached where it becomes untenable. To deal with this problem, Facebook has created algorithms that are meant to pick out what it believes are the most relevant posts and only send those to the newsfeed, rather than deliver them all. Thus far, this approach has met with mixed reviews from its user community. The company is hoping that giving its algorithms more smarts, will help improve the quality of newsfeeds.

Deep learning isn't something Facebook created, it's an idea that has been around for several years, Microsoft and Google have used it (Google most famously to help identify cats in YouTube videos). IBM uses it too, as part of Watson, the supercomputer that beat Jeopardy champions on television. Netflix is experimenting with similar technology to help improve its movie suggestion algorithms and might serve as a guide for how successful Facebook might expect to be with its initiative (movie suggestions are still not all that relevant). But perhaps, that's not the point at all. Instead, maybe it's the process that is the real news. Big companies are starting to spend a lot of money on with the idea of a big payoff. Surely Facebook would be happy if they could improve their newsfeed, but the real motive, as with any big business, will always be about improving the bottom line. And if deep learning algorithms can figure out a way to coax users into clicking on more ads, than the initiative will most certainly be deemed a success by all concerned.

Explore further: What the dog-fish and camel-bird can tell us about how our brains work

More information: via TechReview

Related Stories

Study examines viral reach of hashtags on Facebook

Sep 05, 2013

(Phys.org) —Facebook analysts EdgeRank Checker have performed analysis of over 35,000 posts to discover the level of viral impact of Facebook's hashtags, The discovery is, well, zero. "We decided to dig ...

Recommended for you

Researchers build first working memcomputer prototype

Jul 06, 2015

(Tech Xplore)—A combined team of researchers from the University of California and Politecnico di Torino in Italy has built, for the first time, a working memory-crunching computer (memcomputer) prototype. ...

EU open source software project receives green light

Jul 01, 2015

An open source software project involving the University of Southampton to extend the capacity of computational mathematics and interactive computing environments has received over seven million euros in EU funding.

Can computers be creative?

Jul 01, 2015

The EU-funded 'What-if Machine' (WHIM) project not only generates fictional storylines but also judges their potential usefulness and appeal. It represents a major advance in the field of computational creativity.

User comments : 0

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.