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Facebook wants the world to see a lot more patterns and predictions.

The company said Friday that it was donating for public use several powerful tools for computers, including the means to go through huge amounts of data, looking for common elements of information. The products, used in a so-called neural network of machines, can speed pattern recognition by up to 23.5 times, Facebook said.

The tools will be donated to Torch, an open source software project that is focused on a kind of data analysis known as deep learning. Deep learning is a type of machine learning that mimics how scientists think the brain works, over time making associations that separate meaningless information from meaningful signals.

Companies like Facebook, Google, Microsoft and Twitter use Torch to figure out things like the probable contents of an image, or what ad to put in front of you next.

“It’s very useful for neural nets and artificial intelligence in general,” said Soumith Chintala, a research engineer at Facebook AI Research, Facebook’s lab for advanced computing. He is also one of the creators of the Torch project. Aside from big companies, he said, Torch can be useful for “start-ups, university labs.”

Certainly, Facebook’s move shows a bit of enlightened self-interest. By releasing the tools to a large community of researchers and developers, Facebook will also be able to accelerate its own AI projects. Mark Zuckerberg has previously cited such open source tactics as his reason for starting the Open Compute Initiative, an open source effort to catch up with Google, Amazon and Yahoo on building big data centers.

Torch is also useful in computer vision, or the recognition of objects in the physical world, as well as question answering systems. Mr. Chintala said his group had fed a machine a simplified version of “The Lord of the Rings” novels and the computer can understand and answer basic questions about the book.

“It’s very early, but it shows incredible promise,” he said. Facebook can already look at some sentences, he said, and figure out what kind of hashtag should be associated with the words, which could be useful in better understanding people’s intentions. Such techniques could also be used in determining the intention behind an Internet search, something Google does not do on its regular search.

Besides the tools for training neural nets faster, Facebook’s donations include a new means of training multiple computer processors at the same time, a means of cataloging words when analyzing language and tools for better speech recognition software.