New version of Google's artificial-intelligence engine will help researchers and developers involve hundreds of computers in learning projects.
Machine learning is considered by many to be tech's next frontier. But for many researchers, its expense might as well place it in outer space.
To help researchers and developers who might otherwise not have access to machine learning's benefits, Google on Wednesday announced a new distributed version of TensorFlow, the artificial-intelligence engine the Web giant uses to add capabilities such as speech and object recognition to its products. The new version of TensorFlow will let researchers perform large-scale machine learning across hundreds of computers, shrinking the training process for some models from weeks to hours.
Google already uses machine learning algorithms to deliver search results, help translate languages and identify objects in photos. Google open-sourced TensorFlow in November, allowing developers to build on its framework, contribute source code and provide feedback.