A deep learning technology that Google has spent several years working with internally, the software was made available through open source and released under the Apache 2.0 license.
Deep learning, also known as machine learning, is an area that Google has been developing for several years with DistBelief, their internal deep learning infrastructure. DistBelief has been used to build and expand artificial neural networks. Fruits of these enhanced neural networks are seen in the way these systems have begun to recognize cats from unlabeled images on YouTube, as well as improvements to speech recognition in the Google app.
Unfortunately, DistBelief was not without limitations, as it was fairly inflexible and its close ties to Google’s internal infrastructure obstructed it from sharing research code.
With TensorFlow, sharing code is easier than ever, as just about any gradient-based machine learning algorithm can benefit from its auto-differentiation and optimizers. The moving of information can now happen with no costly code changes. TensorFlow can be quickly shared and scaled-up, uses recognizable C, C++, and Python programs -- all features that allow for efficient collaboration across departments and developers. “Communication is key to quality results,” and TensorFlow makes it simple and stress-free to do.
Google hopes that other researchers, engineers and hobbyists speed up the machine's development. With TensorFlow, Google has established itself as a non-conformist who wants to nurture research on AI. By making it available to everyone, people can apply the technology to realms Google hasn’t tried or explored yet.
Although TensorFlow is a great resource for researching AI, it is also ready to use in products as well. You can move your idea swiftly from training on your desktop GPU to have it running on your mobile phone, as long as your GPU’s are compatible.
While Google hopes to create better algorithms that would be more agile at solving complex problems, the initial release of TensorFlow is still very beneficial. TensorFlow has the capacity to cut out mundane repetitive tasks that take up a company’s valuable time and energy.
Using TensorFlow and AI intelligence to benefit everyday life has never been easier. Learning systems have already made it possible to create and improve apps when it comes to speech and image recognition technologies. Google already uses this technology in many of their products, including photos with face recognition, image search, real-time translation in Google Translate, and Smart Reply in Gmail.
There are other deep learning tools; Pinterest, for example, paired with Caffe to create their new feature, which allows users to crop and search within an image for specific images. Say you look up an image of a dining room and you really like the table in it. Crop the image to just include the table, and Pinterest will go through deep learning to find images that match or seem similar enough.
Machine-learning technology creates a better overall experience. It learns the more you use it and leads to a very personalized user experience. By making TensorFlow free of cost, Google is providing many the opportunity to take advantage of the company’s AI research department, a core factor in the innovations that are soon to come to AI.
Lolay is excited for projects to come using TensorFlow technology. TensorFlow’s availability will make it a game changer and we cannot wait to be a part of it. Subscribe to our email to stay updated with the latest in mobile & web development or contact us online today.