Tensor2Tensor, shortly known as T2T, is a library of pre-configured deep learning models and datasets. The Google Brain team has developed it to do deep learning research faster and more accessible. It uses TensorFlow throughout and aims to improve performance and usability strongly. Models can be trained on any of the CPU, single GPU, multiple GPU and TPU either locally or in the cloud. Tensor2Tensor models need minimal or zero configuration or device-specific code. It provides support for well-acclaimed models and datasets across different media platforms such as images, videos, text and audio.

New neural network architectures and novel AI research papers come out every week from professors at universities, researchers at Google and other big tech firms, or even just developers with a strong interest in Deep Learning. Unfortunately for individuals who don't have a Ph.D. or robust fluency in back-propagation, linear algebra, or computational math, implementing these new Deep Learning techniques with no high-level API (like Keras) can be challenging and time-consuming. Thankfully, the Google Brain team recognizes these widespread problems in the AI community and subsequently created an open source library to help address these issues. Although Deep Learning isn't always the silver bullet people hope for in the Data Science world, it is a very useful tool for Natural Language Processing (NLP) task. For example, the use of word embeddings has revolutionized the effectiveness of language understanding techniques. I wanted to make an offline French to English translator for my team and our clients, using the best current techniques, which at the time was the Transformer architecture.

Time is one of the biggest obstacles to the adoption of deep learning. It can take days to train one of these systems even if you have massive computing power at your disposal -- on more modest hardware, it can take weeks. Google might just fix that. It's releasing an open source tool, Tensor2Tensor, that can quickly train deep learning systems using TensorFlow. In the case of its best training model, you can achieve previously cutting-edge results in one day using a single GPU.