That’s great news! Google just open-sourced TensorFlow, its deep (machine) learning library.
The engine is widely used at Google: by speech recognition systems, in the new Google photo product, in Gmail, in search, etc.
From now on startups will be able to develop systems as intelligent as a 4 year old children. More interestingly, code sharing in python between researchers or data scientists has never been easier.
The limitations of the previous system no longer exist:
[DistBelief] was narrowly targeted to [artificial] neural networks, it was difficult to configure, and it was tightly coupled to Google’s internal infrastructure — making it nearly impossible to share research code externally. […] TensorFlow has extensive built-in support for deep learning, but is far more general than that — any computation that you can express as a computational flow graph, you can compute with TensorFlow (see some examples). Any gradient-based machine learning algorithm will benefit from TensorFlow’s auto-differentiation and suite of first-rate optimizers. And it’s easy to express your new ideas in TensorFlow via the flexible Python interface.
Maybe the engine will soon get available for its cloud-based service on a clustered architecture…
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