Bits & Bytes

Intel open sources nGraph neural network compiler.

  • The newly open-sourced compiler, originally announced last summer and discussed on TWIML Talk #31, provides support for multiple deep learning frameworks while optimizing models for different hardware solutions. It supports six deep learning frameworks: TensorFlow, MXNet, neon, PyTorch, CNTK, and Caffe2.

Google unveils augmented reality microscope.

  • The prototype, which can detect cancer in real-time, was unveiled at an event organized by the American Association for Cancer Research. The new tool relays its predictions directly into the field of view of the user and has the ability to be retrofitted into existing microscopes.

Google extends semantic language capabilities.

  • Building on the hierarchical vector models at the heart of Gmails’s Smart Reply feature, the new work extends these ideas by creating vectors for larger chunks of language such as full sentences and small paragraphs. The company published a paper on its Universal Sentence Encoder and launched the Semantic Experiences demonstration site. A pre-trained TensorFlow model was also released.

IBM releases Adversarial Robustness Toolbox.

  • The open-source software library aims to support researchers and developers in defending deep neural nets against adversarial attacks. The software, which currently works with TensorFlow and Keras, can assess a DNNs robustness, increase robustness as needed, and offer runtime detection of potential threats.

MATLAB 2018a adds deep learning features.

  • Many self-taught data scientists were initially exposed to MATLAB via Octave, the open source clone Andrew Ng used in his original Stanford machine learning online course. Well, the commercial software continues to evolve, with its latest version adding a host of new deep-learning related features including support for regression and bidirectional LSTMs, automatic validation of custom layers, and improved hardware support.

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