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Jarek Wilkiewicz
6,827 followers -
ML @ 10^100
ML @ 10^100

6,827 followers
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In addition to gRPC APIs TensorFlow ModelServer also supports RESTful APIs for classification, regression and prediction on TensorFlow models. This page describes these API endpoints and format of request/response involved in using them.

https://github.com/tensorflow/serving/blob/master/tensorflow_serving/g3doc/api_rest.md
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AI at Google: our principles
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super proud of the team: Google Duplex: An AI System for Accomplishing Real World Tasks Over the Phone "[...] At the core of Duplex is a recurrent neural network (RNN) designed to cope with these challenges, built using #TensorFlow Extended (https://www.tensorflow.org/tfx/ ) [...]"

https://ai.googleblog.com/2018/05/duplex-ai-system-for-natural-conversation.html #TFX #TensorFlow
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If you're coming to #googleio2018 don't miss the "TensorFlow in production" session about @TensorFlow Extended (TFX) on Wednesday May 9th. It will cover several components integrated with TFX including tf.hub and tf.serving.
Google I/O 2018
Google I/O 2018
events.google.com
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#nips2017 paper: TensorFlow-Serving: Flexible, High-Performance ML Serving http://learningsys.org/nips17/assets/papers/paper_1.pdf

"We describe TensorFlow-Serving, a system to serve machine learning models inside Google which is also available in the cloud and via open-source. It is extremely flexible in terms of the types of ML platforms it supports, and ways to integrate with systems that convey new models and updated versions from training to serving. At the same time, the core code paths around model lookup and inference have been carefully optimized to avoid performance pitfalls observed in naive implementations. Google uses it in many production deployments, including a multi-tenant model hosting service called TFS2."
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Some very interesting predictions by Rodney Brooks: http://rodneybrooks.com/my-dated-predictions/
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