InfoQ Homepage Machine Learning Content on InfoQ
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Conference Recap: Google Cloud Next
Cloud enthusiasts from around the world attended Google Cloud Next to hear an update from the search giant. Three broad themes emerged from the many keynotes and 200+ sessions: service scale and maturity, usable machine learning, and enterprise-friendliness.
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TensorFlow 1.0 Released
Google recently announced TensorFlow version 1.0. Python API is now stable and experimental APIs for Java and Go have been added. XLA delivers significant performance increase. Keras can also be integrated with TensorFlow using a build-in module. tf.transform, tf.layers, tf.metrics, and tf.losses all add new features to the framework..
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Android Things Brings TensorFlow-Based Machine Learning and Computer Vision to IoT Devices
Recently released Developer Preview 2 (DP2) for Android Things makes it easier to use TensorFlow for machine learning and computer vision on IoT devices. Additionally, it extends USB audio for several IoT platforms, adds Intel Joule support, and enables direct use of native drivers through a new Native PIO API.
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MindMeld’s Guide to Building Conversational Apps
MindMeld, a conversational AI company, has published The Conversational AI Playbook, a guide outlining the challenges and the steps to be made to create conversational applications.
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Zero-Shot Translation with Google Neural Machine Translation System
Google’s Multilingual Neural Machine Translation System creates an interlingua and translates between language pairs and phrases with no previous direct translation available, dubbed Zero-Shot translation.
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Intel Open-Sources BigDL, Distributed Deep Learning Library for Apache Spark
Intel open-sources BigDL, a distributed deep learning library that runs on Apache Spark. It leverages existing Spark clusters to run deep learning computations and simplifies the data loading from big datasets stored in Hadoop.
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Mathieu Ripert on Instacart's Machine Learning Optimizations
Instacart is an online delivery service for groceries under one hour. Customers order the items on the website or using the mobile app, and a group of Instacart’s shoppers go to local stores, purchase the items and deliver them to the customer. InfoQ interviewed Mathieu Ripert, data scientist at Instacart, to find out how machine learning is leveraged to guarantee a better customer experience.
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AFK-MC² Algorithm Speeds up k-Means Clustering Algorithm Seeding
“Fast and Probably Good Seedings for k-Means” by Olivier Bachem et al. was presented on 2016’s Neural Information Processing Systems (NIPS) conference and describes AFK-MC2, an alternative method to generate initial seedings for k-Means clustering algorithm that is several orders of magnitude faster than the state of art method k-Means++.
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Facebook Builds an Efficient Neural Network Model over a Billion Words
Using Neural Networks for sequence prediction is a well-known Computer Science problem with a vast array of applications in speech recognition, machine translation, language modeling and other fields. FB AI Research scientists designed adaptive softmax, an approximation algorithm tailored for GPUs which can be used to efficiently train neural networks over vocabularies of a billion words & beyond.
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Logz.io Offers Machine Learning Based Log Analysis
Logz.io offers a hosted service which performs intelligent log analysis by using machine learning to derive insights from human interactions with log data that includes discussions on tech forums and public code repositories.
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Spark Summit EU Highlights: TensorFlow, Structured Streaming and GPU Hardware Acceleration
Apache Spark integration with deep learning library TensorFlow, online learning using Structured Streaming and GPU hardware acceleration were the highlights of Spark Summit EU 2016 held last week in Brussels.
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CommAI, a Training and Testing AI System by Facebook
Facebook recently announced CommAI-env, a platform for training and evaluating an AI system. Inspired by A roadmap towards Machine Intelligence the system aims for teaching intelligent agents general learning capabilities that would serve as the groundwork for further, more specialized training by human or machine level interaction. The article provides a high level overview of current state and..
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How YouTube's Recommendation Algorithm Works
In a recent paper published by Google, YouTube engineers analyzed in greater detail the inner workings of YouTube’s recommendation algorithm. The paper was presented on the 10th ACM Conference on Recommender Systems last week in Boston. In this news item we analyze how YouTube uses deep learning to operate one of the largest and most complex recommendation systems in industry.
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IBM Creates Artificial Neurons from Phase Change Memory for Cognitive Computing
A team of scientists at IBM Research in Zurich, have created an artificial version of neurons using phase-change materials to store and process data. These phase change based artificial neurons can be used to detect patterns and discover correlations in Big Data (real-time streams of event based data) and unsupervised machine learning at high speeds using very little energy.
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Google Details New TensorFlow Optimized ASIC
The machine learning and engineering communities weigh in on news of Google's new TensorFlow optimized processor, the TPU and possibly influence several industry leaders in the hardware space like Intel and Nvidia.