InfoQ Homepage Machine Learning Content on InfoQ
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Tracks Announced for the Inaugural QCon.ai in 2018
Recently, the people behind QCon (InfoQ’s conference for senior developers, architects, and leaders in software) announced a new conference called QCon.ai.
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Microsoft and AWS Collaborate on Machine Learning
Microsoft and AWS have recently announced a new collaboration aimed at democratizing deep learning and artificial intelligence. Gluon is a joint effort between Microsoft Research and Amazon AI and is intended to make developing solutions using machine learning easier and quicker.
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Smart Replies for Member Messages at LinkedIn
LinkedIn has launched a new natural language processing (NLP) recommendation engine which is used to provide members with smart-reply recommendations to messages. The models and infrastructure development process has been documented in detail in a recent blog post by the engineering team.
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Book Review Python Machine Learning - Second Edition
The book Python Machine Learning, second edition by Sebastian Raschka and Vahid Mirjalili, is a tutorial to a broad range of machine learning applications with Python. It provides a practical introduction to machine learning. The main revision to the first edition is neural network practices. There are now five chapters that discuss neural networks, and their implementation in TensorFlow.
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Microsoft Updates AI Services and Tools for Data Scientists and Developers
At the recent Ignite conference, Microsoft released several updates related to its Artificial Intelligence (AI) services and tools. These updates include the release of the Azure ML Experimentation service, Azure ML Model Management service, Azure ML Workbench and the general availability of Microsoft Cognitive Services.
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Apple Reveals the Inner Workings of Siri's New Intonation
Apple has explained how they use deep learning to make Siri's intonation sound more natural. IPhone owners can interact with Siri by asking questions in natural language and Siri responds by voice. At WWDC 2017, Apple announced that in iOS 11 Siri would use a new text to speech engine. In August 2017, Apple's machine learning journal unveiled how they were able to make Siri sound more human.
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Facebook Transitioning to Neural Machine Translation
Facebook recently announced the global rollout of NMT. Switching from phrase based translation models to NMT has been rolled out for more than 2,000 translation directions and 4.5 billion translations per day. According to Facebook this provides an 11% increase in BLEU score. We will discuss how it was achieved, what it means for machine generated translation and how it fares against competition.
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Q&A with Andrew Brust of Datameer Regarding Big Data's Role in AI
Rags Srinivas talks to Datameer's Andrew Brust about the larger role of Big Data in AI and how it's operationalized with SmartAI.
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Google Uses Machine Learning to Identify Intrusive Android Apps
Google uses a clustering algorithm to automatically analyze Android apps and detect which ones can be considered intrusive, write Google security engineers Martin Pelikan, Giles Hogben, and Ulfar Erlingsson.
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Scalable Chatbot Architecture with eBay ShopBot Shopping Assistant
Robert Enyedi, software engineer at eBay spoke at QCon New York 2017 Conference about ShopBot personal shopping assistant application. ShopBot, launched in late 2016 based on Facebook Messenger bot, leverages AI components and the eBay user data to provide shopping options in a conversational style.
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Electronic Frontier Foundation Measuring Progress of Artificial Intelligence
The Electronic Frontier Foundation (EFF) started a document containing progress artificial intelligence (AI) research on multiple tasks. The goal of the document is to be the place for people to find progress on difficult tasks. Currently, many tasks don't have the metrics, datasets, and benchmarks to keep track of them. The EFF made a notebook to which researchers and developers can contribute.
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QCon New York: Evaluating Machine Learning Models - A Case Study in Real Estate
Opendoor, a real estate company that helps customers with buying and selling homes, uses machine learning techniques to drive pricing models. Nelson Ray, data scientist at Opendoor, spoke at QCon New York 2017 Conference about how they developed a simulation-based framework for reasoning about machine learning models to assess the risk in reselling homes.
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Managing Data in Microservices
Randy Shoup from Stitch Fix team spoke at QCon New York 2017 Conference about managing the data and isolated persistence in Microservices based applications. He also talked about events as a first class construct for microservices.
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Facebook Publishes New Neural Machine Translation Algorithm
Facebook’s Artificial Intelligence Research team published research results using a new approach for neural machine translation (NMT). Their algorithm scores higher than any other system on three established machine translation tasks.
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Developing Virtual Assistant Apps with Amazon Lex and Polly Deep Learning Technologies
Greg Bulmash from Amazon spoke at the OSCON 2017 Conference last week about developing your own virtual assistant applications using Amazon's Lex and Polly technologies.