InfoQ Homepage Machine Learning Content on InfoQ
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Microsoft Previews Neural Network Text-To-Speech Capabilities
In a recent blog post, Microsoft announced a public preview of their neural network-powered text-to-speech capability, which is part of their Azure Cognitive Services offering. Within this release, the service makes computer generated voices indistinguishable from actual recordings. This technology has applications in chatbots, virtual assistants and converting digital text into audio books.
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Connecting Business Challenges and Emerging Technologies
Caragh O'Carroll spoke about three emerging technologies at Women in Tech Dublin 2018: Blockchain, robotic process automation, and artificial intelligence and machine learning. She explored how these technologies provide solutions to the challenges that businesses are facing.
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Q&A with Christoph Windheuser on AI Applications in the Industry
Increased hardware power and huge amounts of data are making existing machine learning approaches like pattern recognition, natural language processing, and reinforcement learning possible. Artificial Intelligence is impacting the development process; it’s increasing the complexity of things like version control, CI/CD and testing.
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Microsoft Announces AI-Assisted IntelliCode for TypeScript and JavaScript in VS Code
Beyond the typical IntelliSense or code completion developers have come to appreciate, earlier this year Microsoft announced IntelliCode, a set of capabilities that provide AI-assisted development. The VS Code team has now announced a new experimental extension to bring IntelliCode to TypeScript and JavaScript users.
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TensorSpace.js Delivers Neural Network 3D Visualization Framework
TensorSpace.js provides an open source browser-based neural network data visualization framework to complement the growing machine learning landscape by supporting pre-trained models created with TensorFlow.js, Keras, or TensorFlow.
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Azure Machine Learning Services Now Generally Available
Microsoft has announced the general availability of the Azure Machine Learning service. Azure Machine Learning automates machine learning to make it easier to build, train and deploy models. The service is generally available now, with pricing to go into effect February 1, 2019.
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QCon.ai San Francisco 2019: AI & ML Conference Focused on Software Engineers Announces Tracks
QCon.ai, the first conference from the people behind QCon and InfoQ focused solely on artificial intelligence and machine learning for the software engineer, announces the tracks for the 2019 conference.
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AWS Marketplace Offers Machine Learning Algorithms and Model Packages
Amazon Web Services is offering machine learning algorithms and model packages on their AWS Marketplace. This was announced at AWS re:Invent Conference last week.
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Recap of AWS re:Invent 2018 Announcements
If you thought Amazon Web Services (AWS) might run out of services to launch, this year's re:Invent put that fear to rest. At the recently concluded event, AWS shared a flurry of announcements across a range of categories. re:Invent rarely has a "theme" for its announcements. But there was heavy attention on machine learning, databases, hybrid cloud, and account management.
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Google Introduces AI Hub and Kubeflow Pipelines for Easier ML Deployment
Google is launching two new tools, one proprietary and one open source: AI Hub and Kubeflow pipelines. Both are designed to assist data scientists design, launch and keep track of their machine learning algorithms.
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Google Open-Sources Speaker Diarization AI Technology, Claims 92% Accuracy
In a recent blog post, Google announced they have open-sourced their speaker diarization technology, which is able to differentiate people’s voices at a high accuracy rate. Google is able to do this by partitioning an audio stream that includes multiple participants into homogeneous segments per participant.
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Google Open-Sources BERT: A Natural Language Processing Training Technique
In a recent blog post, Google announced they have open-sourced BERT, their state-of-the-art training technique for Natural Language Processing (NLP) . Google has decided to do this, in part, due to a lack of public data sets that are available to developers. In addition, optimizations have been made to Cloud TPUs to reduce the amount of time required for training NLP.
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Facebook Releases PyTorch 1.0 Preview, with Google, AWS and Microsoft Azure Integrations
At a recent PyTorch developer conference in San Francisco, Facebook released a developer preview version of PyTorch 1.0. PyTorch is an open source, deep learning framework used to reduce friction in taking research projects to production. In this release, many investments have been made by public cloud and hardware companies to better support the PyTorch ecosystem.
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New Updates to Firebase: Enterprise-Grade Support, ML Kit Face Contours, Management API, and More
Firebase is a service available on the Google infrastructure, enabling developers to build apps for Android, iOS, and the web. Recently, Google updated Firebase with paid enterprise-grade support, ML Kit Face Contours, a Firebase Management API, Test Lab for iOS, Performance Monitoring improvements, and Firebase Predictions.
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Introducing EmoPy: An Open Source Toolkit for Facial Expression Recognition
In a recent blog post, Angelica Perez shared information about a new open source project for an interactive film experience. The project is called EmoPy and focuses on Facial Expression Recognition (FER) by providing a toolkit that allows developers to accurately predict emotions based upon images passed to the service.