InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Core ML 3 Extends Available Model Types, Adds On-Device Model Retrain
Announced at WWDC 2019, Core ML 3 introduces a number of new model types, many new neural network layer types, and adds support for on-device retraining of existing models using new data generated locally by the user.
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Amazon Announces New Cross-Skill Conversational Model for Alexa
At Amazon's re:MARS AI conference in Las Vegas, Alexa vice president Rohit Prasad demonstrated a new conversational model for the Alexa smart assistant. In this new model, Alexa can seamlessly transition between skills and remember the context of the conversation to resolve ambiguous references.
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Teaching Machines to Understand Emotions with Sentiment Analysis
Sentiment analysis teaches computers to recognise the human emotions present in text. The fundamental trade-off in sentiment analysis is between simplicity and accuracy. Approaches vary from using a list of words associated with emotions, to deep learning with techniques like word embeddings, neural networks and attention mechanisms.
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Google Uses Mannequin Challenge Videos to Learn Depth Perception
Google AI Research published a paper describing their work on depth perception from two-dimensional images. Using a training dataset created from YouTube videos of the Mannequin Challenge, researchers trained a neural network that can reconstruct depth information from videos of moving people, taken by moving cameras.
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Google Announces TensorFlow Graphics Library for Unsupervised Deep Learning of Computer Vision Model
At a presentation during Google I/O 2019, Google announced TensorFlow Graphics, a library for building deep neural networks for unsupervised learning tasks in computer vision. The library contains 3D rendering functions written in TensorFlow, as well as tools for learning with non-rectangular mesh-based input data.
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Google's Cloud TPU V2 and V3 Pods Are Now Publicly Available in Beta
Recently, Google announced that its second- and third-generation Cloud Tensor Processing Units (TPU) Pods — its scalable cloud-based supercomputers with up to 1,000 of its custom TPU — are now publicly available in beta. With these Pods, Machine Learning (ML) researchers, engineers, and data scientists can speed up the time needed to train and deploy machine learning models.
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Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
The WalmartLabs engineering team developed a real time A/B testing tool called Expo that collects and analyzes user engagement metrics. It uses Spark Structured Streaming to process the incoming data and stores the metrics in KairosDB.
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Databricks MLflow Integration Now Generally Available
Databricks recently made MLflow integration with Databrick notebooks generally available for its data engineering and higher subscription tiers. The integration combines the features of MLflow with those of Databrick notebooks and jobs. MLflow provides the following three main capabilities: experiment tracking, projects, and MLflow models.
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Microsoft Launches Several New Machine Learning Services and Extends Its Cognitive Services
Before its Build Developer Conference, Microsoft released several new Machine Learning services and Cognitive Services updates, ranging from no-code tools to hosted notebooks, with several new APIs and other services in-between.
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OpenAI Introduces Sparse Transformers for Deep Learning of Longer Sequences
OpenAI has developed the Sparse Transformer, a deep neural-network architecture for learning sequences of data, including text, sound, and images. The networks can achieve state-of-the-art performance on several deep-learning tasks with faster training times.
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Making Robots More Intelligent, Microsoft Releases Autonomous Systems Platform
At the recent Build conference in Seattle, Microsoft announced, in limited preview, an end-to-end toolchain to help developers and organizations build autonomous systems for their industries. The platform includes machine teaching tools and simulation technologies that enable intelligent robotic systems to complete tasks like running autonomous forklifts and robotic inspection platforms.
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ML.NET, an Open Source Machine Learning Framework for the .NET Ecosystem: Pranav Rastogi Q&A
Earlier this month Microsoft released the first major version of ML.NET, an open source machine learning (ML) framework for the .NET ecosystem. ML.NET allows the development of custom ML models using either C# or F#. These models can be used in scenarios involving sentiment analysis, fraud and spam detection, product and movie recommendation, image classification, and more.
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Databricks Open Sources Delta Lake to Make Data Lakes More Reliable
Databricks recently announced open sourcing Delta Lake, their proprietary storage layer, to bring ACID transactions to Apache Spark and big data workloads. Databricks is the company behind the creators of Apache Spark, while Delta Lake is already being used in several companies like McAffee, Upwork etc . Delta Lake is addressing the heterogeneous data problem that data lakes often have...
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Microsoft Open-Sources Approximate Nearest Neighbor Search Algorithm Powering Bing
Microsoft's latest contribution to open source, Space Partition Tree And Graph (SPTAG), is an implementation of the approximate nearest neighbor search (NNS) algorithm that is used in Microsoft Bing search engine.
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QCon San Francisco 2019: Registrations Open & Top Videos from QCon SF 2018
QCon San Francisco, the software conference that attracts attendees from all over the world, returns November 11-13, 2019, for the 13th year. QCon is organized by the people behind InfoQ & is dedicated to providing a platform for innovators & early adopters to share their story in the global epicenters of software development: Beijing, London, New York, Sao Paulo, Shanghai, and San Francisco.
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