InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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AWS Enhances Deep Learning AMI, AI Services SageMaker Ground Truth and Rekognition
Amazon Web Services (AWS) announced updates to their Deep Learning virtual machine image, as well as improvements to their AI services SageMaker Ground Truth and Rekognition.
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Amazon Personalize Is Now Generally Available, Bringing ML to Customers
After the first announcement of Amazon Personalize during AWS re:Invent last November, the service is now generally available for all AWS customers. With this service, developers can add custom machine learning models to their application, including ones for personalized product recommendations, search results and direct marketing, even if they don’t have much machine learning experience.
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Democratizing AI for Business Applications, Microsoft Release AI Builder Preview
At the recent Business Applications Summit in Atlanta, Microsoft announced a new Artificial Intelligence (AI) service for the Power Platform called AI Builder. The new service brings AI capabilities to low code application and workflow services: Microsoft PowerApps and Microsoft Flow which run on top of the Common Data Service (CDS), an enterprise-grade datastore.
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MIT Researchers Open-Source AutoML Visualization Tool ATMSeer
A research team from MIT, Hong Kong University, and Zhejiang University has open-sourced ATMSeer, a tool for visualizing and controlling automated machine-learning processes.
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Los Angeles CTO Roundtable about AI and Data
The recent "Leaders in Data CTO Roundtable" in Los Angeles included discussions about an artificial intelligence (AI) framework/platform for business, data in the next five years, data software stacks, and acquiring data talent.
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Amazon Enters Enterprise Content Management Space, Announces General Availability of Textract
In a recent press release, Amazon announced the general availability of Amazon Textract, a fully managed, machine learning service that extracts content from text and structured document data. Using Amazon Textract, customers can automate document workflows, index and catalog important information for use in downstream applications.
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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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