InfoQ Homepage Machine Learning Content on InfoQ
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Bringing Intelligence to Enterprise Content Management, Google Releases Document Understanding AI
At the recent Google Cloud Next Conference, Google announced a new beta machine learning service, called Document Understanding AI. The service targets Enterprise Content Management (ECM) workloads by allowing customers to organize, classify and extract key value pairs from unstructured content, in the enterprise, using Artificial Intelligence (AI) and Machine Learning (ML).
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Amazon Expands Its Machine Learning Offering with AWS Deep Learning Containers
Recently, Amazon introduced AWS Deep Learning Containers (AWS DL Containers), which are Docker images pre-installed with deep learning frameworks allowing customers to deploy custom machine learning environments quickly.
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Facebook Open-Sources PyTorch-BigGraph Embedding Framework
Facebook AI Research is open-sourcing PyTorch-BigGraph, a distributed system that can learn embeddings for graphs with billions of nodes.
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Convolutional Neural Network Deep Learning Techniques for Crowd Counting
Deep learning techniques like Convolutional Neural Networks (CNNs) are a better choice for crowd-counting use cases, compared to traditional detection or regression based models. Ganes Kesari, co-founder and head of analytics at Gramener, spoke last week at the AnacondaCon 2019 Conference on how to count things using artificial intelligence (AI) models.
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DeepMind's AI Defeats Top StarCraft Players
DeepMind's AlphaStar AI defeated two top professional StarCraft players 5-0.
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Introducing TensorFlow Privacy, a New Machine Learning Library for Protecting Sensitive Data
In a recent blog post, TensorFlow announced TensorFlow Privacy, an open source library that allows researchers and developers to build machine learning models that have strong privacy. Using this library ensures user data are not remembered through the training process based upon strong mathematical guarantees.
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Q&A on Condé Nast's Natural Language Processor and Content Analysis
Beginning in 2015, Condé Nast created a natural-language-processing and content-analysis engine to improve the metadata around content created across their 22 brands. The new system has led to a 30% increase in click-through rates. InfoQ spoke with Antonino Rau, a software engineer and technology manager at Condé Nast US about the evolution of their NLP-as-a-service system named HAL.
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Deep Learning for Speech Synthesis of Audio from Brain Activity
Research teams use deep learning neural networks to synthesize speech from electrical signals recorded in human brains, to help people with speech challenges.
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Autonomous Analytics: Driving the Future of Data in Business Analytics
Autonomous data analytics will be the driver of business analytics in the future. and will be seamlessly integrated into our lives. John Thuma, from Arcadia Data, spoke at Enterprise Data World 2019 Conference in Boston about self-driving analytics.
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Amazon Alexa Enables an Ambient Computing Lifestyle
Alexa is becoming ubiquitous in the home through a purposeful Amazon Web Services (AWS) strategy to make Alexa, voice-activated service, a central component of an ambient computing lifestyle, according to Dave Limp, Amazon’s senior VP of devices and services in a recent article in the Verge.
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IBM May Have Found a Path to Dealing with Decoherence in Current Quantum Computers
In a recent Nature paper, researchers from IBM and other institutions devised two quantum algorithms to train a quantum support vector machine (SVM) classifier and proposed a novel approach to dealing with decoherence and noise in current quantum hardware.
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San Francisco: QCon.ai Schedule Nearing Completion
April 15-17 software engineering teams will gather in the Bay area for the Second Annual QCon.ai Software Conference. QCon.ai is focused on helping teams adopt and validate roadmaps in machine learning by hearing and learning from those that are doing it today. What truly differentiates QCon.ai is its machine learning focus given through the lens of the software engineer.
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Uber Open-Sources Ludwig Code-Free Deep-Learning Toolkit
Uber Engineering is open-sourcing Ludwig, a deep-learning toolkit that allows users to experiment with a variety of neural network structures without writing code.
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Making Machine Learning Adoptable for Clinicians
Dr. Alexander Scarlat explains the core tenants of machine learning in his 12-part series "Machine Learning Primer for Clinicians." Scarlat covers defining aspects of machine learning, followed by examples that communicate aspects of measuring the performance of machine learning models. The series uses animated charts in place of the math to help readers understand the machine learning concepts.
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Microsoft Announces Azure IoT Edge Support for Virtual Machines
In a recent blog post, Microsoft announced support for Azure IoT Edge on virtual machines. This new capability expands Microsoft’s support for virtualization platforms, including VMware vSphere and Hyper-V. Using these virtualization platforms, customers can choose to run Azure IoT Edge on Windows, a variety of Linux distributions or containers.