InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Microsoft Announces ML.NET 1.2
Earlier this month Microsoft announced ML.NET 1.2, along with updates on its Model Builder and CLI. ML.NET is an open-source, cross-platform machine learning (ML) framework for the .NET ecosystem.
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The First AI to Beat Pros in 6-Player Poker, Developed by Facebook and Carnegie Mellon
Facebook AI Research’s Noam Brown and Carnegie Mellon’s professor Tuomas Sandholm recently announced Pluribus, the first Artificial Intelligence program able to beat humans in 6 player hold-em poker. In the past years, computers have progressively improved, beating humans in checkers, chess, Go, and the Jeopardy TV show. Poker poses more challenges around information asymmetry and bluffing.
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Researchers Develop Technique for Reducing Deep-Learning Model Sizes for Internet of Things
Researchers from Arm Limited and Princeton University have developed a technique that produces deep-learning computer-vision models for internet-of-things (IoT) hardware systems with as little as 2KB of RAM. By using Bayesian optimization and network pruning, the team is able to reduce the size of image recognition models while still achieving state-of-the-art accuracy.
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Google Adds New Integrations for the What-If Tool on Their Cloud AI Platform
In a recent blog post, Google announced a new integration of the What-If tool, allowing data scientists to analyse models on their AI Platform – a code-based data science development environment. Customers can now use the What-If tool for their XGBoost and Scikit Learn models deployed on the AI Platform.
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Google Releases Post-Training Integer Quantization for TensorFlow Lite
Google announced new tooling for their TensorFlow Lite deep-learning framework that reduces the size of models and latency of inference. The tool converts a trained model's weights from floating-point representation to 8-bit signed integers. This reduces the memory requirements of the model and allows it to run on hardware without floating-point accelerators and without sacrificing model quality.
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QCon SF 19: Biggest Savings Deadline (July 27th) & Track Host Announcement
QCon San Francisco (Nov 11-15) is the conference for senior software engineers and architects to learn about the patterns, practices and use cases leveraged by the world’s most innovative software organizations, such as Google, Netflix, BBC, AWS, Microsoft, and GitHub. By registering before July 27 you can save $750 on the full three-day conference pass.
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Microsoft Announces Public Preview of Azure Data Share
Microsoft has announced the public preview of Azure Data Share, which provides capabilities to share data with users in the own organization, as well as with other organizations. Essentially, Microsoft positions the recently announced service as a big data tool, though it’s also possible to share individual files.
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Google Acquires Elastifile to Expand Its Cloud File Storage Offering
Google recently acquired Elastifile, a provider of scalable, enterprise file storage in the cloud. With the acquisition, Google further extends its current file storage offering, Cloud Filestore, and third-party partner offerings.
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Robot Social Engineering: Brittany Postnikoff at QCon New York
At QCon New York, Brittany Postnikoff presented “Robot Social Engineering: Social Engineering Using Physical Robots”. Quoting findings from academic research literature, she demonstrated that humans can often be manipulated via robots. A core message of the talk was the need for security and privacy to be part of any robot's fundamental design.
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Amazon Releases Aurora PostgreSQL Serverless to General Availability
Recently, Amazon announced the general availability of the PostgreSQL-compatible edition of Aurora Serverless.
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Google Releases TensorFlow.Text Library for Natural Language Processing
Google released a TensorFlow.Text, a new text-processing library for their TensorFlow deep-learning platform. The library allows several common text pre-processing activities, such as tokenization, to be handled by the TensorFlow graph computation system, improving consistency and portability of deep-learning models for natural-language processing.
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Google Releases Deep Learning Containers into Beta
In a recent blog post, Google announced Deep Learning Containers, allowing customers to get Machine Learning projects up and running quicker. Deep Learning consists of numerous performance-optimized Docker containers that come with a variety of tools necessary for deep learning tasks already installed.
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Facebook Open-Sources Deep-Learning Recommendation Model DLRM
Facebook AI Research announced the open-source release of a deep-learning recommendation model, DLRM, that achieves state-of-the-art accuracy in generating personalized recommendations. The code is available on GitHub, and includes versions for the PyTorch and Caffe2 frameworks.
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Moving Embodied AI forward, Facebook Open-Sources AI Habitat
In a recent blog post, Facebook has announced they have open-sourced AI Habitat, an Artificial Intelligence (AI) simulation platform that is designed to train embodied agents, such as virtual robots. Using this technology, robots can learn how to grab an object from an adjacent room or assist a visually-impaired person in navigating an unfamiliar transit system.
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Celia Kung on LinkedIn's Brooklin Data Streaming Service
Celia Kung from LinkedIn's team spoke at the QCon New York 2019 Conference last week about Brooklin data streaming service that supports pluggable sources and destinations. These can be data stores or messaging systems making the solution flexible and extensible. Brooklin is part of the streams infrastructure platform developed at LinkedIn.