InfoQ Homepage Machine Learning Content on InfoQ
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Introducing KiloGram, a New Technique for AI Detection of Malware
A team of researchers recently presented their paper on KiloGram, a new algorithm for managing large n-grams in files, to improve machine-learning detection of malware. The new algorithm is 60x faster than previous methods and can handle n-grams for n=1024 or higher. The large values of n have additional application for interpretable malware analysis and signature generation.
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Predicting the Future, Amazon Forecast Reaches General Availability
In a recent blog post, Amazon announced the general availability (GA) of Amazon Forecast, a fully managed, time series data forecasting service. Amazon Forecast uses deep learning from multiple datasets and algorithms to make predictions in the areas of product demand, travel demand, financial planning, SAP and Oracle supply chain planning and cloud computing usage.
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Google Open-Sources Real-Time Hand Tracking for Android and iOS
Google has open-sourced a new component for its MediaPipe framework aimed to bring real-time hand detection and tracking to mobile devices.
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Amazon Introduces Two New Features for Polly: Neural Text-to-Speech and Newscaster Style
Recently, Amazon announced the general availability of Neural Text-to-Speech (NTTS) technology in their Polly service in AWS, which turns text into lifelike speech. Furthermore, Amazon Polly now also offers a Newscaster speaking style.
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Microsoft Open-Sources TensorWatch AI Debugging Tool
Microsoft Research open-sourced TensorWatch, their debugging tool for AI and deep-learning. TensorWatch supports PyTorch as well as TensorFlow eager tensors, and allows developers to interactively debug training jobs in real-time via Jupyter notebooks, or to build their own custom UIs in Python.
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Baidu Open-Sources ERNIE 2.0, Beats BERT in Natural Language Processing Tasks
In a recent blog post, Baidu, the Chinese search engine and e-commerce giant, announced their latest open-source, natural language understanding framework called ERNIE 2.0. They also shared recent test results including achieving state-of-the art (SOTA) results and outperforming existing frameworks, including Google’s BERT and XLNet in 16 NLP tasks in both Chinese and English.
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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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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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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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MIT Debuts Gen, a Julia-Based Language for Artificial Intelligence
In a recent paper, MIT researchers introduced Gen, a general-purpose probabilistic language based on Julia aimed to allow users to express models and create inference algorithms using high-level programming constructs.
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Front End Architecture in a World of AI
At QCon New York 2019, front end software engineer Thijs Bernolet of Oqton explained some of the challenges in creating front end architectures influenced by machine learning.