Almost everyone today uses machine learning unintentionally. Several algorithms support the search features of Google, Facebook, or LinkedIn.

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Yelp’s latest update will compile a list of Popular Dishes for each restaurant, using AI to figure out what everyone prefers to eat based on the restaurant’s reviews. The details: Yelp is using machine learning to skim the reviews for each restaurant in its considerable catalog. Once it does, it determines the most popular dishes …

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Embedded machine learning technology is increasingly being incorporated into rich, predictive user interactions.

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Today NVIDIA made a number of announcements centered around Machine Learning software at the Computer Vision and Pattern Recognition Conference in Salt Lake City. "NVIDIA is kicking off the conference by demonstrating an early release of Apex, an open-source PyTorch extension that helps users maximize deep learning training performance on NVIDIA Volta GPUs. Inspired by state of the art mixed precision training in translational networks, sentiment analysis, and image classification, NVIDIA PyTorch developers have created tools bringing these methods to all levels of PyTorch users."

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You probably use machine-learning systems every day without even knowing it. The technology gives us spam filters, our Facebook News Feeds, digital assistants, search engines, Netflix picks, Amazon recommendations, fraud detection systems, chatbots and more. And it’s only going to become more pervasive. Machine learning may soon assess your risk of heart disease, drive your car and automatically check out your groceries.

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An in-memory computing platform with continuous learning capabilities enables a range of real-time decision making use cases.

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June’s NAACL conference saw machine learning specialists from technology company Iprova present a paper introducing a new and effective method for the unsupervised training of machine learning algorithms to infer sentence embeddings.

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Machine learning makes it possible to discover patterns in supply chain data by relying on algorithms that quickly pinpoint the most influential factors to a supply networks’ success, while constantly learning in the process.

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AI breakthroughs continue to be infused in developer tooling, with a new machine learning framework for the upcoming iOS 12 being the latest example.

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