AI-machine learning data can trip companies up if they don't take into account an unknowable future, said MIT's Iyad Rahwan.

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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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Discover how AI has moved data collection beyond finding the what and how to a more predictive and prescriptive presentation of actionable data.

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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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Advances in computer vision algorithms and the application of modern artificial intelligence (AI) techniques have made writing visual tests practical. With AI in testing, autonomous testing becomes possible. The boring and rote tasks will be delegated to the AI so that the tester can do the thinking.

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The applications of AI in healthcare are boundless, and healthcare, in turn, is one of the numerous areas where AI can have a significant impact

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Artificial Intelligence (AI) and Machine Learning (ML) are often used interchangeably, but they are different.

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New tools for developers make it easier to integrate machine learning into apps; it's like training wheels for AI.

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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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