AI & RoboticsNews

Algorithmia: 50% of companies spend over 3 months deploying a single AI model

Incorporating AI and machine learning technologies into everyday workflows isn’t as easy as the testimonials would have you believe. That’s the top-level finding from a survey of 750 business decision makers conducted by Algorithmia, which found that while machine learning maturity in the enterprise is generally increasing, the majority of companies (50%) spend between 8 and 90 days deploying…
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AI & RoboticsNews

Sproutt raises $12 million to find your best life insurance policy with AI

Life insurance isn’t as popular as it once was, despite the fact that a majority of people consider it to be important. Over 80% of consumers agreed in a recent survey that people need a life insurance policy, yet just 62% say they have one themselves. In fact, only 44% of U.S. households held individual life insurance as of 2010 — a 50-year low — compared with the 72% of Americans who owned…
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AI & RoboticsNews

Google taps AI to improve news results in Search

Google says it’s implementing AI and machine learning techniques to improve story suggestions in Google Search. In a blog post this morning, the tech giant announced that users in the U.S. in English (with more languages and locations to come in the next few months) who…
AI & RoboticsNews

LeanDNA raises $15 million for AI factory inventory and delivery management software

Factories regularly face inventory shortages and missed deliveries, but they’re wounds of a self-inflicted nature. Just ask Richard Lebovitz, the founder of LeanDNA, who previously founded Factory Logic, which was acquired by SAP for an undisclosed amount. He’s the founder and CEO of LeanDNA, an Austin, Texas-based startup building a cloud-based actionable intelligence platform for factory…
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AI & RoboticsNews

MIT and IBM’s ObjectNet shows that AI struggles at object detection in the real world

Object recognition models have improved by leaps and bounds over the past decade, but they’ve got a long way to go where accuracy is concerned. That’s the conclusion of a joint team from the Massachusetts Institute of Technology and IBM, which recently released a data set — ObjectNet — designed to illustrate the performance gap between machine learning algorithms and humans. Unlike many…
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