AI Servo Monitor uses artificial intelligence to predict possible failures of the drive systems for FANUC servomotors and spindle motors. AI Servo Monitor, in conjunction with MT-LINKi through machine learning, analyzes the daily performance of machines equipped with FANUC CNCs. Daily data is displayed in intuitive graphs which allows users to easily monitor abnormalities on these machines. Artificial intelligence automatically creates a baseline model of the machine while running in a normal state. An "anomaly score" developed expresses a difference in the baseline model and the daily recorded values.

FANUC's AI Servo Monitor provides machine health data and analysis to maximize uptime. HOFFMAN ESTATES, Ill.–(BUSINESS WIRE)–Downtime is the enemy of profitability in manufacturing, which is why FANUC, a leading global automation solutions provider, has introduced a new Industrial Internet of Things (IIOT) software designed to prevent production problems before they happen. AI Servo Monitor uses artificial intelligence to predict possible failures of the drive systems for FANUC servomotors and spindle motors. AI Servo Monitor, in conjunction with MT-LINKi through machine learning, analyzes the daily performance of machines equipped with FANUC CNCs. Daily data is displayed in intuitive graphs which allows users to easily monitor abnormalities on these machines.

Wouldn't it be great if there was a tool that scored your post and told you how it could be improved? Just enter the URL of any Medium blog post into the input field and click'Go'. You'll get back a score for your post and a full breakdown of how the score was calculated. First, the key features are extracted from your post -- things like the length of the title, number of images, tags, follower count, the time it was published, where it was published etc. These features are then shown to a machine learning model which has been trained to predict the number of recommendations that a given post will get, based on these features.

In June 2017 Apple released its Core ML API designed to make AI faster on its iPhone, iPad, and Apple Watch products. The API covers all sorts of ML operations such as image and face recognition, object detection, NLP (natural language processing) and NLG (natural language generation). Core ML supports popular ML tools and models, including neural networks (deep, convolutional, recurrent), linear models and decision trees. It may be easily integrated into an Xcode development environment and become a part of your iOS app functionality. By making pre-trained ML models available for iOS developers, Apple's Core ML promises to increase the scope of iOS applications with core AI/ML functionality available to users of Apple products.

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