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Inside Machine Learning

Machine learning is a pervasive and powerful form of artificial intelligence (AI) and it is changing almost every industry. The potential and limitations of machine learning, as well as how it’s being used needs further discovery. This interesting news came to us from the Massachusetts Institute of Technology (MIT) in their article, “Building explainability into the components of machine-learning models.”

Machine learning is behind chatbots and predictive text, language translation apps and how your social media feeds are presented. It powers autonomous vehicles and machines that can diagnose medical conditions based on images. 

When companies today deploy AI programs, they are most likely using machine learning — so much so that the terms are often used interchangeably, and sometimes ambiguously. Machine learning is a subfield of AI that gives computers the ability to learn without explicitly being programmed.

Explanation methods that help users understand and trust machine learning models often describe how much certain features used in the model contribute to its prediction. Data Harmony is Access Innovations’ AI suite of tools that leverage explainable AI for efficient, innovative and precise semantic discovery of new and emerging concepts to help find the information you need when you need it.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, changing search to found.

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Melody Smith

Melody K. Smith has provided organizational, social media and digital communication services to a large non-profit for the past twenty years. Prior to that she championed employee engagement and communications in the healthcare field. She holds a Bachelors degree in Marketing. When not wrangling and writing TaxoDiary content for your reading pleasure, Melody writes fiction, rescues dogs and throws legendary dinner parties.