The Next Step with Deep Learning

Artificial intelligence (AI) and machine learning are the cornerstones of the digital transformation in computing. These technologies hinge on the ability to recognize patterns then, based on data observed in the past, predict future outcomes. This interesting topic came to us from Venture Beat in their article, “Deep learning is bridging the gap between the digital and the real world.”

Think of the suggestions coming from Amazon and Netflix that feel a little too perfect. Although machines utilizing AI principles are often referred to as smart, most of these systems don’t learn on their own. Human programming is still necessary. Data scientists prepare the inputs, selecting the variables to be used for predictive analyticsDeep learning, on the other hand, can do this job automatically. 

Deep learning methods are a modern update to artificial neural networks that exploit abundant cheap computation. Algorithms have always been at home in the digital world, where they are trained and developed in perfectly simulated environments. The current wave of deep learning facilitates AI’s leap from the digital to the physical world. The applications are endless, from manufacturing to agriculture, but there are still hurdles to overcome. 

Melody K. Smith

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

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.

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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.