AI Articles and Analysis about Business intelligence and analytics

Understanding customer feedback gets harder and harder at greater scale and with a greater variety of channels through which customers can provide feedback. Businesses that seek to better grasp the sentiments of their customers might have to sift through thousands of messages in order to get a feel for what customers are saying about their products or services.

Computer vision, an AI technology that allows computers to understand and label images, is now used in convenience stores, driverless car testing, daily medical diagnostics, and in monitoring the health of crops and livestock.

As the web grows and we spend more and more time online, moderation becomes a bigger and bigger challenge. Content influences buyers, and businesses eager to gain the trust of those customers are likely to do whatever they can to win.

According to research firm Zinnov, India is the fourth largest geography globally in terms of AI talent pool. Zinnov’s research says India is home to more than 200 AI startups that attracted about $200 million+ funding in 2017. A few major companies that are implementing AI include Amazon, AIG, Equifax, Infosys and NVIDIA - all of which we've covered in depth in our recent "AI in India" research.

This article is based on a presentation at a joint United Nations / INTERPOL conference for law enforcement agencies held in Singapore entitled “Machine Learning and Machine Vision Cutting-Edge Trends and Implications in Law Enforcement” delivered by Emerj CEO Daniel Faggella.

Businesses today around the world have some portion of their operations being automated, which concurrently has meant that a lot of data about these processes is being collected (from sensors or internal company data etc). A combination of AI, big data analytics, and data science techniques seem to be a growing trend in many industry sectors, with predictive analytics being one of the most well-known.

According to data from the U.S. Department of Health and Human Services, the progress of the value-based healthcare delivery system in the U.S. — a provider payment model based on patient outcomes — has run almost parallel to the significant implementation rate of electronic health records/electronic medical records (EHR/EMR).

We've noticed a lot of interest from our readers for our pieces dealing with AI applications in the finance and banking sectors. New applications for artificial intelligence often seem to develop by transferring an existing use-case in a related field, and this might be the case with AI applications for ATMs as well.