Increased use of artificial intelligence in media and entertainment will mean spending could reach $8.4 billion by 2023. Plus, what obstacles do manufacturers need to overcome for advanced machine learning to be successful. And, some additional predictions for data science & analytics forecasts in 2022.

High-Level Machine Learning: What Will It Take?

By Deepak Turaga & James Wells, contributing writers for

Machine learning is being utilized in service businesses to run standard, routine, repeatable parts of processes. During the recent OPEX Summer virtual conference, the daily sessions were filled with service companies presenting their approach to using machines to run the core business processes that are executed a dozen to a hundred times a day.


AI in Media and Entertainment Market to Reach US$8.4 Billion by 2023

By Aratrika Dutta, contributing writer for

The global AI in the media and entertainment market is expected to grow from US$1.8 billion in 2018 to US$8.4 billion in 2023 at a CAGR of 30.0% during the forecast period. The increasing use of artificial intelligence in media and entertainment in gaming, fake story detection, plagiarism detection, personalization, production planning and management, sales and marketing, talent identification, and other industries is driving the growth of AI in the media and entertainment market across the globe.


How to integrate IoT, big data and analytics into Industry 4.0

By Mary Shacklett, contributing writer for

Industry (or Manufacturing) 4.0 started as a German government initiative in 2011. It refers to a Fourth Industrial Revolution characterized by smart factories using robotics, autonomous operations, the Internet of Things, big data, analytics, artificial intelligence, and a convergence of IT and OT. The goal is to create efficient, agile and intelligent manufacturing.


Data Science & Analytics Predictions, Trends, & Forecasts

By Shelby Hiter, contributing writer for

The world of data science is expanding as new technologies and use cases push innovation to meet the rising demand for data-driven business outcomes.


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