Artificial Intelligence in Sports - Current and Future Applications

Artificial Intelligence in Sports – Current and Future Applications

The North American sports industry is a cultural and economic staple generating billions of dollars in revenue each year. Spectator sports fall under the broader category of arts, entertainment, and recreation, representing 1.1 percent of the GDP in 2016. Artificial intelligence in sports may have been rare just five years ago - but now AI and machine vision are making their way into a number of sports industry applications, from chatbots to computer vision and beyond.

Telecom Machine Learning Applications -

Telecom Machine Learning Applications – Comparing AT&T, Verizon, Comcast and More

As a business leader, you know the essential role of telecommunications in running a business. In the digital era, the telecom industry has shifted from basic phone and Internet service to a sector that is going high-tech and constantly evolving into a more mobile, wearable and automated environment.

A VC's Perspective –7 Artificial Intelligence Trends That Actually Matter

A VC’s Perspective –7 Artificial Intelligence Trends That Actually Matter

The following article has been written by Luigi Congedo, principal at BootstrapLabs. BootstrapLabs is an AI-focused VC firm in San Francisco. Editing and quotes added by the Emerj team.For information about our contributed material and publishing arrangements with brands, please visit our partnerships page.

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Machine Learning Marketing – Expert Consensus of 51 Executives and Startups

When it comes to business applications of machine learning, marketing is always near the top of the list. Modern digital marketing offers a huge volume of quantifiable data for teams to work with, and marketing can be said to take precedent over other areas like customer service and business intelligence because of it's direct tie to driving revenue. Machine learning marketing applications are still relatively novel for most small and medium-sized business, but this may change drastically over the next five years.

How to Apply Machine Learning to Business Problems 3

How to Apply Machine Learning to Business Problems

It's easy to see the massive rise in popularity for venture investment, conferences, and business-related queries for "machine learning" since 2012 - but most technology executives often have trouble identifying where their business might actually apply machine learning (ML) to business problems.

Artificial Intelligence Industry – An Overview by Segment 950×540

Artificial Intelligence Industry – An Overview by Segment

Today's artificial intelligence market is not easy to quantify. Besides the lack of consensus on a coherent definition for "artificial intelligence" as a term, the field's nascent stage of development makes it difficult to carve out silos or hard barriers of where one industry or application ends, and another begins.

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Artificial Intelligence at KeyBank

KeyBank is a financial services institution with a rich history dating back to 1825 and headquartered in Cleveland, Ohio. With 17,000 employees, operations across 15 states, and assets totaling $187 billion, KeyBank's commitment to innovation is evident in its strategic application of AI technologies to enhance both workforce management and customer service. 

Driving Responsible Approaches to AI through Operations and Development Workflows

Driving Responsible Approaches to AI Through Operations and Development Workflows – with Ranjan Sinha of IBM and Tsavo Knott of Pieces

This interview analysis is sponsored by Pieces and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

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The Evolution of Artificial Intelligence – with Matt Berseth of NLP Logix

Natural language processing (NLP) is a branch of artificial intelligence meant for analyzing, understanding, and generating human language. It enables computers to process and interpret natural language data, allowing for more natural interactions between humans and machines.

The Future of IT in Life Sciences-1

The Future of IT in Life Sciences – with Steven Zhang of Deloitte

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

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