Search Results for: Natural Language Processing – Business Applications

Machine translation has significantly evolved over time, especially in terms of accuracy levels in its output.

Talent sourcing and recruitment are at the center of developing and maintaining the U.S. labor force. The U.S. Bureau of Labor Statistics (BLS) projects that over the decade spanning from 2016 to 2026, the labor force will increase by 11.5 million. This increase is approximately equivalent to a 0.7 percent annual growth rate.

This article was written in partnership and collaboration with the IEEE. For more information about content partnerships visit the Emerj Partnerships page.

Artificial intelligence companies continue to find ways of developing technology that will manage laborious tasks in different industries for better speed and accuracy. In the legal profession, AI has already found its way into supporting lawyers and clients alike.

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.

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.

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.

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.

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.

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.