Artificial Intelligence in Atlanta - Strengths, Weaknesses, and Trends in the Atlanta AI Ecosystem 1

Artificial Intelligence in Atlanta – Strengths, Weaknesses, and Trends in the Atlanta AI Ecosystem

Last September I had the chance to do a series of AI-related speaking engagements in Atlanta (one of those presentations became one of our most popular articles on “enterprise AI adoption”), but unlike most trips, I spent very little time in the hotel.

Machine Learning in Email Marketing

Machine Learning in Email Marketing – Comparing 5 Current Applications

Despite the emergence of chat apps and social media over the past decades, email has continued to thrive. A 2017 study from Radicati marketing research claimed that email accounts were expected to reach 4,920 million by the end of 2017, a number that has not changed much since 2013, and that about 100 billion business emails are sent daily.

Industrial AI Applications - How Time Series and Sensor Data Improve Processes

Industrial AI Applications – How Time Series and Sensor Data Improve Processes

Over the past decade, the industrial sector has seen major advancements in automation and robotics applications. Automation in both continuous process and discrete manufacturing, as well as the use of robots for repetitive tasks are both relatively standard in most large manufacturing operations (this is especially true in industries like automotive and electronics).

Achieving Intelligent Automation - Leveraging IoT Data from Automated Systems

Achieving Intelligent Automation – Leveraging IoT Data from Automated Systems

In this episode of AI in Industry, we speak with Brendan Kohler, the CTO of Co-founder of Boston-based startup Sentenai. Brendan speaks about how businesses today can effectively leverage the data being collected by their existing IoT and automation systems. Though example applications and use-cases, Brendan elaborates on what kinds businesses might use this technology today and what they can expect in the near future.

Dan Faggella AI in Real Estate

Machine Learning in Real Estate – Trends and Applications Presented

This article is based on a presentation originally given by Daniel Faggella, CEO & Founder at Emerj (formerly TechEmergence) to a group of real estate executives at a Grupo4s "Future of Real Estate" event in San Francisco, in March of 2018.

Applications of Machine Vision in Heavy Industry

Applications of Machine Vision in Heavy Industry – Telecom, Transportation, and More

Episode summary: In the last two or three years we at Emerj have witnessed a definite uptick in AI applications like predictive maintenance and heavy industry. Many exciting business intelligence and sensor data applications are making their way into “stodgy” industries like transportation, oil and gas, and telecom - where machine vision has countless applications.

Business Intelligence Through Intellectual Property Analytics - Examining Facebook and Amazon

Business Intelligence Through Intellectual Property Analytics – Examining Facebook and Amazon

Intellectual property (IP) is about more than preventing competitors from copying a technology or idea. IP informs a number of other strategic initiatives for companies:

AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY

AI in the Accounting Big Four – Comparing Deloitte, PwC, KPMG, and EY

Deloitte, EY, PricewaterhouseCoopers (PwC) and KPMG are among the largest service providers in the accounting industry— collectively referred to as the Big Four. Many of the financial and consulting services offered by these firms - such as advising on investment decisions - involve finding patterns in very large sets of data. This data is often beyond the understanding of a single person (or team of persons) and is often “noisy” and without a set format.

Applications of Machine Vision in Heavy Industry 1

Artificial Intelligence and the Opioid Epidemic – Applications for Relapse Treatment, Abuse Prevention, and More

The opioid overdose crisis continues to maintain a strong grip on the nation. According to the National Institute on Drug Abuse (NIDA), the epidemic claims more than 115 lives in the United States every day.

How to Assess an Artificial Intelligence Product or Solution for Non-Experts

How to Assess an Artificial Intelligence Product or Solution (Even if You’re Not an AI Expert)

Many products today leverage artificial intelligence for a wide range of industries, from healthcare to marketing. However, most business leaders who need to make strategic and procurement decisions about these technologies have no formal AI background or academic training in data science.