Augmented Reality Shopping and Artificial Intelligence - Near-Term Applications 2

Augmented Reality Shopping and Artificial Intelligence – Near-Term Applications

AI is finding itself in the physical retail space by way of augmented reality, or AR. Research and Markets estimated the size of the AR in retail market around $1.155 billion in 2018. As of now, numerous companies claim to provide AR support to shopper experiences in a variety of industries, including automotive and fashion.

Facial Recognition in Law Enforcement

Facial Recognition in Law Enforcement – 6 Current Applications

According to the US Government Accountability Office, the Federal Bureau of Investigation’s database contains over 30 million mugshots of criminals and ID card images from 16 states. This is just one of many law enforcement databases which also contain further identity information, including fingerprints and text data.

Virtual Mirrors and Computer Vision - Current Applications 2

Virtual Mirrors and Computer Vision – 9 Current Applications

According to a Deloitte study, 90 percent of worldwide retail sales are still done in physical stores. To compete with the convenience and endless aisle assortment offered online, this research suggests that meaningful customer experiences and brand engagement is crucial.

Emerj CEO Spoke at the Conference on Disarmament at the United Nations in Geneva

Emerj CEO Spoke at the Conference on Disarmament at the United Nations in Geneva

Event Title: The Conference on Disarmament at the United Nations in Geneva

Event Host: the United Nations

How AI Ethics Impacts the Bottom Line - An Overview of Practical Concerns

How AI Ethics Impacts the Bottom Line – An Overview of Practical Concerns

This week on AI in Industry, we are talking about the ethical consequences of AI in business. If a system were to train itself to act in unethical or legally reprehensible ways, it could take actions such as filtering or making decisions about people in regards to race or gender.

Machine Vision in Finance - Current Applications and Trends

Machine Vision in Finance – Current Applications and Trends

According to the Automated Imaging Association (AIA), machine vision is a combination of hardware like cameras, image sensors, and image processing software that can help automate applications like inspection and analysis by allowing machines (such as robots) to ‘see’ their surroundings.  

How Recommendation Engines Actually Work - Strategies and Principles

How Recommendation Engines Actually Work – Strategies and Principles

Episode Summary: When we think of recommendation engines, we might think of Amazon or Netflix, but while consumer goods and entertainment might be the most prominent domains for recommendation engines, there are others. This week, we speak with Madhu Gopinathan of MakeMyTrip, one of the few Indian unicorn companies, about recommendation engines for travel companies.

Stock Brokerage Firms and Artificial Intelligence - Current Applications

Stock Brokerage Firms and Artificial Intelligence – Current Applications

Stockbrokerage might be viewed by investors as a traditionally human-based service allowing them to buy and sell equities. When looking at the shift in how stock brokerage is different today compared to the early 2000s, the largest change seems to be in software-based automation. Put simply, a lot of what was being done by humans (such as executing trades, giving advice to investors, discretionary trading) can now be done through software.

AI for Speech Recognition - Current Companies, Technology, and Where Its Headed 1

AI for Speech Recognition – Current Companies, Technology, and Trends

Speech recognition is technology that can recognize spoken words, which can then be converted to text. A subset of speech recognition is voice recognition, which is the technology for identifying a person based on their voice.

What Executives Should be Asking about AI Use-Cases in Business

What Executives Should be Asking about AI Use-Cases in Business

When contemplating a new venture into AI or machine learning, companies need to take on a number of important considerations that relate to talent, existing data, and limitations. One way executives can judge how successful or appropriate and AI project would be for their company is to examine use cases of businesses that have previously done something similar.