Expert Insights

blog

Data & AI


Ethics of AI - Chapter 1: The Human Difference

The first question when considering machine ethics is “where to start?”  We could start with a definition of ethics, an understanding of what is possible, or how machines are improving at an increasing rate.

Nathan Lasnoski by Nathan Lasnoski

Computer Vision: What does Ai see in the real world on Microsoft platform?

Microsoft Cognitive Services allows for your applications, websites, or services to become more aware of the natural surroundings by giving ability to hear, see, speak, and understand the user and environment around the user.  So, what can a computer see? Do android dream of electric sheep?

Lwin Maung by Lwin Maung

ETHICS OF AI – INTRODUCTION

We are experiencing a generational shift in the impact of technology in the human experience.  The infusion of technology into every aspect of life is changing the way we live our daily lives and the way businesses engage their customers, partners, and employees.   

Nathan Lasnoski by Nathan Lasnoski

Leveraging Facial Recognition in your systems

Security is an important aspect of our lives and we use various means of security every day. In order for us to secure items in our lives, we have to have a trust factor. This applies to our bank accounts, our passwords, and even vehicles that we utilize every day. Sometimes, security can be complex -- in the case of bank account being accessed over the internet, or a rolling security codes in your car's remote start module, or RFID and barcodes in your driver license or passport.
 

Lwin Maung by Lwin Maung

Concurrency Data and Analytics Internship

Hi! My name is Chance Alexander, and this blog post will entail the experiences and responsibilities within Concurrency's internship program on the data and analytics team.

Chance Alexander by Chance Alexander

Data Science Primer: Reducing Downtime with Machine Learning

Downtime is one of the biggest financial risks in manufacturing. Asset-heavy companies are exposed to a lot of risk, because every time a machine breaks they lose labor costs, suffer from decreased production, and possibly even miss sales targets. But typical maintenance schedules are somewhat arbitrary and tend to be expensive. Companies pay technicians to look at machines in no danger of breaking down even as actual problems get overlooked. Machine learning allows manufacturers to combine sensor data with the power of the cloud to catch problems just before they happen, all while spending less on routine maintenance.
 

Brian Goodwin, PhD by Brian Goodwin, PhD