A Glossary For Next-Generation AI Posted on : May 24 - 2019

As business adoption of artificial intelligence (AI) expands rapidly, so does the vocabulary used to describe the technology and the myriad ways companies are putting it to work.

While terms such as algorithm, machine learning and neural networks have become as familiar today as cloud, SaaS and IoT, dozens of new AI terms and trends are already entering the field or rising in importance. Here’s a look at some of those—and why you should become familiar with each.

Adversarial data

A machine-learning training technique in which scientists intentionally expose algorithms to corrupted data to trick them into making faulty predictions or reach incorrect conclusions. The technique allows developers to uncover security vulnerabilities that could be exploited by hackers or to examine the results for hidden bias that could lead to flawed results.

AI architect

A data scientist who takes a direct role in applying artificial intelligence to improve business processes. AI architects look for applications of AI for the company as a whole, such as automating recruiting and hiring, as well as for ways to put AI to work automating routine work (like developing chatbots for customer service).

AIOps

Processes that automate IT operations using Big Data analytics in real time. AIOps uses advanced data analysis and pattern recognition to enable IT teams to streamline many of their traditional management functions, maximizing systems performance. By 2022, Gartner predicts that 40% of large companies will replace current human-led IT services with automated AIOps systems. View More