Articles

Our world is full of images, and most of the time, we humans can decipher exactly what those images are and what they mean quite easily. For computers, that’s not so simple. 

We’ve all heard the saying, “A picture is worth a thousand words.”

Maps are one of the most effective ways to present data. They display where we live, where we move, who we interact with and, ultimately, where we’re headed.

Managing paper documents is like juggling ping pong balls.

We’re all a little paranoid when it comes to data loss.

Deep learning is an intelligent machine's way of learning things.

Artificial intelligence is used as a broad catchall term for many subsets of AI, which is in and of itself a subset of computer science.

We’ve all seen the trope on crime TV shows: a detective stares at a blurry security image and demands someone “enhance” it. The technician taps a keyboard, the image zooms in, and suddenly every detail is crystal clear.

What is annotation? Annotation, also known as data labeling, is the process of annotating or labeling data, typically image data, but also videos, text, and audio. This process has become increasingly more important and popular with the rise of machine learning and supervised learning in specific. Supervised learning algorithms need to be fed training data that is labeled. Although there are a host of labeled datasets that are public and accessible, companies are seeing the importance of building their own proprietary annotated data sets. They are using data labeling software to achieve these goals.

Practically everyone knows user experience (UX) is an important consideration when creating a website or app. No one wants to use an unintuitive app with a terrible user interface (UI).