An Intellyx Brain Candy Brief
Let’s say you’re driving on a city street, and you take a photo through the windshield. At the far left of the image is a partial view of a person on the curb, cut off at the edge of the image. Is the person about to step into the street?
A human could easily tell whether the person was facing toward the street or not, even though the image didn’t include the whole person – but an AI-driven image recognition program might have a much harder time.
Problems like this one are the focus of what Scale API offers its customers. Scale API has a number of human labelers on staff whose job is to take video and still images and label their contents as per customers’ instructions in order to better train their machine learning algorithms.
The results are then available via API, similar to Amazon’s Mechanical Turk service. The main difference between Scale API and the Mechanical Turk, however, is the latter is crowdsourced, while Scale API carefully staffs and trains its human labelers.
Scale API’s core barrier to entry is its AI-enabled labeling tools that give the human labelers a leg up on their job, focusing their attention on the salient elements of the image or video.
Copyright © Intellyx LLC. Intellyx publishes the Agile Digital Transformation Roadmap poster, advises companies on their digital transformation initiatives, and helps vendors communicate their agility stories. As of the time of writing, none of the organizations mentioned in this article are Intellyx customers. To be considered for a Brain Candy article, email us at pr@intellyx.com.
