Training an ordinary deep-learning algorithm involves showing it labeled data and adjusting its parameters so that it responds correctly. In the case of an image classification algorithm, an ...

Similarly, the AI startup Handl uses labeled data to more accurately convert documents to structured text. We’ve all heard of OCR (Object Character Recognition), but with AI-powered by labeled ...

Creating smart, accurate AI algorithms is an ongoing effort that requires validation of training sets and some level of human intervention. Here's a guide to how to craft effective ones.

If there’s one thing that has fueled the rapid progress of AI and machine learning (ML), it’s data.Without high-quality labeled datasets, modern supervised learning systems simply wouldn’t ...

No company or public institution is willing to publicize its data and algorithms for fear of being labeled racist or sexist, or maybe worse, having a great algorithm stolen by a competitor.

The algorithm isn't racist, but the data that has been fed to it is biased in such a manner as to further perpetuate the same skewed view "whereby, for example, poor people have less access to ...

It is often cheap to gather bio-signal data, but it can be expensive to label it. Instead, researchers can use the unlabeled data as a warm-up for the machine-learning algorithm.