If data is the new oil, these companies are the new Baker Hughes

Artificial intelligence runs on data. And today, in most cases, that data needs to be labeled by humans.

This is particularly true when using computer vision to identify tumors on medical scans, spot roof damage from aerial photography or figure out whether an object crossing in front of your self-driving car is a plastic bag or a mother pushing a stroller. But it’s also true for speech recognition: To train the software, someone must provide an accurate transcript to match an audio recording.

See full article at https://fortune.com/2020/02/04/artificial-intelligence-data-labeling-labelbox/