Significance of Training Data for Self-Driving Cars

Description

Training a new driver is straightforward and makes them practice until they can master basic skills well enough to pass a driver's license exam. But there are no such tests for Self Driving Cars, leaving it up to developers to decide when their technology is safe enough to deploy.

Collecting this data requires using data other innovators make available or doing it yourself and scaling the process. Larger autonomous car developers deploy fleets of test vehicles to capture data. Unfortunately, collecting all this data in-house using a limited fleet of test vehicles isn’t sufficient. Test vehicles typically operate in limited geographies, such as a small group of cities, to start. For self-driving cars to become more widely available, their AI systems must be trained using globalized data sets. This includes paying attention to factors like differences in rules, road signs, area wildlife, unusual obstacles, and weather conditions.

At TagX, we combine technology with human care to provide image annotations and video annotations with pixel-level accuracy. Our data labelers maintain quality while processing & labeling the image data which can be used efficiently for various AI and ML initiatives.