Synthetic Data's Growing Role in Healthcare AI, Machine Learning and Robotics

Today there is a bottleneck in the development of artificial intelligence and machine learning – real-world data collection. AI and machine learning models require large datasets to become proficient at a task.

But preparing these datasets for model training is both costly and labor-intensive. It is a conundrum, and the lack of large, accurately labeled datasets for specific applications is holding back the development of artificial intelligence and machine learning.

Beyond synthetic data, computer vision as a whole is a promising technology for the healthcare industry. From a health and safety perspective, computer vision can monitor how often and how long healthcare providers wash their hands, evaluate in real-time whether hospital-bed patients are motioning for help, and keep track of medical tools within a room.