We live in an era of skyrocketing demand for ML algorithms in every aspect of our lives, from fun face-masking applications such as filters on Instagram or Snapchat to deeply useful applications designed to improve our work and living experiences, such as assisting in diagnosing illness or recommending treatment. Among the prime opportunities are emotion and engagement recognition, better homeland security features and better anomaly detections in industrial contexts.
At the same time, while people and businesses are hungry for ML/AI-based products, algorithms are hungry for data to train on. All of that means we will inevitably see more and more different data needs, and entirely manufactured data is the key.
Continue reading Sergey Toporov's opinion article for VentureBeat: https://venturebeat.com/ai/the-multi-billion-dollar-potential-of-synthetic-data/