Two years ago, the entire world spent an estimated $800 million on data labeling: the painstaking process of annotating images and other information to train machine-learning and AI models. Now, the ...

IDC predicts worldwide spending on artificial intelligence (AI) systems will reach $35.8 billion in 2019, and 84% of enterprises believe investing in AI will lead to greater competitive advantages ...

Data labeling plays a pivotal role within the ever-expanding realm of AI. This intricate process involves the meticulous tagging and categorization of raw data, encompassing various formats such as ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

AI data trainer roles have moved from obscure contractor gigs to a visible career path with clear pay bands and defined skills. Companies building chatbots, recommendation engines, and large language ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...

The demand for labeled data has skyrocketed with the advancement of artificial intelligence technologies, leading to a new economic opportunity for remote workers. Often likened to a modern gold rush, ...