Checkr runs a background service to vet prospective hires for more than 100,000 businesses. To perform more than 1.5 million of those background checks, it needed an AI model that was accurate and ...

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, ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.