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, ...

To reduce the threat of model loss, synthetic data corruption and insight erosion, CXOs must create a new class of "AI-aware" data recovery capabilities.

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