AI models drift just like cars wear down, and with GenAI, that drift is public, risky and constant — making real-time ...

Back in 2019, Gartner predicted that the vast majority of AI projects would continue to fail: Only 53% of projects make it from prototypes to production, and 85% of those blow up. And that’s more or ...

The transition from experimental AI models to production systems exposes the true quality of training data. Edge cases that were absent during testing become frequent. Small inconsistencies in ...

Data stream classification and concept drift detection are essential components in the realm of real-time data analytics. As data streams continuously flow from sources such as sensors, financial ...

Decisions anchored in data can help organizations compete, scale and avoid risk, but only if teams verify the integrity of the data feeding analytics or AI systems before models are trained or ...

Recent advancements in AI and computer vision capabilities have massively increased the scale and demand for training data. While real world data continues to dominate AI training, it is often ...

Founder and Managing Principal of DBP Institute. I consult companies on how to transform technology and data into a valuable business asset. There are many reasons for this poor success rate, one of ...