3 things to get right with data management for gen AI projects [Video]

After nearly two years of experimentation with generative AI, many IT leaders are ready to scale up. Before they do, however, they need to rethink data management.

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According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. While a few elite organizations like Nvidia use gen AI for things like designing new chips, most have settled on less sophisticated use cases that employ simpler models, and can focus on achieving excellence in data management.

And Doug Shannon, automation and AI practitioner, and Gartner peer community ambassador, says the vast majority of enterprises are now focused on two categories of use cases that are most likely to deliver positive ROI. One being knowledge management(KM), consisting of collecting enterprise information, categorizing it, and feeding it to a model …