The traditional artificial intelligence that grew up over the past decade crunched numbers — seeking out patterns and providing predictive analytics based on likely probabilities. Enter generative AI which, among its many capabilities, provides a gateway to numerical AI predictions and observations, opening up possibilities for highly interactive verbal inquiries.
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Generative AI helps open the formerly very obscure black box of AI for a range of enterprise functions, and may even help close the divide between operational and information technology, says Peter Zornio, senior VP and CTO for Emerson. I recently caught up with Zornio in New York, where he explained how generative AI and numerical AI represent two ends of a continuum. The two variations are based on numerical models and language-based models.
The technical foundation of the two AI variations is the same, he says, but how we work with them is different. « The numerical-oriented production models are based on datasets of numbers, » he explains. « The language models use datasets based on zillions of documents, images, and other stuff. »
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