Why AI leaders need a ‘backbone’ of large language models

AI adoption may be steadily rising, but a closer examination shows that most enterprise companies may not be quite ready for the big time when it comes to artificial intelligence.

Recent data from Palo Alto, California-based AI unicorn SambaNova Systems, for example, shows that more than two-thirds of organizations think using artificial intelligence (AI) will cut costs by automating processes and using employees more efficiently. But only 18% are rolling out large-scale, enterprise-class AI initiatives. The rest are introducing AI individually across multiple programs, rather than risking an investment in big-picture, large-scale adoption.

That will create an increasing amount of distance between companies that are AI leaders and innovators and those that fall behind, said Marshall Choy, senior vice president of product at SambaNova, which offers custom-built dataflow-as-a-service (and won VentureBeat’s AI Innovation Award for Edge AI in 2021).

Companies that are more mature in AI and able to invest in large-scale adoption will reap the rewards, he told VentureBeat, while the ones introducing AI across multiple programs will suffer from information and insight silos. “We see time and time again that leaders need to have a holistic view across their organization.”

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