Hello and welcome to Eye on A.I. At Fortune’s Brainstorm Tech conference in Deer Valley, Utah, last week, generative A.I. was threaded through every conversation I had. I’ve been reporting from the Bay Area this week, where it is pretty much the same story. Companies large and small are racing to put generative A.I. into practice.
But it is also clear from the conversations I’ve been having that a lot of companies are struggling to figure out exactly what the best use cases for the technology are. “People are throwing everything at the bazooka right now, hoping magic comes out,” Sean Scott, the chief product officer at PagerDuty, said during a morning breakout session at Brainstorm Tech on A.I. and data privacy. The bazooka he’s referring to are large language models (LLMs), and Scott’s point was that sometimes such firepower isn’t necessary. Often, a smaller A.I. model, or some good old-fashioned rule-based coding, will do the job just as well, or maybe even better, at a much lower cost. “At the end of the day, it’s about what problem you are trying to solve and what is the best way to solve that problem,” he said.
