When it comes to generative AI, size definitely matters. The large in large language model is almost an understatement at times.
But many businesses are finding that what they need from AI doesn’t necessarily take a trillion parameters of knowledge. Those are the companies IBM is targeting with its latest Granite family of models, which feature reasoning, vision focused specifically on document understanding, and—like previous IBM releases—open-source availability.
At the HumanX conference in Las Vegas this week, we caught up with David Cox, VP for AI models at IBM Research, about the lane the enterprise giant is seeking to carve out with small language models in a crowded AI race.
Super-smart, giant models that can grapple with an advanced math problem, then turn around and write a poem, are certainly valuable, Cox said. But businesses are more often concerned with narrower, more routine sets of tasks than that.
“There’s a little bit of a fork in the road,” Cox told us. “There’s this AGI push where we’re trying to say, ‘We want to create the all-powerful, all-knowing single model,’ versus another path, which says, ‘Hey, now, all of a sudden, all of the unstructured text in my enterprise, all of the images and everything, all that unstructured data is now suddenly unlocked, and I’m going to write enterprise applications that take advantage of that.’”
Keep reading here.—PK
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