Why LinkedIn says prompting was a non-starter — and small models was the breakthrough
LinkedIn is a leader in AI recommender systems, having developed them over the last 15-plus years. But getting to a next-gen recommendation stack for the job-seekers of tomorrow required a whole new technique. The company had to look beyond off-the-shelf models to achieve next-level accuracy, latency, and efficiency.“There was just no way we were gonna be able to do that through prompting,” Erran Berger, VP of product engineering at LinkedIn, says in a new Beyond the Pilot podcast. “We didn't even try that for next-gen recommender systems because we realized it was a non-starter.”Instead, his team set to develop a highly detailed product policy document to fine-tune an initially massive 7-billion-parameter model; that was then further distilled into additional teacher and stu [...]
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Alembic melted GPUs chasing causal A.I. — now it's running one of the fastest supercomputers in the world
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