למה רקומנדרים LLM יהיו האפליקציות הגדולות ביותר של AI — Devansh Tandon, Meta

תקציר מקורי באנגליתFour of the 10 most-used apps in the world are content feeds, and for an hour of engagement they can be up to 100x cheaper to run than AI chat apps. The reason is that a feed decodes pointers to existing content instead of generating every token itself. Devansh Tandon, who leads Meta Recommendations Research, argues that recommendation systems scale just like LLMs, that the field is still early on that curve, and that the LLM recommender will become one of the biggest consumer applications of AI. Tandon lays out four S-curves the industry is climbing: traditional recsys, LLM-inspired, LLM-native and agentic. He then walks through the recipe for building an LLM recommender. First, tokenize content with semantic IDs, which turns a three-minute Reel from about 10,000 tokens into about 10. Nex