{"id":"9b73c637-1873-4cc8-8d21-cf125af621ef","url":"https://api.tumn.com/news/9b73c637-1873-4cc8-8d21-cf125af621ef","title":"Meta’s Generative Ads Model (GEM): Scaling the Central Model and Compute Engine for Frontier Ads AI","summary":"Last year, we introduced GEM, the industry’s largest recommendation system (RecSys) foundation model. GEM established Meta’s first LLM-inspired paradigm for ads recommendation, driving major performance gains. Building on this foundation, our next goal is to further scale both co","sections":[],"faq":[],"sources":[{"url":"https://engineering.fb.com/2026/10/13/ml-applications/generative-ads-model-gem-scaling-frontier-ads-ai/","title":"Meta Engineering","publishedAt":"2026-10-13T16:01:00.000Z"}],"author":"TUMN 큐레이션","aiAssisted":false,"reviewStatus":"automated","reviewNote":"원문 제목과 공개된 발췌를 인용하고 원문으로 연결합니다. 내용을 재작성하거나 요약하지 않았습니다.","publishedAt":"2026-10-13T16:01:00.000Z","modifiedAt":"2026-10-13T21:24:54.000Z","checkedAt":"2026-10-13T21:24:54.647Z","language":"ko","kind":"link","sourceLabel":"AI 공식","profile":null,"via":null,"formats":{"json":"https://api.tumn.com/news/9b73c637-1873-4cc8-8d21-cf125af621ef.json","markdown":"https://api.tumn.com/news/9b73c637-1873-4cc8-8d21-cf125af621ef.md"}}