{"blog_url":"https://techblog.ap-com.co.jp/","title":"Scaling RAG and Embedding Computations with Ray and Pinecone","html":"<iframe src=\"https://hatenablog-parts.com/embed?url=https%3A%2F%2Ftechblog.ap-com.co.jp%2Fentry%2F2024%2F06%2F13%2F115821\" title=\"Scaling RAG and Embedding Computations with Ray and Pinecone - APC \u6280\u8853\u30d6\u30ed\u30b0\" class=\"embed-card embed-blogcard\" scrolling=\"no\" frameborder=\"0\" style=\"display: block; width: 100%; height: 190px; max-width: 500px; margin: 10px 0px;\"></iframe>","blog_title":"APC \u6280\u8853\u30d6\u30ed\u30b0","width":"100%","categories":["Databricks_EN","Databricks","DAIS2024"],"provider_url":"https://hatena.blog","version":"1.0","type":"rich","image_url":"https://cdn-ak.f.st-hatena.com/images/fotolife/a/apc_watanabe/20240607/20240607105046.png","url":"https://techblog.ap-com.co.jp/entry/2024/06/13/115821","height":"190","description":"Preface In this session, we explored how to efficiently scale Retrieval-Augmented Generation (RAG) and embedding computations using Ray and Pinecone. Engineers Roy (Engineering Manager at Pinecone) and Cheng Su (Engineering Manager from AnyScale's data team) utilized their extensive experience for a\u2026","provider_name":"Hatena Blog","author_url":"https://blog.hatena.ne.jp/ywchen/","author_name":"ywchen","published":"2024-06-13 11:58:21"}