Explore the latest advancements in AI-powered search with this informative video on SPLADE, the first search model to outperform BM25. Dive into the world of sparse and dense vector search, comparing their advantages and limitations. Learn how SPLADE, a cutting-edge sparse embedding model, addresses the shortcomings of traditional methods like TF-IDF and BM25. Discover how SPLADE can be used alongside dense embedding models for optimal results. Gain insights into the inner workings of SPLADE, including its use of transformers and masked language modeling. Understand the vocabulary mismatch problem and how SPLADE tackles it. Get hands-on with practical implementation examples using Python, PyTorch, and Hugging Face. Explore the Naver SPLADE library and contemplate the future of vector search in this comprehensive 29-minute tutorial.