New DeepLearning.AI Course on Multi-Vector Image Retrieval with ColPali and MUVERA
Blog post from Qdrant
DeepLearning.AI has launched a new intermediate-level course on Multi-Vector Image Retrieval, led by Qdrant’s Senior Developer Advocate, Kacper Łukawski. This free online course is aimed at AI developers working with multi-modal data, providing them with the skills to implement advanced image retrieval systems in their applications. The course explores multi-vector approaches, which offer more precise search capabilities by encoding images into multiple vectors for each visual patch, thus transforming fine-grained matching between text queries and visual content. Participants will learn about multi-vector embeddings, optimization techniques like quantization and pooling, and the practical implementation of ColPali and MUVERA for efficient text-to-image search. The course builds on the foundation of retrieval optimization, focusing on detailed visual understanding applications such as e-commerce product search and document analysis.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 5 | 1,607 | 321 | 133 | +4% |
| LLM | 1 | 4,308 | 744 | 242 | -15% |
| RAG | 1 | 974 | 222 | 101 | -17% |
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