Vespa Newsletter, April 2024
Blog post from Vespa
In the April 2024 Vespa Newsletter, significant updates and advancements are highlighted, including the introduction of the SPLADE Embedder, which enhances learned sparse retrieval by using term impact scores from large language models, and the support for half-precision floating-point (float16) ONNX models, improving inference performance on GPUs. New guides are available for using Cohere embedding models, which now support binary and int8 vectors, offering cost savings and performance benefits. The newsletter also discusses enhancements to the ColBERT embedder, allowing multi-paragraph inputs and highlights recent blog posts and case studies showcasing Vespa's application in semantic search and recommendation systems across various companies. Additionally, it announces upcoming meetups and conferences focused on improving the usefulness of large language models and retrieval augmented generation.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| Vector Search | 10 | 2,613 | 257 | 91 | +44% |
| RAG | 6 | 1,795 | 223 | 72 | +55% |
| LLM | 1 | 3,398 | 379 | 136 | +44% |
| Real-time | 1 | 2,334 | 631 | 194 | -8% |
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