The Singaporean government has deployed Vespa to search every word ever said in their Parliament.
"A good decision is an informed one [...] The heart of a good RAG system is a good search engine to retrieve the relevant data chunks for ingestion"
Many teams are racing to make use
vespa.ai
586 posts
Vespa.ai - the open source platform for combining data and AI, online.
Vectors/tensors, full-text, structured data; ML model inference at scale.
Joined September 2017
- We have become our own company! Expect even more features, even faster. blog.vespa.ai/vespa-is-becom…
- Announcing the open sourcing of Vespa, Yahoo’s Big Data Processing and Serving Engine at vespa.ai: blog.vespa.ai/post/165763618…
- Announcing our $31 million raise from Blossom Capital blog.vespa.ai/announcing-our… We'll spend it all on features.
- Spotify launches semantic search in Podcasts, powered by vespa.aiHere’s the problem: you want to search for a podcast, but you can’t remember the name, only what it’s about.😖 Here comes Natural Search 🔍 to save the day! engineering.atspotify.com/introducing-na…
- LangChain Webinar on retrieval for LLMs with @lateinteraction and our very own @jobergum in six hours. Save your spot at
- Choosing an algorithm for fast vector search for big data serving medium.com/vespa/approxim… Read if you are interested in combining fast vector search with filters, text, and real-time updates. Or in how professionals choose algorithms from the literature for production usage.
- Having trouble keeping up? Guidebook to the State-of-the-Art Embeddings and Information Retrieval by @aapo_tanskanen at @thoughworks is out today - a great resource to get up to date. linkedin.com/pulse/guideboo…
- Search is going through a paradigm shift - neural methods are outperforming traditional methods by a wide margin. Can you use it real production systems? [1/4]
- What the world need most now is more research on #covid19, faster. We've created cord19.vespa.ai to help with that. It lets researchers find research papers by combining text and structured search with exploring by semantic similarity using the scibert-nli model.The @vespaengine team released cord19.vespa.ai based on the CORD-19 dataset released by the @allen_ai. Since everything is open-sourced, you can contribute to the project in multiple ways. 👇 #NLP #NLProc #SearchEngine #COVIDー19 medium.com/@thigm/vespa-a…
- Do you want to work on - search relevance - recommendation - personalization using - machine-learning - embeddings - vector or hybrid retrieval but are kinda tired of all the plumbing? Thread time 👇
- After extensive benchmarking, Marqo migrated their underlying engine from OpenSearch to Vespa: "For Marqo 2, we looked at a number of open source and proprietary vector databases, including Milvus, Vespa, OpenSearch (AWS managed), Weaviate, Redis, and Qdrant."
- We made it simpler to create semantic search applications on Vespa - No need to create vectors yourself - No code needed - No limits, once you want to grow add features









