Hard problem indeed. Not everyone wraps google or start from scratch though. Case in point: Perplexity builds on vespa.ai vespa.ai/perplexity/

So much gold in these comments 😂

A lot more coming around chunking soon. One of those areas where human and LLM needs meaningfully differ.

We'll have time to explain later, but for those who understand, enjoy Vespa 8.530.

cool to learn Ai2 are using vespa.ai! and binarized embeddings are amazing for cost/perf, this is a great model

Training competence getting commodified

Context engineering x.com/karpathy/statu… + RAG

Correct. And furthermore it's the only humanism.

June vespa.ai newsletter is out! Lots of cool new stuff (e.g. built-in chunking) and educational content (e.g. demo E-commerce apps with new ideas) Check it out and let us know of any feedback: blog.vespa.ai/vespa-newslett…

which level is your RAG?

New Vespa features covered in the June newsletter: - Layered ranking: Rank chunks in documents. - Elementwise bm25 - top, filter_subspaces, and cell_order tensor functions - chunking support in indexing - element-gap: Proximity over chunks - filtering in grouping results -

so much of so-called moral intuition, like that fun wears out and utopia is ultimately boring, is contingently downstream of being permanently imprisoned in rickety rube kludgeberg machine of matryoshka shock collars and dopamine needlepricks for driving a biorobot around a

Announcing: The RAG Blueprint Build RAG like the world's most successful applications. Start from our open source sample app which contains all you need to do to achieve world-class quality at any scale. Sample app: github.com/vespa-engine/s… Blog post: blog.vespa.ai/the-rag-bluepr…

People are coming up with so many great uses for layered ranking. Nice to see innovation driven by scaled RAG apps benefiting all kinds of use cases.

We just did a podcast about the process of migration (trade-offs included) from #Elasticsearch to vespa.ai With Dainius Jocas and Kevin Petrie 🙌 em360tech.com/podcasts/vinte…