Joe McElroy

Searchkit: React Components for elasticsearch. Make fast usable searches quick! searchkit.co

@JesseCohenInv I don’t think this leaves people jobless for those who want to work. It should be viewed as entry level roles disappear because the bar is higher. We will also have a higher ceiling to excel.

@JesseCohenInv We need to stop viewing AI as a replacement for the worker and start seeing it as the treadmill. It’s raising the floor of what a human needs to do, but it’s also providing the gym for them to get that strong before they even start.

Anthropic CEO Dario Amodei warns: “50% of entry-level white-collar jobs could be disrupted within the next 1–5 years.” From law to finance to consulting, he says that AI is capable of handling a wide range of knowledge work.

Great move. Excited to try this out.

@johtani_en @xeraa Hey Jun, could you tell me steps you did where you encountered the issue? Happy for this to be in a DM :)

@xeraa It is basicaly fine. But the search-lab pages are buggy unfortunately...

Um, I clicked the link to the search lab page on Elastic web site, then it shows always 404 page... Because of the language selector... I always edit the URL on my browser...

Domain-specific generative AI: comparing pre-training, fine-tuning, and RAG as approaches for storing and retrieving knowledge from LLMs. Learn more: go.es.io/47EQJn6 #ElasticSearchLabs #GenerativeAI

Vector Similarity Computations FMA-style elastic.co/search-labs/bl…

🦜🏁Self Query Template (@elastic) Often times documents come with really useful metadata! But how can you best take advantage of this metadata when doing RAG? 🤔 Self-query is one way to do so. This converts a 🗨️natural language query into one piece that is embedded and compared via cosine similarity, just as in naive RAG. But then a "metadata filter" is also extracted, that can be applied to metadata present in the vectorstore ❓This is useful because often times a query may not only refer to semantic meaning, but could also reference some of the metadata For example: "what is a movie about aliens from the year 1980" 👽 While "aliens" may be a semantic query, "year == 1980" is not, this is an explicit filter that should be applied Most vectorstores allow for some metadata filters, so this can be used with most of them Check out our recent template which does this for ElasticSearch: github.com/langchain-ai/l… This is an example "query construction" - check out @RLanceMartin's awesome post on this from earlier in the week: blog.langchain.dev/query-construc…

Interested in multilingual vector search with #Elasticsearch? New blog post drop featuring @Microsoft's multilingual E5 embedding model. Have a read, run the notebook, und suche in deiner Sprache! 😉 search-labs.elastic.co/search-labs/mu…

@derekcheungsa @llama_index @elastic Hey! I've updated the documentation to better reflect the ElasticsearchStores abilities. Thanks for providing feedback!

@llama_index @elastic @phoey1 This is a great addition! I see in the example the retrieval says it did not find the context info for the question. Is there anything missing in the retrieval parameters

LlamaIndex + @elastic 🚀 This has been a highly requested feature (a lot of our users are using Elasticsearch!) HUGE shoutout to @phoey1 for making this happen. - Vector/text/hybrid search - Metadata + metadata filtering - es_filters - And more! gpt-index.readthedocs.io/en/stable/exam…

@llama_index @elastic Thanks so much for accepting the contribution! More to come :)

The latest and greatest in 🦜🔗: 🧠 @neural_internet Bittensor LLM ⚡ DashVector store 🤖 @zep_ai vector store ♻️ @elastic search self-querying retriever a 🧵:

♻️ @elastic search self-querying retriever Combine the power of the Elasticsearch vector store with LangChain’s query constructor chain to create a self-querying retriever. Huge s/o to @phoey1 for continuing to add Elasticsearch features to 🦜🔗! Docs: python.langchain.com/docs/modules/d…

more #elasticsearch integrations coming your way :) PS: we'll also have LangChain at our upcoming ElasticON AI event in san francisco: elastic.co/events/elastic…

New in 🦜🔗==0.0.265! 3 new model wrappers and vector store improvements: 🐾 Ernie chat model 🚅 @berriai LiteLLM chat model support 🪄 @neuralmagic DeepSparse LLM 🤹 Major @elastic vector store improvements a 🧵:

🤹 New @elastic vector store @phoey1 has done a huge revamp and added a new Elasticsearch-backed vector store, allowing for a number of new index / query strategies. Try it out: ``from langchain.vectorstores import ElasticsearchStore`` Docs: python.langchain.com/docs/integrati…

This is why optimization tasks are addictive! Getting some nice improvements for vector search in Apache Lucene 9.7. github.com/erikbern/ann-b…

Why we designed, in the last couple of years, Elasticsearch and Lucene vector database implementation the way we did, and where we are heading elastic.co/fr/blog/vector…

I ❤️Lucene. Like so many times before (real time search, doc values, bm25, bkd, compressions, …), we are actively investing in making Apache Lucene also a great Vector Database elastic.co/blog/accelerat…

If I don’t say it enough, this is a fantastic resource lnkd.in/gX6c8fqA