Category: AI
Articles tagged AI
ChatGPT and Elasticsearch: enhance user experience with faceting, filtering, and more context
By providing ChatGPT more context and using Elasticsearch's facets & filters, you can refine the search and lower ChatGPT costs. Here's how.
ChatGPT and Elasticsearch: APM instrumentation, performance, and cost analysis
Learn how to instrument a Python application that uses OpenAI, analyze its performance & cost and integrate large language models (LLMs).
Elasticsearch and LangChain: unlocking the potential of large language models (LLMs)
Explore the synergy between LangChain and Elasticsearch and how they are pushing the boundaries of what's possible with large language models (LLMs).
Privacy-first AI search using LangChain and Elasticsearch
The world of search is changing very quickly. ChatGPT has cemented generative AI's place in making finding data faster. We'll use Elasticsearch and LangChain to build a private trivia bot on fun Star Wars trivia data.
How to use Elasticsearch to prompt ChatGPT with natural language
This blog post presents an experimental project for querying Elasticsearch in natural language using ChatGPT.
Monitor OpenAI API and GPT models with OpenTelemetry and Elastic
Learn how to monitor OpenAI API and GPT models using OpenTelemetry and Elastic in this blog post. Explore mothods for monitoring performance, cost, and more.
Introducing Elasticsearch Relevance Engine (ESRE) — Advanced search for the AI revolution
Explore the Elasticsearch Relevance Engine (ESRE) by Elastic. ESRE powers gen AI solutions for private data sets with a vector database and ML models for semantic search.
How to implement image similarity search in Elasticsearch
Searching through images to find the right one has always been challenging. With similarity image search, you can create a more intuitive search experience. Learn how to implement image search in Elastic.
Train, evaluate, monitor, infer: End-to-end machine learning in Elastic
To use machine learning in the Elastic Stack, all you need is for your data to be stored in Elasticsearch. Learn how to extract valuable insights from your data with a few clicks and build a fully operational end-to-end machine learning pipeline.
Save space with byte-sized vectors
Elasticsearch is introducing a new type of vector that has 8-bit integer dimensions. This is 4x smaller than the current vector with 32-bit float dimensions, which can result in substantial space savings.
