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We have the relevance workbench as a public demo here: https://www.elastic.co/demo-gallery/relevance-workbench
For the ESRE GenAI, we have only a Navattic demo: https://elastic.navattic.com/dev-esre-genai
Elasticsearch Relevance Engine (ESRE) Engineer: develop the skills and knowledge required to build RAG applications using natural language and deliver highly relevant results, generate contextually rich content, and solve real-world problems.
https://www.elastic.co/training/elasticsearch-relevance-engine-(esre)-engineer/
Wondering how you can take advantage of AI to improve your search results?
Are you interested in understanding how generative AI applies to your use cases?
In this hand-on workshop, you will learn how vector search, modern natural language processing and generative AI can modernie your search experience and unstructured data analysis and how to implement these new techniques in Elastic.
Vector search, also known as semantic or similarity search, uses machine learning to capture the meaning and context of unstructured data, including text and images, in a numeric (vector) representation.
A major hurdle in the introduction of these approaches was that the underlying AI models had to be adapted to specific application areas. By using novel "parsimonious" approaches that generalize well to different needs and combining them with traditional lexical search capabilities, you can achieve superior relevance without the need for AI expertise or manual configuration and annotation.
What will you learn?
- You will learn about vector search and modern NLP models
- Implementing similarity search on text and image data
- Application of sentiment analysis, categorisation and question answering
- Learn how generative AI can take your search results to the next level
https://github.com/elastic/genai-workshop-codespaces
https://www.elastic.co/enterprise-search/generative-ai
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