Iulia Feroli
Harry Potter and the Elastic Semantic Search
#1about 3 minutes
The evolution of NLP from early models to modern LLMs
Tracing the rapid advancement of natural language processing from early models like Word2Vec to the powerful generative AI we see today.
#2about 5 minutes
How vector embeddings represent language as numbers
Vector embeddings turn words and sentences into numerical arrays, allowing computers to understand semantic relationships through mathematical operations.
#3about 7 minutes
Using vector similarity and LLMs for semantic operations
The distance between vectors in an embedding space represents semantic similarity, enabling operations like finding related concepts or answering questions.
#4about 4 minutes
Using Elasticsearch as a vector database for search
Elasticsearch serves as a vector database to store document embeddings and integrates with models from sources like Hugging Face for inference.
#5about 7 minutes
Demonstrating advanced keyword search with the Python client
The Elasticsearch Python client enables complex, multi-field queries with boolean logic to filter data based on precise criteria before adding semantic layers.
#6about 4 minutes
Enriching data with sentiment analysis pipelines
An inference pipeline can automatically apply a sentiment analysis model to all documents, adding a new field to enable filtering by positive or negative tone.
#7about 4 minutes
Implementing semantic search with embedding models
By converting all text into vectors using an embedding model, you can perform a k-NN search to find the most semantically relevant results for a query.
#8about 5 minutes
Refining results with hybrid search techniques
Hybrid search combines the power of semantic vector search with traditional keyword filters and exclusions to create highly relevant and precise results.
#9about 19 minutes
Audience Q&A on models and implementation
The speaker answers audience questions about ensuring relevance, handling out-of-vocabulary terms, updating data sources, and debugging model outputs.
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