World Congress 2024 Nov 3, 2024 Session details

Carl Lapierre - Exploring Advanced Patterns in Retrieval-Augmented Generation

Carl Lapierre

Carl Lapierre proves basic vector search fails complex enterprise data. Discover how agentic RAG, hybrid algorithms, and DAGs create highly accurate, production-ready retrieval pipelines.

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#1 about 2 min

Speaker background and introduction to applied robotics work

How robotics and artificial intelligence applications solve industry challenges.

#2 about 2 min

Reviewing the basic retrieval-augmented generation pipeline

A walk-through of data preparation, chunking, embedding, vector storage, and retrieval.

#3 about 2 min

Real-world project examples and common pipeline requirements

Three case studies showing why explainability, accuracy, and complexity matter in search systems.

#4 about 1 min

Enhancing accuracy with hybrid search and reranking

Combining exact keyword matching with semantic search to improve retrieval relevance.

#5 about 1 min

Post-retrieval techniques using sibling and parent nodes

Expanding document context sizes prior to sending data to the language model.

#6 about 1 min

Data preparation improvements with abstractive processing

Using recursive abstractive processing to generate summary tree nodes for augmented context.

#7 about 2 min

Transitioning toward agentic retrieval-augmented generation frameworks

Adding reasoning steps through tool usage, memory, and orchestration components.

#8 about 2 min

Training models with reward functions and reinforcement learning

How large language models generate reinforcement learning reward functions for robots.

#9 about 3 min

Implementing self-critique and reflection in corrective systems

Evaluating retrieved node relevance to separate noise from useful knowledge snippets.

#10 about 2 min

Query translation and fusion for broadened search attempts

Rewriting user inputs across different perspectives to maximize relevant knowledge retrieval.

#11 about 1 min

Extending agent capabilities with customized function calling

Permitting the model to utilize external calculations, web lookups, and specialized algorithms.

#12 about 2 min

Managing complex query planning and reasoning loops

Comparing naive prompt routing to complex recursive reasoning patterns that isolate required tools.

#13 about 2 min

Parallel processing through directed acyclic graph frameworks

Modeling task dependencies to execute sub-queries simultaneously via advanced compiler architecture.

#14 about 2 min

Delegating workloads using multi-agent hierarchical collaboration

Separating concerns by creating atomic reasoning nodes equipped with specific capability scopes.

#15 about 3 min

Production considerations for advanced language model systems

Avoiding token cost overruns, unstable planning loops, and poisoned retrieval context.

Matching moments

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Architectural patterns for developing robust generative AI applications

Julián Duque Julián Duque · WWC 2025

2:05 min

Enhancing language models with retrieval-augmented generation

Mary Grygleski Mary Grygleski · LIVE

1:44 min

Understanding basic retrieval-augmented generation architectures in chatbots

Stan Girard Stan Girard · WWC 2024

1:24 min

Expanding AI capabilities using retrieval-augmented generation

Cedric Clyburn Cedric Clyburn · WWC 2024

2:00 min

Exploring retrieval augmented generation and advanced prompting techniques

Daniel Töws Daniel Töws · WWC 2024

1:57 min

Understanding overarching retrieval and generation steps in RAG architectures

Csenge Szabo Csenge Szabo · Europe 2026 Virtual

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