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Neo4j y GenAI

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Neo4j

Luis Salvador

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Neo4j Inc. All rights reserved 2023
Neo4j and GenAI
Luis Salvador
PreSales Engineer EMEA South
Graph creates a
more intuitive and
connected view of
data relationships,
unlocking deeper
insights and context
2
THE PROPERTY GRAPH: SIMPLY POWERFUL
Employee City
Company
Nodes represent
objects (nouns)
Relationships are directional
Relationships connect nodes are
represent actions (verbs)
Relationships can have
properties (name/value pairs)
Nodes can have
properties (name/value
pairs)
name: Emil Eifrem
date_of_birth: 1979-03-01
employee_ID: 1
:HAS_CEO
start_date: 2008-01-20
:LOCATED_IN
3
Hybrid Workload Duality
Intelligent
Applications
Transactions -
Security -
Performance & Scalability -
ACID Consistency -
Intelligent Modeling
- Extensive & Supported Algo Library
- Scalable
- Graph Visualization
- Graph Transformations
Graph
Transactions
Graph Analytics
& Data Science
4
© 2023 Neo4j, Inc. All rights reserved.
Neo4j
Graph Data Science
5
What’s in it for you:
● Improve model accuracy by 30%
● Simplify processes and remove
headaches
● More projects into production without
additional hiring
Neo4j Graph Data Science
Analytics
Feature
Engineering
Data
Exploration
Graph
Data
Science
Queries & Search
Machine Learning Visualization
6
Ad

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Neo4j y GenAI

  • 1. Neo4j Inc. All rights reserved 2023 Neo4j and GenAI Luis Salvador PreSales Engineer EMEA South
  • 2. Graph creates a more intuitive and connected view of data relationships, unlocking deeper insights and context 2
  • 3. THE PROPERTY GRAPH: SIMPLY POWERFUL Employee City Company Nodes represent objects (nouns) Relationships are directional Relationships connect nodes are represent actions (verbs) Relationships can have properties (name/value pairs) Nodes can have properties (name/value pairs) name: Emil Eifrem date_of_birth: 1979-03-01 employee_ID: 1 :HAS_CEO start_date: 2008-01-20 :LOCATED_IN 3
  • 4. Hybrid Workload Duality Intelligent Applications Transactions - Security - Performance & Scalability - ACID Consistency - Intelligent Modeling - Extensive & Supported Algo Library - Scalable - Graph Visualization - Graph Transformations Graph Transactions Graph Analytics & Data Science 4
  • 5. © 2023 Neo4j, Inc. All rights reserved. Neo4j Graph Data Science 5
  • 6. What’s in it for you: ● Improve model accuracy by 30% ● Simplify processes and remove headaches ● More projects into production without additional hiring Neo4j Graph Data Science Analytics Feature Engineering Data Exploration Graph Data Science Queries & Search Machine Learning Visualization 6
  • 7. When do you need Graph Algorithms? Query (e.g. Cypher) Real-time, local decisioning and pattern matching Graph Algorithms Global analysis and iterations You know what you’re looking for and making a decision You’re learning the overall structure of a network, updating data, and predicting Local Patterns Global Computation 7
  • 8. What’s important? Prioritization Who has the most connections? Who has the highest page rank? Who is an influencer? What’s unusual? Anomaly & Fraud Detection Where is a community forming? What are the group dynamics? What’s unusual about this data? What’s next? Predictions What’s the most common path? Who is in the same community? What relationship will form? Pl ay s Lives_in In_sport Likes F a n _ o f Plays_for K n o w s Knows Knows K n o w s Answer critical business questions 8
  • 9. © 2023 Neo4j, Inc. All rights reserved. Vector Index Search 9
  • 11. What is a vector ● Length ● Direction ● Components have meaning horizontal vertical 11
  • 13. What are vector embeddings ● Same concepts, just “an arrow” ● 100s or 1000s dimensions ● Each dimension corresponds to an interesting feature or characteristic 13
  • 14. Kings and Queens king − man + woman ≈ queen k i n g man wom an 1 k i n g man wom an 2 q u e e n ? 3 14
  • 15. Neighborhoods ● cosine ● direction / angle based vector point query nearest 4 ● Euclidean ● distance based 15
  • 16. KGs enable searches with explicit and implicit (vectors) relationships 16
  • 17. Neo4j and Vector Search Find relevant documents and content for user queries Find entities associated to content and patterns in connected data. Improve search relevance & insights by enhancing a Knowledge Graph. Use graph algorithms and ML to discover new relationships, entities, and groups. Vector Similarity Search Graph Traversals & Pattern Matching Knowledge Graph Inference & ML Vector Search Graph Database 17
  • 18. © 2023 Neo4j, Inc. All rights reserved. LLMs and GenAI 18
  • 19. 19
  • 20. 20
  • 21. Gen AI is everywhere We’re at mile one of the marathon 21 The next big thing
  • 22. 22
  • 23. 23
  • 24. 24
  • 25. Learns random sentences from random people Talks like a person but doesn’t really understand what it’s saying Occasionally speaks absolute nonsense Is a cute little bird Yes Yes Yes Yes Yes Yes Yes No The limitations of GenAI 25
  • 26. LLM Hallucinations Definition: Language models generate text that is incorrect, nonsensical, or unreal. • Appear to answer questions confidently even if they don’t have facts • May provide contradicting or inconsistent responses to similar prompts 26
  • 27. The limitations of GenAI Hallucinates Limited input sizes for fine tuning Lack of enterprise domain knowledge Inability to verify answers Sensitive to prompt (input) phrasing Ethical and data bias concerns 27
  • 28. How to Help LLMs Do Better? Fine-Tuning Grounding Provide completed examples “shots” to the AI as context in prompts. a.k.a In-Context Learning Provide additional training data to better tune GenAI to your use case Provide AI with the information to use for generating responses All of these are useful, but grounding is where Neo4j adds value Neo4j as the data source for Grounding 28 Few-Shot Learning
  • 29. Ground LLMs in Neo4j’s Knowledge Graph 29 29
  • 30. 30
  • 31. 31 1 2 LLMs for Language Generation Gen AI use cases
  • 33. 33 1 2 LLMs for Language Generation RAG-based Applications Gen AI use cases
  • 34. Grounding with Retrieval Augmented Generation (RAG) Neo4j Inc. All rights reserved 2023
  • 35. Natural Language (NL) Search on explicit relationships Neo4j Inc. All rights reserved 2023
  • 36. Neo4j Inc. All rights reserved 2023 36 Natural Language Search combining explicit and implicit relationships
  • 37. 37 1 2 3 LLMs for Language Generation RAG-based Applications Gen AI use cases Knowledge Graph Construction
  • 38. Creating a Knowledge Graph From Unstructured Text was Difficult Neo4j Inc. All rights reserved 2023
  • 39. Knowledge Graph Creation with Cypher Templates Neo4j Inc. All rights reserved 2023 39
  • 40. © 2023 Neo4j, Inc. All rights reserved. How will you transform your organization?
  • 41. © 2023 Neo4j, Inc. All rights reserved. Thank You! See you 9th April 2024 at our next GraphSummit Madrid! 41