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Neo4j : Graphes de Connaissance, IA et LLMs

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Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j Les graphes de connaissances et le Machine Learning sont les deux principales méthodes de représentation et d’exploitation des connaissances. Ce qui est intéressant et plutôt méconnu, c’est qu’ils sont hautement complémentaires. Cette présentation vous éclairera sur la manière dont ces deux domaines interagissent, mettant en avant la synergie entre eux et comment les variantes les plus récentes du ML (IA générative et LLMs) s’intègrent avec des graphes de connaissances pour construire des applications sémantiques modernes.

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© 2023 Neo4j, Inc. All rights reserved.
Neo4j : Graphes de
Connaissance,
IA et LLMs
Jesus Barrasa RVP, Field Engineering
Neo4j Inc. All rights reserved 2023
Gen AI is everywhere
We’re at mile one of the marathon
2
The next big thing
The limitations of Gen AI
Hallucinates
Neo4j Inc. All rights reserved 2023
3
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
4
Neo4j Inc. All rights reserved 2023
Gen AI need knowledge graphs
KGs
5
LLMs
+
Better Together
Knowledge
Facts
Context
Language
Statistics
Creativity
Knowledge Graphs enable searches with
explicit and implicit (vectors) relationships
Neo4j Inc. All rights reserved 2023
6
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Neo4j : Graphes de Connaissance, IA et LLMs

  • 1. © 2023 Neo4j, Inc. All rights reserved. Neo4j : Graphes de Connaissance, IA et LLMs Jesus Barrasa RVP, Field Engineering
  • 2. Neo4j Inc. All rights reserved 2023 Gen AI is everywhere We’re at mile one of the marathon 2 The next big thing
  • 3. The limitations of Gen AI Hallucinates Neo4j Inc. All rights reserved 2023 3 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
  • 4. 4
  • 5. Neo4j Inc. All rights reserved 2023 Gen AI need knowledge graphs KGs 5 LLMs + Better Together Knowledge Facts Context Language Statistics Creativity
  • 6. Knowledge Graphs enable searches with explicit and implicit (vectors) relationships Neo4j Inc. All rights reserved 2023 6
  • 7. Neo4j Inc. All rights reserved 2023 7 1 2 3 LLMs for Language Generation RAG-based Applications Gen AI use cases Knowledge Graph Construction
  • 8. Neo4j Inc. All rights reserved 2023
  • 9. Neo4j Inc. All rights reserved 2023 Generate personalized Natural Language experiences 9
  • 12. Natural Language (NL) Search on explicit relationships
  • 14. 14 Natural Language Search combining explicit and implicit relationships
  • 16. Creating a Knowledge Graph From Unstructured Text The patient was a 34-yr-old man who presented with complaints of fever and a chronic cough. He was a smoker and had a history of pulmonary tuberculosis that had been treated and cured. A computed tomographic (CT) scan revealed multiple tiny nodules in both lungs. A thoracoscopic lung biopsy was taken from the right upper lobe. The microscopic examination revealed a typical LCH. The tumor cells had vesicular and grooved nuclei, and they formed small aggregations around the bronchioles (Fig.1). The tumor cells were strongly positive for S-100 protein, vimentin, CD68 and CD1a. There were infiltrations of lymphocytes and eosinophils around the tumor cells. With performing additional radiologic examinations, no other organs were thought to be involved. He quit smoking, but he received no other specific treatment. He was well for the following one year. After this, a follow-up CT scan was performed and it showed a 4 cm-sized mass in the left lower lobe, in addition to the multiple tiny nodules in both lungs (Fig.2). A needle biopsy specimen revealed the possibility of a sarcoma; therefore, a lobectomy was performed. Grossly, a 4 cm-sized poorly-circumscribed lobulated gray-white mass was found (Fig.3), and there were a few small satellite nodules around the main mass. Microscopically, the tumor cells were aggregated in large sheets and they showed an infiltrative growth. The cytologic features of some of the tumor cells were similar to those seen in a typical LCH. However, many tumor cells showed overtly malignant cytologic features such as pleomorphic/hyperchromatic nuclei and prominent nucleoli (Fig.4), and multinucleated tumor giant cells were also found. There were numerous mitotic figures ranging from 30 to 60 per 10 high power fields, and some of them were abnormal. A few foci of typical LCH remained around the main tumor mass. Immunohistochemically, the tumor cells were strongly positive for S-100 protein (Fig.5) and vimentin; they were also positive for CD68 (Dako N1577, Clone KPI), and focally positive for CD1a (Fig.6), and they were negative for cytokeratin, epithelial membrane antigen, CD3, CD20 and HMB45. The ultrastructural analysis failed to demonstrate any Birbeck granules in the cytoplasm of the tumor cells. Now, at five months after lobectomy, the patient is doing well with no significant change in the radiologic findings.
  • 17. © 2023 Neo4j, Inc. All rights reserved. Prompt Definition Target Ontology Unstructured Text (Natural Language) LLM Entity / Relationship Extraction Structured data formats Cypher MERGE (p:Person { id: $pid}) ON CREATE SET p.name, MERGE (p)-[:HAS_SYMPTOM]->()... Knowledge Graph https://github.com/neo4j-partners/neo4j-generative-ai-azure/tree/main/ingestion
  • 18. © 2023 Neo4j, Inc. All rights reserved. © 2023 Neo4j, Inc. All rights reserved. Demo time!
  • 19. © 2023 Neo4j, Inc. All rights reserved. Knowledge graphs + LLMs enables trusted and effective AI 19
  • 20. © 2023 Neo4j, Inc. All rights reserved. Merci ! 20