Graphs Are Fundamental to Modern AI Systems

Artificial Intelligence (AI) is poised to drive the next wave of technological disruption across nearly every industry. Just like previous technology revolutions in web and mobile, however, there will be winners and losers based on who harnesses this technology for a true competitive advantage.

Neo4j customers are demonstrating that graph database technology brings tremendous value to AI and machine learning projects, especially in the area of knowledge graphs.

Because of their structure, knowledge graphs add essential context for AI applications by capturing facts related to people, processes, applications, data and things, and the relationships among them. They also capture evidence that attributes the strengths of these relationships.

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Fast Track

  • Ernst & Young (EY): Knowledge Graphs, the Path to Enterprise AI

    Knowledge graphs are a foundation of artificial intelligence. This presentation includes a range of how-to information for building an enterprise knowledge graph, including how to recognize graph problems.

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  • Neo4j & Expero: Lower Risk & Stop Fraud Using Graph-Enhanced Machine Learning & AI

    Understand how successful financial services, banks and retailers are using graph technology and embedding intelligence to quickly identify risk and fraud patterns as they evolve.

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  • eBay’s ShopBot Delivers Recommendations with Artificial Intelligence & Neo4j

    eBay’s Chief Product Officer explains how he turned to graph technology because existing product searches and recommendation engines were unable to provide contextual information within a shopping request.

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Business Outcomes

Real-time responsiveness

Whether your AI solution is chatting with customers or driving an autonomous vehicle, real-time feedback loops are essential for meaningful machine learning that evolves your intelligence models.

Evolves with business requirements

In the emergent industry of AI, business and user requirements are still being defined, tweaked or completely upended. The graph data model is more agile and flexible than a traditional RDBMS in meeting these new and changing requirements.

Challenges

Disparate (and changing) data sources

Your machine learning algorithms consume data from a variety of ever-changing sources and data types, meaning you need a database with a versatile and adaptable schema.

Multiple hop queries

In order to determine context for the most appropriate action, AI solutions must query several layers deeper within their databases than previous technologies required. This means the database layer must be able to support multi-hop (4+) queries without affecting performance.

Why Neo4j?

Native graph store

Unlike relational databases, Neo4j stores interconnected data that is neither linear nor purely hierarchical. Neo4j’s native graph storage makes it easier to decipher your data by not forcing intermediate indexing at every turn.

Flexible schema

Neo4j’s versatile property graph model makes it easier for organizations to evolve machine learning and artificial intelligence models – especially for those based on knowledge graphs.

Performance and scalability

Neo4j’s native graph processing engine supports high-performance graph queries on large datasets to enable real-time decision making by AI solutions and the engineers behind them.

Popular Graph Technology Use Cases for AI

Knowledge Graphs

Provide Rich Context for AI

AI Visibility

Human-Friendly Graph Visualization

Graph System of Record

Maintain a Source of Connected AI Truth

Graph-Enhanced AI Models—Learning

Faster, More Accurate Development

Graph-Enhanced AI Models—Execution

Operationalize Real-Time OLAP and Monitoring

Graph Analytics

Enrich AI Inputs with Graph Algorithms

Articles

Datanami: Why Knowledge Graphs Are Foundational to Artificial Intelligence
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Computer Business Review: Creating The Most Sophisticated Recommendations Using Native Graphs
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Neo4j & Expero, Inc.: Thwart Fraud Using Graph-Enhanced Machine Learning & AI
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Community

Neo4j Machine Learning Extensions
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David Mack on Medium: Review Prediction with Neo4j and Tensorflow
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Neo4j Blog: Machine Learning, Graphs & the Fake News Epidemic
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Your enterprise is driven by connections – now it's time for your database to do the same. Click below to download and dive into Neo4j for yourself – or download the white paper to learn how today's leading enterprises are using Neo4j to achieve sustainable competitive advantage.

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