The document discusses moving from data silos to cognitive platforms that allow for multi-source and multi-agent interoperability. Specifically, it discusses: 1) Current challenges around making different data services and silos interoperable to cross-reference data and make large amounts of data intelligible for specific business needs. 2) An example use case of a TV channel needing to automatically extract valuable information from various content received from different news agencies. 3) The concept of a cognitive platform that is workflow-driven and based on multi-agents, using a knowledge graph to provide exploitable and interoperable information from multiple sources and agents.

1. FROM DATA SILOS TO
MULTI-SOURCES AND MULTI-AGENTS
COGNITIVE PLATFORMS
AYMERIC BRISSE
XLDB 2017 – LIGHTNING TALK

2. Big Data
| Applications
• NoSQL & distributed FS address the storage and access issues (Cassandra, CephFS, etc.)
• Data scientist & Machine Learning address the valuable information extraction issues
• This allows awesome services to be built (image recognition, recommandation, etc.)
• How to make these different services & data silos interoperable to cross-reference the data?
• How to make intelligible the mass of data now available to meet specific business needs?
2
| New challenges

3. Use case
| Example
• A TV Channel receives various content (footages, pictures, wires) from dozens of news agencies
• Automate the valuable information extraction
• Retrieve structured & intelligible information (who, where, what)
3

4. Cognitive Platform
4
| Workflow driven, based on multi-agents

5. Knowledge Graph
5
| Exploitable & Interoperable information

6. Stack
| Under the hood
6
• Base - Openshift (Kubernetes with Docker containers & DevOps tools)
• Runtime - One Docker image per Agent
• Communication - RabbitMQ for message delivery
• Databases - Various
• Storage - Ceph
• DevOps Philosophy - « 12-Factor App » (https://12factor.net/)

7. Aymeric BRISSE - CTO
aymeric.brisse@perfect-memory.com