from data silos to multi-sources and multi-agents cognitive platforms Aymeric, Brisse, CTO of Perfect Memory. So today I am going to make a short presentation about multi-agents cognitive platforms. What is it, and for what type of scenarios it is made for. AYMERIC BRISSE XLDB 2017 – LIGHTNING TALK

Big Data | Applications | New challenges 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? | New challenges To resolve the main issues brought by Big Data, we had to invent new tools. To be able to store and to access so much data, we have built new databases & new filesystems like Cassandra & CephFS To be able to find in that tools valuable information, a new computer science field has emerged, the data science with tools like the ML We have seen in the last years a lot of awesome new services like image recognition and recommendation used by thousand of companies. And that brings new challenges too.

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) Let’s take a simple use case to illustrate these challenges. A TV channel receives binary content like footages from dozens of news agency. And that TV channel wants to automate the information extraction. By information we talk about structured & intelligible data). For that, they want to use a cognitive platform

Cognitive Platform | Workflow driven, based on multi-agents Basically, a cognitive platform is able to adapt the workflow to the content it process, it will know what to do and how, and will use for that use multiple agents. Each agent is dedicated to a very specific task like Image Analysis. The platform brings a framework allowing each agent to act as a bridge between the service it uses and the platform semantic language. For example, a part of the workflow is dedicated to the audio track processing. So it will use first use for example an agent that is specialized in STT, while another agent will process that text to extract the named entities (persons, organizations, places) and finally another agent will retrieve additional information on the Linked Open Data (like Wikidata or dbpedia) on these entities. As the workflow is run, the knowledge graph of the footage is gradually built via the merging of each individual agent knowledge. So it’s really the cooperation made available by the cognitive platform between them allows high level questions to be answered: what’s going on in that video?

Knowledge Graph | Exploitable & Interoperable information Because in the end the TV channel wants to obtain structured information like : This physics-related video displays the Physicist Rainer Weiss and talks about the gravitational waves.

Stack | Under the hood 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/) @ Perfect Memory has developed its cognitive platform, and you can find on that page some information on the stack we use. So the platform runs on Openshift. It means that each agent runs in it own docker container, and communicates with other agents with RabbitMQ For knowledge access & storage, we use various databases, mainly ontotext for the semantic graph database. For files storage we use the distributed FS ceph with rados And last but not least, we did implement all the best practices of the “12 factor app” manifest which helped us a lot 6

Aymeric BRISSE - CTO aymeric.brisse@perfect-memory.com OK that’s it, I will be happy to give you more details on the platform after during the poster session Aymeric BRISSE - CTO aymeric.brisse@perfect-memory.com