AI and Cognitive systems process knowledge that is far too complex than traditional datasets that current databases were made for. Current databases could not model complex domains and the query languages are not capable of interpreting complex data relationships. Therefore, these knowledge-oriented systems require much advanced data infrastructure to meet the needs of Artificial intelligence computing.
In this community, we will discuss various use cases in AI and Cognitive computing and the data infrastructure built to support the system. We will discuss the applications of relational databases, NoSQL databases, graph databases, as well as hyper-relational databases such as GRAKN.AI tailored for knowledge-oriented systems.
The group is for engineers to demonstrate their solution and share the lessons they learnt, as well as business stakeholders who have implemented or invested in AI and Cognitive computing systems in their organisations.
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Automating Data Science over a Human Genomics Knowledge Base
Featuring Radouane Oudrhiri
Radouane Oudrhiri will talk about how Eagle Genomics is building a platform for automating data science over a human genomics knowledge base. Rad will dive into the architecture Eagle Genomics and also discuss how Grakn serves as the knowledge base foundation of the system. Rad also give a brief...data datascience database knowledgebase humangenomics lifescience
GDPR: threat or opportunity?
Featuring Samuel Pouyt
In May 2018, the European Union’s General Data Protection Regulation (GDPR) will take effect. Companies that do not comply might be fined 20M, or 4% of their annual global turnover, whichever is greater.data grakn knowledgegraph knowledgebase gdpr
Shared principles and concepts for the artificial and human. In pursuit of a common language for intelligence
Featuring Marco Lin
The domains of Artificial Intelligence and Neuroscience have a long tradition of mutual inspiration, which is the spirit of this talk.cognitiveneuroscience theoretical interdisciplinary ai grakn data
Question Answering at Scale
Featuring Max Bartolo
The world's expertise is captured in layer upon layer of unstructured text. Compliance documents, legal texts, financial records, even web pages - there is a wealth of information available which our most advanced systems have difficulty comprehending.scalingexpertise transferlearning nlp deeplearning questionanswering
The hyper-relational database for knowledge-oriented systems
Featuring Haikal Pribadi
AI systems process knowledge that is far too complex for current databases. They require more expressive data schemas and intelligent query languages to provide a strong abstraction over complex data and their relationships. In this talk, we will discuss how GRAKN.AI, a distributed...database cognitivesystems ai data opensource
Big Data Analytics
Featuring Jason Liu
In this talk, we first explore two big data processing models: map-reduce and Pregel. Then we introduce how we make use of these modes to build Grakn Analytics our powerful tool for big data processing. We will also discuss how we transform common algorithms to their massive parallel versions, so...datadnalytics ai map-reduce data
Logical Inference in a Hyper-Relational database
Featuring Domenico Corapi
Inference is something we humans do all the time. Given a set of facts about the world, we derive new ones using some form of inference. Automated reasoning has been studied extensively but its value in providing a more powerful abstraction layer for database languages has been overlooked so far....inference databases automatedreasoning computationallogic distributedsystems data
Using GRAKN.AI to detect patterns in credit fraud data
Featuring Oscar Darwin
The worlds of first order logic and machine learning don’t usually collide. With increasing sizes of datasets around the web and, more importantly, complex relationships that need to be represented, analysts need ways of applying machine learning techniques to discover patterns in their datasets....
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