Graph Technologies - Santa Clara, CA, US
Details
https://secure.meetupstatic.com/photos/event/d/5/c/5/600_465414725.jpeg
WARNING - This meetup will take place at 6pm US Pacific. However the meetup community is in the UK time-zone. So the software will send out thank you for participating 8 hours too early! We apologize for the confusion and have not figured out a workaround.
JanusGraph: Looking Backward and Reaching Forward - by Jason Plurad (https://www.linkedin.com/in/pluradj) (@pluradj (https://twitter.com/pluradj)):
The JanusGraph (http://janusgraph.org/) project started at the Linux Foundation earlier this year, but it is not the new kid on the block. We'll start with a look at the origins and evolution of this open source graph database through the lens of a few IBM graph use cases. We'll discuss the new features in latest release of JanusGraph (http://janusgraph.org/), and then take a look at future directions to explore together with the open community.
https://secure.meetupstatic.com/photos/event/c/9/7/600_465243223.jpeg
===================================
Graph Data: a New Data Management Frontier -- Huawei’s view and Call for Collaboration by Demai Ni: (https://www.linkedin.com/in/demai-ni-8533a18/)
Huawei provides Enterprise Databases (http://e.huawei.com/au/solutions/business-needs/data-center/storage), and are actively exploring the latest technology to provide end-to-end Data Management Solution on Cloud. We are looking at to bridge classic RDMS to Graph Database on a distributed platform.
https://secure.meetupstatic.com/photos/event/c/a/6/600_465243238.jpeg
===================================
Integrating Knowledge Bases with Neural Networks - by Nick Powell (http://www.linkedin.com/in/nicolas-powell-6b744989):
Knowledge bases are used as the under-pinning for reasoning systems. This talk will describe experiences using deep learning to facilitate knowledge base completion (https://blog.grakn.ai/using-grakn-ai-to-enhance-neural-network-models-for-knowledge-base-completion-bb84bfd1dfdd). With an existing knowledge base as a training set, we programmed the neural net as a binary classifier (https://en.wikipedia.org/wiki/Binary_classification) to find likely relationships and then insert them back into the graph. We'll describe lessons learned and next steps.
https://secure.meetupstatic.com/photos/event/c/a/3/600_465243235.jpeg
===================================
Event Details
Time & Date: 6pm, Wednesday, October 18, 2017
Address: Huawei (Building E) (https://maps.google.com/maps?f=q&hl=en&q=2890+Scott+Blvd%2C+Santa+Clara%2C+CA+95050%2C+CA%2C+us)
2890 Scott Blvd, Santa Clara, CA 95050, CA
Timings:
6 - 6:30pm: Pizza and refreshments
6:30 - 7:05pm: JanusGraph: Looking Backward and Reaching Forward by Jason Plurad (https://www.linkedin.com/in/pluradj)
7:05 - 7:25pm: Graph Data: a New Data Management Frontier -- Huawei’s view and Call for Collaboration by Demai Ni (https://www.linkedin.com/in/demai-ni-8533a18/)
7:25pm - 8pm: Integrating Knowledge Bases with Neural Networks by Nick Powell (http://www.linkedin.com/in/nicolas-powell-6b744989)
8pm - 8:30pm: Networking
===================================
What is Cognitive & AI Data Infrastructures?
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.
===================================