REDWOOD CITY, Calif., Sept. 17, 2020 (GLOBE NEWSWIRE) --
TigerGraph, the only scalable graph database for the enterprise, today announced the final agenda and speaker lineup for
Graph + AI World 2020, the first industry conference devoted to democratizing and accelerating AI and machine learning through graph algorithms and graph analytics. More than 3,000 people are expected to attend the free virtual event, including data scientists, data engineers, architects, business and IT executives from more than 100 companies from the Fortune 500. The final roster includes speakers from UnitedHealth Group, Intel, JPMorgan Chase, Jaguar Land Rover, Intuit, AT&T, Xandr (part of AT&T), Scotiabank, Accenture, KPMG, Publicis Sapient, Xilinx
, and innovative startups including Near, Ippen Digital, OpenCorporates, Expero, Abhay Solutions, SaH Analytics International, CAS, FinTell Inc. and Landing.AI.
AI is the new electricity – something we use and rely on every day. We use the PageRank algorithm for every web search, and we depend on community detection algorithms to detect fraud and money laundering rings. Meanwhile, similarity matching algorithms identify healthcare patients who need urgent help or customers in financial services, retail and eCommerce who are ready to buy.
Graph algorithms are the driving force behind the next generation of AI and machine learning that will power multiple industries and use cases. TigerGraph has organized Graph + AI World to democratize the use of graph with AI and machine learning. The event will showcase new deployments and first-of-a-kind solutions, including next-generation recommendation engines, fraud and anomaly detection and knowledge graphs powering more intelligent conversational AI with natural language processing (NLP) and chatbots.
Join data scientists, engineers, architects, IT professionals and business leaders at Graph + AI World 2020 for lively keynotes, business and technology tracks, hands-on workshops, real-world graph and AI use case presentations, training workshops, certification opportunities and more.
Session highlights at-a-glance include:
- Keynote featuring the world’s largest healthcare graph combined with AI to serve 50 million patients
- Keynote featuring acceleration of automotive supply chain planning for Jaguar Land Rover from 3 weeks to 45 minutes with graph analytics
- Session on how to triple the performance of your fraud and anomaly detection with graph + AI
- Exec roundtables focused on banking, financial services, media and entertainment to discuss industry best practices for accelerating AI with graph
- Session focused on hardware-accelerated machine learning solution combining graph database with FPGA (Field Programmable Gate Array) to find similar customers based on 200 features among millions in 25 milliseconds
- Session focused on building the next-generation entity resolution, recommendation engine, fraud and anomaly detection with PageRank, community detection, similarity matching, clustering and Graph Convolutional Network (GCN)
Graph + AI World will feature keynotes by thought leaders from the most innovative Fortune 500 companies, including:
- UnitedHealth Group has developed the largest graph database in the healthcare industry as a system to link, analyze, and make real-time care path recommendations for 50 million patients. The session will cover the business drivers for using graph analytics and lessons learned from deploying graph. Speaker: Ed Sverdlin, VP, Advanced Technology Collaborative and R&D, UnitedHealth Group
- The automotive supply chain is one of the most complex and global in the world, with the average car being made up of around 4,500 parts from a supply base of 30,000 individual parts, produced by hundreds of suppliers, relying on forecasts issued years in advance. This session will cover how by using graph, Jaguar Land Rover has reduced query times across its complex supply chain model from 3 weeks to 45 minutes, allowing them to accurately plan and rapidly pivot in response to supply and demand uncertainties around the COVID-19 pandemic. Speaker: Harry Powell, Director, Data & Analytics, Jaguar Land Rover
- Dr. Jay Yu, Distinguished Engineer & Architect, Intuit will present a keynote session featuring the use of a knowledge graph as the foundational technology for an AI-driven expert platform.
Learn from business case studies focused on compelling use cases as well as executive and data science roundtables:
- “Graph-Based Identity Resolution at Scale” - Xandr (part of AT&T) case study: One of the main drivers of AT&T, WarnerMedia, and Xandr's success story has been combining their data assets to provide targeted, personalized product offerings for customers. To this end, Xandr has built a multi-node, high-availability TigerGraph cluster to consolidate a vast amount of data, which includes billions of identifiers stored in an identity graph.
- “How to Build an AI-Based Customer 360 Platform” - Intuit case study: This session includes design principles and patterns for building a Customer360 platform for the AI needs of the enterprise.
- “Executive Roundtable - Realigning Business and Tech Priorities for COVID-19 Pandemic and Digital Transformation”: The COVID-19 pandemic has disrupted the business and technology priorities for all organizations. Join us to learn how leaders are adapting to this unprecedented challenge by leveraging graph, advanced analytics and AI. Participants: UnitedHealth Group, Jaguar Land Rover and SaH Analytics International
- “Executive Roundtable - Transforming Media & Entertainment With Graph + AI”: Graph databases are used to identify, link and merge duplicate customer entities and for building insightful 360-degree views of customers. This typically leads to higher revenues as a consequence of more precise and effective product and service recommendations. Join executives from AT&T and Ippen Digital to hear how graph and AI are transforming media and entertainment.
- “Executive Roundtable - Transforming Financial Services With Graph + AI”: Financial services organizations are competing in a time of unprecedented change. The most innovative businesses are embracing graph analytics as a way to increase profits, improve customer satisfaction, and find and stop fraud and financial crimes. In this session, executives from Intuit, JPMorgan Chase and OpenCorporates will discuss how graph and artificial intelligence are changing the financial services industry in ways that would have been unimaginable a decade ago.
- “Data Scientist Panel: Transforming Data Science with Graph + AI” - An open discussion on what graph database, analytics, and AI can do for a data scientist in terms of new capabilities as well as use cases and the augmentation of existing use cases. Join executives from Optum (part of UnitedHealth Group) and Xandr for this interactive session.
- “The Future of Graph Query Languages: The GQL and SQL/PGQ Standards”: Join thought leaders from the ISO standards committee, including executives from RedisGraph, data.world, Optum, and TigerGraph, as they discuss the progress toward two forthcoming property graph standards that will deliver cross-vendor compatibility and exciting new capabilities for graph users.
Participate in sessions from leading technology providers and system integrators:
- “Supply Chain & Logistics Management with Graph DB & AI” - Publicis Sapient session: Manufacturers face great challenges tracking enormous numbers of parts, components and materials from multiple globally distributed vendors. By leveraging Graph DB technology and predictive analytics, these companies can optimize production planning to ensure parts availability, minimize quality fallouts and improve overall assembly and delivery.
- “The Key to Creating a Golden Thread: The Power of Graph Databases for Entity Resolution” - Accenture session: Entity Resolution is an important concept in big data and is the root of every successful knowledge graph. What is entity resolution, why is it such a powerful thing for every business to get right or wrong, and how is graph so well positioned to do it right? This is an introduction to entity resolution, one of the most popular use cases addressed with a graph database.
- “Fast Parallel Similarity Calculations with FPGA Hardware” - Joint session by Optum and Xilinx: The foundation of recommendation is finding similar customers and their purchasing patterns. Yet, if you have 100 million customers it can take hours to do similarity calculations on just 200 features. Join experts from Optum and Xilinx to see how these calculations can be done in parallel, and how using an FPGA allows these calculations to be done in under 30 milliseconds.
- “Hardware-Accelerated Machine Learning Solution for Detecting Fraud and Money Laundering Rings” - Xilinx session: How can you find fraud and money laundering rings faster? One answer: Combining FPGA with graph database and analytics to accelerate the Louvain community detection algorithm. Join executives from Xilinx and TigerGraph for this discussion.