TigerGraph has announced the finalists of its Million Dollar challenge that it started in February. The judges are now analysing more than 147 completed submissions from over 1500 initial registrations across various challenges.
Dr Yu Xu, founder and CEO of TigerGraph, commented: “We issued a challenge to the world’s most brilliant minds — and the call was answered. TigerGraph has always recognized graph’s potential to change the world, and we put our claim to the test by creating the Graph for All Million Dollar Challenge. The overall participation, as well as the quality of submitted projects, totally exceeded our expectations. There’s no denying that graph is the technology of the future — and these projects underscore graph’s ability to literally change the world.”
More than 92 countries are represented in the final submissions, and they come from various organisations. TigerGraph published a small sample of the submissions, which are included below. It demonstrates what is possible for Graph databases.
The potential, Yu believes, is huge and can make a real difference. Xu recently spoke to Enterprise Times about how Graph Databases are reaching maturity and the different use cases they help solve. The million-dollar challenge further demonstrates the power of Graph databases and how they could help change the world.
The judges have already narrowed down the field. They will announce the fifteen winners on May 25th at the Graph + AI Summit. The Summit is an open conference with speakers from across the industry with sessions on various subjects.
Submissions
Each submission below includes a video which gives a brief description of the proposal. The quality is high, with Dan McCreary, Distinguished Engineer – AI at Optum and Graph for All Million Dollar Challenge judge noting: “Graph technologies are new to many organizations. Learning ways that graph can be used to solve complex problems and improve results creates the foundation for knowing how to use graph in your organization. So many important answers lie in connected data.
“What I love about the Million Dollar Challenge is the incredible diversity and creativity of the projects we are seeing. With this challenge, the world is opening up their eyes to graph — and I believe that several new business plans are now being written because of the work done in these projects.”
TigerGraph for United Nations (UN) Data:
Connect the unconnected! Source, clean, and load UN data for the environment, the economy, health, refugees, crops, and more into a single graph and make it available for anyone to use.
UAWelcome
In response to the war in Ukraine, a graph-based crowdsourcing platform connecting refugees with those who can help, optimizing limited and scattered resources. Designed to be simple to use and maintain for rapidly changing workflows.
Fact-Checker: Fighting Misinformation at Scale
Misinformation is everywhere, on social media, on websites, and even face-to-face. It’s hard to know what to believe, and even harder to figure out what’s true. This solution is a multi-platform, multi-lingual, real-time fact-checking system powered by machine learning and graph technology.
ShockNet
Prevent crises by predicting the transfer of shocks through the world economy. Users can adjust assumptions, investigate the predicted chains of shocks, and identify ways to avoid economic crises.
Finding Drug Interactions in Silico with Graph
Drug-drug side-effects are rarely tested directly in the pharmaceutical development process. This system can generate in silico indications of drug-drug interactions using graph machine learning.
Anti-Mafia Analytics Platform
Organized crime negatively impacts society from issues such as drug trafficking to corruption to murder. Tackling these issues relies on understanding the complex interconnected web of crime incidents, criminals, and financial activity. This project seeks to provide an analytics platform that can detect “moles” within the police force and spot fraud transactions.
Enterprise Times: What does this mean
While in itself this is a great marketing tool for TigerGraph itself, it raises an important point for the wider industry. The submissions will indicate how Graph databases can help change the world for the better. The key is gaining access to enough quality data around any subject area.
What will be interesting is seeing whether these and other projects actually make a difference. If they do, then the value to the interested parties is much higher than the $1 million prizes on offer.
One hopes that TigerGraph will repeat the exercise next year, and some even harder problems will be attacked and potentially solved. For now, it is about waiting for the announcement on May 25th and then following what happens to the winning solutions over the following 12 months.
