Three Wild Card Teams Selected to Enter the IBM Watson AI XPRIZE

May 08 2018

XPRIZE

The $5M IBM Watson AI XPRIZE just gained three innovative new contestants! They’ll be joining the global challenge to create AI applications that solve some of humanity’s most pressing challenges across a variety of fields.

With AI technologies advancing at such a rapid pace, we designed the AI XPRIZE to re-open registration twice during its timeline for a “Wild Card round” as a way of staying on top of new AI applications. The goal of these rounds is to ensure that the competition will result in disruptive approaches using AI technologies that have the potential to transform and solve the grand challenges facing our world.

We received 16 entries for first Wild Card round, but in the end our judges identified just three teams as having what it takes to join the rest of the competition. These three teams each demonstrate newly different approaches to address three very different challenges, all of which are incremental to what we’ve seen from our current competitors. 

Working out of the Netherlands, OPTOSS AI is creating a hybrid AI/crowdsourced platform that can improve the notification systems currently in place for natural and man-made disasters. Built to provide warnings and predict extreme conditions, their solution compares past weather forecasts with observational data of the Earth (e.g., satellite imagery and ground station data) to determine how timely and effective the forecasts were. Moreover, in-built AI coupled with the stream of real-time conditions data and crowdsourced human feedback improves the performance and effectiveness of future local predictions. This information provides emergency response organizations with much needed additional time to prepare and react in the most optimal manner.

A Wild Card team from Israel, Zzapp Malaria, will be building systems from satellite observations to plan and track operations and protect against a very different kind of disaster—malaria, a disease that affected 200 million and killed more than 400,000 people in Africa last year alone. 

Despite how widespread and devastating malaria has proven to be, the team identified that limited resources and expertise, as well as unreliable infrastructure, inhibited every malaria eradication campaign in Africa to date. That’s why Zzapp Malaria is taking a personalized approach. They propose to generate optimized intervention strategies for individual villages and towns by using machine learning to analyze satellite images (past and present) and information from online databases to better predict the impact of malaria interventions for different conditions and environments. 

The third Wild Card team is the United States-based Mt. Cleverest. This team is working to improve education outcomes at a global scale—they propose creating a platform that blends crowdsourcing and natural language processing to provide a free, “self-improving” online textbook that delivers real-time and demonstrable enhancements to learning outcomes. They seek to overcome issues in educational content customization, curriculum integration, curation, cost, and testing. Their system plans to also provide instructors with automated assessments, recommendations, and grading of crowdsourced content alongside the ability to monitor real-time student performance.

We are excited to support the work of these Wild Card teams, and can’t wait to see all that they accomplish.

The next opportunity to enter a Wild Card Round will be this fall, and will be the last chance for new teams to join the IBM Watson AI XPRIZE.

XPRIZE