 Most AI systems today require sufficient historical data. And so they do okay as long as the future resembles for the most part the past. In many cases, that is not what happens. That was the whole premise behind us coming up with evolutionary AI. Shortly after the pandemic started, we started working on applying evolutionary AI to the question of predicting and then of course coming up with the best policies regionally and globally for tackling the pandemic itself. XPRIZ saw that system that we set up in May and approached us and said how about we actually create a competition around this. We set up the competition in two phases. We had 104 teams from 28 countries. Phase one was about predictions. And so the teams had to come up with models that would predict globally and regionally the number of cases of COVID-19. Phase two then was about taking this prediction as a reference and trying to come up with policies that do best on two counts. We want to minimize the number of cases in a region but at the same time we want to minimize the economic impact. Now while the competition phase is over and winners have been announced and prizes have been given we really didn't come together just for a competition. Neither did we as cognizant nor the teams nor XPRIZ. This was about creating something that would be used as a blueprint and as a reference and for use, real use out in the world by various different regions to tackle the pandemic and to take it even further from there as a reference and a blueprint for future global problems in a not just competition form but in a collaborative form. In addition to the teams collaborating with one another the models that they were contributing, the AI models end up collaborating with one another and coming up with models that do better for regions globally. When we first developed evolutionary AI we thought it would be really useful for manufacturing, finance, business decision making which is great but we never thought it would be used at this scale to help tackle humanity's greatest problems and that's just simply amazing.