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Kira Radinsky: We have reached a critical amount of data and computation power to start finding repeating patterns in history systematically. We built a predictive model based on more than 150 years of historical news data that examines past events with similar outcomes. Our system also incorporates related contextual information pulled from LinkedData, a project that finds connections between hundreds of resources. The combination allows the software to extrapolate from news of a cholera outbreak in Angola, for example, to predict a similar outbreak in Rwanda.So do you believe that history has a tendency to repeat itself?
The probabilities are always changing, but some patterns, if we abstract them correctly, always remain. And if we incorporate the most recent information we can learn about new patterns emerging all the time. Think about how children learn—they receive reinforcement from the environment and learn patterns. This is also how we learn. I would say the work I have done is not about predicting the future, it is more about making deep analysis on probabilities of future outcomes based on what we have seen, just as an expert in the field would do if he had the time to look at all the available data in the world.
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I became fascinated with the idea of predicting the future at very early age. At some point I came to realize there is so much untapped data that can be leveraged in amazing ways. I believe that not often a person has the opportunity to do something really big that can help many people. My passion is to make big things that can affect people's lives for the better.With all the focus on the "end of the world," do you see this software being able to predict an end of the world-scale catastrophe like a nuclear holocaust or zombie apocalypse?
The system is built upon probabilities based on patterns it saw in the past. As far as I know, there haven’t been any zombie apocalypses. So far, the system predicted the first Cholera outbreak in Cuba in 130 years, riots in Turkey and Syria, and recently the ones in Sudan. Many critical decisions are not based on real data, because we didn’t have the means to do this. However, using our software, we can now potentially empower important decision makers in the world with the tools to make better decisions.Do your methods work for looking into the past as well?
In our first experiments, we utilized 150 years of New York Times data and we already have access to data going back to 1500. The system has no limitation on how far in the future it predicts as long as we have enough data to see the patterns. Some patterns have 20 years of distance between the events.
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The implications of this technology also extend to the business world. My current venture, SalesPredict, pioneers predictive modeling to increase sales. We help companies increase their sales pipelines by 75 percent. The system is still piloting and we only now started working with international organizations. However, the product is already working and companies are enjoying it. I believe that this type of technology will be widespread in a matter of years.The predictive algorithms are general purpose, in the sense they can be used to predict a variety of events given the right data. In the future, I believe predictive analytics can be incorporated into everything we do—including predicting mental and physical diseases based on our search behavior.”More tech stuff: How Drug Traffickers Have Been Hacking Shipping ContainersIs Wikipedia for Sale?Which States Are Poised to Cash In on the Drone Boom?