The IBM project involves a humanitarian effort to find ways of implementing low cost, smart solutions to help lift rural villages in developing countries, specifically India, out of poverty, and enhance the overall quality of life. IBM is working with Diversatech and ML@B on a joint project to take a data-driven approach to this problem - Diversatech would handle the various strategic, logistical, and business aspects of the process, while the purpose of our team would be to actually design solutions that take advantage of all the data available with respect to the economic and social state of the villages, including data collected by Diversitech to further this problem, such as interviews, focus groups, and other research. Ultimately, the project would begin with the identification of a few specific infrastructural issues affecting villages in India, and would deliver a prototype solution aimed at solving these problems using IBM's existing cognitive solutions (eg Watson). This project is very open-ended and would involve a lot of ideation and analysis, followed by the design of an actual ML model. In the past, machine learning has been applied to similar problems to both discover insights into root causes affecting poverty-stricken areas as well as implementing actual solutions to increase the economic welfare of those areas.
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