AI Harvard University Path to Happiness
A paper, Deep Longevity, that was published in collaboration with Harvard University, may have found the quickest path to happiness using AI-powered deep neural networks. Two models of human psychology based on data from the Midlife in the US were created, with the first using several neural networks to predict respondents’ chronological age as well as psychological well-being in 10 years using information from a psychological survey.

What they discovered was that emphasis on personal progress is constantly declining, but the awareness of having a purpose in life fades only after 40-50 years old. The second model is essentially self-organizing map that doubles as a foundation for a recommendation engine for mental health applications. It split all respondents into clusters depending on their likelihood of developing depression and determines the shortest path toward a cluster of mental stability for any individual. So, the big questions is…what is the quickest path to happiness? There is no definitive answer, but this study does give us insights on mental stability. Harvard researchers also developed Blueswarm, autonomous robot fish that swim in schools.

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This study offers an interesting perspective on psychological age, future well-being, and risk of depression, and demonstrates a novel application of machine learning approaches to the issues of psychological health. It also broadens how we view aging and transitions through life stages and emotional states,” said Vadim Gladyshev, Professor from Harvard Medical School.

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