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AI Death Calculator: Can this AI tool accurately predict date and time of your demise? Check out

The life2vec artificial intelligence system, which is intended to predict a range of unique factors such as personality traits, international relocations, and death, was recently presented in a paper published in Nature Computational Science.

Life2Vec: This AI tool can predict your life events, even your death, Check Out

AI Death Calculator: How would you feel if you could find out your exact date of death, your future residence, or your personality type via an artificial intelligence (AI) system? Science fiction, perhaps, but according to a recent study published in Nature Computational Science, it is feasible, at least in part. Using data on millions of Danish citizens, the researchers created a revolutionary artificial intelligence system dubbed life2vec, which can forecast life events in general.

What is Life2Vec?

 life2vec uses a machine-learning methodology to evaluate intricate life events and provide precise forecasts. The algorithm outperformed conventional actuarial tables and other machine-learning techniques, demonstrating over 78 per cent accuracy in forecasting mortality rates among the research population during a four-year period. Furthermore, based on self-reported questionnaire responses, life2vec showed potential in connecting personality traits with life events, as proven by its 73 per cent accuracy in predicting international relocations.

How does it work?

Based on language modelling principles, this innovative prediction tool uses a model architecture akin to well-known AI chatbots like Google’s Bard and OpenAI’s ChatGPT. Life2vec uses machine learning to predict future life trajectories by converting individual data into distinct timelines made up of noteworthy occurrences, symbolised as digital “tokens.” Life2vec provides a flexible platform that has the ability to transform predictive analytics across multiple spheres of human existence, thanks to its architecture that can be adjusted and its large training data set.

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