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【funinusa.net comprehensive report].Artificial intelligence developed to simulate written language can be used for events in people's lives。A research project from the German Technical University, the University of Copenhagen, the International Telecommunication Union and Northeastern University in the United States has shown that if you use a lot of data about people's lives and train the so-called"Converter model"(e.g. ChatGPT) to process language, they are able to systematically organize data and ** what will happen in a person's life, and even estimate the time of death.
Published inNature Computational Sciencenature computational scienceAn article entitled"Using the Sequence of Life Events ** A Man's Life".using sequences of life-events to predict human livesIn a new scientific article, the researchers published a new scientific article called"life2vec"The model analysed health data and access to the labour market for 6 million Danes. After the initial phase of training of the model (i.e., learning patterns in the data), the model outperforms other advanced neural networks (see data boxes) and can accurately measure results such as personality and time to death. "We use this model to solve a fundamental question: to what extent can we base your past conditions and events on your future events?Scientifically, it's not the ** itself that excites us, but the aspect of the data that enables the model to provide such precise answers"Sune Lehmann, the first author of the article and a professor at the German Technical University, said. Time of Death**Life2vec's ** is an answer to general questions, such as:"Death in four years?Death in four years?"？The researchers analyzed the model's responses and found that the results were consistent with existing research in the social sciences;For example, all things being equal, people in leadership positions or with high incomes are more likely to survive, while men who are skilled, or have mental illness are at higher risk of dying. Life2vec encodes the data into a massive vector systemIt is a mathematical structure that organizes different pieces of data. The model determines where to place data on time of birth, schooling, education, wages, housing, and health. "It's exciting to think of a person's life as a long sequence of events, just as a sentence in a language is made up of a series of words. Converter models in AI are often used for this type of task, but in our experiments, we use them to analyze what we call life sequences, which are events that occur in human life"Suni Lyman said: Ask ethical questionsThe researchers behind the article point out that there are several ethical issues surrounding the life2vec model, such as the role of protecting sensitive data, privacy, and data bias. A deeper understanding of these challenges is essential before using the model to assess an individual's risk of contracting illness or other preventable life events. The model opens up important positive and negative perspectives that can be discussed and addressed from a political perspective. Similar technologies for life events and human behavior are now being used within tech companies, for example, that track our behavior on social networks, conduct extremely precise profilings of us, and use these profilings to educate and influence us. Sune Lehmann said: "This discussion needs to be part of the democratic conversation so that we can think about where technology will take us and whether this is the development we want. The researchers believe that the next step will be to incorporate other types of information, such as texts and images or information about our social relationships. The use of data opens up entirely new avenues of interaction between the social sciences and the health sciences. Research projectsUsing Life Event Sequences** The Human Life Research Project is based on labour market data as well as data from the National Patient Registry (LPR) and Statistics Denmark. The dataset includes all 6 million Danes and contains information on income, salary, allowances, job type, industry, social benefits, and more. The health dataset includes medical professional or hospital visits, diagnoses, patient types, and urgency. The time span of the dataset was 2008 to 2020, but in several analyses, the researchers focused on the period 2008-2016 and a subset of age-restricted individuals. Converter modelA converter model is an AI deep learning data architecture that is used to learn language and other tasks. Through training, these models can understand and generate language. The converter model is designed to be faster and more efficient than previous modelsIt is often used to train large language models on large datasets. Neural networksA neural network is a computer model inspired by the brains and nervous systems of humans and animals. There are many different types of neural networks (such as transformer models). Like the brain, neural networks are made up of artificial neurons. These neurons are connected to each other and can send signals to each other. Each neuron receives input from other neurons, then calculates the output and passes it on to other neurons. Neural networks can learn to solve tasks by training them on large amounts of data. Neural networks rely on training data to learn and improve their accuracy over time. But once the accuracy of these learning algorithms is fine-tuned, they become powerful tools in the fields of computer science and artificial intelligence, allowing us to classify and group data at high speeds. One of the most well-known neural networks is Google's search algorithm. Welcome to Funinusa.NET forum discussions