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AI-based System To Predict Premature Deaths

For the study, the team included over half a million people aged between 40 and 69

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Researchers have developed an Artificial Intelligence (AI)-based system to predict the risk of early deaths due to chronic disease in middle-aged adults.

The study, published by PLOS ONE journal, found that the new AI Machine Learning models known as “random forest” and “deep learning” were very accurate in its predictions and performed better than the current standard approach to prediction developed by human experts.

Such new risk prediction models take into account demographic, biometric, clinical and lifestyle factors for each individual, and assess even their dietary consumption of fruit, vegetables and meat per day, said Stephen Weng, Assistant Professor at the University of Nottingham in Britain.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

The traditionally-used “Cox regression” prediction model, based on age and gender, was found to be the least accurate at predicting mortality and also a multivariate Cox model which worked better but tended to over-predict risk.

“Preventative healthcare is a growing priority in the fight against serious diseases so we have been working for a number of years to improve the accuracy of computerised health risk assessment in the general population,” said Weng.

Also Read- TRAI Believes, New Broadcast Tariffs Have Put In Place A System of Transparency

For the study, the team included over half a million people aged between 40 and 69.

Although these techniques could be new to many in health research and difficult to follow, clearly reporting these methods in a transparent way could help with scientific verification and future development of AI for health care, said Joe Kai, Professor at the varsity. (IANS)

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Researchers Develop AI Algorithm That can Solve Rubik’s Cube in Less Than a Second

According to the researchers, the ultimate goal of projects such as this one is to build the next generation of AI systems

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Researchers have developed an AI algorithm that can solve a Rubiks Cube in a fraction of a second, faster than most humans. The work is a step toward making AI systems that can think, reason, plan and make decisions.

The study, published in the journal Nature Machine Intelligence, shows DeepCubeA — a deep reinforcement learning algorithm programmed by University of California computer scientists and mathematicians — can solve the Rubik’s Cube in a fraction of a second, without any specific domain knowledge or in-game coaching from humans.

This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state – each of six sides displaying a solid colour – which apparently can not be found through random moves.

“Artificial Intelligence can defeat the world’s best human chess and Go players, but some of the more difficult puzzles, such as the Rubik’s Cube, had not been solved by computers, so we thought they were open for AI approaches,” said study author Pierre Baldi, Professor at the University of California.

“The solution to the Rubik’s Cube involves more symbolic, mathematical and abstract thinking, so a deep learning machine that can crack such a puzzle is getting closer to becoming a system that can think, reason, plan and make decisions,” Baldi said.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

For the study, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the shortest path to the goal state about 60 per cent of the time.

The algorithm also works on other combinatorial games such as the sliding tile puzzle, Lights Out and Sokoban.

The researchers were interested in understanding how and why the Artificial Intelligence (AI) made its moves and how long it took to perfect its method.

Also Read: Amazon Alexa May Come to Windows 10’s Lock Screen

“It learned on its own, our AI takes about 20 moves, most of the time solving it in the minimum number of steps,” Baldi said.

“Right there, you can see the strategy is different, so my best guess is that the AI’s form of reasoning is completely different from a human’s,” he added.

According to the researchers, the ultimate goal of projects such as this one is to build the next generation of AI systems. (IANS)