NEW YORK: A study shows that scientists found a method that leads to an extended human lifespan. The United States conducted a major study that found that people who maintain regular exercise routines will experience increased lifespan and improved health.
Harvard University conducted the study, which monitored over 110000 participants from 30 different countries during their entire lives. The research team gathered information about the participants’ medical history, exercise patterns and lifestyle choices through two-year intervals.
The research study evaluated various physical activities which included walking and jogging and stair climbing, cycling, tennis and squash sports.
The study found that people who were involved in diverse forms of exercise showed a 20% lower chance of death from any cause. The simplest exercises produced the highest health advantages. People who walked regularly experienced a 17 percent decrease in their death rates.
The risk of death from playing sports like tennis and squash decreased by 15 percent, while running or weight training resulted in a 13 percent reduction. The risk of death decreased by 11 percent for joggers and 10 percent for people who climbed stairs and 4 percent for cyclists.
The research showed that people who continued exercising throughout their lives showed a 13 to 41 percent decreased risk of dying from heart disease and cancer and respiratory diseases and other medical conditions.
The researchers identified limitations of the study because it used self-reported data which could not establish direct cause-and-effect relationships. The research proved that continuous physical activity throughout life results in extended human life expectancy.
The medical journal BMJ Medicine published the study results.
Study finds human brain processes language like AI models
Meanwhile, the human brain’s spoken language comprehension has been found by a new study to be operating with a strikingly similar mechanism to that of state-of-the-art artificial intelligence (AI) models.
The research that appeared in the journal Nature Communications made use of the method known as electrocorticography (ECoG) to observe the brain activity of individuals who were listening to a short podcast. The scientists could then identify when and where the neurons responded during the processing of words.
The results indicated that the brain did not decipher the meaning of each word instantly. Rather, the comprehension of language went through several neural layers in a manner similar to how megamodels like GPT-2 and LLaMA 2 dissect the text.
The researchers elucidated that “the brain at first attends to single words and then little by little combines the context, the intonation, and the overall meaning.” This “processing hierarchy” is very similar to the way AI models comprehend language, although they are implemented very differently.
The research has come to a conclusion that AI-generated patterning may represent some attributes of the human cognitive process that are natural and consequently, the use of AI technologies might be extended from the simple text generation to other areas.
The researchers stated that the previously unexpected similarity between human neural processing and AI language models was, in fact, more pronounced than anticipated, thus shedding light on both the fields of neuroscience and AI development.
