For centuries, eternal life has been a common quest for women and men around the world. Even today, tech tycoons like Jeff Bezos and Sam Altman are investing in startups that aim to reverse ageing by making tweaks to animal cells. While this sounds like a wonderful new era of carefree living, one expert has cast doubt over whether it would even be a good idea. Dr Stephen Cave, a philosopher at the University of Cambridge, said an extended human lifespan would be'absolutely catastrophic'. Attempts to radically lengthen lifespans will put too much pressure on Earth's resources, he claims – and could mean humanity will go extinct sooner.

Automatic segmentation of brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is critical for tissue volumetric analysis and cortical surface reconstruction. Due to dramatic structural and appearance changes associated with developmental and aging processes, existing brain tissue segmentation methods are only viable for specific age groups. Consequently, methods developed for one age group may fail for another. In this paper, we make the first attempt to segment brain tissues across the entire human lifespan (0-100 years of age) using a unified deep learning model. To overcome the challenges related to structural variability underpinned by biological processes, intensity inhomogeneity, motion artifacts, scanner-induced differences, and acquisition protocols, we propose to use contrastive learning to improve the quality of feature representations in a latent space for effective lifespan tissue segmentation. We compared our approach with commonly used segmentation methods on a large-scale dataset of 2,464 MR images. Experimental results show that our model accurately segments brain tissues across the lifespan and outperforms existing methods.

Humans are on the verge of living to more than 130 years of age, with the record for the oldest person guaranteed to be broken by the end of the century, study shows. The number of people who live past the age of 100 has been on the rise for decades, up to nearly half a million people worldwide as of this year. There are, however, far fewer'supercentenarians,' people who live to age 110 or even longer, explained researchers from the University of Washington. The oldest living person, Jeanne Calment of France, was 122 when she died in 1997; currently, the world's oldest person is 118-year-old Kane Tanaka of Japan. Such extreme longevity will continue to rise slowly by the end of this century, they found, and estimates show a lifespan of 125 years, or even 130 years, is possible.

Humans are never going to be able to live beyond 150 years of age, according to scientists who developed an app to predict the maximum lifespan. Experts in biology and biophysics fed an artificial intelligence system vast amounts of DNA and medical data, on hundreds of thousands of volunteers in the UK and US. This allowed them to develop an AI-driven iPhone app that, with simple input from a user, can accurately estimate the rate of biological ageing and maximum lifespan. As part of the big data study, they found there were two key parameters responsible for human lifespan, both covering lifestyle factors and how our body responds. The first factor is our biological age, linked to stress, lifestyle and disease, and the second is resilience, reflecting how quickly the first factor returns to normal.

Humans are never going to be able to live beyond 150 years of age, according to scientists who have predicted that this is our maximum lifespan. Experts in biology and biophysics fed an artificial intelligence system vast amounts of DNA and medical data, on hundreds of thousands of volunteers in the UK and US. This allowed them to develop an AI-driven iPhone app that, with simple input from a user, can accurately estimate the rate of biological ageing and maximum lifespan. As part of the big data study, they found there were two key parameters responsible for human lifespan, both covering lifestyle factors and how our body responds. The first factor is our biological age, linked to stress, lifestyle and disease, and the second is resilience, reflecting how quickly the first factor returns to normal.

Dmitry Kaminskiy speaks as though he were trying to unload everything he knows about the science and economics of longevity--from senolytics research that seeks to stop aging cells from spewing inflammatory proteins and other molecules to the trillion-dollar life extension industry that he and his colleagues are trying to foster--in one sitting. At the heart of the discussion with Singularity Hub is the idea that artificial intelligence will be the engine that drives breakthroughs in how we approach healthcare and healthy aging--a concept with little traction even just five years ago. "At that time, it was considered too futuristic that artificial intelligence and data science … might be more accurate compared to any hypothesis of human doctors," said Kaminskiy, co-founder and managing partner at Deep Knowledge Ventures, an investment firm that is betting big on AI and longevity. Artificial intelligence in healthcare is attracting more investments and deals than just about any sector of the economy, according to data research firm CB Insights. In the most recent third quarter, AI healthcare startups raised nearly $1.6 billion, buoyed by a $550 million mega-round from London-based Babylon Health, which uses AI to collect data from patients, analyze the information, find comparable matches, then make recommendations.