Why Your Body Clock Miscalculates Your True Age: How AI Can Provide Accurate Insights

Posted on January 23, 2026 by Igor Mitreski

You May Be Historically Older Than Your “Real Age”

Reuters/Toru Hanai

Biological Age Representation — You May Be Historically Older Than Your “Real Age”

Reuters/Toru Hanai

Years ago, when I began discussing the concept of aging, the “biological clock” emerged as a key topic. This term, synonymous with the aging clock and “true age” measurement, highlights the difference between chronological age—the number of years since birth—and biological age, which indicates the actual aging process within our bodies.

Generally, biological aging follows a predictable pattern: a gradual decline in physical and mental functions throughout adulthood. Our intuitive judgments of age often incorporate visible signs like wrinkles, gray hair, and variations in posture, gait, mental sharpness, and voice.

The goal of determining biological age is to encapsulate this aging process into a single measurable figure. This provides insight into an individual’s health trajectory, emphasizing that some people age significantly faster than others.

Most individuals find their biological age within a few years of their chronological age. However, discrepancies can be stark: one 56-year-old may exhibit a biological age akin to someone in their 30s, while another may resemble a person in their 70s. Notably, biological age can increase or decrease at a different rate than chronological age.

Understanding biological age serves as a valuable tool, offering individuals clear, understandable insights into their health. This information can motivate lifestyle modifications and help assess the effectiveness of interventions like diet and exercise. The demand for biological age assessments is evident, as numerous companies now offer testing services, albeit often at a premium.

For scientists investigating anti-aging strategies, biological age measurements serve as immediate indicators of intervention success, eliminating the need for long-term studies involving human or animal subjects. Furthermore, tracking biological age enables us to comprehend the inner workings of our bodies as they age.

Despite its advantages, the concept of biological age requires refinement. The initial biological clocks were based on epigenetic markers—molecular indicators that alter gene expression. Innovators like Steve Horvath from UCLA discovered that these markers change predictably throughout life, allowing for the estimation of biological age through complex algorithms.

Yet, epigenetics isn’t the sole estimation approach. Various other biological markers—such as blood proteins, telomeres, urine metabolites, facial imagery, and even X-rays—can also inform biological age assessments. However, the inconsistency between these different measurement methods raises concerns about their reliability.

For instance, according to a recent analysis of the CALERIE trial, which examined caloric restriction as an anti-aging intervention, five different aging clocks were applied to a cohort of 220 adults. Only two showed a significant decline in biological age among calorie-restricted participants, leaving questions about which clock to trust—a dilemma faced by both individuals and researchers utilizing aging assessments.

Another challenge is the misleading perception of accuracy. Most companies report a single biological age figure without indicating a margin of error, leading to potential misinterpretations. A recent study published in npj Aging pointed out that many existing biological clocks do not perform as anticipated, which could lead to unnecessary anxiety regarding health outcomes.

But does this imply that biological clocks are without value? Not entirely. Research indicates that many limitations associated with these methods could be addressed. According to Dmitri Kulikov and fellow researchers from the Skolkovo Institute of Science and Technology, overcoming these challenges is feasible, although determining whether it is worth pursuing these improvements remains an open question.

Meanwhile, innovative solutions are on the horizon. Emerging methodologies that utilize artificial intelligence, particularly large-scale health models (LHM), hold promise. These AI-driven models, akin to those powering systems like ChatGPT, analyze vast datasets to assess individual risks related to mortality and the development of age-related conditions. A recent study in Natural Medicine suggests these modern methods may outperform traditional biological clocks.

As LHM continues to evolve, it may address many current limitations of biological age assessments. Thus, if you are contemplating determining your biological age, proceed with caution. If you’ve already done so, take the outcomes with a degree of skepticism. In future reflections on aging, I promise to approach this subject with a more critical perspective, blending newfound knowledge with experience.

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Source: www.newscientist.com

Breakthrough Study Unveils First Accurate Explanation of Lightning Formation in Nature

Posted on July 29, 2025 by Igor Mitreski

A recent study by Professor Victor Pasco from Pennsylvania and his team reveals the method for determining the robust electric field associated with thunder, which collides with molecules such as nitrogen and oxygen, resulting in x-rays that trigger intense storms through additional electrons and high-energy photons.

NASA’s high-population ER-2 plane is equipped with instruments for the fly-eye Earth Intake Mapper Simulator and the Ground Gamma Ray Flash (ALOFT) Mission, which records gamma rays from ThunderClouds (illustrated in purple). Image credit: NASA/ALOFT team.

“Our research provides an accurate and quantitative explanation of the initial processes leading to lightning,” stated Professor Pasco.

“It connects the underlying physics of X-rays, electric fields, and electron avalanches.”

In their study, Professor Pasco and colleagues employed mathematical modeling to validate and elucidate field observations related to photoelectric phenomena within the Earth’s atmosphere.

This phenomenon, known as terrestrial gamma-ray flashes, consists of invisible, naturally occurring bursts of x-rays along with their associated radio emissions.

“By creating a simulation that mirrors the observed field conditions, we offered a comprehensive explanation of the x-rays and radio emissions occurring inside Thunderclouds,” added Professor Pasco.

“Our research illustrates how electrons, accelerated by lightning’s strong electric field, can generate x-rays upon colliding with air molecules like nitrogen or oxygen, leading to an avalanche of electrons that create high-energy photons to initiate lightning.”

Through their model, the researchers analyzed field observations gathered by various research teams utilizing ground-based sensors, satellites, and high-altitude surveillance platforms to simulate thunderstorm conditions.

“We elucidated the mechanisms of photoelectric events, the triggering conditions for electron cascades in thunder, and the sources of diverse radio signals detected in clouds preceding a lightning strike,” explained Professor Pervez.

“To validate the lightning initiation explanation, I compared our findings with previous models, observational studies, and my own investigations into lightning bolts, specifically intercompact cloud discharges that typically occur within limited regions of Thunderclouds.”

This process, termed photoelectric feedback discharge, models the physical conditions where lightning is likely to happen.

The equations employed to develop the model are available in the published papers, enabling other researchers to apply them in their own studies.

Besides elucidating the onset of lightning, the scientists clarified why ground-level gamma-ray flashes can often occur without the accompanying light and radio emissions that signify lightning in rainy conditions.

“In our simulations, the high-energy X-rays generated by relativistic electron avalanches create new seed electrons driven by photoelectric phenomena in the air, rapidly amplifying these avalanches,” Professor Pasco remarked.

“Moreover, while this runaway chain reaction is generated in a compact volume, it can happen across a varied range of intensities, often with minimal optical and radio emissions but detectable X-ray levels.”

“This explains why these gamma-ray flashes originate from regions that are visually dim and appear silent in wireless frequency.”

The team’s findings will be published in the Journal of Geophysical Research: Atmospheres.

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Victor P. Pasco et al. 2025. The photoelectric effect in the air accounts for the initiation of lightning and the occurrence of terrestrial gamma rays. JGR Atmosphere 130 (14): E2025JD043897; doi: 10.1029/2025JD043897

Source: www.sci.news

Research Shows Accurate Age Predictions Can Be Made with Just 50 DNA Molecules

Posted on July 15, 2025 by Igor Mitreski

Researchers at Hebrew University leveraged a deep learning network to analyze DNA methylation patterns, achieving a time series age (defined as postnatal time) with median accuracy for individuals under 50 years, ranging from 1.36 to 1.7 years. result This work will be published in the journal Cell Report.

Utilizing ultra-depth sequences from over 300 blood samples of healthy individuals, the research indicates that age-dependent methylation changes happen in a probabilistic or coordinated block-like fashion across clusters of CPG sites. Image credit: Ochana et al., doi: 10.1016/j.celrep.2025.115958.

“We observe that our DNA leaves measurable marks over time,” commented Professor Tommy Kaplan from Hebrew University.

“Our model interprets these marks with remarkable precision.”

“The essence lies in how our DNA evolves through a process known as methylation – the chemical tagging of DNA by methyl groups (CH)₃.

“By focusing on two vital regions of the human genome, our team successfully decoded these changes at the level of individual molecules, employing deep learning to generate accurate age estimations.”

In this research, Professor Kaplan and his team examined blood samples from over 300 healthy subjects and analyzed data from a decade-long study of the Jerusalem Perinatal Study.

The model developed by the team showed consistent performance across various factors, including smoking, weight, gender, and diverse indicators of biological aging.

In addition to potential medical applications, this technique could transform forensic science by enabling experts to estimate the age of suspects based on DNA traces.

“This provides us with a new perspective on cellular aging,” stated Yuval Dor, a professor at Hebrew University.

“It’s a striking example of the intersection between biology and artificial intelligence.”

Researchers found new patterns in DNA alterations over time, suggesting that cells encode both mature and tuned bursts, akin to biological clocks.

“It’s not solely about knowing your age,” explained Professor Ruth Shemmer of Hebrew University.

“It’s about comprehending how cells and molecules keep track of time.”

“This research could redefine our approach to health, aging, and identity,” added the scientist.

“From assisting physicians in treatment based on an individual’s biological timeline to equipping forensic investigators with advanced tools for crime-solving, the capability to decipher age from DNA paves the way for groundbreaking advancements in science, medicine, and law.”

“Moreover, it enhances our understanding of the aging process and brings us closer to unraveling our body’s internal clock.”

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Bracha-Lea Ochana et al. Time is encoded by changes in methylation at clustered CPG sites. Cell Report Published online on July 14th, 2025. doi:10.1016/j.celrep.2025.115958

Source: www.sci.news

Wimbledon Officials Stand by AI Usage as Jack Draper States It’s Not “100% Accurate”

Posted on July 4, 2025 by Igor Mitreski

The Wimbledon organizer defended the implementation of AI line judges after Jack Draper claimed the technology wasn’t “100% precise.”

The UK’s first-line judge was deemed “embarrassing” and removed after colliding with 36-year-old former finalist Marin Cilic in the second round.

The 23-year-old Draper expressed his frustration with the AI-enhanced Hawk-Eye system during Thursday’s match, especially after a contested serve from his opponent went unchallenged over four sets.

“Honestly, I don’t think it’s 100% precise,” he mentioned in a post-match conference. “Some of the calls today showed marks on the court. There’s no way chalk would indicate that. I don’t believe it’s 100% precise—it’s in millimeters.”

He acknowledged that it was unfortunate the judge was removed but conceded he might have been wrong regarding a specific call.

Tournament Director Jamie Baker stood by the system’s accuracy and refrained from commenting on whether he missed the human line judge, who had been part of Wimbledon’s tradition for 147 years.

Baker stated: “The concept of live line calling is standard across the tour. It’s essential for the entire ATP tour. Two of the other Grand Slams have utilized it for four or five years.”

“What that means is the level of refinement and authentication around the system becomes increasingly specialized and robust over time.”

“The overall accuracy, reliability, and robustness of the system are on par with tennis from a moderation standpoint.”

Baker refuted claims that the electronic system influenced Ben Shelton’s decision to halt his second match, which occurred while the 22-year-old American was serving.

Shelton, ranked No. 10 in the world, was outraged at the judge’s ruling, which came at 9:31 PM due to diminishing sunlight. Baker asserted that the decision was not related to technology and that the match could continue later.

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Baker remarked: “It won’t be effective if no one is able to call the lines, but we haven’t hit that threshold yet, although we are getting closer.

“It’s not just about how technology has evolved, but also about the number of cameras on each court, allowing for longer playtime with the challenge system.”

Baker noted that players were previously able to continue playing as daylight faded, but they have since struggled to manage this.

“Sometimes players liked it, sometimes they didn’t,” he said. “In reality, we have more time now that we can extend matches. But last night, we were approaching the limit, and hadn’t quite reached it yet.”

“This sport requires high-level performance at a fast pace, and when darkness falls, it becomes a challenge even for seasoned officials.”

Source: www.theguardian.com

Meteorologists face backlash despite accurate storm forecasts

Posted on October 17, 2024 by Igor Mitreski

overview

Forecasts for hurricanes Helen and Milton were very accurate.
Meteorologists say they are facing unprecedented skepticism and vitriol despite the strong information they have released.
Some blame pre-election political tensions, while others point to climate change denial and the spread of misinformation on social media.

Nearly five days before Hurricane Milton hit Florida, forecasters at the National Hurricane Center predicted its path to within 19 miles of where the storm would later make landfall.

The forecast for Hurricane Helen was similarly accurate. Long before the storm reached the coast, the National Weather Service said “record flooding” in North Carolina, about 400 miles from the coast, was “one of the most significant weather events” in the state’s history. I warned you it would happen.

“The forecast was very accurate and I don’t think anyone was surprised by the landfall location and strength of this storm,” said NBC 6 South Florida meteorologist and hurricane expert John Morales.

But some meteorologists say this is the first time they’ve faced so much skepticism, hatred and conspiratorial backlash at a time when hurricane forecasts are at their most accurate.

They have been unfairly accused, primarily on social media, of steering the hurricane toward Florida or Appalachia. Some people have reported threats of violence online, while others say they have been personally attacked.

“Conspiracy theories have increased tremendously over the past two months, especially on social media, and it’s hurting our ability to do our jobs effectively,” said Matthew Cappucci, a meteorologist at Mailer Weather and The Washington Post. ” he said. “People will see false signals on radar and think we’re having a hurricane. Some people will think we can lead a hurricane into red states.”

Capucci said social media commenters criticized his Harvard education and said he should be fired. Cappucci added that he was recently interrupted at a bar in Louisiana by a man who noticed his MyRadar shirt and claimed that Cappucci worked for Bill Gates.

“He continued to harass me for the next 14 minutes about weather modification,” Capucci said.

Bradley Panovich, chief meteorologist at WCNC in Charlotte, North Carolina, said the messages are “getting more personal, meaner and more persistent.”

“It also takes time and effort away from the job of predicting the weather,” he added.

The wave of opposition and attacks comes as climate change intensifies and meteorologists grapple with the psychological toll of more severe and damaging hurricanes.

“Losing someone to a weather disaster is like losing a patient to a doctor on the operating table,” said Kim Klokow McClain, a senior social scientist supporting the National Weather Service. “Forecasters feel like they can save everyone. They take it personally.”

Hurricane forecasts are now more accurate

Hurricane forecasting has improved dramatically over the past 50 years.

Shel Winkley, a meteorologist at the nonprofit research group Climate Central, said that advances in computing power and a better understanding of storm physics have allowed the National Hurricane Center to develop forecast cones (forecast forecasts) before tropical cyclones develop. He said that he is now able to announce his future career path.

“Our cone is leaner,” Winkley said, meaning forecasters have more confidence in the hurricane’s path.

The National Hurricane Center annually releases data on how its forecasts match reality, and the trend shows tracking errors have been decreasing since the 1970s. At the time, storm forecasts issued 36 hours in advance could be off by about 230 miles. According to NOAA. So far in the 2020s, that margin of error is approximately 57 miles.

Capucci said the center’s predictions for Hurricane Milton were “almost prescient” and among the best in the center’s history.

Source: www.nbcnews.com

AI Death Calculator: Highly Accurate Prediction of Your Time of Death

Posted on December 24, 2023 by Igor Mitreski

This is a matter of life and death – no doubt about it. bot it.

Most people aren’t in a huge hurry to know when the big bite is going to bite, but a newly developed AI death calculator can now predict when a person will die with eerily accurate accuracy.

“We use the technology behind ChatGPT (what we call the Transformer Model) to analyze human life by representing each person as a series of events that occur in their life,” December 2023. said Sune Lehmann, lead author of the study.Predicting human life using a sequence of life events” he told the Post.

In their report, the professor of networks and complex systems at the Technical University of Denmark and his co-authors describe a method known as “life2vec,” which uses selected details of an individual’s life, such as income, occupation, place of residence, and health history. Introducing the algorithm that can be used. Determines life expectancy with 78% accuracy.

“We take advantage of the fact that human life in some ways shares similarities with language,” Lehman explained. “Just as words follow one another in a sentence, events follow one another in human life.”

It’s a little different than ChatGPT. It’s the ever-popular bot that tech wizards are employing to land their dream job or curate the perfect outfit. By closely examining a man or woman’s past, life2vec can calculate the outcome of that person’s life.

“This model can predict almost anything,” Lehman told the Post. He said his research team also uses this specialized program to predict people’s personalities and international movement decisions.

“We predicted death because that’s what people (insurance companies, for example) have been doing for years,” he added. “So we were very aware of what could happen.”

From 2008 to 2020, Lehman’s team studied a heterogeneous population of 6 million Danes of different genders and ages. Analysts used life2vec to identify participants who were likely to survive at least four years after January 1, 2016.

“The scale of our dataset allows us to represent individual human life trajectories at the sequence level, providing a detailed representation of how each person moves over time,” the report said. is written. “We’re looking at how an individual’s life evolves across different types of events (information about heart attacks mixed with information about salary increases and moving from urban to rural areas). You can observe it.”

Researchers used plain language such as “In September 2012, Francisco received 20,000 Danish kroner as a guard at Elsinore Castle” and “Hermione followed in her third year at secondary boarding school.” was used to enter AI-specific information about each study participant. 5 elective classes. ”

We then assigned different digital tokens to each piece of data, all of which were categorized very specifically. For example, a forearm fracture is represented as S52. Working in a tobacco store is coded as IND4726 and income is represented by 100 different digital tokens. And “postpartum hemorrhage” is O72.

life2vec used the information provided to predict who would die by 2020 almost perfectly over three-quarters of the time.

Research shows that factors that can contribute to early death include being male, having a mental health diagnosis, and working in a skilled occupation. Earning a higher income or holding a leadership role were both associated with longevity.

However, Lehman stressed to the Post that study participants were not given a prediction of death.

“That would be extremely irresponsible,” he said, adding that he and his team ultimately hope to share details of the results in a way that protects the privacy of study participants.

“But we can still learn from it [life2vec] What are the factors that might help people live longer?” Lehman said. “We haven’t delved too deeply into this, but this is another important application of the model.”

Currently, this bot is not available to the general public or businesses. And even if it were to be deployed at scale, this AI would not be used to notify specific individuals in cases such as writing insurance policies or making hiring decisions. Probably not, says Prober.

“Forecasting is not used for anything,” Lehman argued. “The point of life2vec is to understand what is predictable and what is not.”

Source: nypost.com

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