Lifeboat Foundation

Tina Woods, serving as Healthy Longevity Champion for the National Innovation Center for Aging, sets forth her vision for a blueprint for healthy longevity for all. Her emphasis is on reaping the “longevity dividend” and achieving five additional years of healthy life expectancy while reducing health and wellbeing inequality. Woods elaborates on the role of emerging technologies like AI, machine learning, and advanced data analysis in comprehending and influencing biological systems related to aging. She also underscores the crucial role of lifestyle changes and the consideration of socio-economic factors in increasing lifespan. The talk also explores the burgeoning field of emotion AI and its application in developing environments for better health outcomes, with a mention of “Longevity Cities,” starting with a trial in Newcastle. In closing, Woods mentions the development of a framework for incentivizing businesses through measurement of their contribution to health in three areas: workforce health, consumer health through products and services, and community health. Woods envisions a future where businesses impacting health negatively are disincentivized, and concludes with the hope that the UK’s healthy longevity innovation mission can harness longevity science and data innovation to improve life expectancy.

00:00:00 — Introduction, National Innovation Center for Aging.
00:00:56 — Discussion on stagnating life expectancy and UK’s life sciences vision.
00:03:50 — Technological breakthroughs (including AI) in analyzing biological systems.
00:06:22 — Understanding what maintains health & wellbeing.
00:08:30 — Hype, hope, important of purpose.
00:10:00 — Psychological aging and “brain capital.“
00:13:15 — Ageism — a barrier to progress in the field of aging.
00:15:46 — Health data, AI and wearables.
00:18:44 — Prevention is key, Health is an asset to invest in.
00:19:13 — Longevity Cities.
00:21:19 — Business for Health and industry incentives.
00:23:13 — Closing.

Continue reading “Harnessing AI & Longevity Science — A Blueprint for Lifespan Extension (Tina Woods)” »

Researchers at the University of Hong Kong (HKU) have designed an innovative pixelated, soft, color-changing system called a Morphable Concavity Array (MoCA).

Pixelated, soft, color-changing systems are malleable structures that can change color by manipulating light. They have applications in a wide range of industries, from medical bandages that change color if there is an infection, to foldable screens on smartphones and tablets, as well as wearable technology where sensors are integrated into the clothing fabric.

The research was co-directed by Professor Anderson Ho Cheung Shum from the Department of Mechanical Engineering at HKU, and Professor Mingzhu Li from the Institute of Chemistry, Chinese Academy of Sciences, and led by Dr. Yi Pan from the Department of Mechanical Engineering at HKU.

Humane, a stealthy software and hardware company, is clearly milking the media hype cycle for all it’s worth. The company’s origin dates all the way back to 2017, when it was founded by former Apple employees Bethany Bongiorno and Imran Chaudhri. In the intervening half-decade, the firm has been largely shrouded in mystery, as it has put together the pieces of a mystery wearable, which it promises will leverage AI in unique ways.

The company’s been buzzy since it first engaged with the media — well before it offered the slightest bit of insight into what it’s been working on. In spite — or perhaps because — of such mysteries, Humane is now an extremely well-funded early-stage startup.

At the tail end of 2020, it raised a $30 million Series A at a $150 million valuation. The $100 million B round arrived the following September, including Tiger Global Management, SoftBank Group, BOND, Forerunner Ventures and Qualcomm Ventures. It all seemed like a strong vote of confidence for the still stealthy firm. This March, it went ahead and raised another $100 million.

In case you missed the hype, Humane is a startup founded by ex-Apple executives that’s working on a device called the “Ai Pin” that uses projectors, cameras and AI tech to act as a sort of wearable AI assistant. Now, the company has unveiled the AI Pin in full at a Paris fashion show (Humane x Coperni) as a way to show off the device’s new form factor. “Supermodel Naomi Campbell is the first person outside of the company to wear the device in public, ahead of its full unveiling on November 9,” Humane wrote.

The company describes the device as a “screenless, standalone device and software platform built from the ground up for AI.” It’s powered by an “advanced” Qualcomm Snapdragon platform and equipped with a mini-projector that takes the place of a smartphone screen, along with a camera and speaker. It can perform functions like AI-powered optical recognition, but is also supposedly “privacy-first” thanks to qualities like no wake word and thus no “always on” listening.”

150 YEARS MAXIMUM BIOLOGICAL AGE — “We observed, that the age-dependent population DOSI distribution broadening could be explained by a progressive loss of physiological resilience measured by the DOSI auto-correlation time. Extrapolation of this trend suggested that DOSI recovery time and variance would simultaneously diverge at a critical point of 120 − 150 years of age corresponding to a complete loss of resilience. The observation was immediately confirmed by the independent analysis of correlation properties of intraday physical activity levels fluctuations collected by wearable devices. We conclude that the criticality resulting in the end of life is an intrinsic biological property of an organism that is independent of stress factors and signifies a fundamental or absolute limit of human lifespan.”

We investigated the dynamic properties of the organism state fluctuations along individual aging trajectories in a large longitudinal database of CBC measurements from a consumer diagnostics laboratory. To simplify the analysis, we used a log-linear mortality estimate from the CBC variables as a single quantitative measure of aging process, henceforth referred to as dynamic organism state index (DOSI). We observed, that the age-dependent population DOSI distribution broadening could be explained by a progressive loss of physiological resilience measured by the DOSI auto-correlation time. Extrapolation of this trend suggested that DOSI recovery time and variance would simultaneously diverge at a critical point of 120 − 150 years of age corresponding to a complete loss of resilience. The observation was immediately confirmed by the independent analysis of correlation properties of intraday physical activity levels fluctuations collected by wearable devices. We conclude that the criticality resulting in the end of life is an intrinsic biological property of an organism that is independent of stress factors and signifies a fundamental or absolute limit of human lifespan.

P.O. Fedichev is a shareholder of Gero LLC. A.Gudkov is a member of Gero LLC Advisory Board. T.V. Pyrkov, K. Avchaciov, A.E. Tarkhov, L. Menshikov, and P.O. Fedichev are employees of Gero LLC.

The patch can calibrate the glucose measurements based on the pH and temperature changes in sweat due to factors such as exercise and eating.

A team of researchers at Penn State has developed a new wearable patch that can monitor your health by analyzing your sweat. The patch, which is made of a special material that can detect glucose, pH, and temperature in sweat, can provide valuable information about your body’s condition and help diagnose and manage diseases such as diabetes.

Credit: Kate Myers/Penn State.

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It encourages wearers to take more steps, covering distances more quickly than they could without it.

A wearable exoskeleton can help runners increase their speed by encouraging them to take more steps, allowing them to cover short distances more quickly.

While previous studies have focused on how wearable exoskeletons can help people reduce the energy they expend while running, the new study, published today in Science Robotics, examines how wearable robots can assist runners as they sprint.

In a recent study published in Science Advances, researchers from the California Institute of Technology, led by Dr. Wei Gao, have developed a machine learning (ML)–powered 3D-printed epifluidic electronic skin for multimodal health surveillance. This wearable platform enables real-time physical and chemical monitoring of health status.

Wearable health devices have the potential to revolutionize the medical world, offering real-time tracking, personalized treatments, and early diagnosis of diseases.

However, one of the main challenges with these devices is that they don’t track data at the molecular level, and their fabrication is challenging. Dr. Gao explained why this served as a motivation for their team.

Aside from faster results, edge computing has the added benefit of increased privacy: If your health information never leaves your wearable, you don’t have to worry about someone else intercepting it — or interfering with it — en route.

So why do we run these apps in the cloud, instead of locally? The problem is that wireless devices have limited processing power and battery — to run a more advanced and energy-intensive AI program, you may have to turn to huge servers in the cloud.

A Stanford-led team has now unveiled NeuRRAM, a new microchip that could let us run advanced AI programs directly on our devices.