Lifeboat Foundation: Safeguarding Humanity
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Observer, backup youthful copy, playing the right piano notes, quantum states oh my.

Dr David Sinclair explain about through his lab experiments, why he thinks there is an observer/backup copy for our youthfulness and what are the possible identities he can think of in this clip.

David Sinclair is a professor in the Department of Genetics and co-director of the Paul F. Glenn Center for the Biology of Aging at Harvard Medical School, where he and his colleagues study sirtuins—protein-modifying enzymes that respond to changing NAD+ levels and to caloric restriction—as well as chromatin, energy metabolism, mitochondria, learning and memory, neurodegeneration, cancer, and cellular reprogramming.

Dr David Sinclair has suggested that aging is a disease—and that we may soon have the tools to put it into remission—and he has called for greater international attention to the social, economic and political and benefits of a world in which billions of people can live much longer and much healthier lives.

Dr David Sinclair is the co-founder of several biotechnology companies (Life Biosciences, Sirtris, Genocea, Cohbar, MetroBiotech, ArcBio, Liberty Biosecurity) and is on the boards of several others.

Continue reading “WHO Is The OBSERVER That Holds The Key For OUR YOUTHFULNESS? | Dr David Sinclair Interview Clips” | >

Alzheimer’s disease has long thwarted our best efforts to pinpoint its underlying causes. Now, a new study in mice suggests that ‘poisonous flowers’ bulging with cellular debris could be the root source of one hallmark of the wretched disease and a beautifully sinister sign of a failing waste disposal system inside damaged brain cells.

The study, led by neuroscientist Ju-Hyun Lee of New York University (NYU) Langone, challenges the long-standing idea that the build-up of a protein called amyloid-beta between neurons is a crucial first step in Alzheimer’s disease, the most common form of dementia.

Instead, it suggests that damage to neurons may take root inside cells well before amyloid plaques fully form and clump together in the brain, a finding which could provide new therapeutic possibilities.

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https://www.kickstarter.com/projects/2125914059/revopoint-mi…m-precison Designers, architects, engineers, we’re all collectively known as creators. The Revopoint MINI handheld 3D scanner just amplifies our creating (or rather re-creating) abilities. Designed to be about the same size as a podcasting microphone (with the tripod and all), Revopoint MINI is an industrial-grade handheld 3D scanner with a staggering precision of 0.02mm. It uses a Class 1 Blue Light that lends it its high accuracy, while still allowing it to be safe on the skin. Just hold it against the object you want to scan and wave it around and like magic, the Revopoint MINI gives you a high-accuracy 3D model, complete with tolerances, textures, and even color information. This makes it perfect for a wide degree of applications, from 3D modeling and animation to medical design, automotive design, jewelry design, even archaeology.

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Researchers from Japan design a tunable physical reservoir device based on dielectric relaxation at an electrode-ionic liquid interface.

In the near future, more and more artificial intelligence processing will need to take place on the edge — close to the user and where the data is collected rather than on a distant computer server. This will require high-speed data processing with low power consumption. Physical reservoir computing is an attractive platform for this purpose, and a new breakthrough from scientists in Japan just made this much more flexible and practical.

Physical reservoir computing (PRC), which relies on the transient response of physical systems, is an attractive machine learning framework that can perform high-speed processing of time-series signals at low power. However, PRC systems have low tunability, limiting the signals it can process. Now, researchers from Japan present ionic liquids as an easily tunable physical reservoir device that can be optimized to process signals over a broad range of timescales by simply changing their viscosity.

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