Lifeboat Foundation: Safeguarding Humanity
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Blog – Page 4059

COVID-19 is defined as a respiratory infection, but the effects of the novel coronavirus are certainly not confined to any one organ.

Dozens of recent autopsies show persistent evidence of SARS-CoV-2 throughout the body, including in the lungs, the heart, the spleen, the kidneys, the liver, the colon, the thorax, muscles, nerves, the reproductive tract, the eye, and the brain.

In one particular autopsy, remnants of the novel coronavirus were found in the brain of a deceased patient 230 days after they first started showing symptoms.

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If all the hype around ChatGPT, Dall-E, Tesla’s Fully Self Driving mode and *ahem* Q.ai, has shown us anything, it’s that artificial intelligence is here to stay. The knee jerk reaction from many old fashioned meat machines, sorry, humans, is a concern around what this means for their income.

For years now, we’ve been told how AI is going to take our jobs, and it’s true that in many industries, machines, robots and other technology have cut workforce numbers dramatically.

With that said, many of the jobs being taken by AI so far are often considered dangerous, repetitive and boring. There aren’t too many people out there who are going to get great job satisfaction from turning the same 5 screws on a production line for 40 hours a week.

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New study demonstrates the potential for machine learning to accelerate the development of innovative drug delivery technologies.

Scientists at the University of Toronto have successfully tested the use of machine learning models to guide the design of long-acting injectable drug formulations. The potential for machine learning algorithms to accelerate drug formulation could reduce the time and cost associated with drug development, making promising new medicines available faster.

The study will be published today (January 10, 2023) in the journal Nature Communications.

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— If human-level AGI is created in the next 10 yrs, whaddaya guess will be the underlying tech? — Deep NNs? Hybrid neural/symbolic/evolutionary cognitive arch. e.g. OpenCog Hyperon? Comp. Neuroscience? Something wild and utterly new?

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Summary: Astrocytes play a crucial role in spatial learning, researchers discovered.

Source: University of Bonn.

There are two fundamentally different cell types in the brain, neurons and glial cells. The latter, for example, insulate the “wiring” of nerve cells or guarantee optimal working conditions for them.

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Researchers at DeepMind in London have shown that artificial intelligence (AI) can find shortcuts in a fundamental type of mathematical calculation, by turning the problem into a game and then leveraging the machine-learning techniques that another of the company’s AIs used to beat human players in games such as Go and chess.

The AI discovered algorithms that break decades-old records for computational efficiency, and the team’s findings, published on 5 October in Nature1, could open up new paths to faster computing in some fields.

“It is very impressive,” says Martina Seidl, a computer scientist at Johannes Kepler University in Linz, Austria. “This work demonstrates the potential of using machine learning for solving hard mathematical problems.”

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