Lifeboat Foundation: Safeguarding Humanity
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In recent years, roboticists have developed a wide variety of robotic systems with different body structures and capabilities. Most of these robots are either made of hard materials, such as metals, or soft materials, such as silicon and rubbery materials.

Researchers at Hong Kong University (HKU) and Lawrence Berkeley National Laboratory have recently created Aquabots, a new class of soft robots that are predominantly made of liquids. As most are predominantly made up of water or other , the new robots, introduced in a paper published in ACS Nano, could have highly valuable biomedical and environmental applications.

“We have been engaged in the development of adaptive interfacial assemblies of materials at the oil-water and water-water interface using nanoparticles and polyelectrolytes,” Ho Cheung (Anderson) Shum, Thomas P. Russell, and Shipei Zhu told TechXplore via email. “Our idea was to assemble the materials that the interface and the assemblies lock in the shapes of the liquids. The shapes are dictated using external forces to generate arbitrary shapes or to use all-liquid 3D printing to be able to spatially organize the assemblies.”

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Lastly, there is the concern that this is all whimsically unimportant, or worse, an obtuse disregard for more prosaic societal concerns. Some people may find debates of this sort to be pedantic and even snobbish, given the justified concern that advanced futuristic technologies are likely to benefit wealthy elites long before they trickle down to the masses. Worse, some people may expect that such technologies are likely impossible and that such metaphysical navelgazing is an ivory tower distraction in a world of real problems and challenges. To that reaction I say the importance is not necessarily in determining the prospects of technological and medical marvels that reside far in the future, if ever. The more relevant issue, and the reason I have committed so much of my life to contemplating and writing about these questions, is that we profoundly desire the most accurate model possible of reality and understanding of the human condition. Ultimately, we want to understand ourselves as conscious beings in the universe and to understand the nature of our existence. That is the real issue here, at least for me.

About the author

Keith Wiley is on the board of Carboncopies.org and is a fellow with The Brain Preservation Foundation. He holds a PhD in computer science from the University of New Mexico and works as a data scientist in Seattle, Washington. His book, A Taxonomy and Metaphysics of Mind-Uploading, is available on Amazon (https://www.amazon.com/dp/0692279849?tag=lifeboatfound-20?tag=lifeboatfound-20). His other writings, interviews, and videos about mind uploading are available on his website at http://keithwiley.com and elsewhere on the web.

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Unlike the plethora of high-res cosmic photography we’ve been blessed with this year, this breathtaking snap doesn’t come from the James Webb telescope but instead, it comes from two astrophotographers who met each other on Reddit.

Stargazers Andrew McCarthy and Connor Matherne first connected on Reddit and then Instagram several years ago after becoming mutual fans of each other’s work.

McCarthy is renowned in his field for his incredibly detailed photographs, taking tens of thousands of photos and stitching them together in a ‘mosaic’ fashion to create incredibly detailed and precise images of his subjects.

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Most materials—from rubber bands to steel beams—thin out as they are stretched, but engineers can use origami’s interlocking ridges and precise folds to reverse this tendency and build devices that grow wider as they are pulled apart.

Researchers increasingly use this kind of technique, drawn from the ancient art of , to design spacecraft components, medical robots and antenna arrays. However, much of the work has progressed via instinct and trial and error. Now, researchers from Princeton Engineering and Georgia Tech have developed a general formula that analyzes how structures can be configured to thin, remain unaffected, or thicken as they are stretched, pushed or bent.

Kon-Well Wang, a professor of mechanical engineering at the University of Michigan who was not involved in the research, called the work “elegant and extremely intriguing.”

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Summary: A new robotic system can learn directly from human interaction videos and generalize the information at the task being completed. This makes the robot well suited to learn household chores effectively and efficiently.

Source: Carnegie Mellon University.

The robot watched as Shikhar Bahl opened the refrigerator door. It recorded his movements, the swing of the door, the location of the fridge and more, analyzing this data and readying itself to mimic what Bahl had done.

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