Lifeboat Foundation

It’s one of the most fascinating aspects of the natural world: shapes repeat over and over. The branches of a tree extending into the sky look much the same as blood vessels extending through a human lung, if upside-down. The largest mammal, the whale, is a scaled-up version of the smallest, the shrew. Recent research even suggests the structure of the human brain resembles that of the entire universe. It’s everywhere you look, really. Nature reuses its most successful shapes.

Theoretical physicist Geoffrey West of the Santa Fe Institute in New Mexico is concerned with fundamental questions in physics, and there are few more fundamental than this one: why does nature continually reuse the same non-linear shapes and structures from the smallest scale to the very largest? In a new Big Think video (see above), West explains that the scaling laws at work are nothing less than “the generic universal mathematical and physical properties of the multiple networks that make an organism viable and allow it to develop and grow.”

Continue reading “Could a pill that lowers our body temperature make us live longer?” »

To check out any of the lectures available from Great Courses Plus go to http://ow.ly/dweH302dILJ

We’ll soon be capable of building self-replicating robots. This will not only change humanity’s future but reshape the galaxy as we know it.

Continue reading “Self-Replicating Robots and Galactic Domination | Space Time | PBS Digital Studios” »

American astrophysicists have used the Decadal Survey (DS)—also called Astro 2020 and produced by the National Academies of Science—to recommend a space telescope capable of photographing potentially habitable worlds.

The report recommends that a flagship space observatory will need a six-meter mirror to “provide an appropriate balance between scale and feasibility.”

An eight-meter aperture telescope of the scale of LUVOIR-B would be unlikely to launch before the late 2040… See more.

DeepMind is mostly known for its work in deep reinforcement learning, especially in mastering complicated games and predicting protein structures. Now, it is taking its next step in robotics research.

According to a blog post on DeepMind’s website, the company has acquired the rigid-body physics simulator MuJoCo and has made it freely available to the research community. MuJoCo is now one of several open-source platforms for training artificial intelligence agents used in robotics applications. Its free availability will have a positive impact on the work of scientists who are struggling with the costs of robotics research. It can also be an important factor for DeepMind’s future, both as a science lab seeking artificial general intelligence and as a business unit of one of the largest tech companies in the world.

Continue reading “DeepMind takes next step in robotics research” »

Something is killing-off galaxies by preventing the birth of stars—and astronomers now think they know why.

While studying 51 galaxies in a “galaxy-cluster” called the Virgo Cluster an international team of scientists have found that molecular gas—the fuel for new stars—is being “swept away by a huge cosmic broom.”

Exactly what is preventing nearby galaxies from birthing new stars has been a long-standing mystery in astrophysics. The new paper, now available online, blames the extreme environment of the Virgo Cluster. It’s been accepted by the journal Astrophysical Journal Supplement Series.

#eldddir #eldddir_space #eldddir_homo #eldddir_future #eldddir_tech #eldddir_jupiter #eldddir_rockets.

A clearer understanding of how a type of brain cell known as astrocytes function and can be emulated in the physics of hardware devices, may result in artificial intelligence (AI) and machine learning that autonomously self-repairs and consumes much less energy than the technologies currently do, according to a team of Penn State researchers.

Astrocytes are named for their star shape and are a type of glial cell, which are support cells for neurons in the brain. They play a crucial role in brain functions such as memory, learning, self-repair and synchronization.

“This project stemmed from recent observations in computational neuroscience, as there has been a lot of effort and understanding of how the brain works and people are trying to revise the model of simplistic neuron-synapse connections,” said Abhronil Sengupta, assistant professor of electrical engineering and computer science. “It turns out there is a third component in the brain, the astrocytes, which constitutes a significant section of the cells in the brain, but its role in machine learning and neuroscience has kind of been overlooked.”

An international team of astrophysicists from South Africa, the UK, France and the US have found large variations in the brightness of light seen from around one of the closest black holes in our Galaxy, 9,600 light-years from Earth, which they conclude is caused by a huge warp in its accretion disc.

This object, MAXI J1820+070, erupted as a new X-ray transient in March 2018 and was discovered by a Japanese X-ray telescope onboard the International Space Station. These transients, systems that exhibit violent outbursts, are binary stars, consisting of a low-mass star, similar to our Sun and a much more compact object, which can be a white dwarf 0 neutron star 0 or black hole. In this case, MAXI J1820+070 contains a black hole that is at least 8 times the mass of our Sun.

The first findings have now been published in the international highly ranked journal, Monthly Notices of the Royal Astronomical Society, whose lead author is Dr. Jessymol Thomas, a Postdoctoral Research Fellow at the South African Astronomical Observatory (SAAO).

The authors present a high-resolution palaeomagnetic record for a Late Cretaceous limestone in Italy. They claim that their record robustly shows a ~12° true polar wander oscillation between 86 and 78 Ma, with the greatest excursion at 84–82 Ma.

The authors propose a new framework, deep evolutionary reinforcement learning, evolves agents with diverse morphologies to learn hard locomotion and manipulation tasks in complex environments, and reveals insights into relations between environmental physics, embodied intelligence, and the evolution of rapid learning.