Lifeboat Foundation

For the first time ever, scientists have successfully grown plants in soil from the Moon.

Researchers from the University of Florida planted seeds from the Arabidopsis plant — commonly known as thale cress — into a few teaspoons worth of lunar soil collected in the late 60s and early 70s during the Apollo 11, 12 and 17 missions.

After about a week of watering and feeding, the seeds grew into and out of the soil, or lunar regolith, according to a paper detailing the experiment published Thursday in the scientific journal “Communications Biology.”

Researchers have used a widespread species of blue-green algae to power a microprocessor continuously for a year—and counting—using nothing but ambient light and water. Their system has potential as a reliable and renewable way to power small devices.

The system, comparable in size to an AA battery, contains a type of non-toxic algae called Synechocystis that naturally harvests energy from the sun through photosynthesis. The tiny electrical current this generates then interacts with an aluminum electrode and is used to power a microprocessor.

The system is made of common, inexpensive and largely recyclable materials. This means it could easily be replicated hundreds of thousands of times to power large numbers of small devices as part of the Internet of Things. The researchers say it is likely to be most useful in off-grid situations or remote locations, where small amounts of power can be very beneficial.

A new method of carbon capture is being developed using microalgae grown in open-air, pond-based systems on coastal desert land. This can be achieved without the need for fresh water.

Less than a millionth of a billionth of a second long, attosecond X-ray pulses allow researchers to peer deep inside molecules and follow electrons as they zip around and ultimately initiate chemical reactions.

Scientists at the Department of Energy’s SLAC National Accelerator Laboratory devised a method to generate X-ray laser bursts lasting hundreds of attoseconds (or billionths of a billionth of a second) in 2018. This technique, known as X-ray laser-enhanced attosecond pulse generation (XLEAP), enables researchers to investigate how electrons racing about molecules initiate key processes in biology, chemistry, materials science, and other fields.

“Electron motion is an important process by which nature can move energy around,” says SLAC scientist James Cryan. “A charge is created in one part of a molecule and it transfers to another part of the molecule, potentially kicking off a chemical reaction. It’s an important piece of the puzzle when you start to think about photovoltaic devices for artificial photosynthesis, or charge transfer inside a molecule.”

Artificial intelligence and machine learning hardware research have concentrated on building photonic synapses and neurons and combining them to do fundamental forms of neural-type processing. However, complex processing methods found in human brains—such as reinforcement learning and dendritic computation—are more challenging to replicate directly in hardware.

A new study contributes to closing the “hardware gap” by creating an “Optomemristor” device that responds to numerous electronic and photonic inputs at the same time. The diverse biophysical mechanisms that govern the functions of the brain’s neurons and synapses allow for complex learning and processing in the mammalian brain.

The chalcogenide thin-film technology interacts with both light and electrical impulses to mimic multifactor biological computations in mammalian brains while spending very little energy.

Would start with scanning and reverse engineering brains of rats, crows, pigs, chimps, and end on the human brain. Aim for completion by 12/31/2025. Set up teams to run brain scans 24÷7÷365 if we need to, and partner w/ every major neuroscience lab in the world.

If artificial intelligence is intended to resemble a brain, with networks of artificial neurons substituting for real cells, then what would happen if you compared the activities in deep learning algorithms to those in a human brain? Last week, researchers from Meta AI announced that they would be partnering with neuroimaging center Neurospin (CEA) and INRIA to try to do just that.

Through this collaboration, they’re planning to analyze human brain activity and deep learning algorithms trained on language or speech tasks in response to the same written or spoken texts. In theory, it could decode both how human brains —and artificial brains—find meaning in language.

Continue reading “Meta wants to improve its AI” »

“The Earth has entered a radically new era, understood by scientists as the Anthropocene: a time when humanity reckons with massive geologic and biospheric forces we, as anthropos, have set in motion. The agency of Nature and the reality of humanity as a collective geologic force is becoming understood differently, even within the Western paradigm. It is a new world our children will inherit, for if humanity is to survive, we must come into new realizations of our place within the planetary life-support systems. To lay a path for future generations through the evolutionary steps that humanity must now take to learn to live in balance with the planet, science must come to balance with Spirit.” ―Oberon Zell, GaeaGenesis.

#OberonZell #GaeaGenesis #GaiaHypothesis #SyntellectHypothesis #GlobalMind #theosophy #consciousness

In the early 1970s, celebrated philosopher and mystic Oberon Zell was the first to propose the radical idea that the biosphere of Earth was a single living superorganism. His initial article on the subject electrified the emerging modern movement of Earth-based spirituality, generating volumes of correspondence, lecture tours, and further articles in various journals and books.

Continue reading “Gaia-Based Theosophy: Conception and Birth of the Living Earth” »

For years, the brain has been thought of as a biological computer that processes information through traditional circuits, whereby data zips straight from one cell to another. While that model is still accurate, a new study led by Salk Professor Thomas Albright and Staff Scientist Sergei Gepshtein shows that there’s also a second, very different way that the brain parses information: through the interactions of waves of neural activity. The findings, published in Science Advances on April 22, 2022, help researchers better understand how the brain processes information.

“We now have a new understanding of how the computational machinery of the brain is working,” says Albright, the Conrad T. Prebys Chair in Vision Research and director of Salk’s Vision Center Laboratory. “The model helps explain how the brain’s underlying state can change, affecting people’s attention, focus, or ability to process information.”

Researchers have long known that waves of electrical activity exist in the brain, both during sleep and wakefulness. But the underlying theories as to how the brain processes information—particularly sensory information, like the sight of a light or the sound of a bell—have revolved around information being detected by specialized brain cells and then shuttled from one neuron to the next like a relay.

Last week, NASA’s Perseverance Rover captured a gorgeous view of Phobos eclipsing the Sun, from the surface of Mars. From the point of view of any Martian microbes lurking out there, the eclipse may have seemed more ominous (yeah ok, there might not be living organisms up there, let alone ones sentient enough to grasp the concept of an eclipse) as the moon is destined by physics to one day slam into the red planet.

Phobos – the closest of Mars’ two moons – is set to get ever closer to the planet, before its final descent, while Deimos will drift ever outwards until it leaves Mars’ orbit.