Lifeboat Foundation

The lander and the rover, which landed on the Moon on August 23, were designed to operate for only one lunar day.

As the lunar day draws to a close, ISRO has decided to put its Chandrayaan-3 rover Pragyan in sleep mode to conserve its battery and protect it from the extreme cold of the lunar night. The rover, which has completed its assigned tasks, is now parked safely and has transmitted the data collected by its payloads to the lander, which in turn relays it to Earth.

Credits: ISRO/twitter.

Continue reading “ISRO puts Chandrayaan-3 rover in sleep mode to survive lunar night” »

A Christian who wants to see God’s will done “on earth as it is in heaven” is piloting the first lunar flight in more than 50 years.

Sriharikota (AP), September 2

ISRO on Saturday launched the country’s ambitious Solar mission, Aditya L1, eyeing history again after its successful lunar expedition, Chandrayan-3, a few days ago.

Continue reading “Moon done for India, over to the sun now as Aditya L1 lifts off successfully” »

Could you mine all the resources needed for space exploration from space itself? China reveals plans to achieve this goal by 2100.

Chinese space scientists have unveiled a preliminary roadmap that aims to establish a comprehensive space resources system spanning the solar system by the year 2100.

The ambitious initiative, named after the Ming dynasty scientist Song Yingxing’s work, “Tiangong Kaiwu” or “The Exploitation of the Works of Nature,” has the potential to transform the global space economy and elevate China’s standing in the world of space exploration, reported South China Morning Post.

NASA has released images of the site from the Moon where Russia’s Luna-25 crashed last month. It revealed that the crash site lies 400 KMS away from the intended landing site of Russia’s lunar probe. It added that the impact of the crash was such that it created a 10 meter crater on the moon. Watch for more details.

#moon #luna25 #russia #nasa #crashsite #lunarsurface #russiamoonmission #images #orbit #roscosmos.

Continue reading “Russia’s Luna-25 Creates 10M Crater After Crash On The Moon | Watch NASA’s Pics Of The Site” »

The mysterious phenomenon that Einstein once described as “spooky action at a distance” was seen as a wavefunction between two entangled photons.

Quantum physics, the realm of science that describes the Universe at the smallest scales, is known for its counter-intuitive phenomena that seem to defy every law of physics on an everyday scale.

Arguably none of the aspects of quantum physics are as surprising or as troubling as entanglement, the idea that two particles can be connected in such a way that a change to one is instantly reflected in the other, even if the two particles are at opposite sides of the Universe. It’s the word “instantly” that troubled Albert Einstein enough to describe entanglement as “spooky action at a distance”.

In what can only bode poorly for our species’ survival during the inevitable robot uprisings, an AI system has once again outperformed the people who trained it. This time, researchers at the University of Zurich in partnership with Intel, pitted their “Swift” AI piloting system against a trio of world champion drone racers — none of whom could best its top time.

Swift is the culmination of years of AI and machine learning research by the University of Zurich. In 2021, the team set an earlier iteration of the flight control algorithm that used a series of external cameras to validate its position in space in real-time, against amateur human pilots, all of whom were easily overmatched in every lap of every race during the test. That result was a milestone in its own right as, previously, self-guided drones relied on simplified physics models to continually calculate their optimum trajectory, which severely lowered their top speed.

This week’s result is another milestone, not just because the AI bested people whose job is to fly drones fast, but because it did so without the cumbersome external camera arrays= of its predecessor. The Swift system “reacts in real time to the data collected by an onboard camera, like the one used by human racers,” an UZH Zurich release reads. It uses an integrated inertial measurement unit to track acceleration and speed while an onboard neural network localizes its position in space using data from the front-facing cameras. All of that data is fed into a central control unit — itself a deep neural network — which crunches through the numbers and devises a shortest/fastest path around the track.

Watch India launch a probe to the sun and Japan attempt its first landing on the moon.

Finally reality is catching up to science fiction from the golden age and we’re seriously talking about moving industry to space and zoning the earth as residential…

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