Lifeboat Foundation

Tesla CEO Elon Musk came out some days ago to try to make a few things clear. He gave an explanation to why the Cybertruck has been postponed so many times, especially why it’s so difficult to produce new cars. In the list of Teslas postponed new vehicles is the Cybertruck, and Tesla s, and we could also include the tesla roadster which has also been postponed so many times seeing as it’s going to be coming with a completely new design from its predecessor. Let’s get into More detail on Elons reason for postponing the launch of these vehicles so much.

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Parkland Corp. is moving to pause its refinery processing operations in Burnaby, B.C., due to a lack of crude oil supply from the Trans Mountain pipeline, which has been shut down as a precaution due to the flooding in B.C.

The company says it plans to maintain the refinery, which is a key source of gasoline for the Vancouver area, on standby mode so that it can resume processing quickly.

“We are maintaining the refinery in ready-mode…which positions us to recommence processing once sufficient crude oil feedstocks become available”, Ryan Krogmeier, Parkland’s senior vice-president of refining, said in a statement.

Artificial neural networks are famously inspired by their biological counterparts. Yet compared to human brains, these algorithms are highly simplified, even “cartoonish.”

Can they teach us anything about how the brain works?

For a panel at the Society for Neuroscience annual meeting this month, the answer is yes. Deep learning wasn’t meant to model the brain. In fact, it contains elements that are biologically improbable, if not utterly impossible. But that’s not the point, argues the panel. By studying how deep learning algorithms perform, we can distill high-level theories for the brain’s processes—inspirations to be further tested in the lab.

Researchers at a Seattle A.I. lab say they have built a system that makes ethical judgments. But its judgments can be as confusing as those of humans.

Most human diseases can be traced to malfunctioning parts of a cell—a tumor is able to grow because a gene wasn’t accurately translated into a particular protein or a metabolic disease arises because mitochondria aren’t firing properly, for example. But to understand what parts of a cell can go wrong in a disease, scientists first need to have a complete list of parts.

By combining microscopy, biochemistry techniques and artificial intelligence, researchers at University of California San Diego School of Medicine and collaborators have taken what they think may turn out to be a significant leap forward in the understanding of human cells.

The technique, known as Multi-Scale Integrated Cell (MuSIC), is described November 24, 2021 in Nature.

Neutrinos may be the key to finally solving a mystery of the origins of our matter-dominated universe, and preparations for two major, billion-dollar experiments are underway to reveal the particles’ secrets. Now, a team of nuclear physicists have turned to the humble electron to provide insight for how these experiments can better prepare to capture critical information. Their research, which was carried out at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility and recently published in Nature, reveals that major updates to neutrino models are needed for the experiments to achieve high-precision results.

Neutrinos are ubiquitous, generated in copious numbers by stars throughout our universe. Though prevalent, these shy particles rarely interact with matter, making them very difficult to study.

“There is this phenomenon of neutrinos changing from one type to another, and this phenomenon is called neutrino oscillation. It’s interesting to study this phenomenon, because it is not well understood,” said Mariana Khachatryan, a co-lead author on the study who was a graduate student at Old Dominion University in Professor and Eminent Scholar Larry Weinstein’s research group when she contributed to the research. She is now a postdoctoral research associate at Florida International University.

NASA on Tuesday night successfully launched its experimental asteroid deflecting spacecraft which is set to smash into an asteroid at 15,000 miles per hour and serve as a test run for countering any future doomsday scenario where a large space rock could end up on a collision course with the Earth.

KEY FACTS The Double Asteroid Redirection Test (DART), developed by NASA and the European Space Agency (ESA) launched from California’s Vandenberg Space Force Base at around 10.20 a.m. local time Tuesday, aboard SpaceX’s reusable Falcon 9 rocket.

Sometime in 2022, the DART spacecraft is expected to smash into the asteroid Dimorphos which orbits a larger satellite called Didymos—neither of which pose a threat to Earth at the moment—with the hope of deflecting its course.

Have you seen C/2021 A1 (Leonard) —a.k.a. “Comet Leonard”—yet? Discovered on January 3, 2021 by Greg Leonard, a senior research specialist at Arizona’s Mount Lemmon Observatory, Comet Leonard is potentially going to become an object visible to binocular and even naked eyes. It’s predicted to reach around magnitude 4 or brighter in December 2021 (for the latest, follow it on Twitter).

It will get closest to the Earth to be super-bright on December 12, 2021, but by then it’s going to be fairly low in the sky. So your best chance is to get up early—about 90 minutes before sunrise—during early December and look east.

Arm yourself with either a small telescope or any pair of binoculars to maximize your chances.

A rare 54-page manuscript featuring preliminary calculations for Albert Einstein’s general theory of relativity sold for about $13 million at auction in Paris Tuesday to an unknown buyer — almost four times more than expected.

It was originally anticipated to fetch $3.5 million.

Auction house Christie’s declined to identify the winning bidder to NBC News.

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