Lifeboat Foundation

A quintillion calculations a second. That’s one with 18 zeros after it. It’s the speed at which an exascale supercomputer will process information. The Department of Energy (DOE) is preparing for the first exascale computer to be deployed in 2021. Two more will follow soon after. Yet quantum computers may be able to complete more complex calculations even faster than these up-and-coming exascale computers. But these technologies complement each other much more than they compete.

It’s going to be a while before quantum computers are ready to tackle major scientific research questions. While quantum researchers and scientists in other areas are collaborating to design quantum computers to be as effective as possible once they’re ready, that’s still a long way off. Scientists are figuring out how to build qubits for quantum computers, the very foundation of the technology. They’re establishing the most fundamental quantum algorithms that they need to do simple calculations. The hardware and algorithms need to be far enough along for coders to develop operating systems and software to do scientific research. Currently, we’re at the same point in quantum computing that scientists in the 1950s were with computers that ran on vacuum tubes. Most of us regularly carry computers in our pockets now, but it took decades to get to this level of accessibility.

In contrast, exascale computers will be ready next year. When they launch, they’ll already be five times faster than our fastest computer —Summit, at Oak Ridge National Laboratory’s Leadership Computing Facility, a DOE Office of Science user facility. Right away, they’ll be able to tackle major challenges in modeling Earth systems, analyzing genes, tracking barriers to fusion, and more. These powerful machines will allow scientists to include more variables in their equations and improve models’ accuracy. As long as we can find new ways to improve conventional computers, we’ll do it.

Many cosmologists believe that the universe’s structure is a result of quantum fluctuations that occurred during early expansion. Confirming this hypothesis, however, has proven highly challenging so far, as it is hard to discern between quantum and classical primordial fluctuations when analyzing existing cosmological data.

Two researchers at University of California and Deutsches Elektronen-Synchrotron DESY in Germany have recently devised a test based on the notion of primordial non-Gaussianity that could help to ascertain the origin of cosmic structure. In their paper, published in Physical Review Letters, they argue that detecting primordial non-Gaussanity could help to determine whether the patterns of the universe originated from quantum or classical fluctuations.

“One of the most beautiful ideas in all of science is that the structure we observed in the cosmos resulted from quantum fluctuations in the very early universe that were then stretched by a rapid accelerated expansion,” Rafael Porto, one of the researchers who carried out the study, told Phys.org. “This ‘inflationary’ paradigm makes a lot of predictions which have been corroborated by data, yet the quantum nature of the primordial seed is extremely difficult to demonstrate directly.”

NASA’s Lucy mission, led by Southwest Research Institute (SwRI), has achieved an important milestone by passing its System Integration Review and clearing the way for spacecraft assembly. This NASA Discovery Program class mission will be the first to explore Jupiter’s Trojan asteroids, ancient small bodies that share an orbit with Jupiter and hold important insights to understanding the early solar system.

The Lucy spacecraft, during its nominal 12-year mission, will fly by and collect data from seven of these primitive worlds, plus a main belt asteroid. Because the Trojan asteroids are remnants of the primordial material that formed the outer planets, they hold vital clues to deciphering the history of the solar system. Lucy, like the human fossil for which it is named, will revolutionize the understanding of our origins.

Over the last few months, the Lucy team has focused on building and testing all the components of the spacecraft, including the scientific instruments, electronics, communications and navigation systems while observing all appropriate pandemic protocols. At this review, the Lucy team demonstrated to an independent senior review board, including NASA and external experts, that the systems and subsystems are on schedule to proceed to assembly, testing and integration.

Consumers are ending up increasingly responsive about sharing their data, as data integrity and security has turned into a developing concern. In any case, with the advent of nations teching up with facial recognition, even explorers need to truly begin thinking about what sort of data they could be reluctantly offering to nations, individuals and places.

Facial recognition innovation is a framework that is fit for identifying or confirming an individual from an advanced picture or a video frame. It works by comparing chosen facial highlights and faces inside a database. The technology is utilized in security frameworks and can be compared with different biometrics, for example, fingerprint or iris recognition frameworks. As of late, it has been grabbed and utilized as a business identification and advertising tool. The vast majority have a cell phone camera fit for recognizing features to perform exercises, for example, opening said a cell phone or making payments.

The worldwide market for facial recognition cameras and programming will be worth of an expected $7.8 billion, predicts Markets and Markets. Never again consigned to sci-fi films and books, the technology is being used in various vertical markets, from helping banks recognize clients to empowering governments to look out for criminals. Let’s look at some of the top countries adopting facial recognition technology.

Circa 2011

Gravity is no obstacle for this climbing robot. It scales vertical walls—even those made of smooth materials like glass. Jeff Krahn, an engineer from Simon Fraser University in British Columbia, created this gecko-inspired tank of a robot, which he detailed in a paper in the journal Smart Materials and Structures this week.

Continue reading “A Gecko-Inspired, Wall-Climbing Tank Bot” »

A team of researchers working on the Borexino project has announced that they have observed carbon/nitrogen/oxygen (CNO) fusion neutrinos from the sun for the first time. Co-spokesman for the group, Gioacchino Ranucci, a physicist at the University of Milan, announced the observation at this year’s virtual Neutrino 2020 conference.

The Borexino solar-neutrino project is an experiment being conducted underground at Gran Sasso National Laboratories in Italy—it has been in operation since 2007. Its mission is to observe neutrinos that are emitted from the sun via two kinds of fusion reactions. The laboratory is located beneath a kilometer of rock to filter noise. Inside, it houses a huge balloon made of nylon and filled with 278 tonnes of liquid hydrocarbons surrounded by water in a tank. The temperature inside the tank is kept constant by heat exchangers and a blanket cover. Photon sensors line the tank. Neutrinos can be observed when they collide with electrons inside the balloon, creating a tiny flash. The researchers determine the characteristics of the flashes, information that can be used to isolate their source.

Researchers on the project observed neutrinos from a type of fusion reaction called a proton-proton chain back in 2012—they are believed to represent 99 percent of the energy released from the sun. Spotting neutrinos produced during CNO reactions has presented more of a challenge because there are far fewer of them. In both cases, hydrogen is fused into helium. The elements that are part of the reaction are referred to as chains because they allow such reactions to proceed. In his presentation, Ranucci, claimed that the team had “…unraveled the two processes powering the sun.”

:ooooo.

What is CAR-T therapy?

CAR-T therapy involves genetically engineering patient T-cells so that they express a chimeric antigen receptor (CAR).

Continue reading “Universal ‘One-Size-Fits-All’ Cancer Treatment” »

Just recycle the hydrogen and bring to another layer in the sun :3.

Remember the movie Sunshine, where astronomers learn that the Sun is dying? So a plucky team of astronauts take a nuclear bomb to the Sun, and try to jump-start it with a massive explosion. Yeah, there’s so much wrong in that movie that I don’t know where to start. So I just won’t.

Continue reading “How Can We Save The Sun?” »

Researchers from the Institute of Industrial Science at The University of Tokyo designed and built specialized computer hardware consisting of stacks of memory modules arranged in a 3D-spiral for artificial intelligence (AI) applications. This research may open the way for the next generation of energy-efficient AI devices.

Machine learning is a type of AI that allows computers to be trained by example data to make predictions for new instances. For example, a smart speaker algorithm like Alexa can learn to understand your voice commands, so it can understand you even when you ask for something for the first time. However, AI tends to require a great deal of electrical energy to train, which raises concerns about adding to climate change.

Now, scientists from the Institute of Industrial Science at The University of Tokyo have developed a novel design for stacking resistive random-access memory modules with oxide semiconductor (IGZO) access transistor in a three-dimensional spiral. Having on-chip nonvolatile memory placed close to the processors makes the machine learning training process much faster and more energy-efficient. This is because electrical signals have a much shorter distance to travel compared with conventional computer hardware. Stacking multiple layers of circuits is a natural step, since training the algorithm often requires many operations to be run in parallel at the same time.