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Scientists from Scripps Research and Los Alamos National Laboratory have devised a method for mapping in unprecedented detail the thickets of slippery sugar molecules that help shield HIV from the immune system.

Mapping these shields will give researchers a more complete understanding of why antibodies react to some spots on the virus but not others, and may shape the design of new vaccines that target the most vulnerable and accessible sites on HIV and other viruses.

The sugar molecules, or “glycans,” are loose and stringy, and function as shields because they are difficult for antibodies to grip and block access to the . The shields form on the outermost spike proteins of HIV and many other viruses, including SARS-CoV-2, the coronavirus that causes COVID-19, because these viruses have evolved sites on their spike proteins where glycan molecules—normally abundant in cells—will automatically attach.

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Ultra high-res displays for gadgets and tv sets may be coming. 😃

By expanding on existing designs for electrodes of ultra-thin solar panels, Stanford researchers and collaborators in Korea have developed a new architecture for OLED—organic light-emitting diode—displays that could enable televisions, smartphones and virtual or augmented reality devices with resolutions of up to 10,000 pixels per inch (PPI). (For comparison, the resolutions of new smartphones are around 400 to 500 PPI.)

Such high-pixel-density displays will be able to provide stunning images with true-to-life detail—something that will be even more important for headset displays designed to sit just centimeters from our faces.

The advance is based on research by Stanford University materials scientist Mark Brongersma in collaboration with the Samsung Advanced Institute of Technology (SAIT). Brongersma was initially put on this research path because he wanted to create an ultra-thin solar panel design.

Continue reading “Scientists borrow solar panel tech to create new ultrahigh-res OLED display” | >

But Silicon Valley is not the home of ingenuity for nothing. When the pandemic hit, many start-up engineers in the area, like Dr. Wessells, moved their gear into their home garages so they could keep innovating. And if it wasn’t the garage, then it was the living room.

Labs closed in the pandemic, but innovation doesn’t stop. So while some workers have the home office, engineers have the garage.

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GE unveils its largest wind turbine prototype yet, a 13MW behemoth that stands 248 metres tall and destined for use in offshore wind farms.

Wind turbine manufacturer GE Renewable Energy has unveiled latest wind turbine prototype, an optimised version of its Halifax-X offshore wind turbine design that can deliver a massive 13MW of output.

It is the largest turbine that GE has produced, standing 248 metres tall, with 107 metre long blades and offers around double the generation capacity of most wind turbines currently deployed around the world.

GE said that a working version of the wind turbine, optimised for offshore projects, had been deployed and was currently undergoing a series of tests to satisfy the requirements for certification.

Continue reading “GE starts testing world’s biggest 13MW offshore wind turbine” | >

Moving from one-algorithm to one-brain is one of the biggest open challenges in AI. A one-brain AI would still not be a true intelligence, only a better general-purpose AI—Legg’s multi-tool. But whether they’re shooting for AGI or not, researchers agree that today’s systems need to be made more general-purpose, and for those who do have AGI as the goal, a general-purpose AI is a necessary first step.

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Humans regularly tackle and solve a variety of complex visuospatial problems. In contrast, most machine learning and computer vision techniques developed so far are designed to solve individual tasks, rather than applying a set of capabilities to any task they are presented with.

Researchers at York University in Canada have been trying to better understand the mechanisms that allow humans to actively observe their environment and solve the wide range perception tasks that they encounter every day, with the hope of informing the development of more sophisticated computer vision systems. In a paper pre-published on arXiv, they presented a new experimental setup called PESAO (psychophysical experimental setup for active observers), which is specifically designed to investigate how humans actively observe the world around them and engage with it.

“The hallmark of human vision is its generality,” Prof. John K. Tsotsos, one of the researchers who carried out the study, told TechXplore. “The same brain and allow one to play tennis, drive a car, perform surgery, view photo albums, read a book, gaze into your loved one’s eyes, go online shopping, solve 1000-piece jigsaw puzzles, find lost keys, chase after his/her young daughter when she appears in danger and so much more. The reality is that as incredible as AI successes have been so far, it is humbling to acknowledge how far there still is to go.”

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A pair of statisticians at the University of Waterloo has proposed a math process idea that might allow for teaching AI systems without the need for a large dataset. Ilia Sucholutsky and Matthias Schonlau have written a paper describing their idea and published it on the arXiv preprint server.

Artificial intelligence (AI) applications have been the subject of much research lately, with the development of , researchers in a wide range of fields began finding uses for it, including creating deepfake videos, board game applications and medical diagnostics.

Deep learning networks require large datasets in order to detect patterns revealing how to perform a given task, such as picking a certain face out of a crowd. In this new effort, the researchers wondered if there might be a way to reduce the size of the dataset. They noted that children only need to see a couple of pictures of an animal to recognize other examples. Being statisticians, they wondered if there might be a way to use mathematics to solve the problem.

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