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Epic Games announces Unreal Engine 5 with stunning PlayStation 5 demo

Epic Games announces Unreal Engine 5 with stunning PlayStation 5 demo | Design, Comm, Sci and Tech | Scoop.it
Epic Games revealed its new game engine, the Unreal Engine 5, on Wednesday, showcasing its capabilities with a breathtaking PlayStation 5 demo. Epic says the engine will release in 2021, and developers will be able to move projects from UE4 to UE5 and take advantage of next-gen optimization for PS5 and Xbox Series X titles.
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Zebra finches can rapidly memorize the signature sounds of at least 50 different members of their flock

Zebra finches can rapidly memorize the signature sounds of at least 50 different members of their flock | Design, Comm, Sci and Tech | Scoop.it

If songbirds could appear on "The Masked Singer" reality TV competition, zebra finches would likely steal the show. That's because they can rapidly memorize the signature sounds of at least 50 different members of their flock, according to new research from the University of California, Berkeley.

 

In recent findings published in the journal Science Advances, these boisterous, red-beaked songbirds, known as zebra finches, have been shown to pick one another out of a crowd (or flock) based on a particular peer's distinct song or contact call. Like humans who can instantly tell which friend or relative is calling by the timbre of the person's voice, zebra finches have a near-human capacity for language mapping. Moreover, they can remember each other's unique vocalizations for months and perhaps longer, the findings suggest.

 

"The amazing auditory memory of zebra finches shows that birds' brains are highly adapted for sophisticated social communication," said study lead author Frederic Theunissen, a UC Berkeley professor of psychology, integrative biology and neuroscience. Theunissen and fellow researchers sought to gauge the scope and magnitude of zebra finches' ability to identify their feathered peers based purely on their unique sounds. As a result, they found that the birds, which mate for life, performed even better than anticipated.

 

"For animals, the ability to recognize the source and meaning of a cohort member's call requires complex mapping skills, and this is something zebra finches have clearly mastered," Theunissen said.

A pioneer in the study of bird and human auditory communication for at least two decades, Theunissen acquired a fascination and admiration for the communication skills of zebra finches through his collaboration with UC Berkeley postdoctoral fellow Julie Elie, a neuroethologist who has studied zebra finches in the forests of their native Australia. Their teamwork yielded groundbreaking findings about the communication skills of zebra finches.

 

Zebra finches usually travel around in colonies of 50 to 100 birds, flying apart and then coming back together. Their songs are typically mating calls, while their distance or contact calls are used to identify where they are, or to locate one another. "They have what we call a 'fusion fission' society, where they split up and then come back together," Theunissen said. "They don't want to separate from the flock, and so, if one of them gets lost, they might call out 'Hey, Ted, we're right here.' Or, if one of them is sitting in a nest while the other is foraging, one might call out to ask if it's safe to return to the nest."

Read the full article at: www.sciencedaily.com


Via Dr. Stefan Gruenwald
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AI model detects asymptomatic Covid-19 infections through cellphone-recorded coughs

AI model detects asymptomatic Covid-19 infections through cellphone-recorded coughs | Design, Comm, Sci and Tech | Scoop.it

An artificial intelligence model can detect people who are asymptomatic with Covid-19, through cellphone-recorded coughs. The work was led by Brian Subirana and colleagues at the MIT Auto-ID Lab.

 

Asymptomatic people who are infected with Covid-19 exhibit, by definition, no discernible physical symptoms of the disease. They are thus less likely to seek out testing for the virus, and could unknowingly spread the infection to others. But it seems those who are asymptomatic may not be entirely free of changes wrought by the virus. MIT researchers have now found that people who are asymptomatic may differ from healthy individuals in the way that they cough. These differences are not decipherable to the human ear. But it turns out that they can be picked up by artificial intelligence.

 

In a paper published recently in the IEEE Journal of Engineering in Medicine and Biology, the team reports on an AI model that distinguishes asymptomatic people from healthy individuals through forced-cough recordings, which people voluntarily submitted through web browsers and devices such as cellphones and laptops. The researchers trained the model on tens of thousands of samples of coughs, as well as spoken words. When they fed the model new cough recordings, it accurately identified 98.5 percent of coughs from people who were confirmed to have Covid-19, including 100 percent of coughs from asymptomatics — who reported they did not have symptoms but had tested positive for the virus.

 

The team is now working on incorporating the model into a user-friendly app, which if FDA-approved and adopted on a large scale could potentially be a free, convenient, noninvasive prescreening tool to identify people who are likely to be asymptomatic for Covid-19. A user could log in daily, cough into their phone, and instantly get information on whether they might be infected and therefore should confirm with a formal test. “The effective implementation of this group diagnostic tool could diminish the spread of the pandemic if everyone uses it before going to a classroom, a factory, or a restaurant,” says co-author Brian Subirana, a research scientist in MIT’s Auto-ID Laboratory.

Read the full article at: news.mit.edu


Via Dr. Stefan Gruenwald
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