Toggle light / dark theme

Brain organization differs between boys and girls with autism, according to a new study from the Stanford University School of Medicine.

The differences, identified by analyzing hundreds of brain scans with artificial intelligence techniques, were unique to and not found in typically developing boys and girls. The research helps explain why autism symptoms differ between the sexes and may pave the way for better diagnostics for girls, according to the scientists.

Autism is a developmental disorder with a spectrum of severity. Affected children have social and communication deficits, show restricted interests and display repetitive behaviors. The original description of autism, published in 1943 by Leo Kanner, MD, was biased toward male patients. The disorder is diagnosed in four times as many boys as girls, and most autism research has focused on males.

For the first time, researchers have created a metasurface lens that uses a piezoelectric thin film to change focal length when a small voltage is applied. Because it is extremely compact and lightweight, the new lens could be useful for portable medical diagnostic instruments, drone-based 3D mapping and other applications where miniaturization can open new possibilities.

“This type of low-power, ultra-compact varifocal lens could be used in a wide range of sensor and imaging technologies where system size, weight and cost are important,” said research project leader Christopher Dirdal from SINTEF Smart Sensors and Microsystems in Norway. “In addition, introducing precision tunability to metasurfaces opens up completely new ways to manipulate light.”

Dirdal and colleagues describe the new technology in the journal Optics Letters. To change , a voltage is applied over lead zirconate titanate (PZT) membranes causing them to deform. This, in turn, shifts the distance between two metasurface lenses.

AI may be “slightly conscious”

The Chief Scientist and Co-Founder of OpenAI, one of the leading research labs for artificial intelligence, has suggested that the latest generation of neural networks are large enough to be “slightly conscious”.

Ilya Sutskever has made several major contributions to the field of deep learning. This includes beta testing of GPT-3 prior to its release. In a 2020 paper, he and his team concluded that the language model, featuring 175 billion parameters, “can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans.”

Thank you to Wren for supporting PBS. To learn more, go to https://wren.co/start/spacetime.

PBS Member Stations rely on viewers like you. To support your local station, go to: http://to.pbs.org/DonateSPACE

Sign Up on Patreon to get access to the Space Time Discord!
https://www.patreon.com/pbsspacetime.

Objective Collapse Theories offer a explanation of quantum mechanics that is at once brand new and based in classical mechanics. In the world of quantum mechanics, it’s no big deal for particles to be in multiple different states at the same time, or to teleport between locations, or to influence each other faster than light. But somehow, none of this strangeness makes its way to the familiar scale of human beings — even though our world is made entirely of quantum-weird building blocks. The explanations of this transition range from the mystical influence of the conscious mind to the grandiose proposition of multiple realities. But Objective Collapse Theories feels as down to earth as the classical world that we’re trying to explain. Let’s see if it makes any sense.