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Canadian startup Xanadu says their quantum computer is cloud-accessible, Python programmable, and ready to scale.

Quantum computers based on photons may have some advantages over electron-based machines, including operating at room temperature and not temperatures colder than that of deep space. Now, say scientists at quantum computing startup Xanadu, add one more advantage to the photon side of the ledger. Their photonic quantum computer, they say, could scale up to rival or even beat the fastest classical supercomputers—at least at some tasks.

Whereas conventional computers switch transistors either on or off to symbolize data as ones and zeroes, quantum computers use quantum bits or “qubits” that, because of the bizarre nature of quantum physics, can exist in a state known as superposition where they can act as both 1 and 0. This essentially lets each qubit perform multiple calculations at once.

Continue reading “In the Race to Hundreds of Qubits, Photons May Have “Quantum Advantage”” | >

Researchers in the UK have developed a way to coax microscopic particles and droplets into precise patterns by harnessing the power of sound in air. The implications for printing, especially in the fields of medicine and electronics, are far-reaching.

The scientists from the Universities of Bath and Bristol have shown that it’s possible to create precise, pre-determined patterns on surfaces from aerosol droplets or particles, using computer-controlled ultrasound. A paper describing the entirely new technique, called ‘sonolithography’, is published in Advanced Materials Technologies.

Professor Mike Fraser from the Department of Computer Science at the University of Bath, explained: “The power of ultrasound has already been shown to levitate small particles. We are excited to have hugely expanded the range of applications by patterning dense clouds of material in air at scale and being able to algorithmically control how the material settles into shapes.”

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SB Acharyya.

This is correct https://www.frontiersin.org/…/10…/fnhum.2010.00224/

Sesame seed-size brains created from a mix of human and Neanderthal genes lived briefly in petri dishes in a University of California, San Diego laboratory, offering tantalizing clues as to how the organs have evolved over millennia.

Scientists have long wondered how human beings evolved to have such big, complex brains. One way to figure that out is by comparing modern genes involved in brain development with those found in our ancient cousins. Though scientists have found plenty of fossilized remains from Neanderthals — cousins of modern humans that died out about 37000 years ago — they have yet to find a preserved Neanderthal brain. To bridge that gap in knowledge, a research team grew tiny, unconscious “minibrains” in petri dishes. Some of the brains were grown using standard human genes, and others were altered using the gene-editing tool CRISPR to have a brain development gene taken from Neanderthal remains.

Continue reading “Scientists grow human-Neanderthal hybrid ‘minibrains’ in petri dishes” | >

SFU-led research team uncovers how fossil dragonfly relatives have been misclassified due to their striking similarity.

For more than 150 years, scientists have been incorrectly classifying a group of fossil insects as damselflies, the familiar cousins of dragonflies that flit around wetlands eating mosquitoes. While they are strikingly similar, these fossils have oddly shaped heads, which researchers have always attributed to distortion resulting from the fossilization process.

Now, however, a team of researchers led by Simon Fraser University (SFU) paleontologist Bruce Archibald has discovered they aren’t damselflies at all, but represent a major new insect group closely related to them.

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Recently published neuroimaging research provides evidence that the directional connectivity between several brain regions plays an important role in emotional processing abilities.

Although interest in emotional intelligence has been steadily growing since the 1990s, the underlying neural mechanisms behind it have yet to be clearly established. The new study, which appears in NeuroImage, is part of a process to begin to fill in this gap in scientific knowledge.

“Emotional intelligence is one of the least studied topics, especially in conjunction with cutting-edge computational neuroimaging techniques,” explained lead researcher Sahil Bajaj, the director of the Multimodal Clinical Neuroimaging Laboratory at Boys Town National Research Hospital.

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Today, machine learning permeates everyday life, with millions of users every day unlocking their phones through facial recognition or passing through AI-enabled automated security checks at airports and train stations. These tasks are possible thanks to sensors that collect optical information and feed it to a neural network in a computer.

Scientists in China have presented a new nanoscale AI trained to perform unpowered all-optical inference at the speed of light for enhanced authentication solutions. Combining smart optical devices with imaging sensors, the system performs complex functions easily, achieving a neural density equal to 1/400th that of the human brain and a more than 10 orders of magnitude higher than electronic processors.

Imagine empowering the sensors in everyday devices to perform artificial intelligence functions without a computer—as simply as putting glasses on them. The integrated holographic perceptrons developed by the research team at University of Shanghai for Science and Technology led by Professor Min Gu, a foreign member of the Chinese Academy of Engineering, can make that a reality. In the future, its neural density is expected to be 10 times that of human brain.

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China laid out seven “frontier” technologies in its 14th Five Year Plan. These are areas that China will focus research on and include semiconductors and brain-computer fusion.

Yuichiro chino | moment | getty images.

However, such work is already underway in the U.S. at Elon Musk’s company Neuralink. Musk is working on implantable brain-chip interfaces to connect humans and computers.

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