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Scientists build mass-producible miniature quantum memory element

Light pulses can be stored and retrieved in the glass cell, which is filled with rubidium atoms and is only a few millimeters in size.

Light particles are particularly suited to transmitting quantum information.

Researchers at the University of Basel have built a quantum memory element based on atoms in a tiny glass cell. In the future, such quantum memories could be mass-produced on a wafer.

It is hard to imagine our lives without networks such as the internet or mobile phone networks. In the future, similar networks are planned for that will enable the tap-proof transmission of messages using and make it possible to connect quantum computers to each other.

Like their conventional counterparts, such quantum networks require memory elements in which information can be temporarily stored and routed as needed. A team of researchers at the University of Basel led by Professor Philipp Treutlein has now developed such a memory element, which can be micro-fabricated and is, therefore, suitable for mass production. Their results were published in Physical Review Letters.

500-mile Tesla Semi starts delivery, features 1-megawatt charging

Tesla late on Thursday started customer deliveries of its semi-trailer truck, which is dubbed the Semi.

The first customer was Pepsi, which placed an order for 100 of the Class 8 trucks following the debut in 2017. Budweiser and Walmart are among the other customers for the fully electric semi truck which features a central driving position, just like the McLaren F1 supercar.

Mysterious Missing Component in the Clouds of Venus Revealed

Researchers may have identified the missing component in the chemistry of the Venusian clouds that would explain their color and splotchiness in the UV range, solving a long-standing mystery.

What are the clouds of Venus made of? Scientists know it’s mainly made of sulfuric acid droplets, with some water, chlorine, and iron. Their concentrations vary with height in the thick and hostile Venusian atmosphere. But until now they have been unable to identify the missing component that would explain the clouds’ patches and streaks, only visible in the UV range.

In a new study published in Science Advances, researchers from the University of Cambridge synthesised iron-bearing sulfate minerals that are stable under the harsh chemical conditions in the Venusian clouds.

Researchers Identify why Cancer Immunotherapy can cause Colitis

The findings are published in Science.

“This is a good example of how understanding a mechanism helps you to develop an alternative therapy that’s more beneficial. Once we identified the mechanism causing the colitis, we could then develop ways to overcome this problem and prevent colitis while preserving the anti-tumor effect,” said senior study author Gabriel Nunez, M.D., Paul de Kruif Professor of Pathology at Michigan Medicine.

Redefining Brain Function: Physicists Overturn Long-Standing Assumptions

Recent research suggests that a number of neuronal characteristics, traditionally believed to stem from the cell body or soma, may actually originate from processes in the dendrites. This discovery has significant implications for the study of degenerative diseases and for understanding the different states of brain activity during sleep and wakefulness.

The brain is an intricate network comprising billions of neurons. Each neuron’s cell body, or soma, engages in simultaneous communication with thousands of other neurons through its synapses. These synapses act as links, facilitating the exchange of information. Additionally, each neuron receives incoming signals through its dendritic trees, which are highly branched and extend for great lengths, resembling the structure of a complex and vast arboreal network.

For the last 75 years, a core hypothesis of neuroscience has been that the basic computational element of the brain is the neuronal soma, where the long and ramified dendritic trees are only cables that enable them to collect incoming signals from its thousands of connecting neurons. This long-lasting hypothesis has now been called into question.

BrainChip demonstrates its neuromorphic processor on Microchip’s 32-bit MPU at CES 2024

BrainChip, a neuromorphic computing device provider, will present a demonstration featuring its Akida neuromorphic processor operating on Microchips’ embedded platform at CES 2024. This will utilize two evaluation boards, namely Microchip’s SAMv71 Ultra board and SAMA7G54-EK board, with a particular focus on showcasing the efficiency of the Akida neuromorphic processor when integrated with a 32-bit microprocessor unit. BrainChip aims to highlight its capabilities in always-on machine learning tasks, including keyword spotting and visual wake words.

“We look forward to demonstrating the potential and ease of integrating Akida for always-on machine learning applications on embedded devices at CES,” says Rob Telson, vice president of Ecosystem and Partnerships at BrainChip.

Neuromorphic computing systems are designed to execute parallel and distributed processing, mimicking the neural structure and functioning of the human brain. BrainChip Akida is an example of such a neuromorphic computing processor, which is designed for edge applications. It operates on an event-based principle, remaining dormant until activated, thereby reducing power consumption.

Google Scientists Discovered 380,000 New Materials Using Artificial Intelligence

New advancements in technology frequently necessitate the development of novel materials – and thanks to supercomputers and advanced simulations, researchers can bypass the time-consuming and often inefficient process of trial-and-error.

The Materials Project, an open-access database founded at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) in 2011, computes the properties of both known and predicted materials. Researchers can focus on promising materials for future technologies – think lighter alloys that improve fuel economy in cars, more efficient solar cells to boost renewable energy, or faster transistors for the next generation of computers.