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Have you wondered will Chat GPT 4 replace programmers? Chat GPT is powerful, but I don’t believe it will replace software engineers any time soon. 😃

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For decades, electronics engineers have been trying to develop increasingly advanced devices that can perform complex computations faster and consuming less energy. This has become even more salient after the advent of artificial intelligence (AI) and deep learning algorithms, which typically have substantial requirements both in terms of data storage and computational load.

A promising approach for running these algorithms is known as analog in-memory computing (AIMC). As suggested by its name, this approach consists of developing electronics that can perform computations and store data on a . To realistically achieve both improvements in speed and energy consumption, this approach should ideally also support on-chip digital operations and communications.

Researchers at IBM Research Europe recently developed a new 64-core mixed-signal in-memory computing chip based on phase-change memory devices that could better support the computations of deep neural networks. Their 64-core chip, presented in a paper in Nature Electronics, has so far attained highly promising results, retaining the accuracy of deep learning algorithms, while reducing computation times and energy consumption.

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The bioactivity of most near-infrared II (NIRII) fluorophores are limited, thereby conflicting the achievement of strong fluorescence and high catalytic activities, due to a lack of free electrons in the method.

To overcome this challenge, Huizhen Ma and a research team in translational medicine, , physics, and materials at the Tianjin University China developed atomically precise gold clusters with strong near-infrared II fluorescence to show potent enzyme-mimetic activities by using atomic engineering, to form active copper single-atom sites.

These gold-copper clusters (Au21 Cu1) showed higher antioxidant nature with a 90-fold catalase-like and 3-fold higher superoxide dismutase-like activity compared to gold clusters alone. These clusters can be cleared through the to monitor cisplatin-induced within a 20–120-minute window to visualize the process in 3D via near-infrared light-sheet microscopy.

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Metasurfaces, artificially engineered surfaces that can manipulate electromagnetic signals in unique ways, have huge potential for several technological applications, including the implementation of sixth generation (6G) cellular communications. The limitations and vulnerabilities of these smart surfaces, however, are still poorly understood.

Researchers at Peking University, University of Sannio and Southeast University recently carried out a study aimed at better understanding the vulnerability of metasurfaces to wireless cyber-attacks. Their paper, published in Nature Electronics, outlines two types of attacks that should be considered and accounted for before metasurfaces can be deployed on a large-scale.

“This work was primarily driven by the need for enhancing security and privacy of in the upcoming 6G era, characterized by unprecedented speeds, ultra-low latency, and vast connection nodes,” Lianlin Li, Vincenzo Galdi and Tie Jun Cui, three of the researchers who carried out the study, told Tech Xplore.

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Tesla’s train at Giga Berlin will take roughly 4,500 employees to work every day and will commute on its route almost 60 times daily.

This week, Tesla confirmed it would use a shuttle connected to the public railway network running between Erkner Train Station and the Giga Berlin property to give both employees and citizens a public transportation option.

The shuttle will travel between the two stops nearly 60 times a day, and according to rbb24, it will bring “more than 1,500 employees directly to the factory at the change of shift alone.”

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Short-lived proteins control gene expression in cells and execute critical roles ranging from assisting brain connectivity to fortifying the body’s immune response. Originating in the nucleus, these proteins are swiftly degraded after fulfilling their purpose.

For decades, the mechanism behind the degradation and removal of these essential proteins from cells remained a mystery to researchers — until now.

In a cross-departmental collaboration, researchers from Harvard Medical School identified a protein called midnolin that plays a key role in degrading many short-lived nuclear proteins. The study shows that midnolin does so by directly grabbing the proteins and pulling them into the cellular waste-disposal system, called the proteasome, where they are destroyed.

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