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Mousavi, S., Seyedmirzaei, H., Shahrokhi Nejad, S. et al. Sci Rep 14, 21,936 (2024). https://doi.org/10.1038/s41598-024-73277-z.
Neurotech company Synchron has been making massive strides over the past couple of years. It’s just announced that a trial participant has used its brain-computer interface (BCI) to turn on the lights in his home, see who is at the door, and choose what to watch on the TV – hands-free and without even a voice command.
That’s thanks to Synchron’s interface translating his thoughts into commands relayed to Amazon’s Alexa service. The virtual assistant is set up on his tablet and connected to his smart home devices. The trial participant, who is living with amyotrophic lateral sclerosis (ALS) and can’t use his hands, can simply think about navigating through options displayed on the tablet to engage them.
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Lunar igneous activities including intrusive and extrusive magmatism, and their products contain significant information about the lunar interior and its thermal state. Their distribution is asymmetrical on the nearside and farside, reflecting the global lunar dichotomy. In addition to previously returned lunar samples all from nearside (Apollo, Luna, and Chang’e-5), samples from the South Pole-Aitken (SPA) basin on the farside have long been thought to hold the key to rebalancing the asymmetrical understandings of the Moon and disclosing the lunar dichotomy conundrum.
Earlier this year, the Chang’e-6 mission of the Chinese Lunar Exploration Program, successfully launched on May 3, landed on the lunar surface on June 2, and returned to the Earth on June 25 carrying a total of 1935.3g of lunar soils. It is the world’s first lunar farside sample-return mission, which landed in the south of the Apollo basin within the SPA basin on the farside. These precious samples would open a window to solve the long-standing question of lunar dichotomy, even reshape human’s knowledge of our closest neighbour. However, compared with the well-known mare volcanism surrounding the Chang’e-6 landing site, the intrusive magmatic activities have a much more obscure presence and origin, impeding future sample analyses when they are available for application.
In a recent research paper published in The Astrophysical Journal Letters, Dr Yuqi QIAN, Professor Joseph MICHALSKI and Professor Guochun ZHAO from the Department of Earth Sciences at The University of Hong Kong (HKU) and their domestic and international collaborators have comprehensively studied the intrusive magmatism of the Chang’e-6 landing site and its surroundings based on remote sensing data. The study revealed their extensive distributions and obscure nature with significant implications for the petrogenesis of lunar plutonic rocks and the Chang’e-6 mission, which will facilitate scientists’ further study of lunar farside.
In recent years, a community of researchers from various universities and institutes across Europe and the United States set out to explore the physics of micro-and nano-mechanical devices coupled to light. The initial focus of these investigations was on demonstrating and exploiting uniquely quantum effects in the interaction of light and mechanical motion, such as quantum superposition, where a mechanical oscillator occupies two places simultaneously. The scope of this work quickly broadened as it became clear that these so-called optomechanical devices would open the door to a broad range of new applications.
Hybrid Optomechanical Technologies (HOT) is a research and innovation action funded by the European Commission’s FET Proactive program that supports future and emerging technologies at an early stage. HOT is laying the foundation for a new generation of devices that bring together several nanoscale platforms in a single hybrid system. It unites researchers from thirteen leading academic groups and four major industrial companies across Europe working to bring technologies to market that exploit the combination of light and motion.
One key set of advances made in the HOT consortium involves a family of non-reciprocal optomechanical devices, including optomechanical circulators. Imagine a device that acts like a roundabout for light or microwaves, where a signal input from one port emerges from a second port, and a signal input from that second port emerges from a third one, and so on. Such a device is critical to signal processing chains in radiofrequency or optical systems, as it allows efficient distribution of information among sources and receivers and protection of fragile light sources from unwanted back-reflections. It has however proven very tricky to implement a circulator at small scales without involving strong magnetic fields to facilitate the required unidirectional flow of signals.
In recent years, these technological limitations have become far more pressing. Deep neural networks have radically expanded the limits of artificial intelligence—but they have also created a monstrous demand for computational resources, and these resources present an enormous financial and environmental burden. Training GPT-3, a text predictor so accurate that it easily tricks people into thinking its words were written by a human, costs $4.6 million and emits a sobering volume of carbon dioxide—as much as 1,300 cars, according to Boahen.
With the free time afforded by the pandemic, Boahen, who is faculty affiliate at the Wu Tsai Neurosciences Institute at Stanford and the Stanford Institute for Human-Centered AI (HAI), applied himself single mindedly to this problem. “Every 10 years, I realize some blind spot that I have or some dogma that I’ve accepted,” he says. “I call it ‘raising my consciousness.’”
This time around, raising his consciousness meant looking toward dendrites, the spindly protrusions that neurons use to detect signals, for a completely novel way of thinking about computer chips. And, as he writes in Nature, he thinks he’s figured out how to make chips so efficient that the enormous GPT-3 language prediction neural network could one day be run on a cell phone. Just as Feynman posited the “quantum supremacy” of quantum computers over traditional computers, Boahen wants to work toward a “neural supremacy.”
Researchers from Japan and the Michigan Technological University have succeeded in building a molecular computer that, more than any previous project of its kind, can replicate the inner mechanisms of the human brain, repairing itself and mimicking the massive parallelism that allows our brains to process information like no silicon-based computer can.
A relatively new technology, molecular electronics is an interdisciplinary pursuit that may very well prove the long-term solution to validate Moore’s law well into the next century. A molecular computer is made of organic molecules instead of silicon. Chips built this way are not only potentially much smaller but also, because of the way they can be networked, able to do things that no other traditional computer, regardless of its speed, can do.
“Modern computers are quite fast, capable of executing trillions of instructions a second, but they can’t match the intelligent performance of our brain,” Michigan Tech physicist Ranjit Pati commented. “Our neurons only fire about a thousand times per second. But I can see you, recognize you, talk with you, and hear someone walking by in the hallway almost instantaneously, a Herculean task for even the fastest computer.”
Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes. Here the authors create layered assemblies of genetically encoded devices that perform non-binary logic computation and signal processing using combinatorial promoters and feedback regulation.
Electrophysical processes are used to create third-order nanoscale circuit elements, and these are used to realize a transistorless network that can perform Boolean operations and find solutions to a computationally hard graph-partitioning problem.
