Computers and Math from Science Daily Feed

Two new articles document progress in neuroprosthetic technology that lets people feel the shape and movement of objects moving over the 'skin' of a bionic hand.

The chemical composition of a material alone sometimes reveals little about its properties. The decisive factor is often the arrangement of the molecules in the atomic lattice structure or on the surface of the material. Materials science utilizes this factor to create certain properties by applying individual atoms and molecules to surfaces with the aid of high-performance microscopes. Using artificial intelligence, a new research group now wants to take the construction of nanostructures to a new level.

The robotics industry should be creating robots that could be reprogrammed and repurposed for other tasks once its life span is completed, researchers have advised.

Researchers applied the mathematical theory of synchronization to clarify how recurrent neural networks (RNNs) generate predictions, revealing a certain map, based on the generalized synchronization, that yields correct target values. They showed that conventional reservoir computing (RC), a type of RNN, can be viewed as a linear approximation, and introduced a 'generalized readout' incorporating further order approximations. Using a chaotic time-series forecasting task, they demonstrated that this approach dramatically enhances both prediction accuracy and robustness.

Paper-thin optical lenses simple enough to mass produce like microchips could enable a new generation of compact optical devices. Researchers have fabricated and tested flat lenses called Fresnel zone plates (FZPs), but did so for the first time using only common semiconductor manufacturing equipment, the i-line stepper, for the first time. These flat lenses currently lack the efficiency of in-production lenses, but have the potential to reshape optics for industries ranging from astronomy to health care and consumer electronics.

Data collected by wearable technology can identify disease flare-ups up to seven weeks in advance.

Researchers have developed a novel 6D pose dataset designed to improve robotic grasping accuracy and adaptability in industrial settings. The dataset, which integrates RGB and depth images, demonstrates significant potential to enhance the precision of robots performing pick-and-place tasks in dynamic environments.

For decades there has been near constant progress in reducing the size, and increasing the performance, of the circuits that power computers and smartphones. But Moore's Law is ending as physical limitations -- such as the number of transistors that can fit on a chip and the heat that results from packing them ever more densely -- are slowing the rate of performance increases. Computing capacity is gradually plateauing, even as artificial intelligence, machine learning and other data-intensive applications demand ever greater computational power.

New insect-scale microrobots can fly more than 100 times longer than previous versions. The new bots, also significantly faster and more agile, could someday be used to pollinate fruits and vegetables.

A new initiative is challenging the conversation around the direction of artificial intelligence (AI). It charges that the current trajectory is inherently biased against non-Western modes of thinking about intelligence -- especially those originating from Indigenous cultures. Abundant Intelligences is an international, multi-institutional and interdisciplinary program that seeks to rethink how we conceive of AI. The driving concept behind it is the incorporation of Indigenous knowledge systems to create an inclusive, robust concept of intelligence and intelligent action, and how that can be embedded into existing and future technologies.

Scientists describe their construction of complementary, internal, ion-gated, organic electrochemical transistors that are more amenable chemically, biologically and electronically to living tissues than rigid, silicon-based technologies. The medical device based on these transistors can function in sensitive parts of the body and conform to organ structures even as they grow. The result is a biocompatible sensor that can monitor brain functions in pediatric patients as they develop and grow.

Researchers have published a study describing how quasiparticles called polarons behave in tellurene, a nanomaterial first synthesized in 2017 that is made up of tiny chains of tellurium atoms and has properties useful in sensing, electronic, optical and energy devices.

Diamond, often celebrated for its unmatched hardness and transparency, has emerged as an exceptional material for high-power electronics and next-generation quantum optics. Diamond can be engineered to be as electrically conductive as a metal, by introducing impurities such as the element boron. Researchers have now discovered another interesting property in diamonds with added boron, known as boron-doped diamonds. Their findings could pave the way for new types of biomedical and quantum optical devices -- faster, more efficient, and capable of processing information in ways that classical technologies cannot.

AI applications like ChatGPT are based on artificial neural networks that, in many respects, imitate the nerve cells in our brains. They are trained with vast quantities of data on high-performance computers, gobbling up massive amounts of energy in the process. Spiking neurons, which are much less energy-intensive, could be one solution to this problem. In the past, however, the normal techniques used to train them only worked with significant limitations. A recent study has now presented a possible new answer to this dilemma, potentially paving the way for new AI methods that are much more energy-efficient.

Engineers have demonstrated a well-known quantum thought experiment in the real world. Their findings deliver a new and more robust way to perform quantum computations and they have important implications for error correction, one of the biggest obstacles standing between them and a working quantum computer.

Are humans or machines better at recognizing speech? A new study shows that in noisy conditions, current automatic speech recognition (ASR) systems achieve remarkable accuracy and sometimes even surpass human performance. However, the systems need to be trained on an incredible amount of data, while humans acquire comparable skills in less time.

Researchers have developed a drastically smaller and more energy efficient method of creating coveted photon pairs that influence each other from any distance. The technology could transform computing, telecommunications, and sensing.

The process of updating deep learning/AI models when they face new tasks or must accommodate changes in data can have significant costs in terms of computational resources and energy consumption. Researchers have developed a novel method that predicts those costs, allowing users to make informed decisions about when to update AI models to improve AI sustainability.

A new study overcomes a key obstacle to switching commercial aircraft from their near-total reliance on fossil fuels to more sustainable aviation fuels. The study details a cost-effective method for producing ethylbenzene -- an additive that improves the functional characteristics of sustainable aviation fuels -- from polystyrene, a hard plastic used in many consumer goods.

Researchers have demonstrated that the direction of the spin-polarized current can be restricted to only one direction in a single-atom layer of a thallium-lead alloys when irradiated at room temperature. The discovery defies conventions: single-atom layers have been thought to be almost completely transparent, in other words, negligibly absorbing or interacting with light. The one-directional flow of the current observed in this study makes possible functionality beyond ordinary diodes, paving the way for more environmentally friendly data storage, ultra-fine two-dimensional spintronic devices, in the future.