Computer Science

Researchers have found two novel types of attacks that target the conditional branch predictor found in high-end Intel processors, which could be exploited to compromise billions of processors currently in use.

The preprint "POLAR: Adaptive and Non-invasive Join Order Selection via Plans of Least Resistance" introduces an adaptive query processing technique that lowers the adoption barrier for existing database systems while decreasing the risk of performance cliffs from ill-performing query plans.

A team of video and AI engineers at Adobe Research has developed an AI application called VideoGigaGAN, that can accept a blurry video and enhance it to make it a much shaper product. The team describes their work and results in an article posted to the arXiv preprint server. They have also posted several examples of the videos that they have enhanced on their project website page.

Researchers at Lawrence Livermore National Laboratory (LLNL) have achieved a milestone in accelerating and adding features to complex multi-physics simulations run on Graphics Processing Units (GPUs), a development that could advance high-performance computing and engineering.

Vehicle passengers using VR headsets to pass the time during travel could be set to enjoy games which move at 'ludicrous speed' without experiencing motion sickness, researchers say.

In recent years, developers have introduced artificial intelligence (AI) systems that can simulate or reproduce various human abilities, such as recognizing objects in images, answering questions, and more. Yet in contrast with the human mind, which can deteriorate over time, these systems typically retain the same performance or even improve their skills over time.

Using data from a 2002 game show, a Virginia Commonwealth University researcher has taught a computer how to tell if you are lying.

In a recent publication in Science China Life Sciences, a research team led by Professor Jing-Dong Jackie Han and Ph.D. student Xinyu Yang from Peking University established a deep learning model for age estimation using non-registered 3D face point clouds. They also proposed the coordinate-wise monotonic transformation algorithm to isolate age-related facial features from identifiable human faces.

We use computers to help us make (hopefully) unbiased decisions. The problem is that machine-learning algorithms do not always make fair classifications if human bias is embedded in the data used to train them—which is often the case in practice.

While the class imbalance issue has been extensively investigated within the multi-class paradigm, its study in the multi-dimensional classification (MDC) context has been limited due to the imbalance shift phenomenon. A sample's classification as a minor or major class instance becomes ambiguous when it belongs to a minor class in one labeling dimension (LD) and a major class in another.

Setting the stage for a new era of immersive displays, researchers are one step closer to mixing the real and virtual worlds in an ordinary pair of eyeglasses using high-definition 3D holographic images, according to a study led by Princeton University researchers.

The step size, often referred to as the learning rate, plays a pivotal role in optimizing the efficiency of the stochastic gradient descent (SGD) algorithm. In recent times, multiple step size strategies have emerged for enhancing SGD performance. However, a significant challenge associated with these step sizes is related to their probability distribution, denoted as ηt/ΣTt=1ηt .

Anonymous authentication plays a crucial role in privacy-focused applications, and it is used for authenticating a user's identity in a privacy-preserving way. If enough privacy is provided, malicious users may misuse privacy. Accountability is necessary to avoid abusing anonymity. Previous anonymous authentication schemes can not hold the basic requirements of public linking and tracing while further ensuring access control simultaneously.

Have you ever felt reluctant to share ideas during a meeting because you feared judgment from senior colleagues? You're not alone. Research has shown this pervasive issue can lead to a lack of diversity in public discourse, especially when junior members of a community don't speak up because they feel intimidated.

Researchers at Tohoku University and the University of California, Santa Barbara, have unveiled a probabilistic computer prototype. Manufacturable with a near-future technology, the prototype combines a complementary metal-oxide semiconductor (CMOS) circuit with a limited number of stochastic nanomagnets, creating a heterogeneous probabilistic computer.

It's a sign of the times: an app store for omics enthusiasts. The Multi-Omics Analysis Portal (MAP) by the end of 2024 will be a one-stop shop for computer applications capable of making sense of various and vast omics data. Genomics, proteomics, lipidomics, transcriptomics—all are welcome.

Deepfakes—essentially putting words in someone else's mouth in a very believable way—are becoming more sophisticated by the day and increasingly hard to spot. Recent examples of deepfakes include Taylor Swift nude images, an audio recording of President Joe Biden telling New Hampshire residents not to vote, and a video of Ukrainian President Volodymyr Zelenskyy calling on his troops to lay down their arms.

Clear guidelines should be established for the generation and processing of synthetic data to ensure transparency, accountability and fairness, a new study says.

A new report led by researchers from UCL finds that the most popular artificial intelligence (AI) tools discriminate against women and people of different cultures and sexualities.

Research led by Minyi Guo, published in Frontiers of Computer Science, addresses the challenge of reducing storage overhead in blockchain systems while maintaining data consistency and tolerating malicious nodes.

A team of computer scientists at the University of Massachusetts Amherst working on two different problems—how to quickly detect damaged buildings in crisis zones and how to accurately estimate the size of bird flocks—recently announced an AI framework that can do both. The framework, called DISCount, blends the speed and massive data-crunching power of artificial intelligence with the reliability of human analysis to quickly deliver reliable estimates that can quickly pinpoint and count specific features from very large collections of images.

High-quality, defect-free, and perfectly dimensioned metal components. Quantum computing power looks set to optimize production processes in the metalworking industry.

How do we know what a quantum computer is good for when it hasn't been built yet? That's what Ph.D. candidate Casper Gyurik investigated by combining two terms you often hear: quantum computing and machine learning.

The human brain, with its remarkable general intelligence and exceptional efficiency in power consumption, serves as a constant inspiration and aspiration for the field of artificial intelligence. Drawing insights from the brain's fundamental structure and information processing mechanisms, brain-inspired computing has emerged as a new computational paradigm, poised to steer artificial intelligence from specialized domains towards broader applications in general intelligence.

The increasing demand in the embedded field has led to the emergence of several impressive Instruction Set Architectures (ISAs). However, when processors migrate from one ISA to another, software compatibility issues are unavoidable.

The concept of Waddington landscape, originally proposed by British developmental biologist Conrad Hal Waddington in 1957, has been influential in describing the dynamical evolution of cellular development.

Nonlinear systems have applications in many diverse fields from robotics to economics. Unlike linear systems, the output is not proportional to the input is such systems. A classic example is the motion of a pendulum. Due to the inherent nature of nonlinear systems, their mathematical modeling and, consequently, control is difficult.

The biological brain, especially the human brain, is a desirable computing system that consumes little energy and runs at high efficiency. To build a computing system just as good, many neuromorphic scientists focus on designing hardware components intended to mimic the elusive learning mechanism of the brain.

A research team from the Empirical Research Support (ERS) at CISPA Helmholtz Center for Information Security has conducted a systematic comparison of the most popular transcription services. The comparison involved 11 providers of manual as well as AI-based transcriptions.

There's a race underway to build artificial general intelligence, a futuristic vision of machines that are as broadly smart as humans or at least can do many things as well as people can.