Sheets of metal just two atoms thick can be produced by squashing molten droplets at great pressure between two sapphires. The researchers who developed the process say the unusual materials could have applications in industrial chemistry, optics and computers. Last year, scientists created a gold sheet that was a single atom thick, which they dubbed "goldene" after graphene, a material made of a single layer of carbon atoms. Such materials have been described as two-dimensional, as they are as thin as chemically possible. But making other 2D metals hadn't been possible until now. The new technique, developed by Luojun Du at the Chinese Academy of Sciences and his colleagues, can create 2D sheets of bismuth, gallium, indium, tin and lead that are as thin as their atomic bonds allow.

When wildfires swept across Maui, Hawaii, last month with destructive fury, China's increasingly resourceful information warriors pounced. The disaster was not natural, they said in a flurry of false posts that spread across the internet, but was the result of a secret "weather weapon" being tested by the United States. To bolster plausibility, the posts carried photographs that appeared to have been generated by artificial intelligence programs, making them among the first known to have used these new tools to amplify the aura of authenticity of a disinformation campaign.

As an artist, it's important to continually explore new techniques and methods to enhance your creative process. While inspiration can strike at any moment, there are certain practices that can help you stay focused, motivated and inspired. In this article, we'll explore five ways to enhance your creative process and take your art to the next level. Trying out new techniques and mediums can be a great way to challenge yourself and to broaden your creative horizons. Whether it's trying out a new painting style or exploring a different medium altogether, experimenting with new techniques can help you stay inspired and motivated.

This paper describes a new technique for object recognition based on learning appearance models. The image is decomposed into local regions which are described by a new texture representation called "Generalized Second Mo(cid:173) ments" that are derived from the output of multiscale, multiorientation filter banks. Class-characteristic local texture features and their global composition is learned by a hierarchical mixture of experts architecture (Jordan & Jacobs). The technique is applied to a vehicle database consisting of 5 general car categories (Sedan, Van with back-doors, Van without back-doors, old Sedan, and Volkswagen Bug). This is a difficult problem with considerable in-class variation.

Machine Learning (ML) is a rapidly growing field that has the potential to revolutionize many aspects of society, including healthcare, finance, transportation, and entertainment. However, like any rapidly growing field, ML also faces significant challenges. In this article, I will discuss four of the main challenges in machine learning. The first challenge in ML is data quality and quantity. ML models require large amounts of high-quality data to learn and make accurate predictions.

An international research team led by Lund University in Sweden has created a new technique for using artificial intelligence (AI) and DNA analysis to date human remains that are up to 10,000 years old. The new method could aid in mapping historical human migration patterns, frequently accomplished by precisely dating ancient remains. Radiocarbon dating has been the accepted dating method since the 1950s. Based on the ratio of two separate carbon isotopes, this dating technique has been extremely influential in contemporary archaeology. Having said that, it can be challenging to map ancient people's movements because the technology can sometimes be inaccurate.

Before you can even think about building an algorithm to read an X-ray or interpret a blood smear, the machine has to know what's what in an image. All of the promise of AI in healthcare -- an area that has attracted $11.3 billion in private investment in 2021, can't be realized without carefully labeled data sets that tell machines what exactly they're looking for. Creating those labeled data sets is becoming an industry itself, boasting companies well north of unicorn status. Today, Encord, a small startup just out of Y Combinator, is looking to take a piece of the action. Aiming to generate labeled data sets for computer vision projects, Encord launched its own beta version of an AI-assisted labeling program called CordVision.

Research suggests that many more women could benefit from targeted breast cancer treatments – we just need to find them.

The world's first high-resolution 3D image of a monkey brain has been revealed, in a breakthrough that could pave the way for treatments for human diseases including Parkinson's. A detailed map of a complete macaque monkey brain was created using fluorescent imaging techniques by a team from the Chinese Academy of Sciences in Beijing. The team used a new technique to show how nerve cells are organised and connected within the monkey brain at a'micron resolution'. The human brain comprises nearly a hundred billion nerve cells with delicate and complex connections, and while up to 17 times larger than that of a macaque, it is similar enough for comparisons to be made between the two, researchers claim. Until now, a mouse brain was the largest to be mapped, taking days to create a complete 3D image, but the new technique made it possible to move up to a macaque brain, which is about 200 times larger in volume than that of a mouse.

Researchers Zhi Wang, Chaoge Liu, and Xiang Cui published a paper last Monday demonstrating a new technique for slipping malware past automated detection tools--in this case, by hiding it inside a neural network. The three embedded 36.9MiB of malware into a 178MiB AlexNet model without significantly altering the function of the model itself. The malware-embedded model classified images with near-identical accuracy, within 1% of the malware-free model. Just as importantly, squirreling the malware away into the model broke it up in ways that prevented detection by standard antivirus engines. VirusTotal, a service that "inspects items with over 70 antivirus scanners and URL/domain blocklisting services, in addition to a myriad of tools to extract signals from the studied content," did not raise any suspicions about the malware-embedded model.