Articles tagged with Artificial Intelligence
A novel convolutional neural network, FMNet, was developed to determine the source focal mechanism of earthquakes rapidly using full waveforms. The method proves effective in calculating parameters within one second with minimal computing resources.
Professor Sam H. Noh, a prominent scientist at UNIST, has been elected as a 2020 ACM Fellow for his groundbreaking work in system software and data storage technology. This recognition is the first for a Korean university scientist and honors his contributions to advancing the field of computing.
A new study proves the fundamental feasibility of using AI to assess surgical skills, achieving 87% accuracy in identifying good or moderate surgical skill. The innovative three-stage approach uses computer algorithms to analyze instrument movement and correlate with expert ratings.
Experts argue that a 'regulatory ecosystem' is necessary for trustworthy AI, rather than relying on public education or increased transparency. Drs Knowles and Richards propose the use of AI documentation, such as IBM's AI Factsheets, to empower specialists in assessing trustworthiness.
Assistant Professor Guoyu Lu is creating an AI system that uses smartphones to analyze crop roots, enabling quick and efficient analysis of root shape, surface area, and angles. The goal is to develop a mobile app that can assess various crops and improve breeding resilient crops.
A study by University of Helsinki found that people consider humanoid robots' moral decisions less ethically sound than those made by humans or traditional robots. The uncanny valley effect is believed to contribute to this phenomenon, where humans perceive human-like artificial intelligence as eerie or creepy.
A new study assesses consumers' likelihood of adopting robo-advisory services, which provide automated investment advice. The analysis reveals that attitudes across cultures shape differences in local consumers' adoption of AI-based services.
The Skoltech team developed an AI system that enables processing images from autonomous greenhouses, monitoring plant growth and automating the cultivation process. The system, based on convolutional neural networks, can classify 18 plant varieties with high accuracy and outperform popular codecs in image size reduction.
A new AI-based emotion detection system, 5G-I-VEmoSYS, recognizes at least five kinds of emotion using wireless signals and body movement, with potential applications in smart cities and public safety. However, the system suffers from serious security issues that need to be addressed for its reliability.
A new algorithm uses artificial intelligence to automate electrocardiogram recordings, improving efficiency and accuracy in heart disease diagnosis. This innovation has the potential to streamline clinical workflows and enhance patient care.
Research from Arizona State University reveals that human-autonomy teams are less efficient than all-human teams due to interaction limitations. Effective synthetic teammates and enhanced HAT interactions are crucial for success in complex environments, as demonstrated by a study on UAV teams with AI pilots.
Researchers from Universitat Rovira i Virgili and Institute of Materials Science of Barcelona have combined experimental data with algorithms to enable an unprecedented predicting capability of the performance of organic solar cells. The study uses a new experimental method to generate large datasets, which are then used to train machi...
Machine-learning algorithms are trained on large datasets to predict the performance of organic solar cells, identifying key parameters such as electronic gap and charge transport balance. This study demonstrates a new approach to predicting material efficiency, paving the way for further analytical models and more complex system under...
The KIT real-world lab 'Robotic Artificial Intelligence' will develop concrete practical applications of robotic AI with civil society and study opportunities as well as risks. Humanoid robots will be used in various scenarios, such as hospitals, schools, and libraries.
Researchers demonstrate that no single algorithm can determine whether a superintelligent AI would produce harm, and deciding on its intelligence is incomputable. The study's containment problem highlights the challenges of controlling such an AI.
Research from the University of Copenhagen found that Danish and Chinese people experience bitter tastes differently, with Chinese test subjects being more sensitive. Anatomical differences in tongue papillae may explain this difference. The study suggests that ethnic differences may play a role in taste perception.
An international research team is creating an AI-powered moderator for social media to mitigate conflict escalation. The virtual mediator uses artificial intelligence to identify hostile comments and intervene in discussions.
The journal features papers on AI in medicine, including new roles for clinicians and AI-aided disease prediction. It also covers the development of chest imaging analysis methods for COVID-19 diagnosis.
Researchers at KU Leuven developed a technique that uses brainwaves to determine within one second whom you're listening to. The system separates sound signals and links them to brainwaves, allowing for faster identification of the desired speaker.
Researchers Mirko Kovac and Aslan Miriyev propose merging artificial intelligence with physical bodies to create lifelike robots. By combining materials science, biology, and computer science, they aim to achieve symbiosis between humans and machines.
Researchers from the University of Seville found that AI can detect birth defects, gestational diabetes, and preterm birth earlier using data on environmental pollution. AI systems can also help monitor women's mental health during pregnancy, improving public health in disadvantaged areas.
Researchers from the University of Kansas have discovered a link between people's attachment styles and their trust in artificial intelligence. Attachment anxiety is associated with reduced trust, while enhanced attachment security increases trust. The study suggests that reminding individuals of their secure relationships can boost tr...
A research team at Hiroshima University has unveiled the mechanism underlying quantum direction and introduced a way to potentially control movement. By manipulating the coin flipping rate, the researchers found that some control can be achieved over the walker's trajectory.
A new study by Aarhus University uses AI to analyse thousands of WW2 photographs, enabling the identification of photographers based on image characteristics. The technology has significant applications in humanities and social sciences, including linking photo archives to war-related research.
The article discusses emerging applications of AI-related medicine, including novel diagnostic approaches, metadata analytical methods, and AI-aided treatment applications in preclinical and clinical uses. New progress in AI-aided disease prediction holds tremendous potential for future clinical use.
A new study by Johns Hopkins University researchers found that the brain detects 3D shape fragments in the early stages of object vision, a strategy also used in artificial intelligence networks. This discovery may hold future opportunities to leverage correlations between natural and artificial intelligence.
A team of researchers using AI technology has counted over 1.8 billion trees and shrubs in the Sahara Desert, revealing a previously unknown factor in the global carbon budget. The study highlights the importance of trees in dryland areas for biodiversity and ecosystems, as well as their potential to improve agroforestry programs.
Researchers developed a new mathematical framework that leverages uncertainty and expert knowledge to create more accurate and efficient computer models. This method provides guarantees on model performance and can lead to breakthroughs in renewable energy, battery technology, and other fields.
International scientists challenge their colleagues to make Artificial Intelligence (AI) research more transparent and reproducible to accelerate the impact of their findings for cancer patients. The authors offer numerous frameworks and platforms that allow safe and effective sharing of data, computer code, and predictive models.
An international group of scientists raises concerns about a recent publication evaluating an AI system for breast cancer screening, citing restrictive data access and lack of transparency. The authors argue that protecting patient privacy should not hinder the broader research community from contributing to methodology and correcting ...
The rapid development of AI in medicine has led to new opportunities for clinicians. However, concerns about replacement have been raised. The authors explore the unlikelihood of complete replacement and propose adaptations to enable successful integration.
Researchers distinguish between brain activities of right-handers and left-handers using functional near-infrared spectroscopy, revealing asymmetry in response to passive touch stimulations. The study may have implications for brain-computer interfaces, rehabilitation robotics, and cognitive enhancement treatments.
AI-controlled sensors can alert clinicians and patients of impending health crises, reducing nosocomial infections. Infrared technologies enable real-time monitoring of patients' vital signs, allowing for timely interventions.
Deep Longevity's 'longevity cloud' will track and analyze aging at multiple levels, providing a novel way to extend human productive longevity and improve performance. The combined company aims to create an end-to-end longevity ecosystem serving researchers, medical doctors, and enthusiasts worldwide.
A team of researchers has successfully harnessed the power of the unconscious mind to make profitable decisions. By monitoring nonconscious brain activity, participants were able to learn and improve their choices without being aware of it. This breakthrough suggests that confidence may play a crucial role in guiding behavior.
The UC Davis-led AI Institute for Next Generation Food Systems aims to optimize crop yields, minimize resource consumption, and improve food safety through AI technologies. The institute will foster collaborations across academia, industry, and government to develop open-source solutions and promote education, outreach, and diversity.
A UTA-owned robot will be used to inspect and analyze the remaining service life of 3.5 miles of pressure pipes in Lubbock. The project aims to evaluate the condition and lifespan of the pipes without replacing unnecessary ones, saving the city costs.
The University of Exeter's AI in Healthcare Summit aims to boost collaboration between AI researchers, healthcare experts, and business leaders to address the biggest challenges in healthcare. The summit features panel discussions on cutting-edge technologies such as contact tracing, vaccines, and precision medicine.
Astronomers used AI to classify spiral galaxies in Subaru Telescope images, achieving 97.5% accuracy and identifying 80,000 galaxies.
Experts have developed a platform for self-testing AI medical services, allowing for automated validation and improvement. The platform provides an opportunity to fine-tune algorithms with unlimited access to data instances, minimizing human factor manipulation.
Experts say AI's portrayal as White removes people of color from the future, perpetuating racial biases in algorithms and workforce. Cultural depictions of AI as White risk creating a 'racially homogenous' technologist workforce.
A new viewpoint piece in JAMA outlines key considerations for implementing chatbots in healthcare, including patient safety, trust, and transparency. The authors propose a framework to inform decision-making on chatbot implementation, emphasizing the need for robust evaluation and research.
A group of doctors and data scientists propose creating clinical departments devoted to artificial intelligence to harness its power in transforming patient care. The plan aims to address issues such as inconsistent implementation, poor data quality, and overdependence on AI, and would bring together diverse expertise for faster benefits.
A multidisciplinary group of Indigenous scholars, including professors and graduate students from Canada and the US, met in Hawai'i to brainstorm how Indigeneity intersects with AI. Their completed position paper offers diverse perspectives on what AI means and offers to Indigenous peoples, challenging long-held assumptions about Weste...
QUT researchers have published a new method for detecting koalas in bushfire areas, using drones equipped with infrared cameras and an artificial intelligence algorithm. The system is more accurate and less invasive than traditional methods, providing a more reliable estimate of the population size.
A team of researchers developed an AI model to forecast complicated large-scale tropical instability waves in the Pacific Ocean. The model, which uses satellite data-driven deep learning, accurately predicted sea surface temperature evolution and captured TIW propagation's spatial and temporal variation.
Researchers used drones with thermal cameras to locate ground-nesting farmland bird nests, identifying a promising conservation tool. The system performed best under cloudy and cold conditions, showing potential for automated nest detection in agricultural practices.
UT Dallas researchers are using the Minecraft mod Polycraft World to simulate dynamic and unexpected events to train AI systems. They aim to create artificial intelligence agents that can respond appropriately in novel scenarios, such as changing weather or unfamiliar terrain.
A new German research project aims to improve the automatic analysis and generation of high-quality texts using artificial intelligence. The goal is to disentangle styles and topics in textual data, enabling enhanced text quality and influencing tone, while overcoming challenges with irony and sarcasm.
Researchers have found a mathematical means to help regulators and businesses manage AI systems' biases towards making unethical and costly commercial choices. The new 'Unethical Optimization Principle' provides a simple formula to estimate its impact, aiming to reduce the risk of AI-driven unethical strategies.
AI systems can learn to recognize abnormalities, but often lack transparency and make 'lazy' diagnoses. Researchers from Radboud University Medical Center developed an approach to improve sensitivity and transparency in AI diagnosis, achieving a 11.2% increase in diabetic retinopathy detection
Researchers at University of Cambridge developed a context-aware AI system that reduces the 'communication gap' by up to 96% for nonverbal people with motor disabilities, enabling faster conversation rates.
A new AI-driven system called ModGraProDep has been developed to predict cancer survival and risk. This innovative tool uses probabilistic modeling and machine learning to provide personalized predictions for patients, enabling more effective treatment planning and improved patient outcomes.
A team of scientists used artificial intelligence to examine whether mandrills' facial features are a result of genetic similarity or selection. They found that half-sisters with the same father exhibit stronger facial resemblance, indicating a possible evolutionary mechanism for social discrimination and nepotism among kin.
The Lancet review calls for guidelines and research agenda to ensure equitable and ethical use of AI in low- and middle-income countries. The recommendations focus on human-centered design, data protection, and regulatory standards.
Researchers developed an intent-defined optical network (IDON) with artificial intelligence-based automated operation and maintenance to address the challenges of manual configuration. IDON achieves intent-oriented configuration conversion, adaptive generation and optimization strategies, and closed-loop intent-guaranteed operations, d...
A scoping review of 405 studies reveals that AI research in primary care is at an early stage, with unique challenges to applying AI in a person-centric approach. To mature, value must be placed on developing rigorous AI and identifying impacts on care delivery and health outcomes.
A recent study found that artificial intelligence can provide results comparable to lung function tests in diagnosing emphysema and classifying its severity. The AI system can automatically analyze chest scans and create a 3D model of the patient's lungs, helping doctors better communicate with patients and track treatment progress.
Researchers found that AI systems can absorb moral responsibility in difficult conversations, allowing humans to trust them more than their human partners. The study explores how AI alters human interactions and suggests potential applications for improving communication with subtle guidance from AI.
Researchers warn of 'exaggerated' AI study claims, highlighting poor quality evidence and methodological flaws in studies. The majority of deep learning medical imaging studies have high bias and lack transparency, fueling hype for rapid implementation.