Articles tagged with Artificial Intelligence
Researchers developed a powerful new AI algorithm called RoboBallet that enables large sets of robotic arms to work together faster and smarter. The system plans movements and tasks automatically, unlocking new levels of flexibility and efficiency in manufacturing.
A new method, AEquity, identifies and corrects bias in health care datasets used to train machine-learning algorithms. The tool can spot well-known and previously overlooked biases across different datasets.
The study found that humans and AI systems interact with flexible and incremental learning modes similarly to working memory and long-term memory in humans. Quicker, flexible in-context learning emerges after a certain amount of incremental learning has taken place, similar to human learning.
The use of AI in the criminal justice system raises concerns about fairness and transparency. Researchers advise for clear understanding of data used and procedure by judges to use guidance from AI systems. Explainable AI systems may help, but transparency doesn't have to mean understanding computer code.
A new study assesses ChatGPT 3.5's performance on hematology-oncology tasks, revealing its strengths and limitations in providing accurate information for patients. The study highlights the importance of physician oversight when using AI-generated medical information.
A new study from Rice University introduces a novel solar thermal-boosted organic Rankine cycle (ORC) system that can recover 60-80% more electricity annually from waste heat in data centers. The approach achieves over 8% higher ORC efficiency during sunny peak hours and lowers the cost of electricity by 5.5-16.5%.
The Wits MIND Institute has received a $1 million boost from Google.org, enabling it to drive next-generation breakthroughs in natural and artificial intelligence. The partnership aims to advance the scientific understanding of both natural and artificial intelligence, foster breakthrough research and technological innovation.
The ITU Global Symposium for Regulators 2025 endorsed guidelines to build sustainable digital ecosystems for essential national services. The new guidelines outline key tools and frameworks to drive regulatory innovation and ensure prosperity for all.
Altmetric introduces AI-powered sentiment analysis to provide deeper insights into research public response and impact. The new feature leverages advanced technology to interpret and visualize sentiment behind mentions on key social media platforms.
Researchers at Penn Engineering introduced AMP-Diffusion, a generative AI tool that designed tens of thousands of new antimicrobial peptides with bacteria-killing potential. The most potent AMPs performed as well as FDA-approved drugs without detectable adverse effects.
Researchers at the University of Minnesota developed AI-guided aerial robots to detect, track and analyze wildfire smoke plumes. The technology provides high-resolution data collection across large areas at a lower cost than satellite-based tools, enabling more accurate computer models for air quality predictions.
Florida Atlantic University's FAU Engineering has received a $827,533 USD grant from the USDA to develop an advanced edge/fog computing-based framework called FogAg. This project aims to revolutionize precision agriculture by enabling real-time sensing and analysis of crop growth and yield.
Researchers at Seoul National University of Science & Technology developed LWMalloc, a lightweight and high-performance dynamic memory allocator for resource-constrained environments. The new allocator outperforms ptmalloc by achieving up to 53% faster execution time and 23% lower memory usage.
A recent study published in Radiology found that AI-assisted mammography catches most advanced breast cancers, but still misses 14% of invasive cases. The AI missed more cases in younger women with tumors 2 cm or smaller, and those with low histologic grade, fewer lymph node metastases, and non-glandular locations.
A team of researchers at UC Santa Cruz developed a system using low-cost WiFi devices and machine learning algorithms to accurately measure heart rate. They found that the system worked regardless of body position or distance from the hardware, with high accuracy even after just five seconds of monitoring.
A new study led by Professor Jonghun Kam predicts that Pakistan will experience major floods and severe droughts on a periodic basis, exacerbated by accelerating global warming. The AI model forecasts these extreme weather events every 15 years for the upper Indus River, and roughly every 11 years for surrounding rivers.
Researchers created a new approach that integrates visual and tactile information to manipulate robotic arms, outperforming conventional vision-based methods. This breakthrough represents a significant advancement in multimodal physical AI.
Achieving universal, meaningful internet connectivity by 2030 would require a significant investment of $2.6-2.8 trillion at current prices. The report outlines the challenges, projected costs, and collaborative strategies needed to make sure everyone, everywhere, can use the Internet.
Researchers at UCLA have developed a wearable noninvasive brain-computer interface system that utilizes AI to interpret user intent, allowing participants to complete tasks significantly faster with assistance. The system demonstrates promising results for technology to assist individuals with limited physical capabilities.
Researchers have introduced a specialized AI model, EnvGPT, which achieves state-of-the-art performance in addressing complex environmental challenges. The model fine-tuned on a curated dataset outperforms larger models in accuracy and relevance, offering a scalable solution for environmental research and policy support.
Researchers at Pusan National University have developed a novel, multi-resin dispensing process for fiber-reinforced polymer fabrication, enabling precise patterning of mechanical properties within a monolithic structure. The breakthrough composite material combines flexibility and strength for advanced robotic applications.
Researchers developed DreamConnect, a brain-to-image system that integrates fMRI with advanced diffusion models. The system can interpret brain activity and edit it with natural language prompts, marking an important step in connecting human dreams with interactive visualization.
A team of computer scientists at UC Riverside has developed a method to erase private and copyrighted data from artificial intelligence models without needing access to the original training data. The approach enables AI models to 'forget' selected information while maintaining functionality with remaining data.
Researchers developed algorithms that enable robots to create the best possible outcomes from their actions while minimizing uncertainty and risk. The new strategies allow robots to anticipate human actions, adapt to different scenarios, and prioritize human safety.
A former diplomat warns that algorithms lack empathy and intuition, which are essential for successful negotiations. However, AI can streamline diplomacy and amplify human aspirations when used carefully. Diplomats need training in AI ethics and global cooperation to ensure equal access and deployment.
The procedure uses a combination of advanced imaging, artificial intelligence, and 3D printing to create a customized implant tailored to each patient's unique anatomy. This technology allows for more precise spinal alignment, reduced surgical complications, and faster recovery times.
Researchers developed AI models that can identify signs of heart failure in patients from Appalachia using low-tech electrocardiogram results. The models achieved high accuracy and could potentially provide clinicians with an edge in protecting patients' cardiac health.
Quantum Research Sciences is partnering with Purdue's Rosen Center for Advanced Computing to develop an AI-driven platform called ACID-R. The platform uses AI to quickly deliver details on commercial products and services, streamlining the process for the Air Force to identify needed technologies from the private sector.
A new AI tool has identified over 1,000 'questionable' scientific journals, including those that charge hundreds or thousands of dollars to publish research without proper vetting. The AI system uses six criteria to evaluate journals, including editorial board composition and website quality.
A new study published in Clinical Gastroenterology and Hepatology shows that AI analysis can accurately identify mucosal ulceration as well as human reviewers, providing a more objective and reproducible assessment of Crohn's disease. The findings have potential implications for education, drug development, and automated care.
Robotics experts disagree with claims that humanoid robots will surpass human capabilities in surgery, factory work, and serving as personal butlers. The main limitation is dexterity, making tasks like picking up objects difficult for current robot technology.
ConcreteSC technology achieves significant speed boosts and improved efficiency in next-generation wireless networks. The innovation integrates user tasks into communication processes, reducing computational complexity and increasing semantic meaning.
Researchers Marie Teich and Wilmer Leal develop a formal framework to analyze metaphors, confirming they are enduring linguistic and cognitive structures. The study reveals two significant metaphorical processes: mappings from concrete to abstract topics and the emergence of new mappings between domains.
Researchers at Tohoku University have developed an AI-built materials map that combines experimental data with computational predictions to identify promising materials for thermoelectric waste-heat recovery. The map enables faster development timelines and reduces trial-and-error, accelerating innovation in energy-related technologies.
A new RAND study found that three widely used AI chatbots are generally consistent in responding to very-high-risk and very-low-risk questions about suicide, but inconsistent in answering intermediate-risk questions. ChatGPT and Claude generated appropriate responses to very-low-risk questions, while Gemini's responses were more variable.
Vasile's research aims to map and model an agent's capabilities, particularly in motion, manipulation, and perception, to reliably predict their behavior. The goal is to use this understanding to plan effectively for large teams of agents.
Energy & Environment Nexus is a pioneering open-access platform exploring the dynamic interplay between energy and the environment. The platform spans key areas such as renewable energy, sustainable technologies, and pollution control, aiming to accelerate innovation and impact.
The University of Tennessee is working with several institutions to address health disparities research and enhance AI performance. The projects aim to train participants in using high-performance computing, cloud-based AI applications, and open data tools in medical research and healthcare delivery.
Simpler, physics-based models can generate more accurate predictions than state-of-the-art deep-learning models for certain climate scenarios. However, simple models are more accurate when estimating regional surface temperatures, while deep-learning approaches excel at local rainfall estimation.
Surya is a visual AI model trained on massive amounts of solar data, leveraging NASA's deep scientific expertise in cutting-edge AI models. The system aims to determine the Sun's magnetic field generation and structure, as well as its impact on the heliosphere and geospace.
A new Mayo Clinic AI tool, UNISOM, has shown promising results in identifying early signs of clonal hematopoiesis of indeterminate potential (CHIP), a condition that raises the risk of leukemia and heart disease. The tool helps detect CHIP-related mutations in standard genetic datasets, opening new avenues for research and discovery.
A new deep-learning model calculates urban heat stress per square meter in the future, considering geodata and weather forecasts. The model simulates a range of climate scenarios, including increased heat stress due to rising greenhouse gas emissions.
The project aims to develop personalized technologies that promote lifelong learning in various educational settings. It will guide the creation of IR systems that can effectively support users with complex information needs and foster information literacy.
A new login system called Client-Side Encrypted Access Logging (CSAL) detects online account compromise without exposing personal devices to invasive tracking. The system verifies whether a login came from a user's own device, addressing a flaw in how major platforms log account access.
A new study offers a powerful AI-assisted method for uncovering exactly how TB drugs kill the bacteria, which could lead to smarter treatment combinations. The approach uncovers molecular details of drug interactions and can predict their impact from images alone.
Researchers at North Carolina State University unveiled Rainbow, a self-driving laboratory that autonomously discovers high-performance quantum dots. The system combines advanced robotics and AI to conduct up to 1,000 experiments per day, accelerating materials discovery.
Researchers developed Vesalius to interpret complex data on cancer cell interactions, leading to potential discoveries in treating hard-to-treat cancers. The tool analyzes whole tissue architecture to identify predictive biomarkers and inform treatment options based on individual disease types.
A new AI-driven framework uses a custom-built catalysis knowledge graph and LLMs to recommend relay catalysis pathways. The system successfully found existing and suggested new pathways for several target molecules, demonstrating its potential to improve efficiency and selectivity in chemical reactions.
Researchers at Uppsala University developed an AI model that can accurately predict battery ageing, leading to longer life and enhanced safety for electric vehicle batteries. The model reduces the need for sensitive vehicle data and provides a detailed picture of chemical processes inside batteries.
The inaugural AI in Agriculture Symposium will bring together experts from academia and industry to discuss the latest research and real-world applications for agriculture. The symposium will feature a roundtable discussion on multidisciplinary collaborations in agriculture.
Researchers at Uppsala University have developed an AI system that can detect subtle tissue changes indicative of prostate cancer, missing it from human pathologists. The study found the AI detected cancers in over 80% of cases where pathologists missed them.
A new reporting checklist introduces key methodological details to improve reproducibility and transparency in AI-based automated image analysis. The guidelines will support clear communication of methods and reduce cognitive bias, promoting the translation of AI tools into routine pathology workflows.
A new study by the University of Surrey found that AI technologies can give hotels, restaurants, and cruise lines a competitive edge while improving environmental and social impact. The research calls for targeted staff training, industry-wide partnerships, and government-backed incentives to speed up AI adoption.
Chung-Ang University researchers develop innovative soft robots using paper electrodes and liquid crystal elastomers, achieving directional crawling through asymmetric bending. The robots utilize temperature-responsive materials and simple electroless plating patterning, enabling efficient and cost-effective fabrication.
A new study reveals that ambient documentation technologies, such as AI-driven scribes, led to significant reductions in physician burnout and improvements in well-being. The findings showed a 21.2% absolute reduction in burnout prevalence at Mass General Brigham and a 30.7% absolute increase in documentation-related wellbeing at Emory...
A new computational framework has been developed to optimize cellular self-organization, allowing scientists to understand and control how cells grow and interact. The framework uses machine learning tools to extract rules that guide cell behavior, enabling the creation of artificial organs and potential treatments for cancer.
A new AI-assisted model combines MRI, biochemical, and clinical information to predict worsening knee osteoarthritis with high accuracy. The model showed improved accuracy in predicting worsening pain and joint space narrowing, suggesting its potential to enhance care.
A team of researchers developed a method to annotate biopsy image data with eye-tracking devices, reducing the burden on pathologists. The resulting AI model achieved an accuracy of 96.3% and surpassed human pathologists' performance in diagnosing skin lesions.
The 12th Heidelberg Laureate Forum brings together 200 young mathematicians and computer scientists with 29 distinguished laureates to exchange ideas and discuss pressing issues in their fields. The event features a diverse range of lectures, talks, and panel discussions.
A novel AI model developed by the Dresden research team simultaneously detects multiple genetic alterations directly from routinely stained histological colon cancer tissue sections. The model recognized shared visual patterns rather than independently identifying individual genetic alterations.