Articles tagged with Artificial Intelligence
A team of scientists from NTU Singapore has developed a new biochip that, when paired with Artificial Intelligence (AI), can detect quickly and accurately extremely small amounts of microRNAs. The device can cut detection time from hours to 20 minutes.
Recent progress in advanced energy manufacturing highlights 3D printing's potential to redefine next-generation lithium batteries. The technology enables precise control over three-dimensional structures, improving ion-transport pathways and mechanical robustness.
The researchers developed an AI-based method that allows users to input natural language prompts about the materials they want to create and suggests optimal procedures for experiments to produce them. The method has been successfully applied to identify catalysts for turning carbon dioxide and hydrogen into carbon monoxide and water u...
Researchers propose a novel brain architecture for efficient processing, integrating parallel cortical and subcortical pathways. This approach may improve decision-making tasks, suggesting current AI models are missing key brain function principles.
Researchers identified a practical strategy to reduce bias in AI systems used in children's mental health care. By analyzing training data, they found that targeted improvements can significantly reduce disparities without diminishing overall model performance.
Advances in high-throughput proteomics and artificial intelligence are transforming biomarker discovery, disease prediction, and drug development. Proteomic technologies enable comprehensive snapshots of physiological and pathological states, driving breakthroughs in early diagnosis and personalized treatments.
The Journal of Management Analytics seeks high-quality research on the intersection of artificial intelligence and business disciplines, focusing on prescriptive intelligence to optimize organizational systems. The symposium will be held in June 2026 at ESCP Turin, Italy, with partial funding available for selected authors.
Ricardo Baeza-Yates has made fundamental contributions to computer science through his pioneering work in algorithms and information retrieval. He has fostered a vibrant transnational research community across Latin America, inspiring young people with the South American Programming Contest.
A new computational model developed by researchers at Chalmers University of Technology shows that onshore wind is likely to supply around 25% of global electricity by 2050 and solar reaching about 20%, aligning with the 2°C target. However, this falls short of what is required for a 1.5°C goal.
The study reveals that metabolic dysfunction-associated steatotic liver disease (MASLD) is emerging as a major contributor to liver cancer worldwide and in China. Researchers call for integrated global prevention and early detection strategies to address this growing burden.
Researchers from Juntendo University found that AI-based assessment of medical interview transcripts is comparable to clinicians' scores while reducing evaluation time. The study demonstrated strong agreement between AI and human evaluations, with AI showing greater consistency across repeated assessments. This suggests a potential 'AI...
A study by Hector Zenil and colleagues reveals that perfect AI alignment with human values is mathematically impossible. Instead, they propose 'managed misalignment' as an alternative strategy, utilizing competing AI agents with different cognitive styles to dynamically aid or thwart one another.
Researchers used 3D imaging and artificial intelligence to analyze the microscopic structure of coral skeletons, revealing subtle changes caused by Stony Coral Tissue Loss Disease. The study found that Attention U-Net performed best in detecting differences between healthy and diseased corals.
A research team has developed a comprehensive dynamic Gaussian processing framework that provides a complete pipeline from data acquisition to practical application. The framework addresses the high storage cost and fragmented tool chain ecosystem associated with volumetric video technology.
The University of Chicago Data Science Institute has welcomed Millennium as a new Industry Affiliate Partner, aiming to advance curriculum and drive innovation. This partnership will support the design of a new quantitative developer certificate program for students.
The University of Chicago has partnered with AI Research Commons and Microsoft to support high-potential AI startups emerging from the Third Coast Foundry universities. Selected companies will receive technical and go-to-market support, up to $350K in startup credits, and connections to the Bay Area AI investor network.
Global warming poses a significant threat to rice production, which has historically been heat-loving but is now facing its limits. Rice can tolerate temperatures below 82°F and 104°F, but rising temperatures will accelerate beyond these thresholds.
Researchers at the University of Washington developed a system that integrates tiny cameras in wireless earbuds with an AI model, allowing users to ask questions about the scene in front of them. The system achieved high accuracy rates for translation and object recognition, making it a promising technology for future applications.
A machine learning technique identifies optimal spots for tree planting to inform climate mitigation strategies. Optimised afforestation can reduce river peaks by up to 43% while preserving groundwater by up to 60%. The study's findings highlight the importance of data-driven technologies in supporting large-scale, smarter planning.
A team of Weill Cornell Medicine investigators is creating a dual-track program to train clinical oncology fellows and cancer research scientists in AI tools and cancer biology. The goal is to develop scientists who can use the latest tools to deliver on the promise of personalized cancer therapies.
A study of 21 large language models found that they excel at accurate final diagnoses but falter at differential diagnoses, highlighting the need for human oversight in healthcare. The researchers developed a novel measure, PrIME-LLM, to evaluate AI's clinical competency across different stages of reasoning.
Current large language models struggle with early diagnostic reasoning and cannot be relied upon for patient-facing clinical decisions. The study highlights the need for further improvement in these areas to enhance patient care.
The new guidance provides practical routes forward for AI use in every publishing role, promoting accountability, transparency, risk-awareness, and innovation. It introduces structured checkpoints and ready-to-use tools to make responsible AI use practical, not theoretical.
A Drexel University study found that teens are concerned about their attachment to AI chatbots, using them for emotional support and entertainment. The study suggests that these interactions can evolve into addiction-like behavior, affecting their lives offline.
New research suggests that AI-powered price discrimination could lead to hidden, personalised pricing that consumers cannot see or understand, potentially reducing trust and affecting behavior. Regulators are now facing pressure to decide whether such practices cross the line under EU competition law.
Researchers developed a new training technique, HarmonyGNN, to improve the accuracy of graph neural networks in heterophilic graphs. The framework achieved state-of-the-art performance on four heterophilic graphs with accuracy improvements ranging from 1.27% to 9.6%.
A new study analyzed thousands of textual descriptions of two-person social interactions using generative AI, resulting in a comprehensive taxonomy of categories. The findings provide a data-driven framework for understanding the structure of social situations, including associations with conflict, power, and duty.
The study, led by Lucy Liu and L. Mahadevan, shows that adding the right amount of noise to individual robot movements can ease gridlock and improve efficiency in crowded environments. The researchers used computer simulations and experiments with small robots to test their ideas.
A custom-built AI system helped uncover how bacterial communities organize themselves, showing that early moments of a biological transition carry more information than previously considered. The findings bring new insight into the relationship between genotype and phenotype in Myxococcus xanthus.
Paschalidis recognized for developing intelligent systems that remain robust under uncertainty, enabling real-world use in medical data. His work showcases the power of convergent research in creating transformative impact on healthcare.
A new study reveals that AI systems mimic the structure of human judgment but with a more rigid, rule-based approach. The researchers found biases in AI judgments, especially across demographic traits, highlighting the need for awareness and understanding how these systems 'think'.
Researchers identified patient-reported symptoms associated with GLP-1s, including menstrual changes, fatigue, and temperature-related complaints, that may not be fully captured in clinical trials or drug labeling. Nearly 4% of Reddit users reported reproductive symptoms, and fatigue was the second most common complaint.
Researchers develop dynamics-driven models to identify disease transitions before symptoms appear, transforming real-time care and personalized treatment. AI systems analyze health data to detect
Researchers propose a temporally developmental continual learning framework inspired by human brain development, enabling cross-domain learning across perception, motor control, and interaction tasks. The approach achieves stable and strong continual learning performance while reducing network size and mitigating catastrophic forgetting.
A new study introduces AI-based control strategies that ensure local grids remain reliable and resilient. By utilizing Artificial Neural Networks, the system can predict and compensate for grid changes in real-time, outperforming traditional control methods.
Scientists at the University of Virginia Health System have developed a suite of AI-powered tools, called YuelDesign, YuelPocket and YuelBond, to transform how new drugs are created. These tools can design drug molecules tailored to fit their protein targets exactly, even accounting for protein flexibility.
Researchers from Tohoku University examined the role of materials databases in supporting modern artificial intelligence tools used in materials science. They found that database architecture can directly affect AI model performance and reliability. The study aims to improve database quality, connectivity, and develop new AI systems th...
UCLA investigators present new research on targeted drug delivery for colorectal cancer, COVID-19's impact on breast cancer outcomes, and AI in cancer diagnosis. These studies offer insights into overcoming drug resistance, enhancing immune responses, and improving outcomes for patients with difficult-to-treat cancers.
Several open-source AI models consistently produced summaries that were more comprehensive than physician-written versions, particularly in capturing molecular and genetic findings. The study found that Llama 3.1 and DeepSeek performed best among the six evaluated models.
Matei Zaharia's work on open-source systems like Apache Spark, Delta Lake, and MLflow has enabled large-scale machine learning, analytics, and AI at global scale. His innovations have made scalable computing accessible to researchers, nonprofits, and enterprises across every industry.
A study of 1,200 musicians in five countries reveals the 'streaming paradox': while artists are more visible than ever, meaningful income remains elusive. Musicians face growing pressure to create engaging content and manage their online presence.
A new survey by Ohio State University Wexner Medical Center finds that only 42% of Americans are open to using AI in their healthcare, down from 52% in a previous survey. The decline in trust is attributed to concerns about AI's accuracy and the potential for it to replace human judgment in medical decision-making.
National Academy of Engineering President Tsu-Jae Liu presents AI as a tool to expand engineers' problem-solving capacity and develop innovative solutions. The editorial calls for multidisciplinary education integrating AI while addressing its limitations and societal implications.
The article highlights the urgent need to modernize scientific record with AI-powered discoveries trapped in a predigital system. Top-tier research universities face $10-15 million annual subscription expenditures, while author-facing processing charges range from $5,000 to over $11,000 per article.
A team of researchers used AI to analyze 289,513 global publications and isolated 4,177 highly relevant studies on China's major basins. The study highlights crucial milestones in Chinese hydrology and aims to guide future research priorities and sustainable water resource strategies worldwide.
Gladstone Institutes investigator Ryan Corces receives $750,000 to investigate unknown genetic variants contributing to Alzheimer's disease. He aims to identify new drivers and therapeutic targets using artificial intelligence and CRISPR tools.
Researchers developed Sandook, a software-based system that tackles three major sources of performance-hampering variability simultaneously. The two-tier architecture optimizes task distribution for the overall pool while faster schedulers on each SSD react to urgent events.
A new study reveals teachers tend to provide regular support to students they've previously helped, rather than targeting all students equally. This finding highlights the need for AI-powered tools that can help teachers track their interactions and allocate time effectively.
The survey maps egocentric vision's major tasks, including subject understanding, object understanding, environment understanding, and hybrid understanding. It identifies bottlenecks such as limited datasets and dynamic first-person video, and highlights the need for stronger data, clearer task definitions, and deeper integration.
A new study showcases a self-supervised AI framework that can detect concrete cracks with strong accuracy and cross-dataset generalization, outperforming several widely used supervised deep learning models. The framework achieves this without relying heavily on large labeled datasets.
The University of Tennessee at Knoxville has received a $300,000 NSF grant to develop quantum computing-based tools for two-step uncertainty optimization problems. This will enable researchers and industry engineers to quickly determine the potential benefits of quantum computing in solving complex decisions.
A new study from CAMH reveals that AI models used to predict aggressive incidents in psychiatric care can amplify existing social and structural inequities. The model showed higher false positive rates for Black and Middle Eastern individuals, men, and those with unstable housing, potentially leading to more distress and loss of trust.
The UNU Hub for AI-Finance at East China Normal University's Shanghai AI-Finance School aims to leverage AI to boost sustainable economic development and financial inclusion. The Hub will prioritize innovation-driven research, global talent training, and international policy advocacy to address the Global South's financial challenges.
The UNU Hub will foster interdisciplinary collaboration, innovation, and policy engagement to address AI's ethical challenges. It aims to establish trusted frameworks ensuring AI serves as a force for equity, sustainability, and human well-being, aligned with UN Sustainable Development Goals.
The AUMOVIO-NTU Corporate Lab will focus on areas like AI, sustainability, novel materials, and connectivity to develop solutions for safer, smarter, and more sustainable transportation. The joint lab aims to accelerate innovations that can support Singapore's future mobility ecosystem.
A new study from Sultan Qaboos University demonstrates how AI can analyze Oman's Labour Law of 2023, revealing complex interdependencies between its articles. The research identifies influential 'hubs' within the law that may be triggered by changes, enabling policymakers to anticipate broader impact.
The Alliance for Clinical Trials in Oncology is enrolling adolescent and young adult cancer patients in various trials, including genetic services and treatment studies. These trials aim to address longstanding gaps in care and improve outcomes for AYAs with cancer.
University of Utah researchers develop framework for assessing varying levels of automation in psychotherapy, highlighting the importance of weighing risks and benefits. They explore how automation can support therapists without replacing them, using large language models to capture core components of treatment and provide feedback.
HSE researchers train a neural network, GSMFormer-PPI, to predict protein–protein interactions by integrating three types of data: sequence, structure, and surface properties. The model achieves 95.7% accuracy, outperforming popular graph-based models.