Articles tagged with Artificial Intelligence
Comprehensive exploration of living organisms, biological systems, and life processes across all scales from molecules to ecosystems. Encompasses cutting-edge research in biology, genetics, molecular biology, ecology, biochemistry, microbiology, botany, zoology, evolutionary biology, genomics, and biotechnology. Investigates cellular mechanisms, organism development, genetic inheritance, biodiversity conservation, metabolic processes, protein synthesis, DNA sequencing, CRISPR gene editing, stem cell research, and the fundamental principles governing all forms of life on Earth.
Comprehensive medical research, clinical studies, and healthcare sciences focused on disease prevention, diagnosis, and treatment. Encompasses clinical medicine, public health, pharmacology, epidemiology, medical specialties, disease mechanisms, therapeutic interventions, healthcare innovation, precision medicine, telemedicine, medical devices, drug development, clinical trials, patient care, mental health, nutrition science, health policy, and the application of medical science to improve human health, wellbeing, and quality of life across diverse populations.
Comprehensive investigation of human society, behavior, relationships, and social structures through systematic research and analysis. Encompasses psychology, sociology, anthropology, economics, political science, linguistics, education, demography, communications, and social research methodologies. Examines human cognition, social interactions, cultural phenomena, economic systems, political institutions, language and communication, educational processes, population dynamics, and the complex social, cultural, economic, and political forces shaping human societies, communities, and civilizations throughout history and across the contemporary world.
Fundamental study of the non-living natural world, matter, energy, and physical phenomena governing the universe. Encompasses physics, chemistry, earth sciences, atmospheric sciences, oceanography, materials science, and the investigation of physical laws, chemical reactions, geological processes, climate systems, and planetary dynamics. Explores everything from subatomic particles and quantum mechanics to planetary systems and cosmic phenomena, including energy transformations, molecular interactions, elemental properties, weather patterns, tectonic activity, and the fundamental forces and principles underlying the physical nature of reality.
Practical application of scientific knowledge and engineering principles to solve real-world problems and develop innovative technologies. Encompasses all engineering disciplines, technology development, computer science, artificial intelligence, environmental sciences, agriculture, materials applications, energy systems, and industrial innovation. Bridges theoretical research with tangible solutions for infrastructure, manufacturing, computing, communications, transportation, construction, sustainable development, and emerging technologies that advance human capabilities, improve quality of life, and address societal challenges through scientific innovation and technological progress.
Study of the practice, culture, infrastructure, and social dimensions of science itself. Addresses how science is conducted, organized, communicated, and integrated into society. Encompasses research funding mechanisms, scientific publishing systems, peer review processes, academic ethics, science policy, research institutions, scientific collaboration networks, science education, career development, research programs, scientific methods, science communication, and the sociology of scientific discovery. Examines the human, institutional, and cultural aspects of scientific enterprise, knowledge production, and the translation of research into societal benefit.
Comprehensive study of the universe beyond Earth, encompassing celestial objects, cosmic phenomena, and space exploration. Includes astronomy, astrophysics, planetary science, cosmology, space physics, astrobiology, and space technology. Investigates stars, galaxies, planets, moons, asteroids, comets, black holes, nebulae, exoplanets, dark matter, dark energy, cosmic microwave background, stellar evolution, planetary formation, space weather, solar system dynamics, the search for extraterrestrial life, and humanity's efforts to explore, understand, and unlock the mysteries of the cosmos through observation, theory, and space missions.
Comprehensive examination of tools, techniques, methodologies, and approaches used across scientific disciplines to conduct research, collect data, and analyze results. Encompasses experimental procedures, analytical methods, measurement techniques, instrumentation, imaging technologies, spectroscopic methods, laboratory protocols, observational studies, statistical analysis, computational methods, data visualization, quality control, and methodological innovations. Addresses the practical techniques and theoretical frameworks enabling scientists to investigate phenomena, test hypotheses, gather evidence, ensure reproducibility, and generate reliable knowledge through systematic, rigorous investigation across all areas of scientific inquiry.
Study of abstract structures, patterns, quantities, relationships, and logical reasoning through pure and applied mathematical disciplines. Encompasses algebra, calculus, geometry, topology, number theory, analysis, discrete mathematics, mathematical logic, set theory, probability, statistics, and computational mathematics. Investigates mathematical structures, theorems, proofs, algorithms, functions, equations, and the rigorous logical frameworks underlying quantitative reasoning. Provides the foundational language and tools for all scientific fields, enabling precise description of natural phenomena, modeling of complex systems, and the development of technologies across physics, engineering, computer science, economics, and all quantitative sciences.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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.
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.
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.
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.
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.
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 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.
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 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.
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 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.
Researchers develop a novel deep learning-enabled method for high-speed, high-precision 3D surface measurements. The technique uses frequency-domain multiplexing and achieves speeds 16 times faster than the sensor's native frame rate.
Experts argue that large language models require symbolic representation to excel in complex tasks, citing examples like the Pirahá people and Leibniz's calculus notation. The proposed approach, known as neuro-symbolic synthesis, combines statistical intuition with human-designed symbol systems for efficient reasoning.
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.
The new book, Monster Transformation, argues that employees are key to overcoming transformational hurdles. By uncovering unique competencies and empowering them, organizations can break through challenges and succeed in a rapidly evolving space. The book offers a story-driven approach to meeting the needs of the current technological ...
Researchers from the University of Bath and University of Hong Kong found that additive advice bias is common in conversations, social media, and AI chatbots. This bias can leave people feeling more overwhelmed than helped, with well-intentioned tips piling on extra tasks.
Researchers develop AI-based model for structural analysis of antibodies, offering precision in less time. The S2ALM model integrates sequence and structure, predicting missing information with high accuracy.
The study combines decision making and machine learning to improve robot learning for water analysis. The Random Forest Classifier achieved an accuracy of 69% which improved to 73% after applying Synthetic Minority Over-sampling Technique (SMOTE) and tuning hyperparameters. The robotic system can detect, analyze, and distinguish drinki...
The new model can predict how well any given molecule will dissolve in an organic solvent, helping chemists choose the right solvent for reactions. The researchers trained two models on a comprehensive dataset and found that their predictions were two to three times more accurate than the previous best model.
The grant aims to support novel applications of data visualization technology that benefit various stakeholders in the research ecosystem. Successful applicants will receive up to £25,000 for their innovative tech ideas.
OEC allows satellites to process data directly, reducing latency and bandwidth constraints. However, research faces challenges due to limited energy storage, heat dissipation, and launch costs.
A new AI hybrid reading strategy for screening mammography reduces radiologist workload by 38% while maintaining comparable cancer detection and recall rates. The strategy incorporates uncertainty quantification, allowing AI to provide certainty estimates for predictions.
A University of Washington study compared AI developers with climate advocates, revealing divergent values and perceptions on topics like ethics. Climate activists saw limited use cases for AI, focusing on automating tasks and connecting communities with nature, while developers had a broader view of the technology's potential impact.
Researchers have discovered a new material that matches or exceeds the performance of commercial iridium-based materials, but at a fraction of the cost. The breakthrough was achieved using a powerful new tool called a megalibrary, which rapidly screened vast combinations of metals to find a suitable alternative.
A new study by UC Davis researchers reveals that popular GenAI browser assistants collect and share sensitive data without users' knowledge. The study highlights the need for stronger safeguards and transparency to protect user privacy online.
A $5 million NSF grant is powering AI innovations in Pegasus, a widely used workflow management network. Researchers aim to develop intelligent workflow management tools that adapt to evolving user needs and dynamic resource conditions.
MIT researchers have developed a method to reveal the inner workings of protein language models, which can accurately predict proteins suitable for drug or vaccine targets. By analyzing sparse representations of proteins, they identified key features that drive these predictions.
A new study suggests that adopting AI in high-stakes settings like hospitals and airplanes requires evaluating algorithms and human decision-making simultaneously. The study found that accurate AI predictions improved participant performance by 50-60%, but inaccurate predictions led to a 100% degradation in proper decision making.
Researchers developed an AI framework to map interactions between content and algorithms on digital platforms, reducing the spread of misinformation. The system would allow users and platform operators to pinpoint sources of potential misinformation and promote diverse information sources.
The 34th International Joint Conference on Artificial Intelligence (IJCAI) will take place in Montreal, Canada, from August 16 to 22, 2025. The conference aims to showcase the frontiers of artificial intelligence research and applications, with a focus on AI's impact on society.
Researchers used machine-learning models to design nanoparticles that can deliver RNA to cells more efficiently. The approach accelerated the identification of optimal ingredient mixtures in lipid nanoparticles, leading to better delivery vehicles for RNA vaccines and mRNA therapies. This could dramatically speed up the development of ...
The study reveals that East and West coasts, Great Lakes and Gulf regions face the highest risk of weather-induced blackouts. The nationwide Power System Vulnerability Index (PSVI) tool identifies areas at increased risk of power outages, enabling policymakers to prioritize preparation for long and frequent power outages.
A recent study found that school-based online surveillance companies are extensively monitoring students' digital behavior beyond school hours, often using AI with little human oversight. The research team identified 14 companies marketing such services, citing concerns about privacy, equity, and oversight.
Isabel Angelo will refine and expand machine learning-driven pipelines for detecting exoplanets, focusing on subtle or unconventional candidates. Her work aims to uncover rare or unexpected planetary systems using cutting-edge AI and astrophysical modeling.
Experts from across industries and disciplines gathered to assess the current state of cybersecurity through a multidisciplinary lens. The workshop explored emerging technologies and the intersection of technology and policy, highlighting the need for a unified ecosystem to address persistent challenges.
University of Houston researchers are developing an AI-powered dashboard for Florida food pantries, aiming to streamline stakeholder collaboration and distribute resources to families in need. The tool will enable emergency coordinators to respond quickly to spikes in demand, prioritizing the needs of vulnerable populations.
Researchers developed a novel approach called R3DG that analyzes representations at varying granularities to capture nuanced emotional fluctuations and reduce computational complexity. This framework demonstrates superior performance in multiple multimodal tasks, including sentiment analysis, emotion recognition, and humor detection.
Researchers designed over 36 million compounds using generative AI algorithms and computationally screened them for antimicrobial properties. The top candidates show promise against Neisseria gonorrhoeae and Staphylococcus aureus (MRSA) by novel mechanisms that disrupt bacterial cell membranes.
Researchers at Radboud University Medical Center found that AI detects breast cancer on mammograms more frequently than radiologists. The study analyzed 42,000 breast scans and showed that one radiologist working with AI detects more tumors than two radiologists alone.
Researchers create digital twin facility management system for relocatable modular buildings, improving asset management and decision making. The DT-FMS enhances the lifecycle management of RMBs, minimizing waste and maximizing value through reuse and reconfiguration.
Researchers have developed a new AI approach called HEAT-ML that accelerates calculations of magnetic shadows in fusion vessels, enabling faster design and operation. This breakthrough could lead to significant improvements in fusion power generation and potentially limitless clean energy.
Researchers leverage machine learning to accelerate solid-state battery development, overcoming material interactions and interface instability. AI-powered strategies optimize battery management systems and decode ion transport for improved energy storage.