Articles tagged with Artificial Intelligence
A KAIST research team developed a next-generation world model that learns executable theories from observation alone. The Neural Theorizer (NEO) model discovers reusable primitives and composes them into executable programs to explain new situations.
A new study found that four AI-powered photo-based calorie-tracking apps underestimated the calories and fat content of meals by about a third. The researchers used standardized photos of 102 meals prepared in a controlled metabolic kitchen to evaluate the apps' accuracy.
Researchers at Harvard John A. Paulson School of Engineering and Applied Sciences have developed a new AI framework called Orla that streamlines building and running AI workflows. In tests, Orla reduced computing costs and response times without sacrificing quality.
The health tech industry is evolving with AI-powered wearables that enable real-time data interpretation, reducing centralized infrastructure demands. Pharmaceutical AI tools like NoHarm automate reviews, freeing up resources for medication errors. These innovations transform healthcare, improving care and patient outcomes.
A team of researchers at Harvard and Max Planck Institute have developed three new functional components for photonic microchips using an inverse design algorithm. The compact designs are about 500 times smaller than conventional designs and offer a path toward higher-performance integrated light technologies.
The City University of New York has received an $18.1 million NSF award to create a cloud-programmable national laboratory that uses artificial intelligence and robotics to speed the discovery, design, and production of advanced bio-inspired materials. Researchers nationwide will have remote access to automated tools for developing sus...
Twenty NII papers were accepted at ACL 2026, including two that won the Best Theme Paper and Outstanding Paper awards. These achievements lay the groundwork for developing trustworthy AI and advancing research in explainability and transparent AI.
Rice University has received a nearly $20 million NSF award to lead an AI-powered materials laboratory that aims to accelerate the manufacturing of electronic and quantum materials. The project, READINESS, will integrate automated synthesis equipment, robotic systems, and digital twins to minimize trial-and-error experimentation and en...
The study of Alan Turing's unpublished short story 'Pryce's Buoy' reveals a more nuanced understanding of the computer scientist. The six-page fragment challenges the stereotype of Turing as socially unaware and isolated, instead portraying him as playful, funny, and emotionally expressive.
The University of Tennessee has received a $20 million NSF grant to establish ATHENA, a national network of AI-powered laboratories for accelerating scientific discovery. The initiative aims to revolutionize materials discovery by accelerating design, synthesis, characterization and autonomous optimization of advanced materials.
Researchers have developed an AI-powered framework that combines multiple AI technologies with automated experiments to accelerate the discovery of advanced energy materials. The '4th+ paradigm' approach enables near-atomic-level accuracy in predicting material properties and rapidly analyzing experimental data.
iFuture, a new academic journal, debuts at WAIC 2026, focusing on foundational AI theories and cutting-edge interdisciplinary research. The journal's supporting platform Oscholar uses AI to support scholarly communication and collaboration, aiming to become a globally recognized high-impact platform for scholarly innovation.
Researchers used AI and single-cell technology to study the 3D genome in brain cells from individuals with Alzheimer's disease. They found increased compartment mingling, reduced gene activity, and altered brain cell organization. The study identifies 3D genome organization as a key layer of Alzheimer's biology.
A UMaine-led research team has been awarded the inaugural DOE Genesis Mission to develop AI-powered models that simulate the impact of microbes on underground chemical reactions. The project aims to improve predictions in groundwater management, environmental remediation, and energy infrastructure planning.
A new study using remote sensing and machine learning found that mining for green technology minerals has unexpected consequences on biodiversity. The research revealed that commodities such as lithium and cobalt have the highest biodiversity risks despite lower levels of forest loss.
Researchers developed an AI that navigates ships using human-like decision-making, handling complex situations such as narrow channels and multiple vessels. The AI achieved compliance with maritime traffic rules and demonstrated unexpected behavior like local navigation customs.
Researchers at Japan Advanced Institute of Science and Technology developed a new computational method combining neural networks with Bayesian localization, achieving accurate predictions while reducing computational cost. This breakthrough enables the high-precision analysis of large-scale materials and complex chemical reaction systems.
A novel cross-modal fusion framework integrates low-altitude drone RSI with ground robot LiDAR-inertial measurement unit (IMU) odometry to create accurate digital models of orchards. The system achieved localization accuracy on the order of a few centimeters, demonstrating robustness to seasonal variations and long-term drift.
The paper proposes 'transcending natural evolution' by using technology to augment human abilities, bridging the gap between biological and algorithmic iteration. Recent advances in AI, robotics, and bioelectronics are blurring the lines between digital and embodied intelligence.
Researchers designed an end-to-end workflow to identify new blue OLED materials using AI and quantum chemistry. They developed a virtual library of over 19,000 molecules and used machine learning to select promising candidates, which were then experimentally evaluated and found to have high color purity and efficiency.
Researchers at Worcester Polytechnic Institute are launching a three-year project to train high school teachers in quantum information science and cybersecurity. The program aims to inspire young people to pursue education and careers in emerging science and technology fields.
Two Rice University teams will use AI to advance quantum computing and sustainable biomanufacturing. One project aims to overcome computational bottlenecks in quantum chemistry, while another develops an AI engine for microbial production of isoprenoids.
The PPPL-led project will use AI to autonomously operate high-power gyrotrons, a crucial method for heating plasma in fusion systems. Researchers from multiple institutions will collaborate on this project.
Two Lehigh University AI projects have been selected for funding from the Department of Energy's Genesis Mission. The RIVER-AI project will improve flood- and water-level prediction, while the REACT project aims to accelerate reactor-scale fusion energy by developing an AI-enabled digital twin. These awards strengthen Lehigh University...
A recent study from Duke University and industry collaborators found that at least 1% of resumes submitted to a popular hiring platform contained hidden instructions designed to trick the AI system. The trend is accelerating quickly, with the rate increasing sevenfold between July 2024 and November 2025.
A Tulane University team is using AI to discover new superconductors, which could improve the nation's electrical grid, medical imaging, and quantum computing. The project combines high-fidelity calculations, physics-aware AI, and experimental measurements to accelerate discovery.
Researchers developed a framework to integrate AI into hospitals, emphasizing patient care, staff experience, and economic sustainability. The Total Mission Value framework aims to ensure high-quality patient care remains the top priority amidst AI's transformative potential.
Researchers developed an AI platform, PeptiVerse, to predict key properties of peptides, enabling early assessment of drug potential. The open-source platform allows users to evaluate ordinary and chemically modified peptides, streamlining the discovery process.
A new study reveals that AI chatbots' popularity stems from their interactive, personalized, and imaginative nature, allowing users to engage with them as trusted companions. The study warns of the potential dangers of these chatbots, including their ability to persuade users to believe false or unethical information.
Researchers developed an AI framework for detecting and managing microplastics in wastewater treatment systems. The system uses computer vision and machine learning to predict removal efficiency and identify pollution sources. While AI can complement chemical analysis, major challenges remain before these tools can be widely deployed.
Researchers have successfully controlled individual molecule spins using electrical signals, opening up new prospects for fast and compact quantum components. This approach enables precise control of quantum-mechanical states without the limitations of magnetic fields.
A recent study by Annabelle Roberts found that consumers tend to distrust others after a negative experience, and this distrust can be difficult to overcome. The researchers conducted 21 studies involving nearly 12,000 people and discovered that people learn attitudes from a single trust interaction, whether positive or negative.
A new study finds that weak AI regulation can lead to less safe products, as companies may offload safety burdens onto downstream developers. However, a balanced approach regulating both general-purpose AI producers and downstream companies could yield safer products and greater profits for all parties involved.
Evo 2 analyzes and generates DNA sequences across various forms of life, marking a major step toward unified AI for biology. The model can predict harmful genetic variants and generate biologically realistic DNA.
NEW Community facilitated international outreach and scholarly exchange during Goldschmidt 2026, focusing on artificial intelligence, environmental science, and sustainability. The platform presented its potential role in interdisciplinary collaboration and open scholarly communication.
Researchers developed an AI-assisted technique to identify and treat malignant brain tumors by targeting multiple arterial pedicles. The approach successfully covered over 85% of each tumor in three patients, reducing delivery outside the intended treatment area.
A research team developed an AI-based system that predicts passenger movements using CCTV footage, allowing for proactive prevention of subway door entrapment accidents. The system achieved a high accuracy of 97.58% in real-time classification.
A research team led by Prof. Jun Won Choi of Seoul National University College of Engineering independently developed SafeDrive, an end-to-end autonomous driving AI model. The work has been recognized for its impact on the field of autonomous driving technology.
A technology has been developed that allows artificial intelligence to inversely determine process conditions for quantum-dot light-emitting diode devices. The technology roughly doubled efficiency and extended operational lifetime more than 40-fold when applied to actual devices.
Researchers are exploring innovative technologies to improve disease diagnosis and treatment. AI models have shown promise in speeding up detection and treatment discovery for rare diseases. Meanwhile, electronic noses are being developed for non-invasive cancer screening.
A researcher at the University of Minnesota Medical School has been awarded a $3.7 million NIH grant to develop robust AI models for primary open-angle glaucoma prognosis. The project aims to improve patient outcomes by identifying patients at high risk of vision loss earlier and more accurately.
A new approach combines AI with high-resolution mass spectrometry and toxicology databases to predict biological effects of environmental chemicals. This framework helps researchers prioritize candidates for laboratory testing and health risk assessment.
This volume of SLAS Technology highlights novel laboratory technologies, open-source software, and disease-specific tools for advancing life sciences research and development. The journal emphasizes the importance of education, knowledge exchange, and global community building to drive innovation in biomedical research.
A new review of existing research found that AI-based nursing interventions can identify patients at greater risk of complications, reducing unplanned hospital visits and potentially lowering healthcare costs. However, there is a need for further research on the impact of AI on patients' emotional well-being.
The researchers developed an image-aided terminal guidance attitude control scheme to tackle airframe disturbances and EFP trajectory dispersion in multirotor strikes. The system realizes finite-time convergence of attitude errors and real-time compensation of wind gusts and model uncertainties, greatly improving aiming stability.
Northwestern University engineers created a drone called Phantom Twist that harnesses motion blur to blend into its surroundings. The drone spins up to 25 times per second, making it difficult for humans to see clearly, and can potentially monitor wildlife or inspect infrastructure with less disruption.
The European Law Institute has approved its first comprehensive framework for dealing with digital assets and personal digital content after death. The rules provide a dual legal framework recognizing the need for protection, privacy, and dignity in digital inheritance.
A recent study found that patients perceive medical professionals as more credible when AI agrees with their diagnosis. However, disagreement can increase perceptions of medical uncertainty and doctor laziness. The researchers suggest strategies to communicate AI disagreement effectively and reduce patient mistrust.
Researchers have developed NovoTags, synthetic fluorescent protein tags that can bind to bright fluorescent dyes with high specificity and affinity. These tags enable multicolor imaging of proteins inside cells, expanding the toolkit for advanced light microscopy techniques.
Researchers have developed a new version of the Daydreaming algorithm, which combines learning and cleaning to improve artificial memory systems' reliability even with biased data. The algorithm focuses on differences between pixels, allowing it to work effectively with strongly biased data, similar to real-world conditions.
Researchers explored how AI and metabolic modeling can inform effective biocontrol strategies to combat antimicrobial resistance in built environments. Microbial biocontrol using 'good' microbes has shown promise, but inconsistent outcomes are due to various factors, including genetic differences and environmental stressors.
Researchers developed DeepHHF, an AI model that identifies patients at high risk of heart failure up to five years in advance. The model analyzes standard ECG recordings and detects subtle abnormalities that are often imperceptible to the human eye.
A new study uses machine learning to predict chemical toxicity in rare and endangered species, reducing the need for direct biological testing. The model achieved strong performance predicting acute and chronic toxicity, with life stage being a key factor.
UCSF Health Converge accelerates development of AI tools for real-world care delivery by co-developing solutions with select companies. The program focuses on building patient-centered, clinically effective AI solutions that align with UCSF Health's standards.
A team of researchers from the University of Cambridge and UC Santa Barbara developed 'adversarial' mathematical systems to map out where AI prediction breaks down. They identified two main reasons why machine learning fails: algorithmic limitations and hidden patterns in complex systems.
A new study from UT San Antonio finds that emergency call takers' word choice can predict depression and anxiety symptoms, while positive expressions are often suppressed in high-stress professions. The research uses natural language processing to evaluate the psychological well-being of a critical but under-researched workforce.
Researchers are developing an AI-driven controller for hybrid microgrid systems that integrates multiple energy sources and storage systems. The system aims to increase efficiency of electrical grids used for data centers and other mission-critical loads.
AI model improves cardiac MRI interpretation, while immersive VR simulators aid poststroke rehabilitation. Meanwhile, menopause tracking apps offer empowerment but also pose risks due to inaccurate information and targeted marketing.
A new 3D computer model developed by the University of Surrey has shown how Pseudomonas aeruginosa grows and spreads its protective layer under constant fluid flow. The model's accuracy was validated through laboratory experiments, demonstrating potential for faster and smarter ways to understand bacterial behavior.
A new AI-based system called ShadowSense learns from real-world data to predict short-term changes in solar module power output. The system outperforms conventional methods with an accuracy rate of over 92%, providing valuable insights for electricity grid management.