Articles tagged with Artificial Intelligence
Researchers developed a low-cost AI tool to forecast demand and optimize medicine allocation in Sierra Leone. The tool increased consumption of allocated medical products by 19% and improved access to essential medicines for over two million women and children under five, with no additional workforce costs.
A new study by Rice University researcher Conner Joyce examines the evolution of cybercriminal communities into politically motivated networks. The research found that online interactions can create strong social bonds that facilitate the spread of political and extremist beliefs.
Researchers developed an ensemble deep learning approach to detect cracks and cold flows on aluminum gas meter lids with over 97% accuracy. The system combines three AI models, significantly outperforming traditional manual checks.
Researchers developed an AI-guided strategy to identify bioactive nucleoside hydrogels for periodontal therapy, using machine learning-based predictive models and experimental validation. The study identified two promising candidates, guanosine monophosphate and deoxyguanosine monophosphate, which successfully formed stable hydrogels w...
Researchers used LLMs to analyze verbal reports of decision-making processes and found that people's own insights are a valuable source of data. The framework also showed that reasons people rely on shift systematically with the structure of the decision problem.
Researchers create custom-fit prosthetic hands with soft magnetic sensors that capture subtle changes in muscle shape and pressure. The system performs consistently and reliably, translating intent into control of a dexterous robotic hand with up to 90% accuracy.
A recent study from University of North Carolina at Chapel Hill found that large language models mimic social behaviors humans display when navigating differences in status and authority. The findings suggest that AI systems can become more accommodating and even comply with unsafe instructions when positioned as subordinates.
Researchers analyzed eight aspects of character portrayal in AI-generated stories, finding that AI models tend to 'play it safe' with their characters, leaving them mysterious or fully understood by the end. Human writers, on the other hand, are more willing to leave questions unanswered and let characters remain open to interpretation.
Researchers built a simple neural network that mimics the brain's processing of visual information, revealing a key role for inhibitory neurons in fine-tuned control. The findings suggest a revised understanding of how the brain processes and represents information.
The article explores AI-driven transformations in digital health, including a novel malaria intelligence platform and the Centers for Medicare & Medicaid Services' Landmark ACCESS program. Genuine institutional change is crucial for safe clinical AI adoption.
A team of physicists, including Giorgio Parisi and Francesco Zamponi, collaborated with AI system Claude to solve a decade-old mathematical problem in physics. They found that two different theoretical approaches to jamming lead to the same physical laws, confirming a surprising relationship.
Prof. Orly Lewis is developing a flexible publishing platform for interactive knowledge environments, while Prof. Nir Friedman is creating an epigenomic liquid biopsy for early detection and monitoring of Metabolic Dysfunction-Associated Steatohepatitis.
A new AI model, SpliceSelectNet, accurately predicts RNA splicing by capturing long-range DNA signals. The model's hierarchical Transformer architecture preserves high computational efficiency while maintaining single-nucleotide resolution, enabling accurate analysis of genomic regions.
A new method uses machine-learning algorithms to detect scatterable PFM-1 landmines over wide areas, providing a first-pass analysis of suspected hazardous areas. The technique requires only a lightweight laptop, drone, and camera, operating without an internet connection.
A chatbot using GPT-4o technology delivers personalized messages to American adults, increasing support for transgender rights and improving attitudes, but effects are short-term. The intervention demonstrates AI's potential as a scalable complement to community-based approaches aimed at fostering inclusion.
Researchers at ISTA have developed a way to guide AlphaFold with experimental data, enabling the model to better reflect physical and biological reality. This approach aims to improve future predictive models by accounting for structural heterogeneity and dynamism in proteins.
Physicists have identified two new superconductors, YRu3B2 and LuRu3B2, using machine-learning to filter material combinations. This breakthrough aims to find a room-temperature superconductor, which could slash global energy consumption and reduce the heat footprint of ICT sector.
University of Jaume I students Pau Montagut and Mario García won first place at the ICRA 2026 robotics conference with an AI model that taught a Toyota HSR robot to perform household tasks. The team's achievement is notable given their undergraduate status, competing against teams of research personnel.
The new photonic architecture harnesses three fundamental degrees of freedom: wavelength, mode, and polarization, achieving 192 parallel computing channels. The chip supports large, reconfigurable convolution kernels up to 13x13, capturing global structural contours while preserving fine details.
Researchers warn that teens' reliance on AI chatbots may bypass opportunities for developing essential relationship skills. The technology offers immediate, nonjudgmental guidance but lacks needed safeguards, potentially reinforcing unhealthy relationship patterns and increasing vulnerability to mental health problems.
The Hebrew University of Jerusalem and Edut 710 have partnered to create a groundbreaking AI-powered living archive, featuring nearly 2,000 survivor, witness, and first responder testimonies. The archive will enable users to search, translate, and explore the accounts through natural language, preserving authenticity and integrity.
A large clinical trial found that an AI support tool improved the quality of clinical documentation and treatment planning, but did not significantly change short-term patient outcomes. The study involved over 9,600 patients in Kenya and used a randomized controlled design to test the effectiveness of the AI tool.
Stanford researcher Ellen Kuhl's AI tool, BurgerAI, creates novel burger recipes optimized for deliciousness, sustainability and nutrition. The burgers were tested in a blinded taste test and found to be comparable to popular fast-food options.
Digital twins are expanding rapidly, using real-time data to simulate and analyze systems before applying them in the real world. The study emphasizes the need for interoperable architectures, machine-readable metadata, and standardized trust frameworks to address challenges such as privacy, cybersecurity, and uncertainty.
The rise of AI-generated content threatens authenticity in the clinical landscape, from AI chatbot impersonations to deepfakes of real physicians. Existing laws and regulations are struggling to keep pace with these emerging challenges.
The review discusses key AI concepts, including algorithms, models, architectures, machine learning, deep learning, and multimodal models. It highlights their clinical applications, such as detection of lymph node metastases, Nottingham grading, biomarker quantification, risk stratification, and prognostic prediction.
The University of Phoenix College of Doctoral Studies has published a new white paper examining the growing AI fluency gap in the workplace. The paper argues that AI fluency is no longer only a productivity issue but a retention issue, as employees are rapidly building AI skills while organizations struggle to keep pace.
Artificial intelligence is being harnessed to integrate multi-omics data from large-scale repositories such as TCGA and GDSC to decode tumour drug resistance. The review advocates for explainable AI frameworks, multimodal fusion strategies, and dynamic liquid-biopsy monitoring to address barriers to clinical adoption.
Researchers developed an AI framework to identify viable target antigens for CAR T cell therapy, using publicly available single-cell RNA sequencing data. The framework showed robust tumor-killing activity in mouse models of multiple cancer types, including melanoma, leukemia, and colorectal cancer.
Researchers developed a new system called Murakkab to optimize agentic workflows for AI applications. It enables developers to describe their intent in high-level terms, automating the selection of models and tools to use, and optimizing hardware configurations in real-time.
The study successfully integrates probabilistic sampling and deterministic computation in generative AI hardware within a single ferroelectric memory array. The technology enables the generation of diverse images reflecting facial attributes, improving area and power efficiency in applications.
The EU project BRISA aims to test safe and clean industrial technologies that reduce risks to human health and biodiversity. The project will protect over 45,000 workers by 2035 and prevent hundreds of premature deaths each year.
Researchers at the University of Washington created PaperTok, a tool that uses AI to help scientists and researchers create short-form videos from research papers. The system generates scripts and video clips in 45 seconds, making it easier for non-experts to engage with scientific content.
JMIR Publications and Jisc have expanded their Flat-Fee Unlimited Open Access Partnership, making APCs free for researchers affiliated with participating institutions. The agreement allows researchers to prioritize open access publishing without financial burdens.
Researchers developed a tandem neural network that rapidly infers key semiconductor material properties from simple transistor measurements, outperforming conventional approaches. The system produces results in under one millisecond with near-perfect accuracy.
A new study has unveiled a high-resolution global map of seagrass, revealing areas of loss and recovery, and providing valuable insights for conservation efforts. The map shows that seagrass ecosystems store approximately 640 trillion grams of carbon, equivalent to the yearly emissions of 500 million cars.
A new article by Trevor van Mierlo highlights the importance of trust in digital behavioral health. Key findings include the need for dynamic governance and verifiable audit trails to address mistrust issues.
Researchers Anna Galler and Bettina Könighofer at Graz University of Technology will use FWF's Astra awards to identify quantum materials for future electronics and develop trustworthy AI systems. Their projects focus on protecting AI systems from risky actions and exploring new materials with unique electronic properties.
A new commission, launched at the Texas Brain Economy Summit, aims to define, measure, and operationalize brain capital, a concept encompassing both brain health and critical cognitive skills. The initiative seeks to address the gap in economic planning and promote brain health as a driver of economic resilience.
Researchers at Tohoku University have created a clearer map for searching for hydrogen storage materials, identifying key physical factors that control their performance. The study suggests adjusting geometry and lattice flexibility to raise capacity while tuning stiffness to keep equilibrium pressure near everyday conditions.
Researchers used AI to analyze mammograms and found that women who developed breast cancer had increasing risk scores over time, while those who did not had stable scores. The study suggests that image-based AI risk scores can predict future breast cancer risk in women without a known genetic mutation or family history.
A self-driving chemistry lab called Flex-Cat has been developed to autonomously search for faster and more selective ways to make important industrial chemicals. The platform combines robotics, high-pressure reactors, and artificial intelligence to identify high-performing catalysts and those that can be programmed to produce different...
Researchers developed RNovA algorithm to identify new PTMs in human cells, expanding capabilities of machine learning in basic biological research. The discovery aims to advance diagnostics and broaden biologists' horizons for cancer and other diseases.
Researchers developed an algorithm, RAPID, to re-identify wild animals using their coat patterns. The algorithm achieved high accuracy rates and demonstrated its speed on various datasets, making it a promising module for wildlife monitoring and ecological analyses.
Researchers have developed a versatile uncertainty-aware AI framework called TRUECAM that provides customizable accuracy guarantees for cancer subtype classifications. TRUECAM outperforms existing approaches to digital pathology AI uncertainty quantification, detecting out-of-scope inputs and improving fairness across sex and race.
A University of Houston engineering professor developed a mathematical model to help decision-makers decide where to spend limited dollars on infrastructure resilience. The model accounts for real-world uncertainty and identifies critical assets to invest in, providing the greatest benefit before disaster strikes.
Thomas Pock's ERC Advanced Grant aims to develop novel generative learning methods and algorithms for computer vision, improving medical imaging by understanding and realistically generating images. The project seeks to establish a close link between data analysis and generation.
A study of funded AI startups reveals occupations with high AI exposure, including office clerks and data scientists, while manual tasks like construction work are less affected. The Occupational AI Startup Exposure (AISE) index also notes that jobs requiring social skills or ethical decision-making may be less likely to automate.
Researchers developed a method combining AI and mathematical models to accelerate MRI scans for breast cancer imaging, achieving improved tumor visibility and high diagnostic sensitivity. The ELITE method has the potential to improve not only MRI scans but also other imaging platforms.
MIT researchers developed a new system-on-a-chip called Gleanmer, which generates highly accurate 3D maps of the robot's environment using Gaussians to represent obstacles. This approach reduces memory and power consumption by up to 99%, making it suitable for lightweight augmented reality headsets.
The US retains its scientific edge but is losing the race to translate discoveries into cures, warns a new report from Cure Innovation Index. Without immediate renewed investment and policy changes, the US scientific edge will not hold.
Researchers develop AI framework using principles of superposition and entanglement to tailor cancer treatment to patients' entire molecular background. The technique predicts health outcomes and suggests genes to target, outperforming standard biomarkers in clinical trials.
The report reveals cutting-edge technologies affecting physical systems, from energy to medicine and manufacturing. These innovations have the potential to make a meaningful impact on pressing challenges like climate change and food insecurity.
Primary and secondary schools in Shanghai are using an AI-based classroom analysis system to support instructional improvement. The platform automatically processes video data and provides theory-informed analytic reports, enabling teachers to track student agency and professional growth over time.
A landmark international competition has revealed that AI systems designed to spot fake faces perform unevenly across demographic groups, with lighter-skinned individuals enjoying higher accuracy while darker-skinned faces are more frequently misclassified. The top-ranked solution combined data curation, mixture-of-experts architecture...
The new report identifies six principles shaping trust in AI: reliability and competence, contextual awareness, transparency and accountability, fairness and integrity, resilience, and relational dynamics. The paper argues that trust must be grounded in demonstrated system performance, governance, and institutional responsibility.
Researchers developed a data-driven method combining GA-BP neural network and chaotic particle swarm optimization to predict and optimize screen-printing parameters for thick-film resistors. The approach achieved an R² of 0.991, recommending optimal settings in 2.38 seconds and reducing resistance deviation within 5%.
A groundbreaking technology called Time to Move (TTM) offers unprecedented control over object and character movement in AI-generated videos. TTM eliminates the need for complex infrastructure or training on millions of videos, making AI video creation more accessible.
A new framework proposes a third way to balance AI innovation and safety: accelerating responsible innovation through technical, organizational, and ethical advancements. The Telus GenAI customer support agent demonstrates how risks can drive further innovation, reducing the need for restrictive safety constraints.
A new research direction proposes building machine-learning systems on top of AI models to detect hidden information and predict behavior. This enables users to supervise the model, control its behavior without understanding the entire mechanism.