Articles tagged with Artificial Intelligence
A new study highlights the growing dependence on 'black-box' tools in science, which can process enormous amounts of information but lack transparency. Researchers recommend prioritizing open-source software, benchmarking proprietary tools, and intensifying efforts towards open science to address this issue.
Researchers developed an AI framework that optimizes ship routes and speed profiles to reduce fuel consumption and peak air-pollutant exposure. The system achieved 20-35% improvement in optimization performance while reducing peak pollutant exposure by 34-78%.
A new AI model, EarlyDetect, can detect precursor signals of active region emergence in the Sun's acoustic activity and magnetic field, forecasting solar eruptions nearly nine hours in advance. This technology has the potential to allow satellite communications companies or power grid companies to prepare for solar storms.
The PolyU developed AI Virtual Patient Simulation System combines multimodal data from genomic, medical imaging and clinical records to create a digital twin model tracking real-time changes in a patient's condition. It predicts the effectiveness of different cancer treatment options and supports personalized medical solutions.
Clinical AI innovations are enhancing healthcare capabilities through competition-driven development, customization, and cost-effectiveness. Modern technologies, such as rehabilitation robotics and AI-powered robots, are personalizing treatment plans to improve recovery rates and reduce healthcare costs.
Professor Fioretto's team develops AI-driven methods for autonomous power grid topology control, improving resilience and efficiency. The Genesis Mission Platform provides access to advanced AI models and high-performance computing resources.
A team of researchers developed a reusable magnetic sensing platform combining surface-enhanced Raman scattering with machine learning to detect trace uranyl ions. The system maintained its detection limit even in complex aquatic environments, with strong selectivity and resistance to interference.
By focusing on the specific regions of antibodies responsible for recognizing disease targets, the AI model improved binding affinity prediction and required fewer computational resources. This approach is similar to human-language AI models, where smaller domain-specific models trained on high-quality data can outperform larger ones.
A longitudinal study of Reddit posts since 2022 reveals that trust in generative AI is generally higher than distrust, with 31% of posts expressing trust and 26% expressing distrust. The study's findings suggest that attitudes toward AI have remained divided over the past four years.
The study proposes a public health agenda for AI to improve delivery of proven health interventions through patient identification, outreach, and care coordination. Government leadership, cross-sector partnerships, and sustained investment are essential for realizing this potential.
Researchers developed an AI model that analyzes routine whole histopathology images to predict cancer subtype, genetic mutations, and survival outcomes across 32 solid cancers. The model achieved a strong predictive accuracy score for TP53 mutation detection and demonstrated the ability to infer RNA expression levels and tumor taxonomy.
A national survey reveals half of sleep-deprived nursing moms rely on AI for breastfeeding advice, often leading to preventable health scares. Pediatricians emphasize the importance of human guidance and expertise over AI-driven solutions.
Researchers developed a novel semiconductor integration platform, BBCube, combining advanced chip packaging, high-density interconnects, and improved thermal management. This enables more precise chip placement, faster communication, and efficient cooling for powerful and energy-efficient AI accelerators.
The review highlights security and ethical risks in AI-powered embodied systems, including hallucinations, synthetic forgeries, and adversarial attacks. It proposes a roadmap toward dependable embodied intelligence through safeguards like contextual checking, forgery detection, and risk-aware reasoning.
Researchers combined AI, genetics, and gut microbiome analysis to shed light on intestinal fibrosis in Crohn's disease. They identified a shared set of 43 key genes linked to disease progression and found that bowel fibrosis is driven by ongoing immune activation, damage to the intestinal lining, and changes in gut bacteria.
Hankelformer improves forecasting of extreme weather events by capturing local spatiotemporal dynamics and enhancing feature invariance. It achieves state-of-the-art performance on multiple datasets, including energy, transportation, and extreme weather domains.
A pilot study by Bayes Business School found that shoppers using digital screens on their supermarket trolleys spent up to 32% more than those without. The study recorded significant spikes in spending and consumption among 'superusers' who engaged with the technology most.
The open-source image analysis pipeline accurately measures brain tissue changes in animal models, reducing variability among thousands of scans. The tool has the potential to improve early-stage evaluation of new therapies for acute ischemic stroke.
Large language models exhibit a preference for higher-quality options first, but later options when quality decreases. Models also show unique biases in name preferences, regardless of context, making them harder to predict and prevent.
A new survey finds that opposition to local data centers has risen sharply among US adults, with 61% opposing construction in their areas. Meanwhile, views on artificial intelligence remain stable, with 39% expressing concerns about its impact.
The DOE has committed funding for UNITY-3, a cutting-edge breeding blanket test facility at ORNL, with Kyoto Fusioneering relocating its US headquarters to Tennessee. This partnership establishes a shared commercial-scale testing infrastructure to validate critical systems and train digital twins of breeding blanket concepts.
Arkansas researchers used a machine-learning approach to study the organization of neighboring genes in bacteria. The novel method distinguished disease-causing strains of Enterococcus cecorum from nonpathogenic ones by analyzing how neighboring genes are organized within the bacterial genome. This new approach may provide valuable clu...
Researchers have developed a machine learning model that can help clinicians assess uncertain variants in prenatal genetic testing, providing more accurate diagnoses and clearer information for families. The approach uses tissue-agnostic episignatures to overcome limitations in epigenetic testing.
The KAIST research team developed an explainable AI technology that detects patterns of foreign-linked influence operations in online news comments. The model identifies 23,998 accounts exhibiting patterns consistent with public-opinion manipulation, targeting division and confrontation within Korean society.
Researchers have developed an AI semiconductor device that temporarily remembers recent inputs while autonomously forgetting older information. This technology enables continuous processing of complex time-series signals without a separate reset process, representing a key innovation for low-power edge AI systems.
Researchers at Aalto University developed an AI model that accurately explains how humans read, using reinforcement learning to recreate reader choices. The model can power smarter AR displays and tailor complex texts to different readers and situations.
A team of researchers found that humans and AI process language similarly during the initial stages of reading, relying on next-word predictions. However, as passages become more complex, human processing differs from AI, highlighting areas where human and machine language understanding diverge.
Florida Atlantic University's video compression technology has been acquired by Dolby Laboratories, contributing to the international VVC Video Compression Standard and reducing video data requirements by approximately 50% while maintaining visual quality. The portfolio comprises 683 IP assets, including 250 granted patents worldwide.
Halide cathode materials, long overlooked due to dissolution in liquid electrolytes, now enable dramatically higher energy densities through a fundamental shift in battery chemistry. Key strategies include multi-electron reactions, protective coatings, and nanostructuring to address stability issues.
A new study by Dr. Wu Yuan's team reveals that retinal AI can lose accuracy in high-altitude populations due to altitude-associated domain shift. MIXFound, a lightweight framework, offers a practical solution to improve robustness and correct for these differences.
The SNU team introduces Cluster-aware Upcycling, leveraging semantic structure of pretrained models to promote specialization among expert modules. This approach outperforms conventional Sparse Upcycling on image-text retrieval and various image classification benchmarks.
The new integrations provide enterprise AI agents direct access to live, structured research data from Dimensions' 430M+ interconnected records. This allows for AI-assisted analytics across one of the world's most comprehensive linked views of global research activity.
Assistant Professor Yingxue Zhang's project aims to develop urban AI models that can efficiently process vast amounts of human-generated data to optimize commute times, traffic safety, and more. The model will utilize offline reinforcement learning to tackle spatial-temporal dynamics in urban life.
Prof. Haim Sompolinsky receives the 2026 Dirac Medal for pioneering contributions to equilibrium statistical mechanics and non-equilibrium statistical mechanics. His work helps establish the field of theoretical neuroscience, elucidating how collective activity supports memory, computation, and learning.
New York's Empire AI Beta has officially launched, providing world-class AI computing power to researchers across the state. The initiative has served as a model for the federal National Science Foundation's State and Regional AI Infrastructure Hubs, which aim to build out regional AI research infrastructure and shared research capacity.
Recent studies examine the effectiveness of drones for prescription delivery and AI models in healthcare, raising questions about their impact on access and misinformation. Regulations around expertise and online content are also being reevaluated to address the root causes of these issues.
Non-invasive approaches are expanding options for assessing portal hypertension, with elastography techniques and biochemical markers showing high sensitivity and specificity. AI-powered predictive models combine clinical data to improve diagnosis, but should not replace invasive HVPG, which remains the gold standard.
A new study suggests that artificial intelligence can enhance the implementation of Medicaid work requirements by helping state agencies keep eligible individuals enrolled. AI tools can analyze existing databases to verify compliance or exemption status, reducing documentation difficulties and administrative complexities. However, huma...
Researchers developed a machine learning framework that predicts microbial contamination and estimates potential public health risks from routinely measured water quality indicators. The approach, called ML-QMRA, achieved high accuracy in predicting pathogen concentrations and their associated health risks.
UniSpec delivers lossless LLM acceleration without retraining while adapting automatically to different hardware platforms and multilingual workloads. The framework achieves up to 2.6× faster inference than existing methods across multiple models, hardware, and languages.
Researchers at Florida Atlantic University are developing a sustainable, AI-guided system to remove excess phosphorus from freshwater systems, preventing harmful algal blooms. The technology combines durable 3D-printed structures with AI-powered monitoring and optimization.
The Altmetric MCP brings real-world engagement data into AI workflows, capturing broader research impact beyond citation counts. This enables medical affairs teams and researchers to demonstrate the value of their work across societal platforms.
Researchers have found a new compound that promotes joint health and reduces inflammation-related genes in a model of osteoarthritis. The drug, M04, has shown promise as an innovative OA therapy by slowing down the disease process, giving people more years of pain-free living.
Assistant Professor Haonan Ling is exploring virtual solutions to biomanufacturing for the Genesis Mission, which aims to strengthen America's energy industry and national security. The project could significantly accelerate the development and deployment of sustainable biomanufacturing for fuels and chemicals.
The NFDI4Earth consortium facilitates access to environmental and climate data, while the DAPHNE4NFDI consortium preserves large-scale measurement datasets for long-term reuse. The NFDI-MatWerk and FAIRmat consortia develop common standards and digital tools for materials research, enabling faster and more targeted material development.
Researchers at Stanford University have developed an AI-powered tool called Evo 2 that can design novel phages to kill bacteria, including E. coli. The tool has already synthesized nearly 300 new phages and identified 16 exceptionally effective ones.
Researchers developed a programmable dynamic memtransistor that can process data at different speeds, reducing prediction errors by up to 40-fold. The technology enables accurate information processing even when input speeds vary.
New research suggests that collecting and spraying rainwater on rooftops during hot weather can significantly reduce energy demand for air conditioning and lower urban temperatures. The study found that this approach could cut the number of heatwave days overall and lessen the intensity of extreme heat events.
A new study found that six leading AI models exhibit a strong masculine bias in generating stories about animal characters, with only 2% being female. The models use neutral pronouns or avoid them altogether to reduce gender bias, but ultimately erase non-masculine identities.
A new AI triage agent will be embedded in Vanderbilt Health's EHR to quickly evaluate patients with Alzheimer's disease. The system will analyze chart information, flag missing details, and recommend referrals for priority or standard evaluation, aiming to reduce wait times from weeks to days.
A new AI model developed by Japan Advanced Institute of Science and Technology identifies the most relevant information in videos, significantly reducing analysis time. The model achieved state-of-the-art performance while using only 15.42% of available visual features and reduced processing time per video by approximately 65%.
Researchers developed GridFusionX, an AI tool that improves forecasts of electricity demand and renewable energy generation. The system reduces uncertainty in predictions, allowing grid operators to plan reserves more efficiently and respond proactively to sudden changes.
Jiaqi Ma's $660,307 grant aims to develop tools for understanding how individual components of training data affect large AI systems. This project will improve the performance and reliability of widely used technologies like language models and recommendation systems.
A WVU study found that ChatGPT-5 Pro can generate realistic psychiatry vignettes with strong diagnostic details but emphasizes the need for human-centered approach to ensure patient safety. The researchers recommend incorporating these vignettes into digital psychiatry curricula with faculty moderation and safeguards.
Researchers have developed a new photonic architecture that enables scalable spatiotemporal interleaving networks for high-density integrated photonic convolution. The SPIN (Spatiotemporal Photonic Interleaving Network) framework reduces waveguide complexity and increases programmability in wavelength-domain interleaving, enabling comp...
Ziyu Yao, Assistant Professor at George Mason University, has received a $674,100 NSF CAREER Award to advance AI interpretability research in code generation. She aims to develop a framework for mechanistic interpretation of language models and explore methods to improve code generation through interpretation-informed approaches.
Researchers at Harvard John A. Paulson School of Engineering and Applied Sciences developed an AI recommendation model that incorporates reinforcement learning to adjust to the uniqueness of each user. This approach improved human-AI performance over traditional one-size-fits-all decision support.
A qualitative study found social license for AI in healthcare is conditional and dynamic, influenced by structural, performance, and relational factors. The findings provide evidence-based recommendations for designing and implementing AI tools that support both consumers and clinicians.
Papers AI provides a fully integrated AI assistant that reads project drafts, datasets, and references together, reducing the need to re-explain context. The platform supports various file types, including Word, Markdown, Jupyter notebooks, and CSV files, and ensures data never leaves users' hardware.
The Smart QS Hackathon 2026 aims to explore innovative applications of Artificial Intelligence (AI) in Quantity Surveying (QS) through cross-sector collaboration, facilitating the intelligent transformation of the construction industry. Participants will have access to AI training sessions and workshops, as well as Cyberport's computin...