Articles tagged with Artificial Intelligence
Researchers from the Weizmann Institute of Science and Intel Labs have developed new algorithms that allow AI developers to combine the power of different AI models, speeding up large language model performance by 1.5-2.8 times. This enables faster collaboration between models, reducing processing power costs and improving overall effi...
Georgia Tech is building a new artificial intelligence-centered supercomputer called Nexus, which will integrate cutting-edge hardware and software services to unify scientific research workflows. NCSA is lending its expertise to assist in the development of this national-scale computational resource.
The Idaho National Laboratory is using Microsoft's Azure cloud and artificial intelligence to automate the nuclear permitting and licensing process. The tool generates reports required for construction permits and operating licenses, streamlining efficiency and accelerating deployment of advanced nuclear technologies.
Scientists use human-AI collaboration to tackle complex questions in condensed matter physics, leveraging machine learning algorithms to identify patterns in simulation data. This approach successfully models the behavior of frustrated magnets and sheds light on quantum computing and gravity.
Researchers have developed a groundbreaking technique that maps temperature in three dimensions within biological tissue using invisible light and artificial intelligence. This new technology has the potential to improve early disease detection and treatment monitoring without the need for costly or invasive imaging technologies.
A new approach by MIT researchers allows scientists to efficiently estimate how combinations of treatments will affect a group, enabling fewer costly experiments while gathering more accurate data. The framework considers the scenario where all treatments are assigned in parallel and controls the outcome by adjusting treatment rates.
A NUS-led global study reveals that 30-minute functional MRI scans deliver up to 22% in cost savings while retaining or improving prediction accuracy. This finding could reshape how researchers design neuroscience and mental health studies, especially for hard-to-recruit populations.
SmartCatch, an AI tool developed by WorldFish, has won the AI for Planet Prize at the 2025 AI for Good Global Summit. The tool helps small-scale fishers record their catches with a simple mobile phone photo, aiming to make catch reporting faster and more accurate in coastal areas with limited internet connectivity.
Stanford researchers introduce a cost-effective way to evaluate AI language models, accounting for question difficulty to ensure fair comparisons. The new approach reduces costs by half and enables rapid progress in the field of artificial intelligence.
Researchers from Memorial Sloan Kettering Cancer Center developed a new approach to induce mutations in resistant cancer cells, making them sensitive to immunotherapy. The study showed positive outcomes in patients over 90 with lung cancer who underwent surgery.
Researchers created a digital twin to detect disease risk, initiate preventive treatment, and simulate effective treatments. The model uses extensive human data from the Human Phenotype Project to identify deviations from expected physiological changes in 17 body systems.
An AI model accurately detected tumor locations and outperformed benchmark models in detecting breast cancer, according to a study published in Radiology. The model learned a robust representation of benign cases to better identify abnormal malignancies, even with underrepresented data.
Researchers aim to create automated tools to safely translate legacy C codebases into memory-safe Rust without sacrificing performance or functionality. The project, backed by DARPA, uses formal methods and AI techniques to develop accurate translations of complex C code.
The Hong Kong Polytechnic University has secured funding from the Research Grants Council to develop a cost-effective and sustainable collaborative Generative AI (Co-GenAI) model. The project aims to democratize AI development by reducing centralized computational demand and enabling broader participation in GenAI research and deployment.
A new deep learning model enhances handheld 3D medical imaging by automatically tracking transducer motion without external sensors. The model produces more realistic 3D US images and can reconstruct blood vessel structures using ultrasound and photoacoustic data.
Researchers found that specific gaze sequences, including looking at an object and making eye contact, are crucial for effective communication. This discovery has implications for social robot development and non-verbal communication training.
Researchers at the University of Pennsylvania used AI-powered screen of global venom libraries to discover dozens of promising drug candidates. The top peptide candidates are being improved through medicinal-chemistry tweaks.
Researchers developed Localizatome to study oxidative stress-related changes in protein localization. The database provides comprehensive information on subcellular protein localization and dynamic localization changes under stress.
The EVOaware project aims to develop an innovative platform that addresses tumour resistance to therapies by using advanced tissue imaging technologies and integrating genetic screening, lineage tracing, and spatial omics techniques. This platform has the potential to accelerate the discovery and development of new cancer therapies.
A recent survey found that nearly two-thirds of U.S. adults consider AI-generated summaries to be somewhat or very reliable, while another 45% say they sometimes give them the answer they need. However, half of respondents are not comfortable with healthcare providers using AI tools.
A new method using label-free optical microscopy and artificial intelligence effectively identifies disease phenotypes in pancreatic cancer. The approach achieved nearly 90% accuracy in predicting tissue phenotypes, demonstrating the promise of combining light-based imaging with AI for precision medicine.
Researchers developed a self-driving lab that collects at least 10 times more data than previous techniques, dramatically expediting materials discovery research while slashing costs and environmental impact. The system uses dynamic flow experiments to continuously characterize samples, capturing data every half second.
A new study by Cornell University reveals Amazon's AI shopping assistant Rufus gives vague or incorrect responses to users writing in some English dialects like AAE. The researchers propose a framework for evaluating chatbots that can better serve users from diverse linguistic backgrounds.
Researchers at The University of Osaka develop an AI-powered framework to measure micro-scale occupancy in open-plan offices, providing detailed data for evidence-based design decisions. The system uses computer vision and 3D pose estimation to analyze video footage and track individuals within predefined zones.
Researchers developed an AI system that enables a four-legged robot to adapt its gait to different terrain, just like animals. The robot learned to switch gaits on the fly and navigate uneven surfaces without any alterations to the system itself, overcoming previous limitations around adaptability.
Researchers from Université Laval designed an ultra-fast and greener optical chip that can transfer massive amounts of data at speeds of 1,000 gigabits per second while reducing energy consumption. This innovation uses the phase of light to add a new dimension to the signal, reaching unprecedented performance levels.
Researchers demonstrated R-STDP synaptic plasticity in a single ferroelectric floating-gate device, enabling SNN to simulate robotic capture tasks with excellent performance. The network achieved a success rate up to 85.5% in dynamic capturing tasks.
Pusan National University researchers developed a comprehensive issue set for MDA implementation, covering technical, organizational, and environmental challenges. The framework helps manufacturers prioritize issues and address them proactively, enabling efficient and effective data-driven smart manufacturing.
The Chan Zuckerberg Initiative's latest AI model, GREmLN, is designed to predict and understand how genes interact within cells. It focuses on the molecular logic that defines gene behavior, allowing researchers to track critical changes pinpointing the earliest signs of disease.
A new report by Digital Science reveals China is outstripping the rest of the world in AI research, with a nationwide innovation ecosystem and a young, growing workforce. The UK remains small but globally impactful, while the EU risks falling behind due to weaker international collaboration.
A new AI tool called Ark+ has demonstrated exceptional capability in diagnosis of lung diseases and rare conditions like COVID-19. The tool outperformed proprietary software developed by Google and Microsoft, making it a potential game-changer for healthcare.
A 70-billion-parameter large language model called ChemELLM has been developed for chemical engineering applications. It was trained on a specialized dataset and demonstrated superior performance in various tasks compared to mainstream models.
A study using AI language models analyzed sentiments and emotions expressed by almost 400 pediatric patients on social media, finding that 94% of comments were negative, with sadness and fear prevalent. The study highlights the need for integrated care approaches to support vulnerable young patients managing complex medical conditions.
Researchers found that LLMs are better at representing non-sensorimotor concepts but struggle with sensory and motor concepts. Incorporating sensory input improves LLM performance and leads to more human-like representation, consistent with previous human studies on multimodal learning.
Yen-Ling Kuo, a UVA computer scientist, has been awarded the NSF CAREER Award to help robots understand and respond to human behavior. Her research focuses on building AI systems that can reason, communicate, and collaborate like humans, enabling robots to support people in various settings.
Researchers at KIT have developed a new AI method that generates high-resolution precipitation maps from low-resolution data, offering improved assessments of regional climate risks and disaster control. The model provides physically plausible precipitation maps with statistical uncertainty, applicable to diverse climatic conditions.
Researchers at Charité analyzed the laws of enzyme evolution on a large scale, revealing that certain areas change faster than others. The findings have implications for the development of new antibiotics and other medicines.
A new AI model developed by Mayo Clinic and Ultromics can detect cardiac amyloidosis, a rare and progressive type of heart failure, with high accuracy. The model was validated on a large patient population and outperformed traditional screening methods in identifying the disease.
The new journal aims to accelerate knowledge dissemination in AI by prioritizing theoretical breakthroughs, practical applications, and societal implications. It features short peer-reviewed contributions and opinion pieces to facilitate swift engagement with contemporary AI issues.
Artificial intelligence (AI) is revolutionizing medical needle procedures by providing unprecedented levels of accuracy and precision. AI-powered robots can assist physicians in complex tasks, enabling safer and more effective procedures. The four components of AI guidance are formalized, categorizing current systems into Eyes-on/Hands...
Researchers developed a way to boost LLMs' performance on challenging tasks using test-time training. This method involves updating some model parameters using new data, leading to significant improvements in accuracy, especially for tasks requiring logic and reasoning.
The journal is seeking original research, viewpoints, and tutorials exploring the use of AI-driven documentation in clinical settings. Submissions should address practical applications, challenges, and future directions of AI-facilitated clinical documentation.
A new report from the University of Cambridge's Minderoo Centre for Technology and Democracy highlights the alarming trajectory of energy use by big tech companies, driven by AI growth. The report predicts that data centres could consume up to 8% of global greenhouse gas emissions by 2040, far exceeding current emissions from air travel.
Researchers developed an AI model that screens for cardiac amyloidosis with high accuracy, outperforming existing methods. The tool analyzes routine heart ultrasound images to quickly detect the condition and differentiate it from other heart issues.
The collaboration aims to develop a predictive, high-fidelity AI model that identifies disease mechanisms and predicts patient outcomes. This initiative will focus on cancer but may expand to other complex medical challenges, such as transplant rejection and immunology.
The Buck Institute is pioneering a cloud-based platform to simulate the dynamic behavior of microbial cells, overcoming current whole-cell models' limitations. The SIMBA project aims to advance our understanding of bacterial behavior and address critical challenges in biomanufacturing and national security.
Researchers have developed an AI-assisted diagnostic system that can estimate bone mineral density in the lumbar spine and femur with high sensitivity and specificity. The system has the potential to transform routine clinical X-rays into a powerful tool for opportunistic screening, enabling earlier detection of osteoporosis.
A study published in Radiology found that AI decision support systems improve breast cancer detection accuracy and visual search patterns among radiologists. With AI assistance, radiologists spend more time examining regions with actual lesions, leading to better performance and efficiency.
A recent study published in the Association for Computing Machinery Conference on Fairness, Accountability, and Transparency found that AI chatbots are not safe replacements for therapists. The researchers evaluated these chatbots against clinical standards for therapists and concluded that they don
A recent study using machine learning and computational modeling reveals that astrocytes play a more active role in brain function than previously thought. Astrocytes subtly modulate communication between neurons during synchronous brain activity, influencing network coordination and stability.
Researchers highlight the benefits of artificial intelligence in glioblastoma management, including improved diagnosis, treatment planning, and personalized therapy. AI-based models can analyze radiological images, predict tumor characteristics, and suggest effective treatments, promising to improve patient outcomes and survival rates.
A team of researchers from UC3M, MIT and Adobe have developed Imprinto, a system for embedding invisible digital information in printed documents. This technology uses infrared ink and a special camera to enable advanced interaction with physical documents without altering their visual appearance.
Researchers at Boston University have created a new language model called PodGPT that combines expert knowledge from podcasts with the latest research articles. The model has been shown to better understand and answer scientific questions, particularly those related to biology, math, and medicine.
A Mayo Clinic team developed an AI system that can automatically identify surgical incisions and flag signs of infection in patient-submitted photos. The model achieved high accuracy in detecting incisions and identifying infections, with potential to streamline communication between patients and their care teams.
A new study reveals that AI systems transition from relying on word positions to meaning-based understanding as they receive enough data for training. The transition occurs abruptly, similar to a phase transition in physical systems, and is driven by the amount of data available.
Frontiers has integrated Cactus' Paperpal Preflight and Clear Skies' Papermill Alarm and Oversight into its AIRA submission-screening system to boost fraud-detection capabilities. This integration strengthens the reliability and integrity of every manuscript submitted to Frontiers.
A new method for rapid generation of aircraft concept solutions based on generative artificial intelligence has been proposed, demonstrating the application potential of large language models in aircraft conceptual design. The method improved efficiency and innovation in the conceptual stage.
Researchers developed an AI-informed method for rapid protein evolution, integrating structural and evolutionary constraints. The approach, AiCE, outperforms traditional methods in predicting high-fitness mutations, enabling efficient protein redesign and applications in precision medicine.
A new study demonstrates that retrieval-augmented generation can eliminate hallucinations in clinical LLMs while protecting patient privacy. The RAG-enhanced model responds significantly faster than cloud-based systems, delivering safer results without compromising data security.
A new technique called WeGeFT improves large language model performance in tasks such as commonsense reasoning and code generation. By fine-tuning key parameters, researchers reduce the need for significant computational power, advancing the field of artificial intelligence.