Articles tagged with Artificial Intelligence
Researchers at Tohoku University utilized AI to develop strategies for water treatment and air pollution control. The study highlights innovative approaches using machine learning in material screening and global distribution simulation of pollutants.
Large language models like ChatGPT are more persuasive than humans, especially when convincing people to adopt veganism or attend graduate school. The AI's ability to provide concrete logistical support and use authority-boosting vocabulary contributes to its persuasiveness.
Researchers from Florida Atlantic University's Charles E. Schmidt College of Medicine conducted a scoping review on AI-driven systems designed to deliver motivational interviewing. The study found that most used AI tools were chatbots, with varying levels of fidelity to core principles like empathy and autonomy.
A new 'future-guided' AI method developed at the University of California, Santa Cruz, has shown significant improvements in predicting seizures using brain wave data. The technique operates with two deep learning models working together, improving predictions further into the future by transferring knowledge.
Despite no decrease in usage, Wikipedia faces challenges from AI data scrapers and Large Language Models. The platform is struggling to allocate resources due to the influx of AI training data, threatening its current structure.
A new AI system called Diag2Diag analyzes sensor data to provide synthetic information for failing or degraded sensors in fusion systems, enhancing robustness and reducing complexity. This technology has the potential to make fusion energy more economical and reliable, enabling 24/7 operation without interruption.
Researchers at Champalimaud Centre for the Unknown used machine learning techniques to show that mice's facial movements reflect their hidden thoughts. This discovery could offer unprecedented insight into brain function and potential new research tools.
Researchers created a high-resolution 3D liquefaction hazard map using machine learning and geotechnical data. The model accurately predicted soil properties and liquefaction risk, identifying high-risk areas in reclaimed coastal zones and river floodplains with unprecedented clarity and precision.
A groundbreaking study enrolls 465 AYA cancer patients to test if chatbot technology and digital education tools increase uptake of genetic counseling and improve patient outcomes. The trial aims to address longstanding gaps in genetic services for AYAs aged 18-39, who often receive care with limited access to genetic specialists.
A new study published in AIAS found that warm red lighting can significantly reduce motion sickness in passengers during nighttime journeys. The research team conducted nighttime road tests and combined subjective ratings with multimodal physiological signals to assess symptoms.
An AI model successfully automates lymph node segmentation and extranodal extension classification from pretreatment CT scans in HPV-associated oropharyngeal carcinoma. Predicted extranodal extension is independently associated with worse oncologic outcomes, highlighting the potential for improved treatment planning.
Research presented at the European Emergency Medicine Congress finds that doctors and nurses are more accurate than AI in triaging patients in emergency departments. While AI showed some promise in flagging critical cases, its overall accuracy was lower than clinicians' across most metrics.
The startup has assessed over 3,400 miles of Indiana roads using advanced computer vision algorithms to quickly and objectively assess pavement conditions. This platform provides actionable insights without requiring in-house data analysis expertise or costly hardware.
A new AI tool called Waldo can scan social media data to discover personal reports of harmful side effects of popular health products. The tool achieved an accuracy of 99.7% in detecting adverse events, outperforming general-purpose chatbots.
Liberate AI project develops an AI model capable of predicting long-term outcomes and potential complications in ischemic stroke patients. The model will be trained using Swarm Learning technology, aiming for explainability and transparency, while striking a balance between these features and accuracy.
Researchers at The University of Osaka developed a reinforcement learning framework to enable spoken dialogue systems to acquire new vocabulary efficiently while minimizing user interruption. This approach improves word segmentation performance while reducing the number of questions asked.
A Harvard Medical School-led research team developed an AI tool called PICTURE that can reliably tell apart glioblastoma and primary central nervous system lymphoma during surgery. The tool distinguishes between the two cancers with near-perfect accuracy, reducing errors in diagnosis and guiding critical treatment decisions.
A new study aims to develop more fair and transparent AI interview systems using psychological measurement principles. Researchers will examine bias at three levels: predictors, outcomes, and perceptions of job seekers.
A recent study found that social benefit recipients have significant reservations about AI-supported decisions, rejecting them more frequently than non-recipients. The study also revealed that non-recipients systematically overestimate the willingness of affected individuals to trust AI.
Researchers at Institute of Science Tokyo developed a new framework for generative diffusion models by reinterpreting Schrödinger bridge models as variational autoencoders. This approach reduces computational costs and prevents overfitting, enabling more efficient generative AI models with broad applicability.
A National Science Foundation grant will support older adults in developing digital technology skills and embracing AI, with a focus on intergenerational storytelling. The project aims to strengthen AI literacy, social connectedness, and resilience among older adults, while cultivating responsible AI awareness in youth.
The new method eliminates the need for extensive AI training or optimization, making video layer editing faster, cheaper, and more accessible. OmnimatteZero preserves complex elements like fur, hair, foliage, shadows, reflections, smoke, or rippling water without current methods' limitations.
A new study found that AI tool accurately captures details in just three minutes from a body scan, highlighting the potential of using AI to repurpose data from routine scans. Visceral adipose tissue volume and fat deposits in muscle are strongly associated with diabetes and cardiovascular disease risk.
Researchers developed AI-powered BlinkWise glasses that track blinking patterns to assess fatigue, mental workload, and eye-related health issues. The device uses radio signals to detect minute eyelid movements with unprecedented detail, preserving privacy and using minimal power.
The European Lighthouse on Secure and Safe AI (ELSA) network has grown to include 41 members, expanding its expertise in pressing AI research topics and fostering knowledge exchange. The network's founding members are renowned for their work on Safety, Security, Artificial Intelligence, and Machine Learning.
A novel detection framework, SORA-DET, is introduced for UAV remote sensing, achieving high accuracy and efficiency while being compact and fast. It outperforms large-scale models with up to 88.1% fewer parameters.
A cross-sectional study found that FDA-cleared AI-enabled medical devices lack standardized efficacy, safety, and risk assessment, highlighting the need for dedicated regulatory pathways and post-market surveillance to address these challenges.
Digital@UNGA 2025 brings together global leaders to discuss the power of technology in tackling urgent challenges and driving sustainable development. The event showcases innovations in AI, quantum computing, and digital skills to benefit all, with a focus on inclusivity, sustainability, and prosperity.
The INSEAD AI50 honors leaders who turn AI research into practical, scaled deployments. Honorees include founders, executives, researchers, and educators from diverse backgrounds, reflecting the school's global presence. The list showcases individuals who apply AI effectively, responsibly, and at scale.
Researchers developed an AI-based system to streamline medical image segmentation, allowing users to mark areas of interest and predict segmentations with decreasing user input. The tool has been shown to outperform state-of-the-art tools in image segmentation tasks, enabling faster study completion and cost reduction.
Researchers at UCLA have created a technology that harnesses photonics to perform generative AI tasks optically, eliminating the need for heavy digital computation. This leads to ultrafast and secure image generators with less energy consumption and water usage.
Researchers from Perugia University explore how machine learning can aid in earlier hazard detection and improved risk communication. However, they caution that ML tools must be used responsibly and transparently to ensure accurate predictions and avoid potential pitfalls.
A new meta-analysis of 327 studies with over 282,000 participants reveals that AI agents excel in situations where a negative response is required, such as rejecting loan applications. However, human presence remains essential in tasks requiring empathy and spontaneity.
The book offers novel human-centered AI techniques to address social intelligence challenges, including multimodal approaches and explainable AI designs. Researchers can integrate artificial and human intelligence to tackle complex social challenges.
Forestry professionals express concerns about AI's impact on land-management decisions and policy, citing 'black box' problems and data quality issues. However, they see potential for AI to support tasks like data analysis and task automation.
Researchers developed a platform called CRESt that incorporates insights from literature, chemical compositions, and imaging to optimize materials recipes. CRESt uses robotic equipment for high-throughput testing and large multimodal models to further optimize materials recipes.
The 12th Heidelberg Laureate Forum brought together top mathematicians and computer scientists to discuss the impact of AI on various issues. The event featured talks and panels on topics such as machine learning revolution and state of science integrity.
The partnership aims to provide cutting-edge professional development to public sector and critical infrastructure leaders across Canada, equipped with strategic skills to outthink and outmaneuver threats. The initiative strengthens Canada's cyber resilience by enhancing national cyber resilience.
Researchers developed SciGuard, an intelligent safeguard for AI models, to control misuse risks in chemical science. It balances safety and scientific progress by providing accurate information while refusing dangerous outputs.
The International Telecommunication Union (ITU) has launched an initiative to bring artificial intelligence and robotics training to students across Africa. The programme combines hands-on AI and robotics training for young people in underserved communities, with a focus on reaching girls and other underrepresented groups.
The University of Texas at Austin has launched a new research consortium, COMPASS, to inform industry partners on options for more sustainable growth of the data center industry. The consortium aims to tackle obstacles and streamline responsible deployment of data centers across Texas.
Researchers assessed the effectiveness of a single session with 'Amanda,' a ChatGPT-4o-based chatbot, versus a brief journaling task in addressing non-abusive relationship conflict. The study found that both interventions improved participants' specific relationship problems, overall relationships, and well-being.
Biomedical engineers at Duke University developed a platform combining automated wet lab techniques and AI to design nanoparticles for drug delivery. The TuNa-AI platform resulted in a 42.9% increase in successful nanoparticle formation compared to standard approaches.
Insilico Medicine's founder Alex Zhavoronkov, PhD, is named among 100 global leaders driving the future of artificial intelligence. The company has developed breakthrough solutions for novel target discovery and drug development using generative AI.
A multidisciplinary team led by Natasha Vermaak investigates developing structural materials resistant to high-frequency thermomechanical loads for rotating detonation engines. The project aims to address the lack of established materials solutions for extreme thermomechanical loadings, enabling advancements in propulsion systems.
Grade school children learn robotics through performance-based learning, exploring science, tech, engineering, arts, and math. The expanded curriculum will introduce ethical considerations, such as fairness, privacy, and bias in technology.
Researchers developed AI tools that use machine learning and natural language processing to extract details from doctors' notes. The tools detected a high-risk asthma subtype that makes some children more vulnerable to acute respiratory infections and asthma exacerbation.
Researchers at FAU have developed a smarter AI framework that can manage complex systems with unequal levels of authority and adapt to imperfect information. The framework, based on reinforcement learning and game theory, reduces unnecessary computation while maintaining system stability and optimal strategy outcomes.
A large-scale randomized trial will examine whether AI supports radiologists in interpreting mammograms more accurately, reducing unnecessary callbacks and anxiety. The PRISM Trial, led by UCLA, aims to inform future policy decisions and best practices in breast cancer screening.
The USC team is developing a new drug aimed at a previously unexplored biological target in Alzheimer’s disease, focusing on a trigger of brain inflammation. They have identified an enzyme that predisposes the brain to inflammation and are now working to find a drug that can block it without harmful side effects.
Researchers at uOttawa are developing an AI tool to provide personalized dietary strategies for people living with inflammatory bowel disease (IBD). The project aims to match specific types of carbohydrates to individual patients' unique gut microbiomes.
This special issue aims to showcase cutting-edge research on assessing, pricing, and managing cyber risks in AI-driven environments. Scholars worldwide are encouraged to submit and join the conversation on cyber risks in the AI era.
Researchers at MIT developed a technique called SCIGEN that steers generative AI models to create promising quantum materials by following specific design rules. The approach led to the synthesis of two actual materials with exotic magnetic traits.
A research team developed a pipeline using pre-trained large language models to unify radiology and pathology reports, achieving high accuracy in tumor presence and stability. The system also predicted survival outcomes without additional training, distinguishing high-risk from low-risk groups.
A new framework developed by Cranfield University aims to balance AI's benefits with safety and fairness concerns in disaster response. The study shows the framework outperforms human operators and conventional AI systems, providing 39% higher accuracy across various scenarios.
A team of scientists developed a novel model, DASFormer, that learns to monitor earthquakes from continuous DAS data on its own, effectively serving as an 'artificial seismologist'. The model achieved the highest performance across all evaluation metrics, with a peak ROC-AUC of 0.906 and an F1 score of 0.565.
Two projects funded by federal grants use AI to design proteins for industrial applications, such as producing acrylates in paints. UC Davis will also expand its student training program in protein design to bring hands-on research opportunities to thousands of students nationwide.
Researchers developed MoBluRF, a two-stage motion deblurring method for NeRFs, achieving high-quality 3D reconstructions from ordinary blurry videos. The framework outperforms state-of-the-art methods and is robust against varying degrees of blur, enabling smartphones to produce sharper and more immersive content.
The University of Texas at Arlington is hosting its fifth annual Texas Health Informatics Alliance Conference, which will delve into the ethical and effective applications of artificial intelligence in healthcare. Keynote speakers and panel discussions will explore topics such as AI security, cybersecurity, and legislative outcomes.
Researchers developed a robust QA system using Retrieval Augmented Generation (RAG) to answer queries on building codes. They found that Elasticsearch was the most effective retriever and fine-tuning Large Language Models (LLMs) significantly enhanced generational accuracy, achieving a 6.83% relative improvement in BERT F1-score.