Researchers at Chalmers University of Technology developed an AI method that adapts fast charging to the health of the battery, increasing its lifespan by almost 23%. The new strategy uses reinforcement learning and takes into account the battery's chemistry and state of health.
A team of researchers has developed a deep learning-based method called DeepAFM to analyze noisy atomic force microscopy (AFM) images and infer protein states. The method produces accurate results, even with background noise and scanning distortions.
A recent study reveals widespread exposure to harm among US teens using AI chatbots, with entertainment being the most common motivation. The study found that nearly half of teens experienced at least one risk, including exposure to unsafe content and encouraging risky behavior.
Machines with advanced AI capabilities are being developed to restore lost senses such as sight and sound, and even simulate touch and taste. This technology has the potential to revolutionize various fields like healthcare and education, but also raises serious concerns about privacy and manipulation.
Researchers used the Rational Inattention model to analyze large language models' hate speech classification performance, finding that it accurately predicts how their performance changes in different conditions. This analysis can help guide digital communities using LLMs for content moderation.
Researchers developed AI models using electronic health records and electrocardiograms to identify individuals at elevated risk for sudden cardiac arrest. The combined EHR-EKG model correctly predicted 153 of 228 high-risk patients who experienced a cardiac arrest, bringing theoretical risk into focus.
A new inspection workflow using AI-assisted review tools is being implemented at Sandia National Laboratories to speed up inspections and catch tiny defects earlier. The system will use high-throughput imaging systems to scan ceramic billets, reducing the need for manual microscopes and training operators.
Researchers found that action-based friction, which required users to search for existing image resources, increased users' ecological responsibility in their AI use. The study also showed that cue-based friction, such as persuasive messaging about AI's environmental impacts, did not tend to affect users' intentions to use AI responsibly.
The UN is highlighting the potential of artificial intelligence (AI) and digital innovation to create smarter, more resilient and sustainable cities. The International Telecommunication Union has released a Call to Action for Humanity, identifying five strategic priorities to address urban challenges.
The AI framework uses environmental and hydrometeorological data to provide early warnings of E. coli contamination risk, giving communities a window to act before health risks emerge. It identified unsafe conditions with approximately 85% accuracy, demonstrating its potential to offer earlier warnings.
Protein language models have immense potential but lack explainability, leading to concerns over reliability and safety. Researchers propose four key places to understand a model's decision-making process and outline the need for more transparent and trustworthy AI in biotechnology.
A new study by Technische Universität Berlin reveals that teaching Large Language Models to mimic human intuition and reasoning improves their ability to provide accurate medical care-seeking advice. The 'human reasoning blueprint' approach increased overall accuracy across all models, with significant gains in self-care advice.
Researchers developed RegVelo, an AI framework that models cellular dynamics and gene regulation to predict cellular fate decisions. The model traces developmental trajectories and simulates regulatory interactions, providing insights into hidden drivers of development and potential therapeutic targets.
A recent study analyzed 138 Indian cities using satellite data and explainable AI methods to show why urban greening needs to be tailored to humidity, canopy structure, and airflow. The findings highlight the importance of considering moisture management and ventilation in urban planning to effectively mitigate heat-related stress.
A new editorial proposes the use of agentic AI systems to address cancer-related malnutrition, a prevalent issue affecting up to 80% of patients. These systems aim to coordinate multiple functions simultaneously and support ongoing clinical decision-making throughout treatment.
Researchers are developing a system that uses AI and robotics to track what's installed inside the growing ship and compare it to a digital twin of the intended structure. The system will create reports of mismatches that workers can use to make adjustments, potentially reducing delays in delivery.
Researchers developed a novel diagnostic support framework using visual question answering to generate interpretable findings from chest CT images. The system demonstrated strong agreement with reference descriptions and provided clinically meaningful outputs.
SourceMeijo University·JournalInternational Journal of Computer Assisted Radiology and Surgery·TypeComputational simulation/modeling·DateMay 11, 2026
Researchers explore how next-gen AI and sensor-rich operating rooms can enable more precise, data-driven, personalized surgery. Advances in multimodal data integration, machine learning, and robotic systems could enhance situational awareness and intraoperative decision-making.
A large language model-based agentic workflow produced AI-generated hospital course summaries with minimal risk of harm identified, reducing physician burnout. The study supports the viability of AI summarization to mitigate documentation burden.
A study by UPF found that AI-generated images of depression reinforce stereotypes and stigmas, particularly in terms of marginalization and social exclusion. The research highlights the need for responsible mental health communication, emphasizing the importance of considering diverse experiences and promoting transparency around AI use.
This review highlights the integration of machine learning with adsorption science and engineering, achieving high precision and interpretability in adsorption processes. The reviewed studies demonstrate that machine learning enables accurate prediction of adsorption performance, accelerates material discovery and process optimization,...
The book captures the AI moment through a chorus of perspectives from science, business, art, journalism, and media, challenging and complementing each other to reveal tensions and contradictions. It paints a vivid picture of how AI is reshaping our self-understanding and what it discloses about us.
Researchers developed an AI-driven wearable skin sensor patch to track reproductive hormones and detect hidden endocrine dysfunction, which can improve conception. The study found that men with normal testosterone levels may still have disrupted hormone rhythms associated with reproductive dysfunction.
Researchers at Washington State University and Google developed an AI system that can process hundreds of thousands to millions of camera trap images in just a few days, reducing analysis time from months to days. The results aligned with human experts' models in roughly 85-90% of cases, making it a significant breakthrough for conserv...
Experts warn that AI-enhanced surgical robotics could enable true personalized surgery and enhance surgical team performance. However, regulatory reforms are needed to address risks from adaptive systems and ensure patient benefits.
A study by Frontiers analyzed three papermill detection tools on over 37,000 manuscript submissions, finding that the tools flag different proportions of manuscripts and have low manuscript-level overlap, highlighting a detection gap. The tools emphasize different types of signals, contributing to the divergence in flagging rates.
Researchers developed an AI model that learns from real-world match data to optimize attacking play against compact defensive structures. The framework models each attacking player as an individual decision-maker while capturing how players interact as a coordinated unit.
Assistant Professor Gianmarco Mengaldo has been appointed to the Joint Advisory Group on Artificial Intelligence at the World Meteorological Organization. He will guide how AI is integrated into global meteorological and hydrological systems, improving forecasting capabilities and early warning systems.
Nine leading AI models failed to perform well on routine administrative tasks, such as counting patients and filtering records. However, a tool-based approach combining LLMs with code-generation improved accuracy for most capable models.
SourcePLOS·JournalPLOS Digital Health·TypeExperimental study·DateMay 7, 2026
A Columbia University School of Nursing AI-assisted audit found nearly 3,000 biomedical papers with fake citations, highlighting an alarming trend in academic publishing. The study recommends publishers verify references and indexing services add metadata for accurate reference assessment.
Researchers at USF Health developed a framework to test AI tools' accuracy in predicting immune responses, aiming to enhance cancer immunotherapies and vaccine development. The study highlights the strengths and weaknesses of current AI approaches, providing guidance for building safe and reliable AI tools for healthcare.
Researchers at Aston University have created an AI-based training method that enables robots to adapt to real-world conditions without extensive data collection. This breakthrough could significantly accelerate innovation in sustainable manufacturing, recycling, and autonomous industrial systems.
The HALLO project uses real-time acoustic and visual data, vessel tracking, and citizen-scientist reports to track and forecast Southern Resident killer whales' movements. The AI-powered system aims to support faster detection and more reliable classification of whales in shipping lanes.
Researchers from MIT have developed a more user-friendly and efficient method to identify potential system failures in cloud computing algorithms. The 'MetaEase' technique analyzes an algorithm's source code directly to uncover hidden blind spots that might cause unexpected failures, reducing the risk of costly network outages.
The research team led by Dr Fei Jing at HKU IDS introduced a rigorous theoretical framework to analyze connection patterns in complex networks. The study demonstrates that global predictability can be decomposed into local contributions from individual connections, significantly reducing computational complexity and improving scalability.
Researchers have developed a simplified mathematical model of learning in neural networks, shedding new light on how these systems produce their responses. The toy model, inspired by physics principles, captures key features of complex systems and offers insights into the surprising efficiency and stability of modern AI systems.
A study published in Radiology used AI to analyze whole-body MRI scans from over 66,000 participants, revealing that skeletal muscle quality is a strong predictor of diabetes, major cardiovascular events, and mortality. The researchers also found that high visceral fat and low skeletal muscle were associated with increased risks of the...
The rise of consumer-facing health AI assistants is transforming healthcare access, offering users personalized medical workspaces and real-time lab result interpretation. However, concerns around data privacy and the risk of misdiagnosis highlight the need for caution in this rapidly evolving landscape.
A study of 1,152 people found that humans cooperate more with fair AI than with AI that is helpful or selfish. Fairness was the key to cooperation, not unconditional niceness. The researchers suggest that humans respond best to AI that can navigate social rules and expectations in a believable way.
Researchers used AI to design new molecules for disinfectants, leveraging a dataset of hundreds of existing quaternary ammonium compounds. The approach yielded 11 promising compounds with activity against antimicrobial-resistant bacteria, offering a potential solution to the growing threat of 'superbugs'.
Sanford Burnham Prebys receives a $5 million gift from Andrew Viterbi to advance its Center for Data Science and Artificial Intelligence. The center is exploring raw or untapped data to uncover patterns and insights that can inform scientists and clinicians.
A new study found that girls struggle to master AI due to low confidence and limited institutional support. To overcome this, schools should provide more female role models and create a supportive classroom environment.
Teachers view AI as a tool to reduce workload, but worry it may erode social aspects of teaching. The study found that affluent schools are better equipped to integrate AI into their curriculum.
The UK-led OpenBind initiative has released its first publicly available dataset and predictive AI model, accelerating the discovery of new medicines using artificial intelligence. The release showcases high-quality, standardized experimental data and a trained predictive model, enabling researchers worldwide to drive the next generati...
A recent study found that people provide less detailed medical information when communicating with AI chatbots compared to human doctors. This lack of detail can result in incorrect medical advice and lower the quality of diagnosis. The study suggests that intelligent design of user interfaces and actively requesting missing details ma...
Researchers discovered that simple artificial intelligence tools can bypass security techniques meant to protect authentic content from use in deepfakes and facial identity theft. The study found that attackers can easily defeat existing image protection using off-the-shelf AI models and simple commands.
The new AI model uses genetic mutation patterns to trace ancestral relationships between species, including humans and mosquitoes. The tool can predict when gene pairs last shared a common ancestor and is faster than traditional statistical methods.
A multi-institutional team led by Sanford Burnham Prebys aims to develop a non-opioid pain therapeutic using lead molecule SBI-810. The effort, funded by a $3.9 million NIH grant, seeks to optimize the compound into a drug that could provide effective pain relief without addiction risks.
A recent study reveals that individuals with higher education or income are more aware of and use AI tools, exacerbating social inequalities. The researchers recommend increasing engagement with AI-related topics through outreach campaigns, educational programs, and community workshops to reduce this new digital divide.
Researchers developed a new framework, 'Mollifier Layers,' to tackle challenging inverse PDEs. This advance could benefit fields such as genetics and weather forecasting by inferring hidden forces that produce observable patterns.
The article warns that AI's rapid integration may stifle scientific creativity and innovation, diverting resources away from solving fundamental problems. Dr. Shim argues for preserving human-centered pathways for knowledge generation to ensure diverse thought necessary for breakthroughs.
A study combines polarization-sensitive optical coherence tomography (PS-OCT) with artificial intelligence to reveal subtle corneal changes that standard imaging often misses. The technique improves detection and classification of subclinical keratoconus, enabling earlier diagnosis and more precise care.
The report examines how generative AI tools are transforming software development, offering benefits such as increased productivity but also raising security vulnerabilities and technical debt. Strong software engineering practices are still required to ensure systems are secure, reliable, and maintainable.
Flinders University experts caution that AI's impressive capabilities do not automatically translate into safe use for patients. The researchers stress the need for strong governance and clearer standards for evaluation to ensure AI supports doctors in busy care settings.
New research from West Virginia University finds that judges are adopting generative artificial intelligence in courtrooms, but remain committed to human control over judicial decision-making. Judges use AI for administrative tasks like document summarization and case organization, but prioritize legal reasoning and final judgment.
A new study published in Science Advances identifies IRS4 as a promising drug target for multiple solid tumors, offering hope for safer cancer treatments. By using AI and natural mutations, researchers prioritized targets with high therapeutic indexes to minimize toxicity.
The review highlights how retrieval-augmented generation can improve the accuracy, transparency, and clinical reliability of AI tools in cancer care. RAG-enhanced systems produced more accurate results than standard AI models across multiple studies.
SourceSAGE·JournalAI in Precision Oncology·TypeLiterature review·DateApr 30, 2026
A new study reveals that menopause causes profound and uneven transformations across the female reproductive system, rather than a uniform decline. The research identified molecular signals associated with aging detectable in blood, allowing for non-invasive monitoring and earlier detection of risks.
Researchers used a new AI-powered computational method to discover that most nucleosomes contain sections of DNA that are partially accessible to the cell. The study found that more than 85% of nucleosomes showed some degree of distortion, with 14 distinct structural states associated with different levels of gene activity.
Researchers warn of potential risks associated with evolvable AI systems, which can tap into the power of biological evolution to create 'selfish' actors that break alignment with human goals. The study recommends guardrails to maintain centralized control over AI reproduction and mitigate risks.