Binghamton University researchers have developed a new way to reduce troublesome fake information in AI chatbots, with high accuracy in identifying disease terms and drug names. The protocol harnesses multiple large language models to verify answers through 'voting', increasing confidence in the results.
The development of AI-enabled research platforms poses a risk of unequal access, potentially excluding scientists without resources or connections. As decisions about platform accessibility are made in the next five years, it will shape the geography of global discovery for generations.
The International Congress of Mathematicians (ICM) 2026 will take place in Philadelphia from July 23 to July 30, featuring the announcement of Fields Medals and top talks on cutting-edge developments in mathematics. The conference will also explore the impact of artificial intelligence on mathematics.
A new study published in the Journal of Big Data highlights the journal's emergence as a leading publication in data science and artificial intelligence research. The study found that JBD has become a central hub for high-impact research worldwide, with significant contributions from top researchers.
The African Engineering and Technology Network (Afretec) has signed its tenth university partner, Addis Ababa Science and Technology University (AASTU), to drive digital transformation in Africa. The network, led by Carnegie Mellon University Africa, aims to create long-term sustained change across the continent through research, educa...
A Japan-US collaborative team has developed the world's first integrated spintronic probabilistic bit on a silicon chip, paving the way for large-scale spintronic p-computers. The innovation addresses computational problems requiring parallel processing of enormous numbers of possible states.
The University of Texas at San Antonio has received significant funding from the Cancer Prevention and Research Institute of Texas to develop innovative cancer research technologies and treatments. The institution will focus on pressing cancers such as Ewing sarcoma, obesity-related endometrial cancer risk, and AI in clinical oncology.
A new AI-powered translation program developed by the National Weather Service (NWS) translates weather forecasts into multiple languages, including Spanish, Chinese, Vietnamese, Samoan, and French. The program aims to provide life-saving information to over 68 million US residents who do not speak English at home.
Researchers at IRB Barcelona used AI to design new chemical entities that selectively target specific cell types, demonstrating superior activity compared to conventional screening strategies. The methodology, called phenotypic discovery, uses observable responses in cells rather than a specific molecular target.
Researchers propose embedding AI foundation models into control software to enable robot swarms to achieve new levels of autonomy and adaptability. This enables robots to switch between tasks in real-time and interact more naturally with humans.
Researchers used an open-source AI model called Mirai to quickly identify high-risk patients and expedite their diagnostic process. This led to a significant reduction in wait times, with some women receiving biopsy results within days of having their mammograms done.
UCLA researchers are developing an AI-enhanced imaging platform to improve yttrium-90 radioembolization planning for patients with liver cancer. The new approach uses dynamic contrast-enhanced MRI scans to better characterize tumor blood flow and predict microsphere distribution.
The center will develop new phage-based treatments for antibiotic-resistant bacterial infections, predicting which phage to use for which patient and designing more effective phages. The goal is to generate unprecedented data and train AI models to identify the right phage for any patient's infection.
The collaboration aims to expand access to Mayo Clinic's knowledge and integrated model of care, using advanced AI capabilities to support earlier diagnoses, personalized treatment decisions, and better patient outcomes. The frontier AI model will be owned by Mayo Clinic and made available through Microsoft Azure Foundry APIs.
A team of researchers developed a method for creating realistic virtual tomato farms that automatically generate data for training agricultural AI systems. The approach uses advanced reconstruction methods and Unreal Engine 5 software to reproduce lighting, textures, and geometry, resulting in highly accurate object detection models.
The journal is seeking articles that explore the transformative power of digital tools to improve safety and health outcomes in occupational settings. Submissions focus on applying mHealth, wearable sensors, and real-time analytics to monitor physical hazards and reduce ergonomic strain.
A nationally representative survey of US adolescents and young adults found that a fifth used AI chatbots for mental health advice. Proactive discussion with parents and clinicians about chatbot use is necessary to promote safety and linkages to evidence-based care.
Researchers highlight latest developments in pathology, diagnosis, and treatment of MASLD and IPFD, revealing correlations with chronic diseases like liver cancer and pancreatic cancer. Innovative treatments, such as AI-driven approaches and organ-targeted therapies, show promise for precision prevention and therapy.
A research team proposes the Metacognitive Laziness Scale (MLS) to measure students' tendency to delegate metacognitive tasks to AI systems. The study found significant positive associations between metacognitive laziness and disaffection with learning, suggesting that excessive reliance on AI may undermine academic achievement.
A recent study by CISPA Helmholtz Center for Information Security examines how users perceive AI labels and their impact on information credibility. The study found that while AI labels can reduce belief in false content, they also trigger skepticism and shape trust more than the content itself.
A remotely operated AI algorithm has identified the critical view of safety (CVS) in pediatric patients, detecting when all safety criteria were met and issuing real-time alerts. This approach combines AI with teleconferencing for potential new intraoperative guidance without requiring specialized hardware.
The LEGO Foundation Fellowship will support up to 10 researchers pursuing ambitious work on how children thrive in crisis and conflict settings, neurodivergent children, and AI-enabled learning. The fellowship aims to deepen understanding of what helps children learn, grow, and thrive.
Researchers at POSTECH develop technology that lowers contact resistance by 50-fold and boosts on-state current by 17 times in ultra-thin tellurium transistors. This breakthrough enables stable operation of devices even at extreme temperatures, paving the way for next-generation 3D integrated circuits.
A new study by Penn Medicine reveals significant gaps in online information about artificial intelligence (AI) and its impact on cancer research and treatment. The study found that only 33% of relevant webpages and 23% of videos were considered high-quality, with many omitting risks of AI use.
A new open-source framework called MEDS has been developed by a Columbia-led team to streamline and accelerate artificial intelligence research using health data. The framework standardizes data format and provides interoperable tools to support machine learning model development, reducing technical barriers and promoting reproducibility.
Frontiers won two EPIC Awards for its landmark whitepaper on responsible AI use in research and publishing, and a digital campaign highlighting research integrity. The awards recognize the institution's commitment to making science open and trusted.
Researchers developed an all-optical artificial synapse that uses light to mimic neural learning and perform in-sensor image processing. The device shows paired-pulse facilitation and depression, allowing it to both enhance and suppress signals, a requirement for realistic neural behavior.
The symposium aims to consolidate and expand partnerships in strategic areas such as energy transition, artificial intelligence, and health. The event will facilitate cooperation among researchers from São Paulo and the UK, with a focus on joint funding opportunities.
Researchers at Texas A&M University are designing how humans will build and survive on the moon, focusing on sustainable construction using lunar regolith. The institution's efforts aim to reduce costs associated with shipping materials to the moon, making it possible to produce rocket propellant locally.
Researchers at PolyU have pioneered a method to store digital data using engineered proteins, achieving high storage efficiency and capacity. They overcame challenges of variable amino acid sequences and degraded proteins by designing a protein template, successfully expressing and retrieving data.
A new Drexel University study finds that most users see AI chatbots as supplements to human therapy, not substitutes. Users express concerns about emotional dependence, misinformation, and overreliance on the technology.
A deep learning model combines knowledge from different catalyst families to identify a top-performing green hydrogen catalyst. The AI correctly predicted the activity ranking of 12 tested catalysts within a previously unexplored material family.
Researchers at the University of Jyväskylä have developed an AI model that can analyze colorectal cancer samples more efficiently and accurately predict the functioning of the cells' DNA repair mechanism. This could lead to shorter diagnosis times, reduced costs, and improved analysis accuracy.
A recent study found that AI-powered chatbots can provide accurate information in 76.2% of healthcare-related questions, with specialties like obstetrics and gynecology performing best. However, internal medicine, neurology, and dermatology saw lower accuracy rates, with risks of harm associated with incorrect responses.
A new study shows AI can generate hundreds of convincing finance research papers efficiently, but also raises concerns about the potential impact on academic community and meaning of scientific discovery. The study demonstrates how AI can accelerate research paper production while highlighting areas for improvement in peer-review systems.
A new study published in PLOS Digital Health identifies simple food substitutions that can improve meal nutritional quality and lower costs. By analyzing 135,491 meal records, researchers trained an AI model to suggest one to three ingredient swaps, resulting in a 10% improvement in nutritional quality and a 22-34% reduction in costs.
A new framework, SUVA, enables organizations to measure and adjust AI chatbots' social preferences, improving their performance in customer complaints and other human-AI interactions. By understanding an LLM's existing tendencies, organizations can decide whether an available model already fits its values and usage scenarios.
A new transfer learning framework connects two gait analysis tasks, predicting continuous gait cycle percentage and classifying discrete gait phases. The method achieved high F1-scores and efficiency, outperforming traditional approaches.
SourceELSP·JournalArtificial Intelligence and Autonomous Systems·TypeExperimental study·DateMay 28, 2026
A robot that catches itself when it falls has been developed using reinforcement learning and artificial intelligence. The system achieved an average success rate of 69.4 percent in arresting the robot's fall and returning it to a stable position.
A new viewpoint article highlights the risk of AI 'collusion' with unreliable human input in mental health settings. The author argues that clinical expertise should be included when designing training data and evaluating AI systems to strengthen safeguards.
A new study published in JAMA Network Open found that approximately 16% of patients with COVID-19 developed long COVID, translating to over 18 million Americans. The study used a novel AI algorithm to identify cases undetected by existing diagnostic systems.
Researchers summarize how AI is accelerating inorganic biomaterial development for various biomedical applications. AI-powered property prediction and inverse design tools are being used to discover effective materials with unique properties.
The Salk Institute has promoted Julie Law to full professor and appointed Talmo Pereira as assistant professor, highlighting their innovative approaches to gene regulation and computational neuroscience. Their research focuses on epigenetics and artificial intelligence techniques, respectively.
Researchers propose a new conceptual framework called Health Elements, which integrates technological factors alongside traditional domains as core drivers of health. The framework highlights the increasingly important role of digital infrastructures in shaping health behaviors and outcomes.
A new approach combines MRI scans and AI tools to measure fluid flow in the brain, shedding light on the glymphatic system’s mechanics. The study reveals two main ways the system washes away particles, with one way moving faster than the other.
A team at Polytechnique Montréal has developed a new material that enables direct light processing on silicon chips, reducing the need for signal conversion and amplification. This breakthrough could help sustain the next wave of AI at scale by giving light a larger role in data processing.
Researchers at Duke University introduce Argus, a 20-eyed robot with no front or back, demonstrating dynamic symmetry and improving performance across various measures. The design surpasses the theoretical maximum of 0.6, enabling robustness, energy efficiency, and resilience to damage.
A team from UChicago PME used AI to generate entire chemical formulations for battery electrolytes, balancing complicated tradeoffs and interactions. The research was published in JACS Au and explores a vast chemical space, generating novel candidates satisfying desired properties simultaneously.
The Association for Computing Machinery announced three technical awards for innovations in global wireless standards, machine learning, and 3D generative AI. Erdal Arikan received the Paris Kanellakis Theory and Practice Award for his discovery of channel polarization and polar codes.
A study from Syracuse University and Ipsos found that AI-generated ads are almost indistinguishable from human-made work, but underperform in actual outcomes. The research suggests that humans and AI should work together for a competitive edge.
Researchers developed an Insect Synergy Circuit that integrates body movement and internal physiological information to guide insect navigation. The system achieved high accuracy in classifying environmental conditions, enabling gentle control over the insect's movements.
A new AI model, MutationProjector, analyzes tumor DNA to predict immunotherapy and chemotherapy outcomes in various cancers. The model identifies biomarkers associated with treatment responses and provides insights into why predictions are made.
A mobile app is being developed to identify disease-carrying insects from their wing patterns using machine learning, aiming to reduce the risk of disease transmission in low-income communities. The technology will enable rapid and accurate identification of vectors, tracing disease clusters and responding effectively to outbreaks.
A new study from the University of Miami Miller School of Medicine suggests that machine learning models using patient-reported outcomes and clinical data can forecast unplanned health care use and elevated symptom burden in cancer survivors. The research offers a potential pathway toward more proactive, personalized survivorship care.
Artificial intelligence can bridge the gap between rich multi-scale data generated by modern exercise biomedicine and urgent clinical need for tailored exercise prescriptions. Four key AI modeling paradigms, including time series learning, multimodal fusion, causal inference, and reinforcement learning, are examined.
A new DGMoE framework enhances EEG-based emotion recognition by modeling individual differences, achieving high accuracy rates on public datasets. The framework's two-stage selection mechanism and graph-convolution-based expert modules improve robustness and generalization to unseen subjects.
A new framework combines a custom-built training dataset with transfer learning to improve the detection accuracy of small and distant objects in omnidirectional videos. The proposed model achieved an overall accuracy of 90%, significantly higher than conventional models for small moving objects.
Researchers from Tohoku University's Advanced Institute for Materials Research use AI and data science to extract valuable insights from decades-old experiments and scientific literature. This approach accelerates materials design and screening in catalysis, solid-state electrolytes, and hydrogen storage research.
Researchers developed a neural network approach that learns to clean co-movement patterns in markets before building portfolios. The method achieved lower volatility and higher Sharpe ratios compared to traditional methods.
Zhe Zhu's doctoral dissertation reveals that trusting AI can increase work engagement and build more sustainable careers. GenAI tools can reshape organisational decision-making and employee experiences of work.