Articles tagged with Artificial Intelligence
Researchers at Tsinghua University Press propose integrating AI technology into launch vehicles to address challenges of high-frequency launches and reliable flights. The system aims to achieve hour-level test, inspection, and decision-making times for large launch vehicles.
Researchers used causal AI to extract insights from ARPES data of cesium vanadium antimonide, a kagome superconducting material. The technology revealed that the chemical bonding state of cesium atoms strongly influences the electronic state of the V3Sb5 layer, responsible for superconductivity.
Researchers from RIKEN and their international collaborators used deep learning techniques to analyze unexamined nuclear emulsion data and identified a new double-Lambda hypernucleus. This is the world's first AI-assisted observation of such an exotic nucleus, providing new insight into neutron star cores.
The new program focuses on advancing foundational research in AI, including innovation in language models and algorithmic efficiency. Google will support research grants, scholarships for students, and educational initiatives at the TAU Center.
A new study uses AI to regulate mechanical ventilation for patients with ARDS, aiming to provide personalized support. The tool combines live patient monitoring with historical data to modulate ventilation parameters and reduce lung injury.
Researchers found that AIs consistently converged on 12 common themes despite diverse prompts, suggesting biases in training data. The models failed to generate novel or creative outputs, highlighting the need for anti-convergence mechanisms and human input for AI's creative potential.
CORAL accurately predicts genetic subtypes and patient outcomes in multiple myeloma without costly genomic tests. The technology could be applied to other cancers, opening the door to personalized, faster and widely accessible cancer care.
Researchers developed RNACOREX, a new open-source software tool that identifies gene regulation networks in cancer. The tool analyzes thousands of molecules simultaneously to detect key interactions, providing an interpretable molecular map that improves understanding of tumors.
Researchers developed a scientifically validated personality test framework for AI chatbots, showing that larger models accurately emulated human traits and could be reliably shaped through prompts. The study raises concerns about AI safety and ethics, highlighting the need for regulation to prevent misuse.
Researchers have identified DNA switches that control how brain cells called astrocytes work, which are known to play a role in Alzheimer's disease. The study used CRISPRi technology and single-cell RNA sequencing to test nearly 1000 potential switches, finding that about 150 of them controlled genes implicated in Alzheimer's disease.
A new AI method has identified 51 old pea varieties with high starch and protein content, potentially suitable for producing plant-based foods. The study shows a close relationship between seed appearance and chemical composition, enabling partial prediction of properties based on images.
The ACM's Technology Policy Council has issued a report on automated speech recognition (ASR) highlighting the need for rigorous audit and governance practices. The report raises concerns about technological bias, inequity, and lack of transparency in ASR systems.
A novel approach has been proposed to facilitate collaboration between human researchers and AI in self-driving labs. The AI advisor model enables humans to make real-time decisions while leveraging AI's data-processing prowess.
A new AI-assisted device, CanvasDx, has been shown to improve autism care access in rural Missouri communities. By reducing travel distances and processing times, families can receive diagnoses up to 5-7 months earlier.
Researchers will use revolutionary technology to transform understanding of extreme environments, revealing how black holes behave and evolve. The project aims to deliver dynamic gravitational tomography, creating 3D movies showing plasma flows around black holes.
A research team at the University of Ottawa developed an AI system to autonomously defend wireless networks against jamming attacks. The dual-agent framework predicts interference events and makes real-time decisions to maintain essential communications during attacks.
Researchers at IIT identified a candidate molecule called Apt1 that enhances existing anticancer therapies by making tumour cells more vulnerable to chemotherapy drugs. The molecule slows DNA repair and impairs the interaction between RAD51 and BRCA2 proteins, inducing synthetic lethality in cancerous cells.
Mayo Clinic researchers developed an AI-ECG model that accurately diagnoses advanced chronic liver disease, allowing for early intervention and potential lifesaving treatment. The study found the model detected twice as many cases as standard methods, highlighting the promise of AI in preventive care.
A new study found remarkable variation in how populations evolve in variable environments, with some cases benefiting from changes and others being hindered. The research has implications for understanding evolution and adapting to climate change, as well as informing AI and machine learning.
A new study from the University of East Anglia finds that AI tools excel at speed and clarity, but human translators remain crucial for tone, cultural nuance, and natural sound. Generative AI can handle parts of video translation, but consumers still notice when something feels off.
A small analysis found AI-generated images of doctors exaggerate and reinforce existing stereotypes on sex, gender, race, and ethnicity. This contradicts recent medical workforce statistics, which show a more diverse range of doctors in the UK and US.
Dr. Tom McClelland from the University of Cambridge believes that our current evidence is insufficient to determine whether artificial intelligence has achieved consciousness. He suggests that sentience, which involves positive and negative feelings, is a more critical factor in making AI ethically significant.
A new AI framework uses a pre-trained viral protein language model to predict the adaptation risk of unknown viruses. The framework, called GIVAL, achieves high accuracy and robustness even with incomplete data, providing critical support for early warning and proactive prevention and control of viral infectious diseases.
A new computational framework allows researchers to recreate different evolutionary trees by changing the structure of the world and tasks AI agents complete. The framework showcases how tasks drove eye evolution in agents, with navigation tasks leading to compound eyes and object discrimination driving camera-type eyes.
Researchers propose integrating processing capability within memory units to reduce energy consumption and latency in AI applications. Inspired by the brain's efficient processing mechanisms, spiking neural networks (SNNs) can respond to irregular events and store information in the same place.
Researchers developed an AI model that can detect coronary microvascular dysfunction using a common electrocardiogram, outperforming previous models in diagnostic tasks. The model can accurately identify a condition often missed in emergency department visits, providing a cost-effective and non-invasive way to diagnose serious heart co...
Researchers have launched a new multimodal medical dataset, Observer, capturing anonymized, real-time interactions between patients and clinicians. The dataset links video, audio, transcripts, and electronic health records to study subtleties like body language and environmental factors affecting care.
A new study led by Harvard Medical School researchers found that AI models analyzing pathology samples can infer demographic information, leading to biased diagnoses. The team developed a framework called FAIR-Path to reduce bias in these models, which showed improved performance across demographics.
An AI-driven robotic assembly system allows people to build physical objects by simply describing them in words. The system uses generative AI models to build a 3D representation of an object's geometry based on the user's prompt, and then iterates on the design based on feedback from the user.
A recent study reveals that sampling biases in bacterial population structure can severely undermine the accuracy of AI models predicting antimicrobial resistance. The researchers recommend evaluating future methods to address this issue.
Researchers propose a novel approach to AI hardware design by integrating neuromorphic systems and compute-in-memory techniques to overcome the limitations of modern computing hardware. This could lead to more efficient data center energy use and enable real-time intelligence in compact, power-constrained systems.
A new study warns that AI is racing ahead of safety checks in GP clinics, putting patients at risk. The research found that many GPs use AI tools without thorough evaluation or regulatory oversight, carrying risks like automation bias and loss of important social details.
A team of MIT engineers developed a deep-learning model that predicts how individual cells will fold, divide, and rearrange during a fruit fly's earliest stage of growth. The model achieved 90% accuracy in predicting the movement of 5,000 cells over the first hour of development.
AI is becoming increasingly used in peer review, with 53% of reviewers now utilizing AI tools to enhance research quality and trust. The study highlights significant untapped potential for AI to support rigor, reproducibility, and deeper methodological insight.
Researchers at Mayo Clinic have developed a smartwatch-based alert system that signals parents to intervene in children with emotional and behavioral disorders, reducing tantrum duration by an average of 11 minutes. The system uses physiological stress signals detected by the smartwatch to prompt parental intervention.
The University of Oklahoma researcher is working on a project using inverse design techniques and AI to create advanced materials that can quickly switch between conductive and insulating states. The goal is to reduce uncertainty in the discovery process and create a scalable material-design methodology.
Stanford engineers develop an AI framework called MetaChat, which rapidly accelerates metasurface design using computational tools and self-reflective AI assistants. This enables rapid solving of optics-related problems, such as designing metal lenses that can focus different wavelengths of light.
Researchers at UT Health Sciences Center have developed an AI-enhanced platform called ENRICH, which leverages advanced analytics with community-based human support to reduce treatment interruptions and improve cancer outcomes. The program identifies patients at highest risk for interruption and deploys targeted support resources.
Researchers used AI to study covert attention and found emergent properties in artificial neural networks, including new neuron types with response properties never highlighted before. The findings have implications for our understanding of the human brain and its ability to process information.
Researchers found a positive relationship between government support and voluntary planting of cover crops in Arkansas. The study showed that soybean-to-soybean rotation is the most common aftercover crop adoption, with voluntary cover crops increasing by 5% over the 2013-2019 period.
A new study found that highly educated, Western European millennials have the most digital concerns, with individuals having higher levels of digital literacy being the most affected. The research also found that people's perceptions of digital harm are heightened by their level of digital exposure and knowledge.
Mass General Brigham's new AI company, AIwithCare, has developed a software platform that leverages generative AI to screen patients for clinical trial eligibility. The tool, RECTIFIER, was found to accurately identify eligible patients and enroll them in clinical trials at a lower cost than traditional methods.
A study published by Michigan Medicine suggests that AI can help increase the chance of people with risky drinking patterns or signs of alcohol use disorder getting outreach and help. The NLP tool analyzed full text of health records and identified over 47,500 patients with some sign of risky drinking.
Researchers trained AI systems on data from two cultural groups playing a video game, finding that the agents learned and applied the group's degree of altruism. This approach, called inverse reinforcement learning, more closely aligns with human development and learning, where values are 'caught' rather than 'taught'.
A new study by researchers at TU Graz and the Know Center shows that AI-powered recommender systems can perpetuate unfairness if not designed with human decision-making in mind. The study proposes a multi-stakeholder approach, involving service providers, municipalities, and local residents, to ensure fairness and transparency.
A new study suggests that a simple ECG reading from a smartwatch can accurately estimate a person's age, potentially offering a secure alternative to facial recognition or ID checks. The method achieved an average error of just under three years and accuracy consistently reached between 93 and 96%.
MIT researchers developed a new fabrication method to stack multiple functional components on top of one existing circuit, reducing energy wasted during computation. The new approach enables the production of more energy-efficient electronics, boosting computation speed and reducing electricity consumption.
A new method has been developed to generate valid confidence intervals for problems involving data that vary across space, helping researchers trust the results of certain experiments. This work can be applied to fields like environmental science and epidemiology.
A third of teenagers use AI companions for social interaction, with some reporting more satisfying conversations than humans. Experts caution against problematic chatbot use as a new environmental risk factor, particularly among vulnerable populations.
Scientists at Michigan Medicine have developed machine learning models that can analyze blood samples for biomarkers to detect ALS earlier and predict disease severity. The models show promising results, with predictions accurate up to 91% in some cases, and could lead to improved diagnostic accuracy and treatment options.
The SWIFTT project presents a hybrid seminar to showcase its platform that helps foresters detect and prevent insect outbreaks, analyse windthrow and fire damage. The event features live demos and presentations from the project team, highlighting the platform's benefits for sustainable forest management.
Researchers at Florida Atlantic University have developed a deep learning model that detects and evaluates Alzheimer's disease (AD) and frontotemporal dementia (FTD) using EEG brainwave analysis. The model achieved over 90% accuracy in distinguishing individuals with dementia from cognitively normal participants.
Researchers develop an integrated pipeline to analyze and visualize NHANES dental caries data, identifying age-driven heterogeneity and novel associations between caries status, environmental factors, and disease markers. The study demonstrates the value of integrating machine learning with large-scale observational data for deeper ins...
The startup aims to bring human integration and industrial usability to its robots, which will operate safely and efficiently in industrial environments. The company's mission is to create a future where humans and robots collaborate daily.
Overleaf is introducing a new AI assistant that combines advanced capabilities with its intuitive editor. The tool helps researchers spend less time coding and more time producing high-quality work. The new features are available in Overleaf Labs and provide a research-focused writing assistant and a first-of-its-kind citation reviewer.
Researchers in Australia and Aotearoa New Zealand will have expanded open access publishing options through a new three-year agreement. The partnership supports fully open access journals and enables the expansion of AI use in teaching and research.
Researchers developed multimodal models integrating imaging, clinical, and molecular data from TAILORx tissue biorepository for early-stage breast cancer. The models demonstrated enhanced prognostic performance compared to existing methods, highlighting their potential for personalized treatment decision-making.
The company's AI tool, RECTIFIER, uses generative AI to screen patients for clinical trial eligibility, significantly outperforming manual screening in accuracy and efficiency. The tool has been shown to more accurately identify eligible patients and reduce the burden of manual chart review in various healthcare settings.
Researchers developed an AI tool to identify patients with undiagnosed Alzheimer's disease using electronic health records, addressing underdiagnosis and healthcare inequities. The model achieved sensitivity rates of 77-81% across diverse populations, promoting fairness while maintaining high accuracy.
A new report highlights the surge in child sexual exploitation and abuse online, with AI-generated material increasing by 1,325% in a year. The WeProtect Global Alliance's Global Threat Assessment 2025 provides a practical tool for technology companies and governments to tackle the crisis.