Articles tagged with Cognitive Robotics
The EMERGE project establishes a philosophical, mathematical and technological framework for collaborative awareness in artificial systems. Researchers found that people can understand an artificial system as aware without assuming subjective experience, and that increasing awareness can improve performance.
Researchers at Harvard and Georgia Tech have developed RLE-Bench, a benchmark that tests AI coding agents' ability to engineer physical robots. The benchmark contains 48 tasks that test the agent's ability to perform engineering work required to build and operate robotic systems, including control and perception algorithms, designing r...
Duke University has received a $24 million award to develop foundational science for engineering systems to counter unmanned aerial attacks. The center, led by Miroslav Pajic, brings together experts in wireless systems, cybersecurity, and AI to develop tools and automated procedures for detecting, thwarting, and controlling enemy drones.
Researchers propose an AI framework, called interoceptive AI, that uses internal states to inform learning and decision-making in dynamic environments. This approach treats internal conditions as a continuous source of context, influencing what an agent learns, prioritizes, and does.
A WVU researcher is working to make AI systems more transparent about their uncertainty, to prevent misinformation and improve trust in high-stakes fields like healthcare. The goal is for AI systems to identify when they're unsure and ask questions or provide more nuanced responses.
Researchers integrate AI into local monitoring sensors to track ecosystem health in near real-time, reducing delays of months to years. The project enables faster release of accessible flux data, helping scientists understand ecosystem responses to change and inform land management decisions.
This theme issue explores clinical efficacy, seamless support systems, and ethical AI integration for home-based care. Research topics include 'invisible' monitoring, computer vision, socio-technical drivers of AI adoption, and clinical implementation.
A new study found that robot-delivered feedback can help learners recover from mistakes, but more personalized feedback was not automatically more helpful in the next moment. Personalized feedback was linked to better overall performance across the whole task, suggesting a trade-off between detailed feedback and learning speed.
Researchers created a virtual robot with curiosity-driven neural network and tested its performance, finding that play-like behavior and exception-handling performance helped the robot understand language faster. The study suggests a combination of curiosity and linguistic diversity is key to children's rapid language acquisition.
The WVU team developed an AI framework that allows satellites to not only detect wildfires but also coordinate with one another and adjust their observation schedules as fires spread. This enables firefighters to respond sooner, taking into account the rapid movement of wildfires, dense vegetation, and hills.
A new learning-based adaptive tuning method integrates chaotic search with particle swarm optimization to improve stability and solution quality in chaotic search algorithms. The approach consistently achieves better results than conventional methods, providing a practical means of enhancing the performance of chaotic search.
Researchers Iris van Rooij and Olivia Guest warn against relying on AI to replace human thinking in psychology research. They argue that AI systems lack the complexity of human cognition and cannot produce meaningful results.
Avishek Choudhury, a WVU researcher, has won the NSF CAREER award to study how healthcare providers' trust in artificial intelligence changes over time. His goal is to humanize algorithms behind AI and improve decision-making quality and patient safety.
The ACM Technology Policy Council's TechBrief examines agentic AI's legal liability, security risks, and workforce impacts. Existing frameworks fall short in addressing accountability questions, highlighting the need for defined authentication and delegation standards, robust audit trails, and sector-specific guidance.
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 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 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.
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.
The Association for Computing Machinery has published its inaugural issue of ACM AI Letters, a premier venue for rapid and timely AI research. The journal aims to bridge the gap between traditional conferences and journals, featuring short, peer-reviewed contributions that accelerate knowledge dissemination across academia and industry.
The International Telecommunication Union (ITU) will host the seventh AI for Good Global Summit from 7 to 10 July 2026 at Geneva’s Palexpo convention centre. The summit aims to guide the future of artificial intelligence and unlock its potential to serve humanity.
Researchers at the University of Pennsylvania have developed HoloRadar, a system that enables robots to reconstruct hidden 3D spaces beyond their line of sight using radio waves processed by AI. This capability can improve safety and performance in driverless cars and cluttered indoor settings.
Researchers at OIST found that combining inner speech with working memory enhances AI learning, enabling easier adaptation to new situations. This discovery holds promise for developing more human-like AI systems capable of handling complex, dynamic environments.
Researchers created a computational model that combines physiological signals, sensory input, and word information to construct human emotions. The model achieved an agreement rate of about 75% when compared to participants' self-reported emotional evaluations.
This book offers a comprehensive exploration of AI-driven analytics in finance, addressing market prediction, fraud detection, and risk assessment. It also discusses AI applications in healthcare and cybersecurity, including disease classification and biometric identification systems.
The Stowers Institute has appointed its first AI Fellow, Sumner Magruder, to harness the potential of artificial intelligence in biological research. He will collaborate with researchers to design new algorithms and unlock insights from large datasets.
Bezzo's project enables embodied cognition capabilities in large language models, equipping robots with human-like understanding of human intent. The work has wide-ranging potential for assistive technologies, collaborative robots, and defense missions.
Researchers developed AI models that can identify signs of heart failure in patients from Appalachia using low-tech electrocardiogram results. The models achieved high accuracy and could potentially provide clinicians with an edge in protecting patients' cardiac health.
A large-scale study found that Green AI significantly improves operational and environmental performance in Pakistani SMEs, but only when leaders invest, and institutions are in place. Adoption works under the right conditions, with perceived ease of use and usefulness driving behavior.
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.
A new study published in the Journal of Experimental Psychology found that interacting with robots through social games makes them seem more human-like. The researchers used a box-shaped robot called Cozmo and found that participants who played games with it considered it more human-like, whereas those who interacted mechanically did not.
A research team developed AI technology that analyzes individual personality traits and values to generate personalized analogies, allowing people to understand others' feelings through familiar experiences. This approach significantly improved emotional understanding and empathy in participants compared to traditional methods.
A new study published in Frontiers in Robotics and AI explores the use of artificial intelligence to detect live oysters. While the AI model ODYSSEE shows promise, it lags behind humans in accuracy, correctly identifying live oysters at a rate of 63% compared to 74% for expert annotators.
Researchers found that artificial intelligence tools can accurately predict disease for patients with typical symptoms but struggle with those exhibiting atypical symptoms. Human oversight is necessary for high-quality patient-centered care when using AI as an assistive tool.
JMIR Mental Health is seeking rigorous research on AI-powered therapy bots and virtual companions for mental health. The journal aims to explore their effectiveness, limitations, and place within broader care models.
Researchers developed a novel vote-based model for accurate hand-held object pose estimation, addressing issues with existing approaches. The new framework achieves significant improvements in accuracy and robustness, enabling robots to handle complex objects and advancing AR technologies.
The collaboration aims to accelerate the development and commercialization of inait's innovative AI technology, using its unique digital brain AI platform. It will focus on joint product development, go-to-market strategies, and co-selling initiatives, initially targeting the finance and robotics sectors.
Researchers developed Torque Clustering, an unsupervised learning method that efficiently uncovers patterns in vast datasets without human guidance. The algorithm outperforms traditional methods, offering a potential paradigm shift for robotics and autonomous systems.
Neuromorphic computing is poised to emerge into full-scale commercial use, driven by the need for energy-efficient solutions. The review article proposes strategies for building large-scale neuromorphic systems that can tackle complex real-world challenges.
The HumanTech Summit 2024 conference brings together experts in technological and social innovation, discussing key topics such as data security and interpersonal relationships. With a proven legacy of impact, the event has attracted over 1,400 participants and featured renowned keynote speakers from top universities.
A review paper explores how robots can aid in understanding the human sense of self, including simulating mind and brain processes and testing social capacities. Researchers aim to transfer some features of human self-awareness to robots, which could provide insights into its development and potential applications.
Researchers used a dog-like robot integrated with AI to automate the identification and control of Red Imported Fire Ants, detecting three times more nests with greater precision. The system's effectiveness was tested in field trials, but challenges remain in scaling up production costs.
Scientists at UVA and Toyota Research Institute create language representations of driving behavior to enable robots to associate words with environmental interactions. This allows cars to provide guidance and adjust speed in challenging situations, improving safety and usability.
A new study on learning has provided insights into the balance between habitual and goal-directed behaviors, with implications for AI development. The research suggests that a balance between these two types of behavior is necessary for efficient and adaptable decision-making in AI systems.
Researchers from UNIGE have developed an AI that can learn a task solely based on verbal instructions, then describe it to another AI, which reproduces the task. This breakthrough is promising for robotics and understanding human language.
Researchers found that participants who were initially skeptical or disagreed with climate change or BLM became more supportive after conversing with GPT-3. The chatbot's response styles differed between topics, with more justification for human-caused climate change.
A new AI system, Coscientist, has demonstrated its ability to autonomously learn about Nobel Prize-winning chemical reactions and design successful laboratory procedures. The system achieved this in just a few minutes, outperforming human chemists in some cases.
The European Union's AI act could enable AI to access our subconscious minds, potentially leading to manipulation. According to Ignasi Beltran de Heredia, only 5% of brain activity is conscious, and the remaining 95% operates subconsciously, making it difficult for us to control or even be aware of.
A recent study by Osaka University's researchers aims to bring science fiction stories closer to reality by studying the mechanical properties of human facial expressions. The team mapped out the intricacies of human facial movements using tracking markers, revealing that even simple motions can be surprisingly complex and nuanced.
A Lancaster University academic argues that AI and algorithms contribute to polarization, radicalism, and political violence, posing a threat to national security. The paper examines how AI has been securitized throughout its history, highlighting the need for better understanding and management of its risks.
Researchers discovered that humans experience empathic embarrassment when witnessing robots in embarrassing situations. The study also found cognitive empathy was stronger for human actors compared to robot avatars.
Researchers developed a tool called SKILL that enables AI agents to learn 102 distinct tasks by sharing knowledge in parallel, reducing the time needed to master new skills. The technology has potential applications in medicine, education, and other fields where vast knowledge is required.
Researchers examine whether robots and AI can replicate the ethical concepts attributed to human nurses, including advocacy, accountability, cooperation, and caring. While AI can inform patients about medical errors and present treatment options, it questions its ability to truly understand and empathize with patients' values.
The CEBRA algorithm captures brain dynamics with high accuracy, allowing for the prediction of complex information such as visual stimuli and arm movements in primates. By analyzing brain signals alone, researchers can decode hidden structure in data, enabling new insights into how the brain processes information.
Researchers developed a robotic finger with high-resolution sensors that capture data along the entire length of each finger. The three-fingered robotic hand can identify objects after just one grasp, with 85% accuracy, using tactile sensing and machine-learning algorithms.
Researchers seek to develop algorithms providing meaningful explanations for AI decision-making, enabling higher human trust and adoption in fields like science. The project focuses on symbolic reasoning and estimating explanation accuracy, addressing the need for transparent AI systems.
Researchers at Cornell University have developed a new system of fluid-driven actuators that enable soft robots to achieve more complex motions. The team's design allows for antagonistic motions and predicts the actuator's possible motions with a single fluid input, resulting in an actuator that can achieve far more complex movements.
A new evaluation method at Osaka University accurately compares android and human facial expressions. The study found that androids have significantly less expressiveness than humans, but the new index may aid in developing more lifelike robots.
The university's new Robotics and Autonomous Systems Teaching and Innovation Center (RASTIC) will provide students with hands-on experience in robotics, autonomous systems, and self-driving technology. The lab aims to boost Massachusetts' competitiveness in the tech sector by supporting innovative projects and startups.
Researchers at Ben-Gurion University successfully trained a goldfish to drive a robotic car in new research exploring animal navigation abilities. The study found that goldfish's innate navigational skills surpass their aquatic environment, demonstrating universal cognitive abilities.
A new study by USC researchers uses GANs to generate synthetic neurological data that can be fed into machine-learning algorithms to improve BCI usability. This approach improved BCI training speed by up to 20 times and enabled rapid adaptation to new subjects.