Articles tagged with Artificial Intelligence
In a new study, NC State University researchers had high school students develop their own machine-learning AI models to analyze data. The project aimed to prepare students for the future workforce and help them understand the potential and challenges of AI. Students created text classification models using StoryQ technology, which all...
A recent Baycrest study found that older adults are less able to distinguish between computer-generated and human speech compared to younger counterparts. This diminished ability could be related to older adults' reduced capacity to recognize emotions in speech, highlighting the need for AI-related training programs.
The University of Huddersfield has launched a smart rolling stock maintenance research facility to investigate cutting-edge technologies for improving the efficiency and reliability of train maintenance. The facility aims to reduce costs, increase reliability, and make rail travel more affordable.
A study on robot deception found that participants were overly trusting of AI and required explicit admission of lying in apologies to repair trust. Apologies that did not admit to deception were more effective at repairing trust, suggesting a need for designers to understand the ramifications of their design choices.
A new study by Cedars-Sinai investigators found that ChatGPT can provide easy-to-understand information about basic knowledge, lifestyle, and treatments for cirrhosis and liver cancer. The AI system has the potential to play a role in clinical practice and empower patients with knowledge about their disease.
A new AI tool, CLEAN, can predict enzyme functions based on amino acid sequences, outperforming leading state-of-the-art tools in accuracy and reliability. The tool was developed using contrastive learning and verified experimentally with both computational and in vitro experiments.
MIT researchers discovered unconventional activation functions that enable optimal neural network performance, leading to better classification on various datasets. The findings suggest that selecting the correct activation function can significantly improve data accuracy in machine learning applications.
Researchers at NIST have developed a new method of digitally simulating hurricanes using AI techniques, accurately representing the trajectory and wind speeds of real storms. The simulations can help develop improved guidelines for building design in hurricane-prone regions.
Researchers at USC have developed a new type of chip with the best memory of any chip thus far for edge AI. The chip uses metal oxide memristors to store information in a compact and stable way, eliminating the von Neumann bottleneck in current computing systems.
A recent study from Brigham Young University proves that artificial intelligence can respond to complex survey questions just like a real human. The researchers found high correspondence between how AI and humans voted in 2012, 2016, and 2020 U.S. presidential elections.
Researchers from the Smidt Heart Institute found that individuals with spherical hearts are 31% more likely to develop atrial fibrillation and 24% more likely to develop cardiomyopathy. The study identified four genes associated with cardiomyopathy and a greater risk of developing atrial fibrillation.
A University of Central Florida professor led a study identifying six challenges humans must overcome to ensure reliable, safe, trustworthy, and compatible AI. The challenges include responsible design, privacy protection, and respectful interaction with human cognitive capacities.
Assistant Professor Reza Ahmadzadeh at UMass Lowell has been awarded a $500,000 NSF CAREER grant to develop new algorithms for robots to learn complex tasks. The project aims to improve robot performance in everyday tasks, enabling them to assist older adults with daily chores and automate difficult duties in the workplace.
A new article in The Journal of Nuclear Medicine explores the potential for using ChatGPT, an artificial intelligence chatbot, in nuclear medicine and molecular imaging. The authors discuss the strengths and weaknesses of current AI bots and highlight the benefits of collaborating with AI allies to cope with increasing workloads.
Researchers have developed a multidisciplinary approach using a new microscope, artificial intelligence algorithm, and voltage indicators to better measure brain activity. The technique enables the imaging of up to 100 neurons at a time, far surpassing previous limits.
The TANGO project seeks to establish a symbiotic relationship between humans and machines, enabling effective and innovative AI systems that expand human reasoning and decision-making capabilities. Real-world use cases will be evaluated to assess the framework's potential impact on individuals and society.
Researchers developed an AI-based diagnostic screening system called DeepGlioma to analyze tumor specimens and detect genetic mutations rapidly. The system identified molecular subgroups with high accuracy and has the potential to improve access and speed of diagnosis for patients with deadly brain tumors.
Astrophysicists used AI to improve mass estimates of galaxy clusters by adding a simple term to an existing equation. The new equation downplays the importance of complex cores in calculations, providing more reliable mass inferences.
An international team used AI to analyze old star chemical abundances and found indications that the first stars formed in groups. The study suggests that first-generation stars must have been clustered together rather than isolated, offering a new constraint on the multiplicity of the first stars.
Scholars developed an AI program using symbolic regression to improve mass inferences of galaxy clusters. The new equations extract jelly at the center and concentrate on doughy outskirts for reliable mass inferences.
A new study using ChatGPT highlights the challenges of AI in academia, including concerns over academic dishonesty. However, researchers believe that AI can also be leveraged to improve education by automating administrative tasks and adapting assessments.
Researchers developed a computer model based on human brain mechanisms to improve speech comprehension. The model extracts multilevel information from ongoing speech and uses non-linguistic knowledge for disambiguating word meanings. This approach is more human-like than existing language models like ChatGPT.
Researchers developed a new method to collect data on animal behaviour and environment using drones and computer vision. The method allows for the extraction of information on spatial distribution, movement, and behaviour, providing rich insights into the social and environmental context of group-living animals.
Researchers developed a novel design for the chip using a crossbar layout, outperforming state-of-the-art photonic counterparts in terms of scalability and technical versatility. The synergy of powerful photonics with the novel crossbar architecture enables next generation neuromorphic computing engines.
A recent NC State University study examines the relationship between artificial intelligence (AI) and law enforcement. The study reveals that law enforcement agencies must be involved in developing public policies regarding AI technologies, such as autonomous vehicles. Key findings also suggest that many officers lack understanding of ...
Researchers developed an AI tool called SILIC to identify 169 species, including 137 birds, from bird sounds in Yushan National Park. The dataset provides detailed acoustic activity patterns of wildlife across short and long temporal scales.
An international team developed a novel method for evaluating AI interpretability methods to decipher the basis of AI reasoning and possible biases. The approach helps users understand what influences AI results and whether they can be trusted, especially in medical applications where AI-powered decisions can impact health and lives.
Researchers develop unsupervised machine learning algorithm to classify osteosarcoma at diagnosis based on gene expression modules. This approach enables personalized treatment strategies for osteosarcoma patients.
A University of Illinois project uses AI-powered object recognition to quantify kernel damage in wheat, enabling faster disease analysis and improved resistance. The technology has shown promising results, with potential for an online portal to automate scoring and support breeders in their efforts to eliminate fusarium head blight.
Researchers developed a self-driven lab, AlphaFlow, that uses AI to optimize complex chemical reactions and discover new materials. The system significantly reduces the time needed to develop new chemistries from months to hours.
A team of dermatologists developed an AI model to detect complications from bacterial or viral infections in atopic dermatitis patients. The model distinguishes between eczema and skin lesions caused by blood cancer, improving patient management and health outcomes.
A team of researchers, led by UMass Lowell's Neil Shortland, is developing AI systems to help doctors triage patients in emergency situations. The project aims to identify the best human attributes that AI can mirror when making difficult decisions.
Researchers argue that Artificial Social Intelligence (ASI) is the next big frontier for AI. ASI requires social perception, Theory of Mind and social interaction to understand others' mental states and cooperate in shared tasks. The field needs a holistic approach mimicking human interaction.
The Meta-Semi algorithm achieves competitive performance on challenging semi-supervised learning tasks, such as CIFAR-100 and STL-10, with only one additional hyper-parameter to tune. This approach naturally yields a meta-learning formulation where the correctly pseudo-labeled data has a similar distribution to labeled data.
A study published in Radiology found that an AI tool can accurately identify normal and abnormal chest X-rays with a high degree of sensitivity. The tool identified abnormal chest X-rays with a 99.1% sensitivity rate, outperforming clinical board-certified radiologists.
The CONFIDENTIAL6G project aims to enhance the security and reliability of 6G networks, enabling their use in emerging AI tools and IoT devices. IMDEA Software Institute will contribute privacy-preserving computation technologies such as secure multi-party computation and homomorphic encryption.
Researchers explore how AI language models like ChatGPT understand and respond to user input, mirroring their users' intelligence. The Reverse Turing Test reveals that chatbots reflect the intelligence level of their interviewers, incorporating their biases into responses.
A novel AI architecture, relational reasoning network, accurately identifies anatomical landmarks in CT scans for orthodontic treatments. The model learns spatial relationships between landmarks without explicit image segmentation, achieving accuracy comparable to conventional methods.
The use of AI is improving diagnostic accuracy for digestive cancers, but challenges in data sharing and standardization hinder its widespread application. Researchers surveyed recent applications of AI to these deadly cancers, finding that AI can automate complex processes and detect patterns not visible to humans.
A new AI model developed at the University of British Columbia accurately predicts cancer patient survival using natural language processing to analyze oncologist notes. The model shows over 80% accuracy in predicting six-month, 36-month and 60-month survival rates.
A team of researchers at Tohoku University has developed an artificial intelligence-driven contact control system to minimize friction between moving parts in machinery, aiming to reduce wear and tear and extend lifespan.
A groundbreaking study used AI and high spatial resolution imagery to analyze over 300,000 satellite images and identify nearly 10 billion trees in sub-Saharan Africa. The research reveals that tree density and carbon stocks in the arid zone are underestimated, with a total carbon stock of 0.84 billion tonnes.
GPT-3 performs nearly on par with humans in decision-making but struggles with causal reasoning and information search. The language model's limitations may be due to its passive information-gathering approach, highlighting the need for active interaction with the world to achieve human-like intelligence.
Researchers have developed a new type of computer using human brain cells, which could lead to significant advances in computing speed and data efficiency. The technology uses small clusters of brain cells grown from stem cells and aims to increase the number of neurons to surpass electronic computers.
Researchers at Johns Hopkins University are developing 'organoid intelligence' using human brain cells, which could exponentially expand computing capabilities and solve energy consumption issues. The technology has the potential to revolutionize drug testing research for neurodevelopmental disorders and neurodegeneration.
A study by MedUni Vienna's Center for Public Health used GPT-3 to analyze the potential of AI in addressing societal megatrends, including digitization, urbanization, and climate change. The findings suggest that AI can improve understanding of these complex issues and provide suggestions for solutions.
A recent study found that Black bots were perceived as more competent and human than their White and Asian counterparts in digital interactions. This challenges past research on human-to-human interactions and highlights the importance of understanding how racial stereotypes interact with artificial intelligence.
A new cybersecurity framework uses digital twin technology, machine learning, and human expertise to detect cyberattacks in manufacturing processes. The framework analyzes continuous data streams from physical machines and their digital twins to identify irregularities and flag potential threats.
A review of 25 years of AI health tech research found that only 24% of studies include patient-reported outcomes, but there has been an increase in recent years. Experts emphasize the importance of integrating patient voices into AI models to support personalized care and prevent digitalization of healthcare.
Automated AI body composition tools achieved high technical adequacy rates (97.8-99.1%) in a large sample of external abdominal CT scans. The results support the generalizability and potential for widespread adoption of these tools, which can help build trust among radiologists and physicians.
The University of Minnesota Medical School has received $1.4 million in funding to develop methods and risk management processes for clinical artificial intelligence and machine learning to optimize patient safety. The team will focus on understanding the performance of clinical AI at the individual patient level.
A new study by NYU researchers found that infants excel at spotting motivations driving human actions, while state-of-the-art AI models struggle. By comparing infant and machine intelligence on a series of tasks, the researchers shed light on the limitations of current AI systems.
The metaverse can be used to investigate the effectiveness of large-scale interventions before implementation, saving time and money. It also provides a platform for people with limited access to natural environments to experience green spaces, reducing negative mental health effects.
A Carnegie Mellon University professor proposes a new AI model that highlights the evidence of fairness in decision-making. The model provides counterfactual explanations to demonstrate whether past decisions were fair or biased. This research has practical implications for legislative efforts, industry norms, and AI model evaluation.
Researchers used AI to analyze thousands of satellite measurements, revealing four categories of ice movements linked to meltwater flow. The study provides insight into how the Greenland ice sheet reacts to warmer temperatures and more meltwater.
The Heidelberg Laureate Forum Foundation offers journalist travel grants to cover the 10th HLF from September 24-29, 2023. Recipients of prestigious awards in mathematics and computer science will gather with young researchers for a week of interdisciplinary dialogue.
A new study by Tulane University demonstrates that even a single atom can act as a reservoir for computing, processing information optically. The researchers proposed a non-linear single-atom computer where input and output are encoded in light, enabling flexible computation with any desired outcome.
Researchers develop a governance model for ethical guidance in AI, combining copyleft licensing with the patent troll approach. The CAITE model assigns enforcement rights to a third-party host, ensuring compliance while promoting flexibility and community participation.
Researchers at University of Gothenburg developed AI method using graph theory and neural networks to analyze cell movement, enabling better understanding of biological processes and development of new medical technologies. The method can reconstruct cell paths and test medication effectiveness as potential cancer treatments.
A Penn State-led research team found that language models can plagiarize content in three ways: verbatim, paraphrase, and idea reuse. The study highlights the need for more research into text generators and their potential ethical implications.