Articles tagged with Ai Common Sense Knowledge
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.
Researchers found that non-expert users' intuitive prompts triggered biased responses as effectively as expert 'jailbreak' techniques. The study used a competition to identify biases in generative AI models and suggests strategies for mitigating issues.
A Michigan State University-led study examines how well AI personas can detect human deception and compares their performance to humans. The results show that AI is more lie-biased and less accurate than humans, highlighting the need for improvement before generative AI can be used for deception detection.
Researchers warn that AI-generated wildlife videos create false connections with nature, leading to misconceptions about wild animals and their behaviors. The proliferation of these videos can undermine conservation efforts and disconnect society from the natural world.
Researchers examine how genAI affects task structure, worker adoption, and job displacement. The authors suggest genAI will widen the 'cone of automation,' substituting for complex work and infrequent tasks.
Researchers at USC Viterbi School of Engineering have developed artificial neurons that physically embody the analog dynamics of biological brain cells. These innovations will allow for significant reduction in chip size and energy consumption, potentially advancing artificial general intelligence.
A new study by Yifan Yu offers guidance on how to deploy emotion AI in various scenarios, emphasizing the importance of balancing human involvement with AI's emotional detection capabilities. The analysis showed that emotion AI works best when integrated with human employees, and some scenarios are better handled by humans alone.
The new report aims to harness the potential of artificial intelligence (AI) in care delivery by modernizing outdated laws, regulations, and payment systems. It highlights promising tools such as ambient documentation, virtual care coordination systems, and personalized clinical education.
Researchers used five advanced LLMs to assess their logical reasoning capabilities and found that they consistently complied with requests for false medical information. Targeted training and fine-tuning improved LLMs' abilities to respond to illogical prompts accurately, but challenges remain in aligning models to every type of user.
A new AI-based risk assessment tool, GRACE 3.0, has shown better predictability of future risk for heart attack patients compared to traditional methods.
Researchers at Institute of Science Tokyo developed a new framework for generative diffusion models by reinterpreting Schrödinger bridge models as variational autoencoders. This approach reduces computational costs and prevents overfitting, enabling more efficient generative AI models with broad applicability.
The Chatbot Assessment Reporting Tool (CHART) statement outlines 12 key reporting items for chatbot health advice studies, providing a checklist and methodological diagram. This guideline supports stakeholders in reporting, understanding, and interpreting the findings of such studies.
Researchers developed a custom speech recognition system trained on Supreme Court hearings, reducing transcription errors by up to 9% compared to leading commercial tools. The AI tool semantically matches paragraphs with timestamps, allowing users to scroll through judgements and instantly watch relevant exchanges from the hearing.
Researcher Angus Fletcher argues that AI excels at logic but fails to replicate human creativity and problem-solving skills. He advocates for developing 'primal intelligence,' which involves intuition, imagination, emotion, and commonsense, and has developed a program to help people tap into this ability.
Researchers at UCR have developed a method to preserve AI safeguards in open-source models by retraining internal structure to detect and block dangerous prompts. The approach avoids external filters or software patches, instead changing the model's fundamental understanding of risky content.
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 former diplomat warns that algorithms lack empathy and intuition, which are essential for successful negotiations. However, AI can streamline diplomacy and amplify human aspirations when used carefully. Diplomats need training in AI ethics and global cooperation to ensure equal access and deployment.
Researchers from the University of Bath and University of Hong Kong found that additive advice bias is common in conversations, social media, and AI chatbots. This bias can leave people feeling more overwhelmed than helped, with well-intentioned tips piling on extra tasks.
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.
The Ateneo de Manila University's Business Insights Laboratory explores how AI can turn handwritten sales logs into manageable digital data. The system uses OCR and LLM technology to recognize products, match prices, and tabulate sales summaries, helping businesses quickly identify bestsellers or slow-moving stock.
The ERIC system combines doorbell cameras and AI to analyze rainfall estimation and automatically adjusts irrigation schedules for more precise water use. Researchers estimate users can save up to $29/month in utility costs and 9,000 gallons of water per month with the innovative irrigation system.
The journal is seeking high-quality submissions that explore the potential of voice and speech analysis in diverse medical applications. Submissions focus on acoustic and voice analysis techniques, voice or vocal phenotyping, and vocal biomarkers in health and medicine.
A team of computer scientists created 2,300 original sudoku puzzles and asked AI tools like OpenAI's ChatGPT to solve them. The results showed that while some AI models could solve easy sudokus, most struggled to provide accurate explanations, raising questions about the trustworthiness of AI-generated information.
Researchers use AI to solve differential equations, such as Schrodinger's equation, for large-scale systems, improving efficiency and accuracy in fields like drug discovery and material design.
A new study from the University of Colorado Anschutz Medical Campus shows that free, open-source AI tools can help doctors report medical scans just as well as more expensive commercial systems without compromising patient privacy. The research highlights a promising and cost-effective alternative to widely known tools like ChatGPT.
A University of Kansas study found that people rate corporate crises messages written by humans as more credible and trustworthy, regardless of the approach taken. However, the approach itself didn't vary between participants who read human or AI-written content.
A new study published in JAMA Network Open found that people judge physicians using AI as less competent, trustworthy, and empathetic. This effect was observed even for administrative uses of AI. The study suggests that addressing concerns about AI's role in medicine is crucial for improving patient-doctor relationships.
A new study by Cornell University reveals Amazon's AI shopping assistant Rufus gives vague or incorrect responses to users writing in some English dialects like AAE. The researchers propose a framework for evaluating chatbots that can better serve users from diverse linguistic backgrounds.
Researchers investigate whether language alone is sufficient to understand color metaphors and find that hands-on experiences using color unlock deeper conceptual representations in language. ChatGPT generates consistent color associations but struggles with novel metaphors and embodied explanations.
The College of Engineering at Texas A&M is developing a suite of university-wide resources to integrate generative AI into course material, research, and outreach. The initiative aims to make generative AI a core part of the academic toolkit accessible to faculty across disciplines.
The study analyzed 50 countries' national AI strategies, finding that only 13 gave high priority to training the current workforce and improving AI education. Common themes included establishing AI-focused programs in universities and on-the-job training, with a focus on human soft skills such as creativity and collaboration.
Researchers used nonsense words to test ChatGPT's language processing capabilities, finding it excelled at discovering relationships and providing definitions for extinct words. However, the AI also generated incorrect or made-up answers in some cases, highlighting its limitations.
Global education leaders call for collaboration, ethics, and human-centered teaching as they confront the benefits and challenges of AI in education. The discussion emphasized the need for responsible use policies, equitable access to AI tools, and preserving uniquely human qualities in education.
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 recent study by Ohio State University researchers found that AI lacks the human understanding of flowers due to its inability to experience sensory and motor aspects. This limitation affects not only flower but also other complex human concepts.
The new minor will equip students with cutting-edge AI and machine learning skills essential for modern business leadership. It combines hands-on experience with practical applications of artificial intelligence in business settings.
Experts Cary Coglianese and Colton Crum argue that management-based regulation, or using
Researchers at Stevens Institute of Technology created an AI architecture to flag unscientific claims in news reports on scientific discoveries. The team's LLM pipelines achieved about 75% accuracy in distinguishing between reliable and unreliable news reports, with potential applications in browser plugins and rankings of publishers.
A University at Buffalo-led study proposes using AI-powered handwriting analysis to identify spelling issues, poor letter formation, and other indicators of dyslexia and dysgraphia. The work aims to augment current screening tools and provide an early detection tool for these neurodevelopmental disorders.
Developers of educational tools focus on technical challenges, while educators are concerned with broader impacts, such as inhibiting critical thinking skills and exacerbating systemic inequality. Researchers recommend designer-centered approach to facilitate development of educator-centered edtech.
Large Language Models (LLMs) like Mixtral can grade student responses quickly, but often rely on shortcuts and assume students understand topics. Researchers found that LLMs are more accurate when provided with human-made rubrics, which include specific rules for grading. This suggests that AI can be used to streamline grading processe...
A study by University of East Anglia compared 145 real student essays with 145 ChatGPT-generated ones, finding that AI essays were coherent but lacked engagement markers like questions and personal commentary. This reflects the limitations of AI in replicating human writing's conversational nuance.
Researchers found that realistic AI avatars are rated more positively than cartoon-style ones for perceived competence, integrity, and benevolence. However, individual factors such as prior AI knowledge and trust in science moderate perceptions of trustworthiness.
A recent study from UTSA researchers reveals that large language models (LLMs) can pose a serious threat to programmers who use them to help write code. The study found that up to 97% of software developers incorporate generative AI into their workflow, and 30% of code written today is AI-generated.
A recent study suggests that AI systems replicate and amplify existing social inequalities when left unchecked, particularly in high-stakes areas like hiring and welfare distribution. The researchers argue for the need for greater transparency, inclusivity, and accountability in AI governance to ensure its use serves social justice.
Researchers at the University of Washington developed a new method called variational preference learning, which predicts users' preferences and tailors its outputs accordingly. This approach overcomes the limitations of traditional RLHF, which can lead to averaging user preferences and resulting in incorrect outputs for all users.
Researchers created a measurement scale to assess robot human likeness, revealing four key qualities: appearance, emotional capacity, social intelligence, and self-understanding. To seem lifelike, robots must exhibit these traits, with self-understanding being the most challenging aspect to simulate.
Researchers tested 24 MLLMs on Raven's Progressive Matrices, finding that open-source models struggled significantly. However, closed-source models like GPT-4V performed relatively well, suggesting a need for more advanced resources and training data to improve AI's cognitive abilities.
The study challenges the idea of creating artificial general intelligence (AGI) with human-level cognition, citing limitations in replicating human cognition. Researchers argue that even under ideal circumstances, it is impossible to achieve AGI due to the complexity of cognitive processes.
A recent study published in PNAS Nexus found that widespread adoption of large language models like ChatGPT led to a significant decline in user activity on Stack Overflow. The study highlights the impact of ChatGPT on public knowledge sharing and its implications for AI's future.
A new study published in JAMA Health Forum found that machine learning can be more effective than traditional methods for distributing scarce treatments to patients most vulnerable during a public health crisis. The model reduces expected hospitalizations by about 27 percent compared to actual and observed care.
A recent study published with the Arkansas Agricultural Experiment Station found that ChatGPT can be a useful tool in teaching agriculture students to program microcontrollers. The study, which aimed to determine the confidence of undergraduate agricultural students in using ChatGPT to write Arduino code for moderately difficult progra...
Researchers created a data set of over 10 million documents to test detection ability in current and future detectors. They found that most detectors only work well in specific use cases and can be easily evaded by manipulating the text. The new tool, RAID, aims to provide a standardized benchmark for robust detection.
New research finds that AI explanations can fuel a perception of fairness without being grounded in accuracy or equity. Humans were more likely to override AI recommendations when explanations highlighted gender rather than task-relevance, but this did not improve decision-making accuracy.
Researchers are developing a framework to combine AI and human intelligence in process safety systems, aiming to enhance safety and efficiency. The study identifies challenges and benefits of using Intelligence Augmentation (IA) and proposes strategies for effective implementation to minimize risks.
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 Carnegie Mellon University study finds that people with autism are using AI chatbots for workplace advice, but raises questions about the quality of the advice and the need for inclusivity. The research highlights the importance of involving individuals with autism in the development of technology to address their specific needs.
A new study by RMIT University found that only over a third of media organizations have an image-specific AI policy in place, highlighting the need for clearer guidelines. The research highlights the challenges of navigating generative AI technologies in visual journalism, including algorithmic bias and copyright concerns.
Researchers created a system called Holodeck to generate interactive 3D environments, leveraging language models like ChatGPT to control it. The system outperformed earlier tools in evaluating realism and accuracy, with human evaluators preferring its outputs across various indoor environments.
Researchers from the University of Washington created an AI algorithm to analyze infant poses using limited training data. By leveraging generative AI, they were able to produce high-quality results, enabling parents to monitor their babies' daily activities and detect potential health issues early.