Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions), and self-correction.
The integration of artificial intelligence (AI) is transforming the battle against food waste and propelling the transition towards a circular economy. By leveraging AI technologies, such as advanced analytics and machine learning, various applications are being developed to optimize food manufacturing, distribution networks, and waste management processes. These AI-driven solutions enhance decision-making, enable efficient resource utilization, and support recycling and upcycling initiatives.
A groundbreaking mathematical model, the FSTSP-DR-MP, has been proposed to transform last-mile logistics into a more sustainable and efficient process. With the surge in online shopping and the subsequent rise in carbon emissions, this innovative approach integrates both delivery and return services using a combination of trucks and drones. The model optimizes routes, considering multiple payloads and customers, to minimize service time.
Researchers investigate the working memory capacity of ChatGPT, a large language model, using n-back tasks. The study reveals consistent patterns of performance decline in ChatGPT as the information load increases, resembling human limitations. The findings contribute to understanding the cognitive abilities of language models, highlighting the potential of n-back tasks as a metric for evaluating working memory and overall intelligence in reasoning and problem-solving.
Demystifying AI: A comprehensive overview of eXplainable AI (XAI) provides a thorough analysis of current trends, research, and concerns in the field, shedding light on the inner workings of AI models for trustworthy decision-making. The review covers various aspects of XAI, including data explainability, model explainability, post-hoc explainability, assessment of explanations, and available XAI research software tools. It highlights the importance of understanding and validating AI systems to ensure transparency, fairness, and accountability in their deployment
By delving into the capabilities and limitations of AI language models like ChatGPT in physics education, this comprehensive overview emphasizes the need for a balanced approach that combines AI's potential with the indispensable role of human educators. The article highlights effective assessment strategies, ethical considerations, and the importance of preparing students for an AI-driven future while nurturing critical thinking and problem-solving skills.
Researchers delve into the intersection of artificial intelligence (AI) and music education, showcasing how AI-driven technologies such as intelligent instruments, music software, and online teaching platforms have revolutionized the learning experience. With the ability to personalize instruction, enhance collaboration, and support students with disabilities, AI in music education holds immense promise for the future of music learning and teaching.
A rapid and accurate technique using machine learning and optical images was developed to measure crystallographic orientations in multicrystalline materials, providing precise results with reduced error. This approach significantly improves efficiency compared to traditional methods, enabling comprehensive data collection for crystal growth analysis and material fabrication processes.
In this study, 3D conductive polymer networks are developed to mimic the brain's neural connections. These networks offer potential for enhanced neuromorphic wetware, paving the way for future advancements in information processing technologies.
A new deep-learning model is developed and validated to assess cardiac function and detect valvular disease using chest radiographs from multiple institutions. This research aims to enhance the understanding of the potential of chest X-rays in evaluating cardiovascular health.
Artificial intelligence (AI) can help people shop, plan, and write -; but not cook. It turns out humans aren't the only ones who have a hard time following step-by-step recipes in the correct order, but new research from the Georgia Institute of Technology's College of Computing could change that.
The study demonstrates the use of text mining to identify emerging ML/AI technologies in the Korean semiconductor industry, enabling SMEs to establish an R&D roadmap and enhance competitiveness. Deep neural networks and AI technology applications in semiconductor R&D and manufacturing processes were found to be crucial, with potential for improved reasoning, learning abilities, and process optimization.
The study explores the potential applications of ChatGPT in business decision-making scenarios, demonstrating its ability to provide comprehensive overviews of subjects. While ChatGPT's responses offer straightforward information, caution should be exercised when relying solely on its responses for complex business decisions. It can be a valuable tool for decision-making professionals looking to enhance productivity and allocate time for other pursuits.
This article explores the challenges of performing surgery in space during Moon and Mars missions and highlights advancements in surgical robotics to address these challenges. Reduced gravity, radiation exposure, and limited medical support pose unique obstacles. The development of miniaturized medical devices, robotic surgery simulations, and autonomous surgical robots, along with the application of AI, haptic sensors, minimally invasive techniques, and 3D printing, offer potential solutions.
This article provides a comprehensive overview of the evolution of AI advertising research by analyzing literature from 1990 to 2022. It identifies key research areas, trends, and challenges in AI advertising and suggests future directions for integrating AI with marketing functions and improving ad effectiveness.
Study examines the implementation of ChatGPT, an AI chatbot, in sport management education. The findings suggest that ChatGPT can generate comprehensive and accurate responses to sport management inquiries, highlighting its potential to enhance teaching and learning in the field.
Researchers introduce a speech emotion recognition (SER) system that accurately predicts a speaker's emotional state using audio signals. By employing convolutional neural networks (CNN) and Mel-frequency cepstral coefficients (MFCC) for feature extraction, the proposed system outperforms existing approaches, showcasing its potential in various applications such as human-computer interaction and emotion-aware technologies.
Embracing artificial intelligence (AI) in urban planning holds immense potential to revolutionize decision-making, optimize urban systems, and create sustainable cities. While challenges exist, the strategic integration of AI tools can empower planners to analyze data, predict scenarios, and design equitable cities for the future.
Researchers have developed the PETAL sensor patch, a paper-like wearable device that incorporates five colorimetric sensors for comprehensive wound monitoring. With the aid of artificial intelligence and deep learning algorithms, the patch accurately classifies wound healing status, providing early warning for timely intervention and enhancing wound care management.
Data-driven insights and analytics are shaping the evolution towards 6G systems, as the growth of data traffic and convergence of technologies become crucial. A case study on Fed-XAI demonstrates the potential of leveraging data for AI operations and quality of service predictions, showcasing the practical applications of data-driven innovation in developing 6G networks.
Manufacturing companies are embracing AI and IoT technologies to revolutionize their operations, achieve sustainability goals, and remain competitive. The implementation of smart configurations, such as digital twins, sensors, 5G networks, and advanced ML models, enables real-time monitoring, analysis, and optimization of production processes.
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