Related papers: A Comprehensive Survey of Artificial Intelligence …
The increasing need for economic, safe, and sustainable smart manufacturing combined with novel technological enablers, has paved the way for Artificial Intelligence (AI) and Big Data in support of smart manufacturing. This implies a…
Artificial Intelligence (AI) faces persistent challenges in terms of transparency and accountability, which requires rigorous documentation. Through a literature review on documentation practices, we provide an overview of prevailing…
Research within sociotechnical domains, such as Software Engineering, fundamentally requires a thorough consideration of the human perspective. However, traditional qualitative data collection methods suffer from challenges related to…
Big data revolutionizes accounting and auditing, offering deep insights but also introducing challenges like data privacy and security. With data from IoT, social media, and transactions, traditional practices are evolving. Professionals…
Artificial Intelligence (AI) has revolutionized food marketing by providing advanced techniques for personalized recommendations, consumer behavior prediction, and campaign optimization. This paper explores the shift from traditional…
This chapter explores the complexities of sports governance, taxation, dispute resolution, and the impact of digital transformation within the sports sector. This study identifies a critical research gap regarding the integration of…
The rise of powerful large language models (LLMs) brings about tremendous opportunities for innovation but also looming risks for individuals and society at large. We have reached a pivotal moment for ensuring that LLMs and LLM-infused…
The recent surge in research focused on generating synthetic data from large language models (LLMs), especially for scenarios with limited data availability, marks a notable shift in Generative Artificial Intelligence (AI). Their ability to…
The field of AI is undergoing a fundamental transition from generative models that can produce synthetic content to artificial agents that can plan and execute complex tasks with only limited human involvement. Companies that pioneered the…
Reduced environmental effect, lower operating costs, and a stable and sustainable energy supply for current and future generations are the main reasons why power optimization is important. Power optimization makes ensuring that energy is…
Artificial intelligence is transforming the way we work with information across disciplines and practical contexts. A growing range of disciplines are now involved in studying, developing, and assessing the use of AI in practice, but these…
The emergence of large language models (LLMs) has revolutionized AI development, yet the resource demands beyond a single cluster or even datacenter, limiting accessibility to well-resourced organizations. Decentralized training has emerged…
Data-centric AI is at the center of a fundamental shift in software engineering where machine learning becomes the new software, powered by big data and computing infrastructure. Here software engineering needs to be re-thought where data…
Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This article surveys the recent literature on data management as…
Artificial Intelligence (AI) is rapidly changing many areas of society. While this transformation has tremendous potential, there are several challenges as well. Using the history of computing and the world-wide web as a guide, in this…
The steady growth of artificial intelligence (AI) has accelerated in the recent years, facilitated by the development of sophisticated models such as large language models and foundation models. Ensuring robust and reliable power…
This study explores the benefits and challenges of integrating Artificial Intelligence with Agile software development methodologies, focusing on improving continuous integration and delivery. A systematic literature review and longitudinal…
In the rapidly evolving field of artificial intelligence, the creation and utilization of synthetic datasets have become increasingly significant. This report delves into the multifaceted aspects of synthetic data, particularly emphasizing…
In this paper, we cover approaches to systematically govern, assess and quantify bias across the complete life cycle of machine learning models, from initial development and validation to ongoing production monitoring and guardrail…
Artificial Intelligence (AI) techniques, particularly machine learning techniques, are rapidly transforming tactical operations by augmenting human decision-making capabilities. This paper explores AI-driven Human-Autonomy Teaming (HAT) as…