The field of artificial intelligence (AI) is rapidly evolving, with a growing emphasis on large language models (LLMs) and their applications in various domains. Recent research has focused on harnessing the power of LLMs to drive innovation, improve research workflows, and enhance knowledge representation. Notably, the use of LLMs is transforming the way researchers approach tasks such as data analysis, workflow generation, and concept map creation. Furthermore, the integration of AI and high-performance computing (HPC) is becoming increasingly important, with efforts to bridge the divide between HPC and cloud computing. The impact of AI on the language of academic papers is also a significant area of study, with evidence suggesting that LLMs are influencing the way researchers communicate their ideas. Overall, the field is moving towards a more automated, efficient, and collaborative approach to research, with AI playing a central role. Noteworthy papers in this regard include:

• Beginner's Charm: Beginner-Heavy Teams Are Associated With High Scientific Disruption, which highlights the importance of beginner fractions in teams for driving innovation.
• Automated Generation of Research Workflows from Academic Papers: A Full-text Mining Framework, which proposes a novel approach for generating comprehensive research workflows from academic papers.