AI Code Generation

As artificial intelligence (AI) and machine learning (ML) continue to grow and become more integral to organizational processes, the necessity for robust security measures has never been more critical. With AI increasingly utilized for creating, sharing, and storing data, there is a heightened

Low-code/no-code (LCNC) platforms are revolutionizing how applications are developed by simplifying and expediting software creation, allowing a broader range of individuals to engage in the development process. Historically viewed as supplementary tools within an organization's tech stack,

In today’s rapidly evolving technological landscape, software enterprises are at a pivotal point where the integration of Machine Learning (ML) and Artificial Intelligence (AI) is no longer a novelty but a strategic necessity to stay competitive and innovative. These advanced technologies are b

The field of artificial intelligence has made significant strides in recent years, particularly in the realm of mathematical reasoning. Researchers from HKUST (GZ), HKUST, NTU, and Squirrel AI have proposed a comprehensive analytical framework to scrutinize the capabilities and limitations of

The rapid advancement of artificial intelligence has brought about significant changes in various fields, including software development. One of the most intriguing and complex issues arising from this technological evolution is the ownership and copyright of AI-generated code. As AI tools like

In an era where software development complexity is escalating, efficiency in code generation is paramount. Salesforce AI Research has developed a pioneering framework named CodeTree to enhance automated code generation. This framework leverages large language models (LLMs) to create executable and