Utilizing generative AI in coding accelerates the code-writing process, enhancing accuracy by generating code based on natural language cues or partial inputs. These digital tools not only suggest code for auto-completion in real-time, similar to email platforms, but also streamline the development workflow.
The rise of AI-assisted code generation tools in software engineering has made them a popular choice for organizations venturing into generative AI technologies. These tools offer a time-saving solution by automating the code creation and updating process, ultimately boosting productivity.
According to a survey by Evans Data Corp., software developers specializing in AI and machine learning prioritize using genAI tools for creating software code, algorithms, and large language models. The integration of genAI is expected to expedite the development cycle and simplify the incorporation of machine-learning capabilities.
Gartner Research predicts that by 2027, 70% of professional developers will leverage AI-powered coding tools, marking a significant increase from the current adoption rate. Furthermore, the integration of AI-augmented testing tools into software engineering processes is projected to reach 80% among enterprises within the next three years.
GitHub Copilot stands out as a leading tool for automated software development using generative AI. Developed by GitHub, OpenAI, and Microsoft, GitHub Copilot is trained on various natural languages found in public repositories, making it a versatile solution for developers.
Since the launch of GitHub Copilot for business, over 50,000 organizations, including industry giants like Autodesk, Dell Technologies, and Goldman Sachs, have embraced this tool for code generation. The widespread adoption of GitHub Copilot signifies the growing interest in AI-assisted coding tools across different sectors.
2024-04-07 16:51:02
Original from www.computerworld.com