📄 中文摘要
文章指出，尽管人们认为自己在使用人工智能工具，但从架构上看，人工智能实际上是在利用人类。随着技术的进步，软件开发的速度和方式正在发生深刻变化。持续学习的概念在这一过程中显得尤为重要，它使得人工智能能够不断适应和优化自身的功能。此外，RLEF（强化学习与经验反馈）作为一种新兴的方法论，正在推动软件工程的演变。文章深入分析了这些趋势对软件开发的影响，并揭示了人工智能在这一领域的真正潜力和挑战。
伟大的抽象：持续学习、RLEF 和人工智能软件工程的真实时间线
📄 English Summary
The Great Abstraction: Continuous Learning, RLEF, and the Real Timeline of AI Software Engineering
The piece highlights the paradox that while humans believe they are using AI tools, the architecture of AI is actually leveraging human input. As technology advances, the speed and methods of software development are undergoing profound changes. The concept of continuous learning is particularly crucial, enabling AI to adapt and optimize its functions continuously. Additionally, RLEF (Reinforcement Learning with Experience Feedback) emerges as a new methodology driving the evolution of software engineering. The analysis delves into the implications of these trends on software development, revealing the true potential and challenges of AI in this domain.