The Most Important Programming Language in the AI Era and Its Evolution

人工智能时代最重要的编程语言及演进史 The Most Important Programming Language in the AI Era and Its Evolution

对于寻求职业发展建议的IT专业人士而言，人工智能时代最重要的编程语言并非Python或Java等广泛使用的技术，而是人类已经掌握并一直在使用的自然语言。如果人们能够听懂人类的日常对话，就已经具备了人工智能时代所需的编程基础。 For IT professionals seeking career development advice, the most important programming language in the era of artificial intelligence is not widely used technologies like Python or Java, but the natural language that humans already know and have been using their entire lives. If individuals can understand everyday human conversation, they already possess the foundational programming skills required for the AI era.

探讨编程语言的发展史有助于理解自然语言为何成为未来的关键。传统上，计算机程序的运行逻辑始于人类的意图，随后这些意图需要被转化为计算机能够理解的机器指令，最后由计算机执行这些指令以输出结果。早期的计算机需要人类去系统学习并适应底层机器语言。 Exploring the history of programming languages helps explain why natural languages have emerged as the key for the future. Traditionally, the operational logic of computer programs started with human intent, which then had to be translated into machine instructions that the computer could understand, and finally, the computer executed those instructions to produce a result. Early computers required humans to systematically learn and adapt to low-level machine languages.

编程语言的演进经历了多个阶段。最初是机器语言和汇编语言，例如应用于IBM主机以及数字设备公司和英特尔系统的基础汇编语言，这些完全是机器的表达方式。随后出现了更接近人类语言的高级语言，包括专用于数学逻辑的Fortran、用于商业的COBOL以及BASIC语言。然而，这些早期的高级语言容易产生被称为“意大利面条式代码”的混乱逻辑结构。 The evolution of programming languages has gone through multiple stages. It began with machine languages and assembler languages, such as the basic assembler languages used in IBM mainframes, Digital Equipment Corporation systems, and Intel systems, which were entirely the machine’s way of expression. This was followed by high-level languages that looked more human-like, including Fortran for mathematical logic, COBOL for business, and BASIC. However, these early high-level languages were prone to creating disorganized logical structures known as spaghetti code.

为了解决代码逻辑混乱的问题，结构化编程语言应运而生，例如PL/1、具有强类型限制的教学语言Pascal以及C语言。此后，编程范式转向面向对象编程，引入了将程序视为对象的概念，代表性语言包括C++和Smalltalk，使得输入、功能处理和输出的过程更加模块化。 To address the issue of disorganized code logic, structured programming languages emerged, such as PL/1, the strongly typed teaching language Pascal, and the C language. Afterwards, the programming paradigm shifted toward object-oriented programming, introducing the concept of treating programs as objects. Representative languages included C++ and Smalltalk, making the process of inputs, function processing, and outputs more modular.

随着互联网的发展，出现了Java、JavaScript和PHP等Web编程语言，其中Java实现了“一次编写，到处运行”的跨平台一致性。随后，Python和Ruby等脚本语言提供了更高层级的抽象。近年来，为了减少代码错误并加强内存管理，Go和Rust等安全性更高的语言被开发出来，分别针对微服务和云环境以及内存异常预防。 With the development of the internet, web programming languages such as Java, JavaScript, and PHP emerged. Among them, Java achieved cross-platform consistency with the principle of write once, run everywhere. Subsequently, scripting languages like Python and Ruby provided higher levels of abstraction. In recent years, to reduce code errors and enhance memory management, safer languages like Go and Rust were developed, targeting microservices and cloud environments, and memory exception prevention, respectively.

编程语言的每一次进化都在使其从底层的机器表达向更自然、更结构化的人类思维靠近。在当前的人工智能时代，自然语言处理技术使得计算机能够直接理解人类的母语。通过大型语言模型，用户可以使用英语、西班牙语或普通话等自然语言作为提示词与人工智能进行直接交互。 Every evolution of programming languages has moved them from low-level machine expression closer to more natural, structured human thinking. In the current AI era, natural language processing technology enables computers to directly understand native human languages. Through large language models, users can directly interact with artificial intelligence using natural languages such as English, Spanish, or Mandarin as prompts.

这种转变意味着人类不再需要将意图翻译成机器指令，而是可以直接从意图获取结果。基于大型语言模型的人工智能已经具备了理解自然语言的能力。因此，编写代码不再是专业程序员的专属领域，因为大众已经掌握了人工智能时代最关键的编程语言。 This shift means that humans no longer need to translate intent into machine instructions, but can instead go straight from intent to results. Artificial intelligence based on large language models already possesses the ability to understand natural languages. Therefore, writing code is no longer the exclusive domain of professional programmers, as the general public already knows the most crucial programming language of the AI era.

ref: IBM Technology

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