转自 | CSDN（ID：CSDNnews） TypeScript 7.0 核心升级：原生编译器登场，性能提升 10 倍 即将到来的 TypeScript 7.0，最重要的变化之一，是引入原生编译器 。 目前该版本已经进入预览 阶段。 Hejlsberg 表 示 ， 原 先 的 TypeScript 编 译 器 是 用 TypeScript 自 己 写 的 ， 并 运 行 在 V8 JavaScript 引擎之上。但随着项目规模和使用场景不断扩大，这种实现方式在性能上已经明显吃紧 ： "我们很快就发现，原生编译器能让性能提升 10 倍——其中一半收益来自原生代码本身，另一半 则源于对共享内存并发特性的充分利用。" 近日 ， T ypeScript 与 C# 的发明者、微 软技术研究员 Anders Hejlsberg 表示， 现有编程语言 之所以更适合 AI 编程 ，并不是因为它们更"先进"，而是因为它们拥有最大的训练数据集 。 而对于 AI，他给出了一个 直接的评价： 当前的大模型，本质上更像是一个"把别人做过的事情重新吐出来，在此基础上做一些简单推演"的 高级复读机。 这 番 表 态 来 自 他 与 Gi ...

近日，TypeScript 与 C# 的发明者、微软技术研究员 Anders Hejlsberg 表示，现有编程语言之所以更适合 AI 编程，并不是因为它们更"先进"，而是因为它们拥有最大的训练数据集。 而对于 AI，他给出了一个直接的评价： 当前的大模型，本质上更像是一个"把别人做过的事情重新吐出来，在此基础上做一些简单 推演"的高级复读机。 这番表态来自他与 GitHub 研究顾问 Eirini Kalliamvakou 的一次对谈。此次访谈中，Hejlsberg 不仅分享 了 TypeScript 团队内部使用 AI 的实际经验，也回顾了 TypeScript 的发展历程，并展望了它未来可能的 演进方向。 TypeScript 7.0 核心升级：原生编译器登场，性能提升 10 倍 即将到来的 TypeScript 7.0，最重要的变化之一，是引入原生编译器。目前该版本已经进入预览阶段。 Hejlsberg 表示，原先的 TypeScript 编译器是用 TypeScript 自己写的，并运行在 V8 JavaScript 引擎之 上。但随着项目规模和使用场景不断扩大，这种实现方式在性能上已经明显吃紧：" ...

Core Viewpoint - The article argues that AI will not replace software developers, emphasizing that the future of software development remains in the hands of developers who can translate ambiguous human thoughts into precise computational logic [1][2]. Group 1: Historical Context - The prediction that "programmers will be replaced" has never come true throughout the history of computing, which spans over 43 years [3]. - The author has witnessed multiple technological revolutions, each heralded as the end of programmers, such as the rise of Visual Basic and low-code platforms [4][6]. - Historical cycles show that each wave of technology has led to an increase in the number of programs and programmers, exemplifying the "Jevons Paradox" with a market size of $1.5 trillion [9]. Group 2: Differences with Current Technology - The current wave of Large Language Models (LLMs) differs significantly from past technologies in scale and impact, with LLMs not reliably improving development speed or software reliability [10][11]. - Unlike previous technologies that provided stable and reliable solutions, LLMs often slow down development and create a dual loss situation unless real bottlenecks are addressed [11]. Group 3: Essence of Programming - The core challenge of programming has always been converting vague human ideas into logical and precise computational expressions, a difficulty that persists regardless of the programming tools used [12][17]. - The complexity of programming lies not in the syntax but in understanding what needs to be achieved, a challenge that remains unchanged over decades [17][18]. Group 4: Future Outlook - AI will not eliminate the need for programmers; instead, the demand for skilled developers will continue to grow, especially as companies realize the true costs and limitations of AI technologies [19][20]. - The future of software development will likely see AI playing a supportive role, assisting in tasks like prototype code generation, while the critical decision-making and understanding will still rely on human developers [19][20].

Core Insights - C has regained the title of "Programming Language of the Year" in the 2025 TIOBE index, marking a significant rise in its ranking after three years [1] - The programming landscape is shifting, with C and C++ swapping positions, and C language maintaining its dominance in the embedded systems market [1] - Perl has made a remarkable leap from 32nd to 11th place, while R language has returned to the top ten, driven by growth in the data science sector [1] - Go language has fallen out of the top ten, and Ruby has dropped out of the top twenty, indicating a potential decline in their usage [1] Ranking Summary - Python remains the top programming language with a rating of 22.61%, although it has seen a slight decrease of 0.68% [2] - C has moved up to the second position with a rating of 10.99%, showing an increase of 2.13% [2] - Java and C++ have dropped to third and fourth positions, respectively, with Java at 8.71% (down 1.44%) and C++ at 8.67% (down 1.62%) [2] - C holds the fifth position with a rating of 7.39%, reflecting an increase of 2.94% [2] - Visual Basic and SQL are in sixth and eighth positions, respectively, with ratings of 2.41% and 2.27% [2] - R has climbed to the tenth position with a rating of 1.82%, up by 0.81% [2] - Perl's rise to 11th place with a rating of 1.63% marks a significant increase of 1.14% [2] - Rust has moved to 13th place with a rating of 1.51%, showing a modest increase of 0.34% [2] - Go has dropped to 16th place with a rating of 1.24%, down by 1.37% [2]

Core Insights - Steve Klabnik, a senior technical expert in the Rust community, has developed a new experimental systems programming language called Rue in just 11 days with the help of AI tool Claude, writing approximately 100,000 lines of Rust code [1][11] - Klabnik's motivation to create a programming language stems from his long-standing interest in language design and compiler development, which he has pursued for over a decade [3][4] - The name "Rue" was chosen for its connection to Klabnik's admiration for Ruby and Rust, as well as its connotations and brevity [8] Development Process - Klabnik initially hesitated to develop a programming language due to the high expectations and complexities involved, which have increased over the years [4][10] - His perspective shifted with the advancement of AI tools, leading him to explore the feasibility of using AI to assist in compiler development [4][12] - The project faced a temporary halt due to work commitments but resumed in late 2025, with Klabnik feeling more adept at utilizing AI for software development tasks [5][6] Project Features and Goals - Rue aims to provide memory safety without relying on garbage collection, positioning itself as a higher-level language than Rust but lower than Go, focusing on usability [8][10] - The development of Rue has already attracted attention from other developers, evolving from a personal experiment into a collaborative effort [6][15] - The project is still in its early stages, with Klabnik emphasizing that it is primarily for fun and exploration rather than a serious push for adoption [15] Community Reactions - The announcement of Rue has sparked discussions in the programming community, with opinions divided on the necessity of new languages in the age of AI [15][16] - Some argue that the emergence of AI reduces the need for learning new languages, while others believe it enhances the value of language experimentation [16]

Core Viewpoint - C has been named the Programming Language of the Year for 2025, marking its second win in three years, based on its significant ranking improvement over the past year [2]. Group 1: C Performance and Evolution - C is recognized as the fastest-growing programming language last year, evolving from a Windows-only enterprise language to a modern, cross-platform, and open-source language [4][6]. - The success of C is attributed to its continuous evolution, introducing new features ahead of mainstream languages and adapting to industry trends, including two major paradigm shifts: from Windows-only to cross-platform and from proprietary to fully open-source [6][7]. - C maintains its competitiveness without being hindered by historical baggage, allowing it to thrive in various domains [7]. Group 2: Market Position and Competition - In the realms of game development, web services, and cloud-native applications, C and Java are nearly equal in market share, with both languages showing minimal differences in their rankings [8]. - The TIOBE index indicates that Java's lengthy syntax and ownership by Oracle may hinder its ability to suppress the increasingly modern and flexible C in the long term [10]. - Microsoft is heavily investing in C, with significant projects like OpenAI, Copilot, Azure, and Unity all leveraging C [10]. Group 3: Ranking Changes and Trends - The TIOBE index for January 2026 shows Python, C, Java, C++, and C as the top five programming languages, with C holding the fifth position [22][23]. - Perl has made a surprising comeback, rising from 32nd to 11th place, while R has re-entered the top 10, reflecting the growing demand for data analysis and visualization [12][14]. - The rankings indicate that languages like Go and Ruby have fallen out of the top 10 and 20, respectively, suggesting that once a language loses its growth momentum, its decline is often irreversible [21].

Core Viewpoint - The article highlights the precarious nature of high-income jobs in the tech industry, illustrating how a sudden loss of income can lead to a rapid descent into financial ruin and homelessness, as exemplified by the story of a programmer who went from earning $450,000 to becoming a homeless individual in just six months [3][10]. Group 1: The "Killing Line" Concept - The term "Killing Line" originally from gaming refers to a critical threshold that, once crossed, leads to irreversible consequences in life, reflecting the fragility of individual and collective survival in society [2]. Group 2: The Programmer's Financial Struggles - The programmer, Jack, had a high salary of $450,000, equivalent to over 3 million RMB, but faced monthly fixed expenses totaling $16,500, including a $12,000 mortgage, $3,000 car loan, and $1,500 in insurance, leaving him with little to no savings [3][4]. - Jack's financial situation exemplifies the "high salary, low savings" phenomenon prevalent among the American middle class, where individuals are often trapped in a cycle of high expenses and lack of financial buffers [4]. Group 3: Job Loss and Its Consequences - Jack's life took a downturn due to an unexpected layoff, a common occurrence in the U.S. employment system, which allows employers to terminate employees without cause or severance [5]. - The tech industry is experiencing a wave of job losses due to AI advancements, making it increasingly difficult for displaced workers like Jack to find new employment [7]. Group 4: Medical Debt and Bankruptcy - Following his job loss, Jack faced a medical emergency that resulted in a $60,000 bill, of which only $12,000 was covered by insurance, leading to insurmountable debt and the loss of his home [8]. - Medical debt is a significant contributor to personal bankruptcies in the U.S., with approximately 25-35% of bankruptcies directly linked to medical expenses, even among insured individuals [10]. Group 5: The Cycle of Despair - Jack's situation illustrates a vicious cycle of homelessness and credit destruction, where lack of a permanent address hinders job applications, further exacerbating his financial instability [9]. - The systemic issues in the U.S. economy, including weak employment protections and a credit system that penalizes individuals for financial misfortunes, contribute to the rapid decline of individuals like Jack from stability to homelessness [10].

Group 1 - The article discusses the importance of maintaining a proper mindset when engaging in freelance work, particularly in the context of compensation and relationships with colleagues [2] - It emphasizes that freelancers should evaluate their own costs and the fairness of the compensation received, rather than focusing on how much their colleagues earn from the same project [2] - The article suggests that maintaining good relationships with colleagues can lead to more opportunities for freelance work in the future [2] Group 2 - The article provides an analogy comparing freelance work to a company project, highlighting that employees typically do not expect to receive a large share of profits from a project completed for their employer [2] - It points out that the colleague who referred the freelance opportunity may have incurred costs or invested effort that is not immediately visible to the freelancer [2] - The overall message encourages freelancers to appreciate the opportunities provided by others and to foster positive professional relationships [2]

Core Insights - The article emphasizes the power of knowledge and the potential for individuals to excel in the technology field through access to free educational resources [2]. - It promotes a comprehensive offering of over 200 hours of free IT self-study courses covering 14 popular subjects, including AI, Java, architecture, Go, cloud-native technologies, and more [2][5]. Course Offerings - The courses are taught by industry experts, including former executives from major tech companies, providing practical insights and experiences [2]. - The curriculum is designed for various skill levels, catering to beginners, experienced programmers, and those curious about new technologies [5]. Specific Course Highlights - Courses include topics such as AIGC applications, multi-modal large model technologies, and practical applications of AI tools [9][10]. - There are specialized sessions on programming languages like Rust, Java, and Go, focusing on performance, reliability, and practical applications [18][22]. Learning Pathways - The article outlines structured learning paths for different audiences, ensuring that everyone can find suitable courses to enhance their skills and career prospects [5]. - It encourages immediate action to enroll in the limited-time offer of free courses, emphasizing the urgency and value of the opportunity [36].

Core Viewpoint - The choice of programming languages is becoming increasingly important in the AI era, as it directly impacts the quality of code generated by AI agents [19][28]. Group 1: Programming Language Comparison - Go is favored in AI scenarios due to its thin abstraction layer and structured nature, making it easier for models to understand and rewrite code. In tests, Go outperformed Python and Rust in generating code for similar small programs [2][27]. - Python remains essential for any company, especially for tasks involving machine learning or data processing, even if it is not used for core services [12][16]. - JavaScript and TypeScript are also unavoidable in the current landscape, with TypeScript often accompanying JavaScript [12][17]. Group 2: Language Evolution and Future Trends - The industry is witnessing a trend towards creating "next-generation languages" designed for human-agent collaboration, as existing languages may not be optimal for this new paradigm [3][29]. - The migration from Python 2 to 3 serves as a cautionary tale for future language transitions, highlighting the complexities involved in such changes [4][6][7]. - Rust has learned from Python's migration challenges by implementing an "edition system" that allows for incremental feature adoption without breaking compatibility with older versions [7]. Group 3: Practical Considerations in Language Choice - The choice of programming language should be pragmatic, focusing on the product being built rather than the code itself. Early-stage companies should limit their technology stack to three or four languages [11][18]. - The emergence of AI tools has shifted the focus from the necessity of a unified codebase to maintaining clear boundaries between systems, enhancing development efficiency [18][20]. Group 4: AI's Impact on Software Development - AI tools are significantly changing the software development landscape, allowing for more efficient coding and problem-solving. A substantial portion of code (over 80%) in some companies is now generated by AI [21][24]. - The role of human developers is shifting towards creative and thoughtful tasks, while AI handles more routine coding responsibilities [21][24]. - The democratization of programming is occurring as AI lowers the entry barrier, enabling more individuals to engage in coding without extensive prior knowledge [25]. Group 5: Error Handling and Language Design - Different programming languages exhibit varying error handling characteristics, which can significantly impact system reliability and user experience [34][35]. - The design of programming languages often involves trade-offs between performance and error handling capabilities, which can affect the overall robustness of applications [40][42].