野田哲夫对话观察者网 【对话/观察者网 唐晓甫】 观察者网：对于非编程相关人员来说，一般会默认编程语言都是开源的，毕竟如果不开源，作为一种语言就不会有太多人使用。但是大家对语言开源的定义 似乎有一些不太一样。野田教授，您能否聊聊开源语言和闭源语言的区别？在Web1.0~2.0时代，从建立生态角度看，究竟是开源好还是闭源好？Ruby作为 一种开源语言，在之前几十年中又扮演了什么样的角色？ AI时代，中美之间的开闭源路线之争正在日趋激烈。以DeepSeek和Qwen为代表的开源AI大模型正在创造新的生态和潮流，并引领中国科技走向世界。但是 也有不少人对开源模式心存疑虑，尤其是对开源软件的盈利模式产生质疑，怀疑选择开源路线究竟能在多大程度上带动地区经济发展，会不会为他人作嫁 衣？ 对于这个问题，我们可以从邻国日本找到参考。早在上世纪末，日本著名软件专家松本行弘就开发了开源语言Ruby，随后岛根县松江市围绕Ruby这一开源 语言成功推动了地区IT产业，促进了相关产业发展。 近日，观察者网邀请到了岛根大学法文学院荣誉教授野田哲夫，请他基于自己的研究经验，谈一谈开源语言对于区域经济乃至软件生态层面的巨大影响。 野田哲夫： ...

Core Viewpoint - The competition between open-source and closed-source AI models is intensifying, with open-source models like DeepSeek and Qwen leading China's tech advancement globally. However, concerns about the profitability and economic impact of open-source models persist [1]. Group 1: Open Source vs Closed Source - Open-source software allows community participation beyond organizational boundaries, which is essential for sustainable development and ecological growth [4]. - The distinction between open-source and closed-source languages is significant, with open-source languages like Ruby fostering broader collaboration and innovation [6]. - The coexistence of open-source and closed-source models is expected, with both contributing to competitive software ecosystems [7]. Group 2: Economic Impact of Open Source - Japan's experience with Ruby demonstrates that open-source languages can empower smaller contractors to engage in larger projects, enhancing local economic development [10][11]. - The presence of Ruby's creator in Shimane Prefecture has been pivotal in establishing a local ecosystem that supports larger engineering projects [11]. - The development of a robust open-source community can help retain local talent and stimulate regional economic growth, as seen in Shimane [12]. Group 3: Lessons for China - China can learn from Japan's open-source initiatives to build a new regional economic engine, especially in light of the risks associated with reliance on closed-source AI models [13]. - The importance of open-source algorithms in AI development is emphasized, advocating for a competitive landscape that includes both open-source and closed-source options [13]. - Educational initiatives to promote understanding of open-source principles are crucial for fostering a skilled workforce capable of contributing to open-source projects [16]. Group 4: Challenges and Future of Programming Languages - The rise of AI in programming may lead to a divide between those who understand programming and those who rely solely on AI-generated code, potentially impacting the future of programming languages like Ruby [19][21]. - The need for education in programming remains critical, as reliance on AI could diminish human cognitive skills in understanding IT [21]. - The balance between efficiency gained through AI and the necessity for human understanding of programming concepts is a key consideration for the future [21].

有人的地方就有江湖，开源世界也并不例外。 最近，一位长期参与开源项目的开发者愤怒指责，称自己深度维护了十多年的项目遭到了"恶意接管"，自己落了个被「踢出局」的下场。随后，这个项目 被一家非营利公司的开源总监接手了，其还大刀阔斧地移除了所有其他维护者，可谓一点情面也没留。 几天后，这些"移除"操作大部分被撤销，而这家组织的开源总监却轻描淡写地称这只是一次"错误"。令人没想到的是，他隔了几天又再次将所有维护者从 GitHub 组织中移除，给的理由是以安全之名。 如此儿戏般的剧情，目前正在主流编程语言 Ruby 社区上演，由此也引发了巨大的争议，其中 Apache CouchDB 的开发者、Relaxed 公司的创始人之一 Jan Lehnardt 在 Mastodon 上质问道："Ruby 到底发生了什么鬼事情？" "惨遭踢出局"的开源维护者 归根结底，这其实是一场关于开源项目管理权的问题，具体源头还得从 RubyGems 和 Bundler 这两款工具说起。 RubyGems 是 Ruby 的标准包管理器， Bundler 则是依赖管理器，它由非营利组织 Ruby Central 赞助。不过，多年来，这些工具由 ...

Core Viewpoint - The emergence of large language models (LLMs) represents a transformative change in software development, comparable to the shift from assembly language to the first generation of high-level programming languages [5][10]. Group 1: Impact of LLMs on Programming - LLMs not only enhance the level of abstraction in programming but also compel a reevaluation of what it means to program with non-deterministic tools [7][10]. - The transition from deterministic to non-deterministic programming paradigms expands the dimensions of programming practices [8][10]. Group 2: Historical Context of Programming Languages - High-level programming languages (HLLs) introduced a new level of abstraction, allowing programmers to think in terms of sequences, conditions, and iterations rather than specific machine instructions [8][9]. - Despite advancements in programming languages, the fundamental nature of programming has not changed significantly until the advent of LLMs [6][9]. Group 3: Embracing Non-Determinism - The introduction of non-deterministic abstractions means that results from LLMs cannot be reliably reproduced, contrasting with the consistent outcomes from traditional programming [10][13]. - The industry is experiencing a radical transformation as developers learn to navigate this non-deterministic environment, which is unprecedented in the history of software development [13].

Financial Data and Key Metrics Changes - RevPAR grew by 1.8%, reflecting the company's geographic footprint and brand depth [6] - Gross system growth was 7.7% and net system growth was 5.4%, driven by development activity and record openings [6] - EBIT increased by 13% and adjusted EPS grew by 19% [6] - The company completed 47% of its $900 million share buyback program, returning over $1.1 billion to shareholders this year [6] Business Line Data and Key Metrics Changes - The Americas fee revenues were down about 1% despite a 1.5% RevPAR growth and around 1.5% adjusted net unit growth [10] - The company signed over 51,000 rooms across 324 hotels, a 15% increase over 2024 [6][20] - Openings in The Americas were up 40% year over year, contributing to future fee growth [24] Market Data and Key Metrics Changes - The company reported a constructive outlook for US demand and hospitality performance, with stable inflation and interest rates [14][15] - In China, the company sees the economy bottoming out, with GDP growth of about 5% in Q2 and expectations for improved RevPAR trends in the back half of the year [66][68] Company Strategy and Development Direction - The company is focused on high-growth opportunities, including investments in technology and expanding its luxury and lifestyle brands [52][54] - The company aims to grow both new builds and conversions, with a strong pipeline of openings and signings [63][110] - The branded residential segment is expected to contribute consistently to fee growth, with 30 properties currently open and more in development [33] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in achieving full-year profit and EPS consensus, despite uncertainties in the short term [15][85] - The company noted that the fundamentals for US hospitality remain strong, with job growth and corporate capital investment driving demand [14][15] - Management is optimistic about the long-term growth potential in China, despite current challenges [66][68] Other Important Information - The company has been investing in technology and process improvements to enhance operational efficiency and scalability [94] - The company expects to see continued margin growth driven by cost savings and ancillary revenue streams [95] Q&A Session Summary Question: Current trading outlook for Q3 and Q4 RevPAR in the U.S. - Management does not provide guidance but feels comfortable with full-year profit and EPS consensus, indicating a stable outlook for U.S. demand [12][15] Question: Explanation for the decline in Americas fee revenues despite RevPAR growth - Management attributed the decline to high-fee hotels exiting and renovations impacting available rooms, but does not see it as a long-term issue [20][22] Question: Insights on branded residential contribution to profitability - Management is excited about the growth trajectory in branded residential, which is expected to contribute consistently to fees [31][33] Question: Investment focus among technology pillars - Management emphasized ongoing investments in technology, particularly in PMS and RMS systems, to ensure competitiveness [34][38] Question: Update on the performance of the Garner brand - Management reported strong progress with 51 open Garners and a robust pipeline, indicating significant international demand [78][79]

Financial Performance - H1 2025 global RevPAR increased by 1.8%[15], with ADR up by 1.4%[15] and occupancy up by 0.3%pts[15] - Fee margin increased by 3.9%pts to 64.7%[15], with TTM EBITDA reaching $1.259 billion, a 10% increase[15] - Adjusted EPS increased by 19% to 242.5¢[15], and free cash flow reached $302 million[15] - The interim dividend increased by 10% to 58.6¢[15] System Growth and Development - Gross system growth increased by 7.7% YOY, and net system growth increased by 5.4% YOY[15] - A record 31.4k rooms (207 hotels) were opened in H1, a 75% increase YOY[15] - Signings reached 51.2k rooms (324 hotels), a 15% increase YOY[15] - The pipeline consists of 338k rooms (2,276 hotels), representing 34% of the current system size[16] Capital Returns - $423 million (47%) of the $900 million share buyback program has been returned, representing 2.4% of the opening share count[15] - The company expects to return >$1.1 billion in 2025, representing 5.9% of the opening market cap[15] Strategic Priorities - Loyalty enrolments increased by 22% YOY in H1[102], with ~65% of room nights booked by members[102] - Co-brand fee revenue is on track to double by 2025 and more than triple by 2028[114] Regional Performance - Americas RevPAR increased by 1.4%[184], with a fee margin of 82.7%[184] - EMEAA RevPAR increased by 4.1%[188], with a fee margin of 65.8%[188] - Greater China RevPAR decreased by 3.2%[192], with a fee margin of 57.9%[192]

Core Insights - The article illustrates the paradox of success in technology, where a highly efficient system can lead to the perception that fewer developers are needed, ultimately jeopardizing the use of that technology [1][29]. Group 1: Technical Debt - The company had a traditional tech stack and needed to develop a real-time service to support 100,000 concurrent users, displaying user activity information [2]. - The initial choice of Ruby was deemed inadequate, prompting discussions on technology selection [3]. Group 2: Technology Selection Battle - The development team proposed using Rust, but management was cautious and requested comparisons with other languages [4][5]. - Concept validation versions were created using Elixir, Rust, Ruby, and Node.js, with Rust being developed by a novice [5][6]. Group 3: Performance Results - The performance results showed Rust as the fastest and most memory-efficient option, followed by Elixir, Node.js, and Ruby [8][10]. - The final decision favored Rust not only for its performance but also for its versatility in future applications [10]. Group 4: Rapid Development - Due to time constraints, a single developer with Rust experience was tasked to lead the project, collaborating closely with the team [11][13]. - The architecture was designed to handle 100,000 connections efficiently, utilizing a WebSocket-based API and in-memory data storage [14]. Group 5: Performance Challenges - The service performed stably under the expected load, but management later decided to shift it to maintenance mode, leading to a lack of oversight [16]. - The service was initially successful, but as the company expanded, management questioned the need for Rust developers due to the service's stability [19][20]. Group 6: Management Decisions - The new director's perspective led to the departure of experienced Rust developers, as they were deemed unnecessary due to the service's lack of issues [22]. - The decision to abandon Rust in favor of more mainstream technologies raised concerns about the existing Rust service's future [23]. Group 7: Node.js Rewrite Attempt - The attempt to rewrite the service in Node.js failed due to its single-threaded nature, which could not handle the required load [24][25]. - The company resorted to using a third-party service, which also proved inadequate [26]. Group 8: Lessons Learned - The Rust service continued to operate effectively but without a dedicated maintenance team, highlighting the risks of having a highly efficient system [28][29]. - The article concludes that sometimes, a less-than-perfect system may be perceived as safer, emphasizing the impact of management changes on technical decisions [29].

Group 1 - The article discusses a situation where a successful Rust project led to its eventual discontinuation within a company due to management changes and a lack of understanding of its value [1][6][9] - The company initially chose Rust for a real-time service due to its superior performance in tests compared to other languages like Ruby and Node.js [3][4][5] - After the successful implementation of the Rust service, the company shifted its focus, leading to the disbandment of the Rust development team and a lack of further investment in Rust technology [6][7][8] Group 2 - The new management, upon realizing the Rust service was stable and required little maintenance, decided to phase out Rust in favor of more familiar technologies like Ruby and Node.js [7][8][9] - The attempt to rewrite the Rust service in Node.js failed due to the inherent limitations of Node.js in handling high concurrency, highlighting the complexity of such a transition [9][10] - The article reflects a broader industry trend where successful projects can be undervalued or misunderstood by new management, leading to missed opportunities for innovation [10]

Core Viewpoint - The article discusses the emerging concept of "Vibe Coding," which allows individuals to create software applications using AI tools without extensive programming knowledge, highlighting its potential to democratize software development and enhance productivity [1][9]. Group 1: Concept of Vibe Coding - "Vibe Coding" is introduced as a method where AI assists in coding, enabling users to develop applications quickly, as demonstrated by Andrej Karpathy's example of creating an iOS app in one hour without prior knowledge of Swift [1][3]. - The rise of AI-assisted coding tools, such as Cursor and Tencent's CodeBuddy, indicates a competitive landscape in the AI programming assistant market, enhancing developers' capabilities [3][4]. Group 2: Success Stories and Frameworks - Developers are sharing their success stories using Vibe Coding, with one user reporting a monthly recurring revenue (MRR) of $7,000 within 30 days of launching an AI product solely using AI tools [5][7]. - The "Vibe Coding entrepreneurial framework" is outlined as a simple process involving one AI tool for building, another for email outreach, and ChatGPT for market insights, showcasing a streamlined approach to product development [7][8]. Group 3: Perspectives on AI in Coding - David Heinemeier Hansson (DHH) emphasizes the importance of maintaining a human touch in coding, arguing that while AI can assist, it should not replace the joy of programming [11][15]. - The article presents contrasting views from developers, with some appreciating AI for alleviating repetitive coding tasks, while others express concern about losing the essence of coding as a creative endeavor [18][21]. Group 4: Market Implications and Future of Coding - The discussion highlights that AI is not just a tool but a new layer of abstraction in programming, suggesting that the future of coding may involve a blend of human creativity and AI efficiency [22]. - The potential of Vibe Coding to lower barriers for non-programmers to engage in software development is noted, indicating a shift towards a more inclusive tech landscape [24].

Summary of Conference Call Company and Industry - The conference call primarily discusses **NVIDIA** and its advancements in the **AI and computing hardware industry**. Key Points and Arguments Product Launches and Innovations - NVIDIA introduced several new products during the conference, highlighting the shift in model architecture towards **reinforcement learning** which enhances the reasoning process during inference [1] - The **Blackwell Ultra NVLink 72** was announced, set to ship in the second half of the year, with bandwidth double that of the previous **GB200** series [2] - The **VR Ruby** is expected to ship in the second half of 2026, boasting performance that is **3.3 times** that of the **GB300 NVLink72** and supporting up to **288GB** of fast memory [3] - The next generation, **Ruby Ultra**, features **NVLink576**, which is **14 times** the performance of **GB300 NVLink72** and supports a bandwidth of **115.2T** [3][4] Hardware Architecture Changes - The architecture of the **NVLink576** has undergone significant changes, allowing for a denser configuration of **288 GPUs** in a single rack [4] - The importance of **PCB** (Printed Circuit Board) has increased, with a shift from copper cables to PCB interconnections, indicating a growth in PCB usage in the **Rubin** generation [5] Networking and Connectivity - NVIDIA announced two new **CPU switches**: the **Quantum X** (InfiniBand architecture) and **Spectrum X** (Ethernet version), with the Quantum X expected to deliver a total bandwidth of **115.2P** [6][7] - The **Quantum X** switch features **four ASICs** with **72 optical engines**, each capable of **200G** service, contributing to the overall bandwidth [7] Market Implications - The design of the **CPU switch** includes a **pluggable optical engine**, which reduces maintenance costs for cloud service providers, potentially increasing adoption rates [8][9] - NVIDIA's focus on applications includes the introduction of the **Dynamo AI inference software**, which can increase token generation by over **30 times** during model execution [10] - The company also showcased advancements in **autonomous driving** and robotics, including a foundational model for general-purpose robots and a comprehensive safety system for autonomous vehicles [10] Future Outlook - The demand for inference is expected to rise significantly due to the integration of reinforcement learning in models, indicating a positive outlook for both domestic and international computing power markets [11] Additional Important Content - The conference emphasized the strategic direction of NVIDIA in enhancing computing power and AI applications, which could lead to substantial growth opportunities in the tech industry [1][11]