公众号记得加星标⭐️，第一时间看推送不会错过。 四年前，英特尔开始为其第四代至强处理器筹备软件定义芯片（SDSi）计划，旨在销售处理器的同 时 ， 通 过 允 许 客 户 激 活 特 定 工 作 负 载 的 加 速 器 来 赚 取 溢 价 。 最 终 ， 该 计 划 正 式 更 名 为 "Intel On Demand"（英特尔按需服务） ……然后便销声匿迹。如今，据Phoronix报道，这家标志性的 PC 芯 片制造商正在悄然终止该计划。 近年来，英特尔基本停止了公开讨论其"Intel On Demand"计划，而缺乏新的补丁也表明其开发活动 放缓，这可能意味着英特尔已不再将其视为优先事项。Phoronix最新报道称，包含支持 Intel On Demand 所需软件组件的 Intel SDSi GitHub 代码库已于去年 11 月被存档，这标志着该计划的积极 开发已经结束。与此同时，英特尔也从其网站上删除了大部分 On Demand 相关文档，目前所有与该 计划相关的内容都只能通过其网站访问到一些旧的 PDF文档。 综上所述，软件支持、文档和公开讨论的消失强烈表明，英特尔已经彻底放弃了软件定义芯片计划， ...

Core Viewpoint - The semiconductor industry is experiencing a transformative phase driven by AI and advanced chip design methodologies, with a shift towards "agent-based AI" that enhances collaboration in chip design [1][2][4]. Group 1: Industry Trends - The demand for AI-related industries has surged, with official forecasts increasing from $950 billion to $1.2 trillion in just one year, driven by data center AI computing and extending to edge computing [2]. - Companies traditionally not involved in chip manufacturing, such as Xiaomi and Alibaba, have emerged as significant players in the semiconductor space, indicating a shift towards "software-defined chips" [2]. Group 2: Technological Innovations - Paul Cunningham introduced the "3D dimensional" integration technology, emphasizing the need for comprehensive system simulation and optimization across various dimensions, including mechanical, thermal, and fluid simulations [4]. - The combination of principle-based methods, accelerated computing, and AI is seen as crucial for addressing the challenges in the semiconductor industry, referred to as the "three-layer cake" architecture [4]. Group 3: AI Evolution in EDA Tools - Cadence's journey in AI began in 2016, focusing on integrating machine learning into tools for faster and higher-quality results, evolving from "AI optimization" to "human-computer interaction transformation" [5][6]. - The introduction of conversational capabilities in Cadence tools allows users to interact using natural language, marking a significant shift towards "virtual engineers" rather than just tools [5][6]. Group 4: Future of Automation and Digital Twins - The vision for the future includes a gradual transition towards full automation in design processes, with digital twins and AI playing a pivotal role in accelerating simulations and providing new scientific breakthroughs [9][10]. - The integration of AI with digital twins is expected to enhance the efficiency of simulations across various fields, including physics and biology, significantly reducing computation time [9][10]. Group 5: Talent Demand and Industry Challenges - There is a growing demand for engineers in the semiconductor industry, with AI seen as a tool to enhance productivity rather than replace human jobs, especially in regions like China where the demand for talent is exceptionally high [11]. - The industry faces a talent shortage, and the integration of AI is viewed as essential for addressing this gap, allowing engineers to work more efficiently alongside AI [11].