半导体生态系统的两大巨头英伟达 和 Synopsys 宣布达成一项里程碑式的多年战略合作，英伟达将向 Synopsys 主导的项目投资 20 亿美元。此次合作旨在将英伟达的 GPU 加速计算平台与 Synopsys 业 界领先的电子设计自动化 (EDA) 和半导体 IP 产品组合相融合，从而显著加快芯片设计周期、大幅 降低功耗，并助力下一代人工智能、汽车和高性能计算芯片的研发。 此次合作的核心在于创建一个统一的云原生设计环境，该环境整合了 Synopsys 的 TestMAX、Verdi 和 VC Formal 工具、NVIDIA 的 cuLitho 计算光刻平台以及更广泛的 Grace-Blackwell 软件栈。设 计人员将首次能够以 GPU 加速的速度运行全芯片布局布线、设计规则检查和电磁仿真，速度比传统 的基于 CPU 的流程快 10 到 50 倍。在发布会上分享的早期基准测试表明，一款 3nm AI 训练芯片此 前需要 12 周的计算时间才能完成的相同签核流程，在运行 Synopsys 工具的 NVIDIA DGX 云实例 上仅需不到 60 小时即可完成。 英伟达首席执行官黄仁勋将此次合作描述为"自 ...

Core Viewpoint - Elon Musk predicts that traditional smartphones and apps will disappear within 5 to 6 years, with AI generating most of the content humans interact with daily [1] Group 1: Predictions on Technology and AI - Musk envisions a future where smartphones will simplify to display and sound output, with AI deeply integrated into every aspect of these devices [1] - He forecasts that AI will surpass individual human intelligence by 2026 and exceed the collective intelligence of humanity by 2030 [1] Group 2: Impact on Chip Design and Engineering - Concerns arise regarding the future of mobile chip and system engineers due to Musk's predictions, as certain aspects of chip design, like analog circuit design, require human creativity and expertise that AI cannot fully replicate [3] - Current AI tools, such as NVIDIA's ChipNeMo and Synopsys.ai Copilot, can assist in coding and note organization but are not capable of independently completing the entire chip design process [3] - System design in mobile technology requires a deep understanding of user needs and hardware optimization, which AI can assist with but cannot replace the essential experience and knowledge of human engineers [4] Group 3: Future of Chip Engineering Careers - The future of chip engineers will depend on two key factors: breakthroughs in AI technology that allow for fully autonomous chip design and a potential shift in the industry towards new design models that do not rely on traditional processes [5] - Despite the technological wave indicated by Musk's predictions, the unique nature of the chip industry suggests that engineers will not be easily replaced, and continuous learning and adaptation to AI tools will be crucial for their future [5]