Group 1: Chip Innovations - Samsung Electronics has launched the Exynos 2600 system-on-chip (SoC), the world's first mobile application processor built using 2nm technology, featuring a 113% increase in AI computing power compared to its predecessor Exynos 2500 [2][5] - The Exynos 2600 integrates a new tri-cluster CPU design with a maximum clock speed of 3.8GHz, achieving up to 39% improvement in overall computing performance and enhanced energy efficiency [5][6] - The new GPU architecture "Huagang" from Moore Threads has been introduced, with two chips "Huashan" and "Lushan" that enhance AI inference training and high-performance graphics rendering, achieving a 50% increase in computing density and a 10x improvement in energy efficiency [3][15] Group 2: Optical Computing Breakthroughs - Researchers from Shanghai Jiao Tong University have achieved a significant breakthrough in optical computing, developing the LightGen chip capable of supporting large-scale semantic media generation models, with results published in the journal Science [9][10] - LightGen demonstrates a two-order-of-magnitude improvement in computing power and energy efficiency compared to leading digital chips, addressing the challenges of running complex generative models [10][11] - The chip can perform high-resolution image generation, 3D generation, and video generation, while supporting various large-scale generative tasks [11][12]

Group 1: Government Initiatives - The State Council, led by Premier Li Qiang, emphasized the need for all departments to align their actions with the central government's economic strategies for the upcoming year, enhancing responsibility and urgency in task execution [2] - Departments are encouraged to collaborate closely and develop specific implementation plans to ensure effective execution of economic policies [2] Group 2: Market Regulation - The National Internet Information Office and the China Securities Regulatory Commission have cracked down on accounts spreading rumors and illegal stock recommendations, highlighting the importance of maintaining market stability [3] - The authorities have urged the public to adopt correct investment philosophies and enhance their ability to discern financial information [3] Group 3: Major Corporate Transactions - China Shenhua announced a significant acquisition involving the purchase of 100% equity in multiple companies, with a total transaction value of 133.598 billion yuan, marking it as the largest acquisition in A-share market history [4][5] - The acquisition will enhance China Shenhua's coal reserves and production capacity significantly, with coal reserves increasing by 64.72% to 6.849 billion tons and production capacity rising by 56.57% to 512 million tons [5] Group 4: Technological Advancements - Researchers at Shanghai Jiao Tong University have achieved a breakthrough in optical computing, developing a chip that supports large-scale semantic media generation, which is crucial for AI and data processing [6] - Moore Threads unveiled a new GPU architecture that improves computing density by 50% and energy efficiency by ten times, indicating advancements in AI computing capabilities [7] Group 5: Regulatory Developments - The National Development and Reform Commission has released the "Internet Platform Pricing Behavior Rules" to regulate pricing practices on online platforms, ensuring fair competition and consumer protection [9] - The rules prohibit platforms from imposing unreasonable restrictions on sellers' pricing autonomy, promoting a healthier e-commerce environment [9] Group 6: Market Movements - Major U.S. stock indices saw gains, with significant increases in tech stocks, indicating a positive market sentiment [11] - The Chinese stock market is set to experience a substantial unlock of restricted shares, with a total of 210.32 billion shares worth approximately 1879.88 billion yuan becoming tradable [14][15]

Core Viewpoint - The article discusses the significant advancements in optical computing technology, specifically the LightGen chip developed by Shanghai Jiao Tong University, which addresses the growing demand for computational power and energy efficiency in large-scale generative AI models [5][12]. Group 1: Breakthroughs in Optical Computing - The LightGen chip represents a major breakthrough in the field of optical computing, enabling the support of large-scale semantic visual generation models [5]. - It integrates over a million optical neurons on a single chip and employs all-optical dimension conversion, which are recognized as key bottlenecks in the industry [9]. - The chip achieves a closed-loop process of "input-understanding-semantic manipulation-generation," allowing it to "understand" and "cognize" semantics [9]. Group 2: Performance Evaluation - LightGen chip demonstrates a significant performance leap, achieving two orders of magnitude improvement in computational power and energy efficiency compared to leading digital chips, even with less advanced input devices [11]. - Theoretical calculations suggest that with cutting-edge input devices, the chip could achieve a seven-fold increase in computational power and an eight-fold increase in energy efficiency [11]. Group 3: Implications for AI Development - The advancements in LightGen are crucial for the practical application of next-generation computing chips in modern AI, particularly for high-latency and energy-intensive tasks like large-scale generative models [12]. - This development opens new pathways for exploring faster and more energy-efficient generative intelligent computing [12].

Core Viewpoint - The article highlights a significant breakthrough in the field of optical computing chips by researchers at Shanghai Jiao Tong University, specifically the development of the LightGen chip, which supports large-scale semantic media generation models [3][4]. Breakthrough Details - The LightGen chip represents the first full-optical computing chip capable of supporting large-scale semantic generation models, addressing the performance gap in traditional chip architectures due to the increasing demands of deep neural networks and large-scale generative models [4]. - Optical computing utilizes light propagation within chips to perform calculations, offering inherent advantages such as high speed and parallelism, making it a promising direction for overcoming computational and energy consumption bottlenecks [4][5]. Performance Enhancements - LightGen has demonstrated a performance improvement of two orders of magnitude in computational power and energy efficiency compared to leading digital chips, even when using relatively outdated input devices [5]. - The chip achieves this leap in performance by overcoming three critical bottlenecks: integrating millions of optical neurons on a single chip, enabling full-optical dimensional transformation, and developing a light-based generative model training algorithm that does not rely on truth values [5][6]. Functional Capabilities - LightGen can complete a closed loop of "input-understanding-semantic manipulation-generation," enabling high-resolution image generation (≥512×512), 3D generation (NeRF), high-definition video generation, and semantic control, while also supporting denoising and feature transfer tasks [6]. Advantages of Optical Computing - Optical computing is characterized by scalability, low power consumption, ultra-high speed, wide bandwidth, and high parallelism, making it a key technology for rapid computation of large-scale data in AI, scientific computing, and multimodal perception [7]. - Recent advancements in optical computing have focused on increasing matrix scale and optical frequency, with notable examples including TSMC's optical computing chip matrix (~512x512) and Caltech's optical frequency exceeding 100GHz, indicating the challenges in achieving further breakthroughs [7]. Future Directions - Expanding computational parallelism is identified as a critical development direction for enhancing optical computing performance and making it practical for real-world applications [8]. - A recent achievement by the Shanghai Institute of Optics and Fine Mechanics has led to the development of a high-parallel optical computing integrated chip, demonstrating a parallelism greater than 100, which addresses key challenges in high-density information processing [8][9].

Core Viewpoint - The article highlights a significant breakthrough in the field of optical computing chips, specifically the development of the LightGen chip by researchers at Shanghai Jiao Tong University, which supports large-scale semantic media generation models [2][3]. Breakthrough Achievements - Researchers have successfully developed the LightGen chip, which is capable of achieving two orders of magnitude improvement in computing power and energy efficiency compared to top digital chips, even when using less advanced input devices [4]. - The LightGen chip overcomes three critical bottlenecks: integration of millions of optical neurons on a single chip, all-optical dimensional transformation, and a novel optical training algorithm that does not rely on ground truth [4]. - LightGen can perform a complete closed-loop process of input, understanding, semantic manipulation, and generation, enabling high-resolution image generation (≥512×512), 3D generation (NeRF), and high-definition video generation [4]. Advantages of Optical Computing - Optical computing is recognized for its scalability, low power consumption, ultra-high speed, wide bandwidth, and high parallelism, making it a key technology for rapid computation of large-scale data in AI, scientific computing, and multimodal perception [5]. - The article notes that traditional chip architectures are struggling to keep pace with the increasing demands for computing power and energy efficiency due to the rapid evolution of deep neural networks and large-scale generative models [3][5]. Recent Developments in Optical Computing - A recent advancement by the Shanghai Institute of Optics and Fine Mechanics has led to the development of a high-parallel optical computing integrated chip, achieving a parallelism greater than 100, which addresses the challenge of high-density information processing on optical chips [6][7]. - The new optical chip system includes a self-developed integrated micro-cavity optical frequency comb and a high-performance parallel computing core, enabling a theoretical peak computing power of over 2560 TOPS with a power efficiency of over 3.2 TOPS/W [7].

Core Viewpoint - Shanghai Jiao Tong University has achieved a breakthrough in the field of next-generation optical computing chips, successfully developing an all-optical computing chip that supports large-scale semantic media generation models, with results published in the journal "Science" on December 19 [1] Group 1: Optical Computing Breakthrough - The rapid evolution of deep neural networks and large-scale generative models has led to a significant gap in performance growth of traditional chip architectures, prompting widespread interest in new architectures like optical computing [1] - Optical computing utilizes light propagation within chips to perform calculations, leveraging the inherent speed and parallelism of light, making it a promising direction to overcome computational power and energy consumption bottlenecks [1] Group 2: LightGen Chip Development - The research team led by Chen Yitong has proposed and implemented the LightGen chip, which demonstrates a two-order-of-magnitude improvement in computational power and energy efficiency compared to top digital chips, even with less advanced input devices [2] - LightGen overcomes three critical bottlenecks: integration of millions of optical neurons on a single chip, all-optical dimensional transformation, and a truth-independent optical generative model training algorithm, enabling end-to-end implementation for large-scale generative tasks [2] - LightGen can complete a closed loop of "input-understanding-semantic manipulation-generation," achieving high-resolution (≥512×512) image semantic generation, 3D generation (NeRF), high-definition video generation, and semantic control, while also supporting denoising and feature transfer tasks [2]

我国科学家实现新一代光计算芯片研究新突破 新华社上海12月19日电（记者陈潇雨）记者从上海交通大学获悉，该校科研人员近日在新一代光计算芯 片领域取得突破，首次实现了支持大规模语义媒体生成模型的全光计算芯片。相关成果12月19日发表于 《科学》杂志。 据了解，随着深度神经网络和大规模生成模型迅猛演进带来超高算力和能耗需求，传统芯片架构的性能 增长速度已出现严重缺口，光计算等新型架构受到广泛关注。 "所谓光计算，可以理解为，不是让电子在晶体管中运行，而是让光在芯片中传播，用光场的变化完成 计算。光天然具备高速和并行的优势，因此被视为突破算力与能耗瓶颈的重要方向。"论文作者、上海 交大集成电路学院助理教授陈一彤表示，把光计算真正用到生成式AI上并不简单，已有的全光计算芯 片主要局限于小规模、分类任务，光电级联或复用又会严重削弱光计算速度。如何让下一代算力光芯片 运行复杂生成模型，是全球智能计算领域公认的难题。 陈一彤课题组此次提出并实现了全光大规模语义生成芯片LightGen，采用极严格算力评价标准的实测表 明：即便采用性能较滞后的输入设备，LightGen仍可取得相比顶尖数字芯片2个数量级的算力和能效提 升。团队 ...

据介绍， LightGen可完整实现"输入—理解—语义操控—生成"的闭环 ，完成高分辨率 （≥512×512）图像语义生成、3D生成（NeRF）、高清视频生成及语义调控，同时支持去噪、 局部与全局特征迁移等多项大规模生成式任务。 "LightGen为新一代光计算芯片助力前沿人工智能开辟了新路径，也为探索更高速、更高能效 的生成式智能计算提供了新的研究方向。"陈一彤说。 下载财联社APP获取更多资讯 准确 快速 权威 专业 7x24h电报 头条新闻 实时盯盘 VIP资讯 据新华社，记者从上海交通大学获悉， 该校科研人员近日在新一代光计算芯片领域取得突破，首次 实现了支持大规模语义媒体生成模型的全光计算芯片。 相关成果12月19日发表于《科学》杂志。 据了解，随着深度神经网络和大规模生成模型迅猛演进带来超高算力和能耗需求，传统芯片架 构的性能增长速度已出现严重缺口，光计算等新型架构受到广泛关注。 "所谓光计算，可以理解为，不是让电子在晶体管中运行，而是让光在芯片中传播，用光场的 变化完成计算。光天然具备高速和并行的优势，因此被视为突破算力与能耗瓶颈的重要方 向。"论文作者、上海交大集成电路学院助理教授陈一彤表示， ...

Core Viewpoint - Shanghai Jiao Tong University has achieved a breakthrough in the field of next-generation optical computing chips, successfully developing an all-optical computing chip that supports large-scale semantic media generation models, with results published in the journal "Science" on December 19 [1] Group 1: Optical Computing Breakthrough - The traditional chip architecture is facing a significant performance growth gap due to the rapid evolution of deep neural networks and large-scale generative models, leading to increased demand for computing power and energy [1] - Optical computing is viewed as a crucial direction to overcome the bottlenecks of computing power and energy consumption, utilizing light propagation in chips instead of electrons in transistors [1] Group 2: LightGen Chip Development - The LightGen chip developed by the research team demonstrates a performance improvement of two orders of magnitude in computing power and energy efficiency compared to top digital chips, even when using relatively outdated input devices [2] - Key breakthroughs in LightGen include the integration of over one million optical neurons on a single chip, full optical dimension conversion, and a novel light-based generative model training algorithm that does not rely on true values [2] - LightGen can complete a closed loop of "input—understanding—semantic manipulation—generation," enabling high-resolution (≥512×512) image generation, 3D generation (NeRF), high-definition video generation, and semantic control, while also supporting denoising and feature transfer tasks [2]

公众号记得加星标⭐️，第一时间看推送不会错过。 光子平台、存储架构和光开关领域的最新进展表明，光计算领域正在不断发展。 世界各地的研究团队正在加速推进光子计算的发展，过去一年发表的研究成果涵盖器件、存储器、开 关、特征提取和高速调制等领域。近期研究成果包括硅锗光子学、集成光存储器、单光子开关、光学 衍射引擎以及400 Gb/s电吸收调制器等，每一项都旨在降低数据密集型系统的延迟或提高带宽。 综合来看，这些项目展现了光学技术如何能够支持未来的人工智能、高性能计算和实时决策工作负 载，同时保持与大规模半导体制造的兼容性。 01 IHP发布搭载140 GHz调制器的SiGe光子平台 IHP 推出了其所谓的首个硅锗光子平台，该平台能够支持带宽远超当前硅光子极限的电吸收调制器和 光电二极管，并报告称其调制器的外推 3 dB 截止频率为 140 GHz，鳍式光电二极管的外推 3 dB 截 止频率高达 200 GHz。 威斯康星大学麦迪逊分校的研究人员开发并测试了一种完全由商用硅光子代工厂现有组件构建的集成 光子存储芯片，为可扩展的光计算硬件提供了一条切实可行的途径。 该器件采用由光电二极管、微环谐振器和光波导构成的"交叉 ...