老黄All in物理AI！最新GPU性能5倍提升，还砸掉了智驾门槛

Core Insights - NVIDIA is fully committed to AI, marking its first appearance at CES in five years without showcasing gaming graphics cards [2] - The next-generation Rubin architecture GPU demonstrates significant performance improvements, with inference and training capabilities being 5 times and 3.5 times that of the Blackwell GB200, respectively [4][17] Group 1: New Product Launches - NVIDIA introduced five new product lines, emphasizing the importance of open-source training frameworks and multimodal datasets, including 100 trillion language training tokens and 100TB of vehicle sensor data [5][6] - The Vera Rubin NVL72 architecture was officially launched, featuring six core components designed to enhance AI data center capabilities [14][15] - The Rubin GPU achieves 50 PFLOPS in inference performance and 35 PFLOPS in training performance under NVFP4 data types, significantly surpassing previous models [17] Group 2: Technological Advancements - The NVLink 6 technology enhances inter-GPU bandwidth to 3.6 TB/s, with a total bandwidth of 260 TB/s across the entire architecture [21][20] - The Vera CPU integrates 88 custom Arm cores, allowing for high thread concurrency and improved memory bandwidth [22] - NVIDIA's new BlueField-4 DPU introduces a memory layer aimed at optimizing key-value cache operations, addressing performance bottlenecks in AI infrastructure [32][34] Group 3: AI Model Developments - The Alpamayo model series was launched for autonomous driving, featuring a 10 billion parameter open-source model capable of interpreting environmental data for decision-making [39][41] - The Nemotron model family expands into voice, retrieval-augmented generation (RAG), and safety applications, enhancing AI capabilities in various domains [49][51] - The Cosmos platform for robotics has been upgraded, providing new models for generating synthetic data that adheres to physical laws [54][58] Group 4: Healthcare and Life Sciences - NVIDIA Clara targets the healthcare sector, aiming to reduce costs and accelerate the implementation of treatment solutions [62] - The company offers a dataset of 455,000 synthetic protein structures to support research in drug discovery and personalized medicine [66][69]