Nvidia(US:NVDA) 虎嗅APP·2026-01-13 13:35Core Viewpoint - The article discusses NVIDIA's recent announcements at CES, particularly the launch of the open-source VLA model, Alpamayo, aimed at revolutionizing autonomous driving technology and its implications for the automotive industry [5][8]. Group 1: NVIDIA's Innovations - NVIDIA introduced the Alpamayo model, which integrates Vision-Language-Action (VLA) technology for autonomous driving, allowing vehicles to interpret sensor data into language and symbols for decision-making [6][10]. - Alpamayo is the first open-source VLA model, providing a foundational framework for automakers to develop their own autonomous driving solutions, thus lowering development costs and complexity [12][14]. - The model is complemented by the AlpaSim simulation framework and a dataset containing over 1,727 hours of driving data, offering a comprehensive toolkit for automotive companies [12][14]. Group 2: Competitive Landscape - The VLA model has attracted interest from various automakers, including Xiaopeng, Li Auto, and others, who are also pursuing similar technologies [10][11]. - Tesla's Full Self-Driving (FSD) system appears to utilize a similar VLA architecture, indicating a competitive race in the autonomous driving sector [10][11]. - Despite Tesla's advancements, NVIDIA's Alpamayo aims to provide a more explainable and controllable decision-making process compared to traditional end-to-end models [11][12]. Group 3: NVIDIA's Business Strategy - NVIDIA's automotive business, while dominant in high-level autonomous driving, has not met revenue expectations compared to its data center operations, prompting a strategic shift [17][22]. - The company aims to provide standardized tools and frameworks to automakers, allowing them to leverage NVIDIA's technology without needing extensive in-house development capabilities [22][26]. - By offering Alpamayo and associated tools, NVIDIA seeks to maintain its market position while addressing the needs of traditional automakers who may lack advanced algorithm development capabilities [23][26].