Nvidia(US:NVDA) 美股IPO·2026-01-05 23:38Core Viewpoint - Nvidia has announced the open-source release of its first inference VLA (Vision-Language-Action) model, Alpamayo 1, aimed at enhancing autonomous vehicle capabilities to "think" and solve problems in unexpected situations, utilizing a 10 billion parameter architecture [1][3][4]. Group 1: Model and Technology Overview - The Alpamayo model is designed to process complex driving scenarios using human-like reasoning, providing new pathways to address long-tail issues in autonomous driving [1][3]. - The model integrates three foundational pillars: open-source models, simulation frameworks, and datasets, creating a comprehensive open ecosystem for automotive developers and research teams [4]. - The model is now available on the Hugging Face platform and allows developers to adapt it for smaller runtime models or as a foundational tool for autonomous driving development [4][10]. Group 2: Industry Support and Collaboration - Major companies in the mobility sector, including Jaguar Land Rover, Lucid, and Uber, have expressed strong interest in utilizing the Alpamayo model to develop inference-based autonomous driving technology stacks [3][11]. - Nvidia's CEO highlighted the importance of the Alpamayo model in enabling autonomous vehicles to navigate rare scenarios safely and explain their driving decisions, which is crucial for scalable autonomous driving [6][11]. Group 3: Simulation and Data Resources - Alongside the Alpamayo model, Nvidia has released AlpaSim, a fully open-source end-to-end simulation framework for high-fidelity autonomous driving development, available on GitHub [9][10]. - Nvidia provides a large-scale open dataset containing over 1,700 hours of driving data, covering a wide range of geographical locations and conditions, essential for advancing inference architectures [9][10]. Group 4: Broader AI Model Releases - Nvidia has also launched several new open-source models, data, and tools across various industries, including the Nemotron family for agent AI, the Cosmos platform for physical AI, and the Isaac GR00T for robotics [12][14]. - These models include extensive datasets, such as 100 trillion language training tokens and 100TB of vehicle sensor data, aimed at accelerating AI development across sectors [14][15].