NVIDIA Highlights Autonomous Vehicle Technology
NVIDIA’s autonomous driving platform received significant recognition at the COMPUTEX Best Choice Awards. The company announced that its NVIDIA Alpamayo autonomous vehicle platform and NVIDIA Jetson Thor edge AI processor were among the technologies honored for innovation in autonomous vehicle development and robotics.
NVIDIA is also heavily promoting “Physical AI” and autonomous machines throughout GTC Taipei, with dedicated sessions focused on robotics, autonomous systems, and AI deployment in transportation.
oToBrite and Turing Drive Demonstrate Unmanned Vehicles
Taiwan-based Vision AI company oToBrite and autonomous driving developer Turing Drive are showcasing real-world unmanned vehicle applications at COMPUTEX 2026. Their demonstrations focus on automotive-grade Vision AI systems designed for autonomous vehicles, robotics, and smart mobility deployments. The companies describe the exhibit as an example of “Physical AI” moving from development into operational deployments.
Edge AI and Automotive Computing Become Major Themes
Several exhibitors are emphasizing automotive edge AI rather than fully autonomous vehicles. Companies including MediaTek and AAEON are showcasing technologies aimed at automotive computing, vehicle AI processing, robotics, and smart mobility applications. The broader theme at COMPUTEX 2026 is the convergence of AI, robotics, mobility, and edge computing.
Key Trend: Physical AI for Transportation
The biggest automotive story emerging from COMPUTEX 2026 is not a new robotaxi launch or consumer self-driving system. Instead, the show is highlighting what NVIDIA calls “Physical AI”—the combination of simulation, synthetic data generation, edge AI hardware, and autonomous machine software that can power vehicles, robots, industrial equipment, and smart infrastructure. Companies such as Foretellix, VinFast, Autobrains, oToBrite, and MICROIP are all presenting different pieces of that ecosystem.
Foretellix Introduces NVIDIA-Powered Toolchain for AI Vehicle Validation
Foretellix has launched a new reference solution for the NVIDIA Alpamayo ecosystem aimed at helping autonomous vehicle developers train, test, and validate AI-powered driving systems more efficiently. The platform combines data curation, synthetic data generation, operational design domain (ODD) analysis, and verification and validation tools into a unified workflow. By transforming raw driving logs into structured datasets, the solution enables engineers to identify valuable driving scenarios, measure testing coverage, and better understand how autonomous systems perform across both real-world and simulated environments.
A key feature of the platform is its ability to identify gaps in ODD coverage and generate targeted synthetic scenarios to fill them. Through integration with NVIDIA Omniverse NuRec and NVIDIA Cosmos, developers can reconstruct real-world scenes, modify vehicle and pedestrian behavior, and create large numbers of new testing environments. Foretellix says this data-centric approach is designed to help automakers and autonomous vehicle companies safely scale AI-driven autonomy while reducing the time and cost required to validate increasingly complex driving systems.
VinFast, NVIDIA and Autobrains Team Up on Level 4 Autonomous Driving Platform for Southeast Asia
VinFast, Autobrains, and NVIDIA have announced a strategic partnership to develop a next-generation Level 4 autonomous driving platform tailored for Southeast Asia. Built on NVIDIA DRIVE Hyperion 10 and powered by Autobrains’ Agentic AI software, the program aims to address the unique challenges of the region’s roads, including dense traffic, unpredictable driving behavior, and highly dynamic urban environments. The collaboration combines VinFast’s vehicle development capabilities, NVIDIA’s autonomous driving platform, and Autobrains’ AI technology to create a scalable and cost-effective path toward advanced self-driving vehicles.
The companies say the initiative is designed to overcome key obstacles that have slowed autonomous vehicle deployment, including high computing costs, system complexity, and limited performance outside controlled conditions. Unlike traditional end-to-end autonomous driving systems, Autobrains’ Agentic AI uses specialized AI agents that activate only when needed, reducing computing demands while improving real-world decision-making. By leveraging NVIDIA’s validated hardware and software foundation, VinFast expects to accelerate development and bring advanced autonomous driving capabilities to market at a more accessible price point, supporting its broader goal of expanding smart mobility solutions across Southeast Asia.
MICROIP Launches AI Vehicle Division and Cross-Platform Edge AI Solutions at COMPUTEX 2026
Taiwan-based ASIC design and AI software company MICROIP is using COMPUTEX 2026 to debut its new AI Vehicle System Business Group and showcase a range of edge AI technologies focused on smart mobility, automotive safety, and cross-platform deployment. The company unveiled an automotive safety system featuring automatic calibration and “triple safety protection,” including traffic light recognition, blind-spot detection, driver fatigue monitoring, and 360-degree AI-based environmental awareness. Designed for fleet operators and commercial vehicles, the system highlights MICROIP’s strategy of using software innovation to accelerate the adoption of intelligent transportation technologies.
MICROIP also introduced its AIVO no-code vision AI platform and XEdgAI deployment platform, which allows AI applications to run across multiple hardware architectures, including NVIDIA Jetson, Intel Core Ultra, and Axelera AI processors. On the semiconductor side, the company highlighted its CATS customized ASIC design service, which uses AI-assisted electronic design automation tools to reduce chip development timelines by up to nine months. Through partnerships with industrial computing company AAEON and neuromorphic AI specialist BrainChip, MICROIP is expanding an ecosystem that spans AI software, custom silicon, and edge deployment solutions aimed at accelerating real-world AI adoption.