TIER IV, a pioneer in open-source autonomous driving (AD) technology, proudly announces the initiation of the Co-MLOps (Cooperative Machine Learning Operations) Project. This new endeavor is aimed at scaling the development of AI (Artificial Intelligence) for autonomous driving. The deployment of the Co-MLOps Platform, developed under this project, will enable the global sharing of managed sensor data, including camera images and LiDAR (Light Detection and Ranging) point clouds, sourced from various regions. Furthermore, the Co-MLOps Platform will offer MLOps functions and Edge AI reference models, empowering partner companies to enhance their proprietary AI for autonomous driving.
TIER IV is set to exhibit edge AI models at CES 2024 in Las Vegas, Nevada, from January 9-12, following a successful initial proof of concept (PoC) test conducted in 2023 across eight global regions, including Japan, Germany, Poland, Taiwan, Turkey, and the United States. The PoC test utilized video data collected from these regions to evaluate the perception capabilities of multitask Edge AI models, which have been optimized to operate at less than 10W of power consumption. This showcase at TIER IV’s booth will highlight the fruits of this innovative project.
Conventional Challenges
In the development of AI for autonomous driving, large datasets are essential to achieve competitive performance levels. Historically, companies and research institutions have independently collected data and engaged in similar technology development, leading to overlaps in database construction and development processes. Furthermore, limited resources for setting up development environments and data collection have made it challenging for some companies to implement development processes that are robust enough to achieve desired performance levels. This has impacted the scalability of technological development across the industry.
Platform Overview
TIER IV is leading the development of the Co-MLOps Platform, set to serve as a foundation for various companies and research institutions to partake in the development of AI for autonomous driving at an industry-leading level. This initiative aims to catalyze technological development that was previously hindered by insufficient scalability and to foster open innovation through open collaboration. The platform will be structured to fulfill the following objectives:
- Ensure that data collected by companies is shared with appropriate privacy and security safeguards.
- Manage the utilization of MLOps functionalities, crucial for the development of AI for autonomous driving, on the large-scale datasets shared among companies.
- Provide opportunities for companies to utilize Edge AI reference models, created using common MLOps functionalities, in their own development of AI for autonomous driving.
The development of the platform is being propelled by leveraging the diverse services offered by Amazon Web Services (AWS). AWS’s key services such as storage, databases, and computing, as well as its extensive global infrastructure, will serve as the cornerstone for the efficient and stable operations. The platform will also adopt a cloud-native approach, eventually supporting updates to the recognition models via Over the Air (OTA). By leveraging the power of AWS, the Co-MLOps Platform will offer cutting-edge technology and a stable infrastructure, thereby accelerating the development of innovative autonomous driving AI.
The platform fosters differentiation by empowering participating companies to retain their proprietary technologies, functional safety and development processes, and quality control measures. Additionally, integrating the outputs developed on this platform with the Open AD Kit, defined by the Autoware Foundation based on the SOAFEE framework, will expedite software development towards SDV mass production while maximizing the utilization of the Arm® Automotive platform.
“We believe this project will catalyze new collaborations and competitions in AI development within the mobility industry, leading to various innovations, particularly in recognition technologies,” said Shinpei Kato, founder, CEO and CTO of TIER IV. “Through collaboration with many partners, we aim to develop the world’s leading AI technologies for autonomous driving and promote the rollout of safe and reliable AD technologies.”
“We anticipate that the construction of a world model will be further boosted by this project, by utilizing a diverse range of large datasets collected worldwide,” said Professor Yutaka Matsuo of the University of Tokyo’s Graduate School of Engineering. “The aim is for our joint research to lead to further development of practical applications for autonomous driving through the integration of generative AI technology. We aim to introduce new methods that will enhance the performance of autonomous driving AI.”
“We support the vision of this project that aims to solve common challenges in the mobility industry and accelerate the creation of innovation,” said Bill Foy, Director of Automotive Solutions and GTM at AWS. “By providing comprehensive support using various AWS services and global infrastructure, we will contribute to the long-term success of this project.”
“Software is changing what it means to own a car today, and to deliver a software-defined vehicle to mass markets requires expertise and collaboration from across the industry, such as through initiatives like SOAFEE,” said Robert Day, SOAFEE SIG Governing Body representative and director of automotive partnerships, Automotive Line of Business, Arm. “The Co-MLOps platform project is another important example of leveraging expertise from across the industry to encourage and further accelerate the development and deployment of software-defined vehicles.”
Future Prospects
In the first half of 2024, TIER IV, in collaboration with its partners, aims to optimize sensor architecture, standardize annotation formats, and develop data search and active learning infrastructure utilizing large language models (LLM). These advancements are expected to enable more efficient and accurate development of AI for autonomous driving. The development of low-power and multimodal AI models for sensor fusion will also allow for the integration of data from various sensors, leading to advanced Edge AI models with highly sophisticated perception capabilities. Furthermore, the generation of learning data using World Models, generative AI, and integration with Neural Simulators will simulate complex real-world scenarios, strengthening the training of AI models.
The second half of 2024 is slated for the commencement of full-scale operations of the Co-MLOps Platform, incorporating these new features. Through this platform, TIER IV seeks to significantly improve the development process of AI for autonomous driving in collaboration with partner companies, thereby accelerating technological advancement in the industry. TIER IV continues to actively seek partners for the development and specification of these functionalities.
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#AI [Source: AI Techpark]