Generative AI Transforms the Automotive Industry
Generative AI is transforming every aspect of the automotive industry, including software development, testing, user experience, personalization, and safety. With the automotive industry shifting from a mechanically driven approach to a software-driven one, generative AI is unlocking a world of possibilities.
Building Features to Enhance Customer Experience
Generative AI is the key to realizing fully autonomous vehicles (AVs) by enhancing AI-based algorithms for better decision-making. It generates and synthesizes datasets across all possibilities, from limited real-time data to training and testing data. This technology is instrumental in delivering vehicle personalization and user experiences. This can encompass a range of capabilities, including advanced search functionalities, language translations, in-car personal assistants, and intuitive recommendations for video and audio entertainment.
Accelerating the Software Engineering Lifecycle
The goal of a software-defined vehicle (SDV) is to provide more flexibility and enrich the user experience, enabling customers to upgrade and update vehicle features based on their convenience. This has increased vehicle complexity, resulting in millions of lines of code. There is high demand for enabling feature-as-a-service models, where automotive features need to be developed and deployed within a few weeks.
Test Case Generation from Unstructured Requirements
Creating test cases from unstructured system requirements is one of the most time-consuming steps within the software engineering lifecycle.
Conclusion
With the expertise in the generative AI and automotive domains, TCS has developed a highly efficient automotive test case generation pipeline using NVIDIA DGX H100 systems and software including NVIDIA NIM and NVIDIA NeMo. This model, fine-tuned with the NVIDIA NeMo framework, along with faster inference possible with NIM, resulted in accuracies and coverage higher than that of existing models available with low latency. TCS has observed ~2x acceleration in its overall test case generation pipeline.
Frequently Asked Questions
Q: What is the primary goal of using generative AI in the automotive industry?
A: The primary goal is to enhance customer experience and accelerate the software engineering lifecycle.
Q: How does generative AI generate test cases from unstructured requirements?
A: Generative AI uses large language models (LLMs) to generate test cases from unstructured system requirements.
Q: What are the benefits of using NVIDIA NIM and NVIDIA NeMo in the automotive test case generation pipeline?
A: NVIDIA NIM and NVIDIA NeMo provide faster inference and higher accuracy and coverage in the test case generation pipeline.
Q: What are the potential applications of generative AI in the automotive industry?
A: Generative AI has the potential to be used in various applications, including advanced search functionalities, language translations, in-car personal assistants, and intuitive recommendations for video and audio entertainment.
