How can AI-driven code generation tools enhance productivity and accuracy in SDV development while balancing creativity and control in engineering processes?
In what ways can AI-powered simulations create more diverse and realistic testing scenarios, and how can they help identify potential issues earlier in the SDV development lifecycle?
How can predictive maintenance algorithms, driven by AI, proactively address software-related issues in SDVs, and what role does real-time data play in enhancing their effectiveness?
What are the key benefits and challenges of integrating AI-optimized CI/CD pipelines in SDVs, and how do they impact the speed and reliability of software updates?
How can AI systems adapt and improve SDV software using real-world data, and what are the implications for software robustness and long-term vehicle performance?