Futureproofing Automotive AI to Manage Lifetime Cost
Cars and trucks are expected to continue their 10– to 20-year lifetimes for the foreseeable future, with corresponding implications for electronics reliability as we already know. More challenging is managing long service times for Automotive AI systems, especially given the rapid evolution of AI technology and the need to manage updates to field service problems discovered or regulatory changes. Recalls to upgrade hardware would be a very expensive option. Equally, Automotive AI software model service updates will depend on scalable systems to support service technicians handling many product lines across many locations. Hardware and software must be scalable both to support and simplify updates over long vehicle lifetimes and to support advancing vehicle architectures for new cars.
To read the full article, click here
Related Semiconductor IP
- MIL-STD-1553 Controller IP
- UFS 5.x Device IP
- UCIe 3.x Controller IP
- Ethernet 800G PCS IP
- CHI to UCIe Bridge IP
Related Blogs
- Virtual Platforms from Arm and Partners Available Now to Accelerate and Transform Automotive Development
- Synopsys Collaborates with Arm to Drive Automotive Design Excellence
- Bluetooth LE and UWB in Automotive Extend Capabilities at Lower System Cost
- Cadence Commits to Join imec Automotive Chiplet Programme
Latest Blogs
- CDM Dependence on Device Capacitance
- What the Cyber Resilience Act means for the future of chip design
- When Your IP Vendor Has Operated 150,000 Base Stations: Introducing Viettel Semiconductor
- Relationship between architecture and validation in system design
- The Post-Quantum Cryptography Mandate: Building Cryptographically Agile Systems for the Quantum Era