Rover AI
On Chip AI
On-chip AI offers numerous advantages that enhance the performance and capabilities of devices including but not limited to
Chip Design and Architecture
Our designers choose an appropriate architecture for on-chip AI optimized for parallel processing.
Model Development and Training
Before being integrated into chips, AI models are developed using large datasets and are capable of learning patterns from these datasets.
The trained models are then optimized to meet the constraints of power, memory, and processing capabilities of the target chip. Techniques like quantization, pruning, and compression are applied to simplify models without significantly sacrificing performance.
Embedded Software Development
Once models are optimized, software that executes these models is developed and embedded within the chip.
The integrated chip with on-chip AI capabilities undergoes rigorous testing in real-world settings to ensure it performs accurately and efficiently.
Implementation in Devices
The final on-chip AI-enabled processors are integrated into various devices, such as smartphones, smart cameras, autonomous vehicles, and IoT devices.
Rover Ai
Book an appointment today!
This BYOM approach not only enhances the personalization of AI solutions but also fosters a robust partnership, as we work collaboratively with clients from conception to implementation and beyond.