USB V3.1 Power Delivery Type-C Port Evaluation board for OTI9108 IP
Performance AI Accelerator for Edge Computing
Our unique differentiation starts with the ability to simultaneously execute multiple AI/ML models significantly expanding the realm of capability over existing approaches. This game-changing advantage is provided by the co-developed NeuroMosAIc Studio software’s ability to dynamically allocate HW resources to match the target workload resulting in highly optimized, low-power execution. The designer may also select the optional on-device training acceleration extension enabling iterative learning post-deployment. This key capability cuts the cord to cloud dependence while elevating the accuracy, efficiency, customization, and personalization without reliance on costly model retraining and deployment, thereby extending device lifecycles.
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Block Diagram of the Performance AI Accelerator for Edge Computing
AI IP
- RT-630 Hardware Root of Trust Security Processor for Cloud/AI/ML SoC FIPS-140
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