Keynote: RISC-V Opportunities at the Edge of AI
summary
Argues that RISC-V’s open, modular ISA plus vector and tensor extensions and domain-specific accelerators let edge devices run real-time AI where latency, power and privacy matter — examples include cars that must “see, decide, act” locally, industrial fleets of thousand of machines, AR-guided surgery, wearables and drones that survive connectivity loss. Claims toolchain support yields zero-day bring-up from $3 sensor to high-end SoCs, and predicts the next trillion dollars of compute will be AI-native and built on RISC-V.
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chapters (5)
- 0:00Introduction to Edge AI
- 3:12Hyperscaler limitations and edge benefits
- 6:03RISC-V for edge AI innovation
- 9:05Real-world RISC-V edge AI examples
- 12:40RISC-V and Edge AI future
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