Machine Learning

GenAI on the Edge Forum: Architecture 2.0: Prompt Engineering and Foundation Models for Edge AI…



Architecture 2.0: Prompt Engineering and Foundation Models for Edge AI Hardware Design
Vijay Janapa REDDI, Associate Professor, Harvard University

TinyML enables AI capabilities on resource-constrained edge devices, but designing specialized hardware for TinyML remains challenging due to high costs, long development cycles, and error risks. The small margins in the TinyML market demand a visionary approach to hardware design. This forward-looking talk introduces Architecture 2.0, a shift toward leveraging foundation models and generative AI to rethink edge AI hardware design. Central to this vision is prompt engineering, adapting foundation models to edge devices’ unique requirements and constraints. Prompt engineering techniques can assist designers in navigating performance, power, and area trade-offs, ultimately leading to accelerated hardware design, reduced costs, and minimized error risks. The talk explores a few examples of prompt engineering applied to generate TinyML hardware designs. But this is only the beginning; thus, the talk emphasizes the critical role of collaboration between TinyML and foundation model communities. Fostering cross-disciplinary partnerships will drive the development of novel prompting techniques, model architectures, and generative AI tools tailored for hardware design, unlocking a new era of efficient and accessible edge AI solutions that promise to drive innovation. This talk aims to inspire the community to collaborate and craft a shared vision, exploring the transformative potential of foundation models and generative AI in TinyML hardware design, and work together towards realizing Architecture 2.0.

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