Stable Diffusion and LLMs at the Edge with Jilei Hou - #633
Published:Jun 12, 2023 18:24
•1 min read
•Practical AI
Analysis
This article from Practical AI discusses the integration of generative AI models, specifically Stable Diffusion and LLMs, on edge devices. It features an interview with Jilei Hou, a VP of Engineering at Qualcomm Technologies, focusing on the challenges and benefits of running these models on edge devices. The discussion covers cost amortization, improved reliability and performance, and the challenges of model size and inference latency. The article also touches upon how these technologies integrate with the AI Model Efficiency Toolkit (AIMET) framework. The focus is on practical applications and engineering considerations.
Key Takeaways
- •Generative AI models like Stable Diffusion and LLMs are being deployed on edge devices.
- •Edge deployment can improve performance, reliability, and amortize costs.
- •Challenges include model size, inference latency, and integration with existing frameworks like AIMET.
Reference
“The article doesn't contain a specific quote, but the focus is on the practical application of AI models on edge devices.”