![The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) artwork](https://is1-ssl.mzstatic.com/image/thumb/Podcasts113/v4/39/58/c6/3958c6ce-86e4-3b80-bfb9-840e1dfd7e4b/mza_491361902049110775.png/100x100bb.jpg)
Stable Diffusion and LLMs at the Edge with Jilei Hou - #633
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
English - June 12, 2023 18:24 - 40 minutes - ★★★★★ - 323 ratingsTechnology News Tech News machinelearning artificialintelligence datascience samcharrington tech technology thetwimlaipocast thisweekinmachinelearning twiml twimlaipodcast Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Today we’re joined by Jilei Hou, a VP of Engineering at Qualcomm Technologies. In our conversation with Jilei, we focus on the emergence of generative AI, and how they've worked towards providing these models for use on edge devices. We explore how the distribution of models on devices can help amortize large models' costs while improving reliability and performance and the challenges of running machine learning workloads on devices, including model size and inference latency. Finally, Jilei we explore how these emerging technologies fit into the existing AI Model Efficiency Toolkit (AIMET) framework.
The complete show notes for this episode can be found at twimlai.com/go/633
Today we’re joined by Jilei Hou, a VP of Engineering at Qualcomm Technologies. In our conversation with Jilei, we focus on the emergence of generative AI, and how they've worked towards providing these models for use on edge devices. We explore how the distribution of models on devices can help amortize large models' costs while improving reliability and performance and the challenges of running machine learning workloads on devices, including model size and inference latency. Finally, Jilei we explore how these emerging technologies fit into the existing AI Model Efficiency Toolkit (AIMET) framework.
The complete show notes for this episode can be found at twimlai.com/go/633