{"title":"边缘设备上的生成人工智能:模型,硬件和系统:教程","authors":"Paul N. Whatmough","doi":"10.1109/MSSC.2025.3579704","DOIUrl":null,"url":null,"abstract":"Generative artificial intelligence (GenAI) refers to the use of neural networks to produce new output data, which could be in the form of text, image, audio, video, or other modalities. During training, these models learn the underlying distributions of the data such that, during inference, they can generate new output data in response to an input prompt (typically a text prompt). In recent years, we have witnessed a staggeringly rapid progression in capability and sophistication of these generative models, following a major boom in investment in AI research during the 2020s. This article provides a brief tutorial on GenAI for edge devices, as a summary of the tutorial of the same name given at the International Solid State Circuits Conference (ISSCC) this year.","PeriodicalId":100636,"journal":{"name":"IEEE Solid-State Circuits Magazine","volume":"17 3","pages":"32-37"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generative Artificial Intelligence on Edge Devices: Models, Hardware, and Systems: A tutorial\",\"authors\":\"Paul N. Whatmough\",\"doi\":\"10.1109/MSSC.2025.3579704\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Generative artificial intelligence (GenAI) refers to the use of neural networks to produce new output data, which could be in the form of text, image, audio, video, or other modalities. During training, these models learn the underlying distributions of the data such that, during inference, they can generate new output data in response to an input prompt (typically a text prompt). In recent years, we have witnessed a staggeringly rapid progression in capability and sophistication of these generative models, following a major boom in investment in AI research during the 2020s. This article provides a brief tutorial on GenAI for edge devices, as a summary of the tutorial of the same name given at the International Solid State Circuits Conference (ISSCC) this year.\",\"PeriodicalId\":100636,\"journal\":{\"name\":\"IEEE Solid-State Circuits Magazine\",\"volume\":\"17 3\",\"pages\":\"32-37\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Solid-State Circuits Magazine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11131398/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Solid-State Circuits Magazine","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/11131398/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generative Artificial Intelligence on Edge Devices: Models, Hardware, and Systems: A tutorial
Generative artificial intelligence (GenAI) refers to the use of neural networks to produce new output data, which could be in the form of text, image, audio, video, or other modalities. During training, these models learn the underlying distributions of the data such that, during inference, they can generate new output data in response to an input prompt (typically a text prompt). In recent years, we have witnessed a staggeringly rapid progression in capability and sophistication of these generative models, following a major boom in investment in AI research during the 2020s. This article provides a brief tutorial on GenAI for edge devices, as a summary of the tutorial of the same name given at the International Solid State Circuits Conference (ISSCC) this year.