Use Case of Computing-Aware AI large model
draft-an-cats-usecase-ai-01
| Document | Type |
Expired Internet-Draft
(individual)
Expired & archived
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|
|---|---|---|---|
| Author | Qing An | ||
| Last updated | 2024-02-12 (Latest revision 2023-08-11) | ||
| RFC stream | (None) | ||
| Intended RFC status | (None) | ||
| Formats | |||
| Stream | Stream state | (No stream defined) | |
| Consensus boilerplate | Unknown | ||
| RFC Editor Note | (None) | ||
| IESG | IESG state | Expired | |
| Telechat date | (None) | ||
| Responsible AD | (None) | ||
| Send notices to | (None) |
This Internet-Draft is no longer active. A copy of the expired Internet-Draft is available in these formats:
Abstract
AI models, especially AI large models have been fastly developed and widely deployed to serve the needs of users and multiple industries. Due to that AI large models involve mega-scale data and parameters, high consumption on computing and network resources, distributed computing becomes a natural choice to deploy AI large models. This document desribes the key concepts and deployment scenarios of AI large model, to demonstrate the necessity of considering computing and network resources to meet the requirements of AI tasks.
Authors
(Note: The e-mail addresses provided for the authors of this Internet-Draft may no longer be valid.)