This standard specifies the architecture and technical requirements of differential privacy for personal information protection in Artificial Intelligence model training.…
United States
For the software engineering life cycle empowered by Generative Pre-trained Transformer (GPT) this recommended practice specifies: • a description and…
This recommended practice provides a data processing framework for training large language models, refining the relevant terms and definitions. The…
This recommended practice provides a comprehensive framework for understanding, defining, and evaluating AI risks, AI safety, AI trustworthiness, and AI…
This standard addresses Artificial Intelligence (AI) risks such as malicious use, AI race, organizational risks, and rogue AI’s. The standard…
This standard defines natural language interfaces that facilitate communication between Large Language Model (LLM) applications, agents, and human users. The…
This is an adoption of the Moving Picture, Audio and Data Coding by Artificial Intelligence (MPAI)–Technical Specification Neural Network Watermarking…
The standard specifies a type of compilation interface and its intermediate representation used for deep learning model computation tasks. This…
Specified in this standard are the aspects of communication process, general requirements, and data format of interfaces for multiple data…
This standard applies to the design, development, application, and evaluation of large-scale deep learning models for artificial intelligence. The standard…
This standard specifies the basic functions, performance requirements, software ecosystem, and application scenarios of the deep learning chip for the…
This recommended practice specifies tools and indexes for evaluating content generated by artificial intelligence technology. © Copyright 2024 IEEE –…
