This standard defines a comprehensive framework for federated machine learning of semantic information agents. It targets two primary layers: ⢅
IEEE The Institute of Electrical and Electronics Engineers Inc.
This standard provides: 1. Agent Components: The building blocks and architectural elements that constitute an educational Large Language Model (LLM)…
IEEE P3429
Recommended Practices for Levels of Artificial Intelligence Generated Content Technologies
This recommended practice provides an overview of Artificial Intelligence Generated Content (AIGC) technologies, levels of those AICG technologies and defines…
This standard defines and provides criteria to measure the capabilities of foundation models. The standard focuses on measurable and objective…
This recommended practice provides a comprehensive framework for understanding, defining, and evaluating AI risks, AI safety, AI trustworthiness, and AI…
For the software engineering life cycle empowered by Generative Pre-trained Transformer (GPT) this recommended practice specifies: ⢠a description and…
IEEE P3419
Standard for Large Language Model Evaluation
This standard establishes a comprehensive set of criteria for the evaluation of Large Language Models (LLMs) and extends to multimodal…
This standard addresses Artificial Intelligence (AI) risks such as malicious use, AI race, organizational risks, and rogue AI’s. The standard…
This recommended practice provides a data processing framework for training large language models, refining the relevant terms and definitions. The…
This standard applies to the design, development, application, and evaluation of large-scale deep learning models for artificial intelligence. The standard…
This recommended practice specifies tools and indexes for evaluating content generated by artificial intelligence technology. Ā© Copyright 2024 IEEE ā…
This standard specifies the basic functions, performance requirements, software ecosystem, and application scenarios of the deep learning chip for the…