This recommended practice provides a holistic framework for AI foundation models. The framework allows sharing of the common computing resources,…
United States
This standard provides: 1. Agent Components: The building blocks and architectural elements that constitute an educational Large Language Model (LLM)…
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 standard addresses the evaluation of safety, explainability, and stability of algorithms implementing autonomous driving levels, as defined by SAE…
This standard defines a comprehensive framework for federated machine learning of semantic information agents. It targets two primary layers: •…
This standard establishes a comprehensive set of criteria for the evaluation of Large Language Models (LLMs) and extends to multimodal…
This standard specifies the architecture and technical requirements of differential privacy for personal information protection in Artificial Intelligence model training.…
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…
