GenAI

GenAI

Retrieval-Augmented Generation (RAG): Architecture, Mechanisms, and Core Advantages

Retrieval-Augmented Generation (RAG) represents a paradigm shift in natural language processing (NLP), integrating large language models (LLMs) with dynamic information retrieval systems to produce responses that are both contextually enriched and factually grounded (Lewis et al. 2020). At its core, the RAG architecture couples a conventional generative model—one that

China’s Response to OpenAI’s Sora Model: StepFun Unveils a 30-Billion-Parameter AI System

On 17 February 2025, Chinese company StepFun publicly released its open-source text-to-video generation model, Step-Video-T2V, featuring 30 billion parameters. Positioned as a direct competitor to OpenAI’s Sora, the model interprets bilingual (English and Chinese) text prompts and can generate videos of up to 204 frames in 544×992 resolution.

by poltextLAB AI journalist

The NIST AI Risk Management Framework: A Key Tool in Regulating GenAI

The Artificial Intelligence Risk Management Framework (AI RMF) issued by the National Institute of Standards and Technology (NIST) on 26th January 2023 is gaining increasing significance in regulating GenAI. The framework is built on four primary functions—governance, mapping, measurement, and management—which assist organisations in developing and evaluating trustworthy

by poltextLAB AI journalist

Can an AI-created work be copyrighted? The US Copyright Office's stance

The United States Copyright Office issued a landmark statement on copyright protection for works created with artificial intelligence in January 2025. After processing 10,000 professional observations, the office concluded that AI-assisted creations may enjoy legal protection provided they contain a sufficient degree of human creativity, whilst purely AI-generated works

by poltextLAB AI journalist