Browsing: generation

Image by Author   # Introduction  Retrieval-augmented generation (RAG) systems are, simply put, the natural evolution of standalone large language models (LLMs). RAG addresses several key limitations…

In this tutorial, we build and run a Colab workflow for Gemma 3 1B Instruct using Hugging Face Transformers and HF Token, in a practical, reproducible,…

Google has announced the release of Veo 3.1 Lite, a new model tier within its generative video portfolio designed to address the primary bottleneck for production-scale…

In the current AI landscape, the ‘context window’ has become a blunt instrument. We’ve been told that if we simply expand the memory of a frontier…

Mistral AI has released Voxtral TTS, an open-weight text-to-speech model that marks the company’s first major move into audio generation. Following the release of its transcription…

OpenAI has announced that its AI video generation app, Sora, is shutting down, and there’s no explanation as to why. In a post on Twitter/X, OpenAI…

header(“11. DISORDERED STRUCTURE -> ORDERED APPROXIMATION”) disordered = Structure( Lattice.cubic(3.6), [{“Cu”: 0.5, “Au”: 0.5}], [[0, 0, 0]], ) disordered.make_supercell([2, 2, 2]) print(“Disordered composition:”, disordered.composition) try: disordered_oxi…

A key development in generative AI is AI-powered video generation. Before AI, creating dynamic video content required extensive resources, technical expertise, and significant manual effort. Today,…

Generating high-quality custom videos remains a significant challenge, because video generation models are limited to their pre-trained knowledge. This limitation affects industries such as advertising, media…

Image by Editor   # Introduction  Synthetic data, as the name suggests, is created artificially rather than being collected from real-world sources. It looks like real data…