Training AI Models

NVIDIA has announced the latest v0.15 release of NVIDIA TensorRT Model Optimizer, a state-of-the-art quantization toolkit of model optimization techniques...

Today’s large language models (LLMs) are based on the transformer model architecture introduced in 2017. Since then, rapid advances in AI compute performance...

Generative AI, the ability of algorithms to process various types of inputs—such as text, images, audio, video, and code—and generate new content, is...

Generative AI models have a variety of uses, such as helping write computer code, crafting stories, composing music, generating images, producing videos, and...

VILA is a family of high-performance vision language models developed by NVIDIA Research and MIT. The largest model comes with ~40B parameters and the smallest...

GPUs were initially specialized for rendering 3D graphics in video games, primarily to accelerate linear algebra calculations. Today, GPUs have become one of...

After exploring the fundamentals of diffusion model sampling, parameterization, and training as explained in Generative AI Research Spotlight: Demystifying...

With Internet-scale data, the computational demands of AI-generated content have grown significantly, with data centers running full steam for weeks or months...

At AWS re:Invent 2023, AWS and NVIDIA announced that AWS will be the first cloud provider to offer NVIDIA GH200 Grace Hopper Superchips interconnected with...

Large language models (LLMs) are a class of generative AI models built using transformer networks that can recognize, summarize, translate, predict, and...