Nvidia Launches H200, A Powerful New Chip for AI Training

Nvidia, the leading company in the field of graphics processing units, has launched a new chip

Generative AI is one of the most exciting and challenging fields of AI research, as it has the potential to unlock new forms of creativity, innovation, and expression. However, generative AI also requires a lot of computational power and memory, as it involves training and running large and complex models, such as generative adversarial networks (GANs), variational autoencoders (VAEs), or large language models (LLMs).

GANs are a type of generative AI model that consists of two competing neural networks, one that generates new content and one that evaluates its quality. VAEs are another type of generative AI model that uses probabilistic methods to encode and decode data, allowing for variations and diversity in the generated content. LLMs are a type of generative AI model that uses natural language processing (NLP) techniques to generate coherent and fluent text, such as stories, articles, or conversations.

To train and run these models, generative AI researchers and developers need powerful chips that can handle massive amounts of data and perform fast and parallel computations. GPUs are the preferred choice of chips for generative AI, as they are designed to process graphics and images, which are similar to the types of data that generative AI models work with. The ability of GPUs to execute several tasks concurrently is crucial for training and managing big and intricate models.

However, not all GPUs are created equal and some are better suited for certain activities than others. This is where the Nvidia H200 comes in. The Nvidia H200 is the latest and most powerful chip from Nvidia, based on the Nvidia Hopper architecture. The Nvidia H200 is the first GPU to offer 141 gigabytes (GB) of HBM3e memory at 4.8 terabytes per second (TB/s), which is nearly double the capacity and 2.4x more bandwidth compared to its predecessor, the Nvidia H100.

The Nvidia H200's larger and faster memory enables it to handle more data and perform more computations, which are crucial for generative AI and LLMs. The Nvidia H200 can also accelerate the inference speed of generative AI and LLMs, which is the process of generating new content based on the trained models.