AMD is excited to release one-step diffusion models that demonstrate the readiness of AMD Instinct™ MI250 accelerators for model training and further research. The models are designed to provide performance comparable to traditional full-step diffusion models while maintaining the efficiency needed for training on data center systems or deployment on edge devices, such as AI-enabled PCs and laptops.

 Full technical blog AMD Nitro Diffusion: One-Step Text-to-Image Generation Models

Amuse 2.2 Beta is now available for download. 

A step-by-step guide on how to run Stable Diffusion 3.5 Large, Stable Diffusion 3.5 Large Turbo or Stable Diffusion 3.5 Medium on AMD Radeon™ Graphics Cards and Ryzen™ AI 300 Series Processors. 

In recent years, the rapid development of artificial intelligence technology, especially the progress in large language models (LLMs), has garnered significant attention and discussion. From the emergence of ChatGPT to subsequent models like GPT-4 and Llama, these language models have demonstrated remarkable capabilities in natural language processing, generation, understanding and reasoning. Continuing AMD tradition of open-sourcing models and code to help the community advance together, we are excited to release our first series of fully open 1 billion parameter language models, AMD OLMo.

To dive deeper into the three stages of training, and AMD OLMo model results, please reference the full article here: Introducing the First AMD 1B Language Models: AMD OLMo

See how AMD Ryzen™ AI 300 series-based PCs compare to the competition in llama.cpp based applications like LM Studio. 

In the ever-evolving landscape of artificial intelligence, large language models (LLMs) like GPT-4 and Llama have garnered significant attention for their impressive capabilities in natural language processing and generation. However, small language models (SLMs) are emerging as an essential counterpart in the AI model community offering a unique advantage for specific use cases.  AMD is excited to release its very first small language model, AMD-135M with Speculative Decoding.  This work demonstrates the commitment to an open approach to AI which will lead to more inclusive, ethical, and innovative technological progress, helping ensure that its benefits are more widely shared, and its challenges more collaboratively addressed. 

Announcing the upcoming availability of Microsoft Copilot+ PC with the AMD Ryzen™ AI 300 series processor.

Amuse 2.1 Beta is now available for Ryzen™ AI and Radeon™ GPU users and brings with it a whole host of new models and bug fixes!

https://ryzenai.docs.amd.com/en/latest/inst.html#install-npu-drivers AMD just released Ryzen™ AI software 1.2 for developers and ISVs!  Ryzen AI software aims to offer a cohesive environment for developers and ISVs to build AI-enhanced applications while maximizing the performance benefits of the underlying Ryzen AI APU hardware architecture (CPU, iGPU, NPU).   Ryzen AI software continues to champion the open-source community by delivering compatibility with top industry frameworks giving developers freedom to deploy AI inference applications on AMD Ryzen AI powered PCs. The Ryzen AI 1.2 software release highlights new capabilities including additional hardware and model support and new ease of use developer tools. Let's dive into the new features! 

Quick and easy guide on how to get a powerful, completely offline, AI assistant that works on both AMD Ryzen™ AI processors and Radeon™ graphics cards.