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

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. 

Running large language models (LLMs) locally on AMD systems has become more accessible, thanks to Ollama. This guide will focus on the latest Llama 3.2 model, published by Meta on Sep 25th 2024, Meta's Llama 3.2 goes small and multimodal with 1B, 3B, 11B and 90B models. Here’s how you can run these models on various AMD hardware configurations and a step-by-step installation guide for Ollama on both Linux and Windows Operating Systems on Radeon GPUs. 

The journey to fully integrating generative AI technology has been filled with challenges. That's where AMD is stepping in and offering powerful solutions to help businesses unlock the potential of generative AI. 

Calling all AI enthusiasts, data scientists, developers, and high-performance computing professionals! The latest release of AMD ROCm 6.2 is here, packed with innovative enhancements designed to elevate your computational tasks. 

AMD Instinct MI300X accelerator is a strong choice for deploying large language models due to its ability to address cost, performance, and availability challenges. By providing a reliable ,efficient alternative, and a strong ROCm ecosystem AMD helps businesses maintain robust AI operations and achieve optimal performance.

The PyTorch deep-learning framework is a foundational technology for machine learning and artificial intelligence. Discover our perspective on the evolution of this enormously successful open-source project and learn about some of the factors behind the unprecedented success of PyTorch.  

Discover AMD AI solutions with day-0 support for Meta's Llama 3.1, delivering efficiency from cloud to edge

The latest update to ROCm 6.1 introduces numerous capabilities for developers and researchers alike. The new features and fixes provided by ROCm 6.1 are designed to improve the stability and performance of applications, enabling AI and HPC developers to explore the farthest boundaries of what's possible.

AMD has unveiled the latest release of its open software, AMD ROCm™ 6.1.3, marking the next step in its strategy to make ROCm software broadly available across its GPU portfolio, including AMD Radeon™ desktop GPUs. The new release gives developers broader support for Radeon GPUs to run ROCm AI workloads.