Did you know that you can run your very own instance of a GPT based LLM-powered AI chatbot on your RyzenTM  AI PC or RadeonTM 7000 series graphics card ? AI assistants are quickly becoming essential resources to help increase productivity, efficiency or even brainstorm for ideas. Unlike cloud based LLMs, your local AI chat bot works without an internet connection and keeps your conversations on your machine.

GPT based Large Language Models (LLMS) can be helpful AI assistants that maximize your productivity and increase the efficiency of your workflow. Running an AI chatbot on your AMD Ryzen AI powered AI PC is easier than ever but did you know that you could customize it all for yourself? 

GPT-based Large Language Models (LLMs) that are running locally on your AMD Ryzen™ AI PC can help you code with confidence. Not only do they not require an internet connection – but your conversations stay private and on your local machine. You can use them to brainstorm new code ideas or even run existing code by them.

We are happy to announce the formal qualification of additional AMD RDNA™ 3 architecture-based GPUs and the addition of ONNX Runtime with AMD ROCm™ 6.0.

Artificial intelligence has enjoyed a meteoric rise in popularity, from science fiction to real-world use within just a few years. But how does AI work, behind the buzzwords? If you are confused about how terms like “artificial intelligence,” “deep learning,” and “neural net” relate to each other or want to better understand what sets generative AI apart from other types of AI, you’ve come to the right place.

As AI PCs become more popular, there’s a growing need for system monitoring tools that can track the performance of the new NPUs (Neural Processing Units) available on select Ryzen™ 8040 Series mobile processors. An upcoming Windows Task Manager update will add that capability to the Ryzen 8040 Series of mobile processors. 

AMD, through its powerful GPU computing platforms like AMD Instinct™ accelerators, AMD Radeon™ GPUs, and AMD ROCm™ software, offers developers and the AI community alternative solutions for AI training and inferencing. Meanwhile, with the establishment of an open AI software ecosystem, AMD allows more partners to participate in contributing variable AI acceleration solutions, particularly for large AI models on AMD GPU platforms.

Posted on Behalf of Michael Schulte, Sr. Fellow Engineer for AMD 

Recent research has demonstrated that narrow data formats (e.g., formats using 8 bits or less per number) have the potential to greatly improve the performance and energy efficiency of AI training and inference with a negligible impact on accuracy [1][2]. Narrow data formats also help reduce the amount of memory used for AI models, while increasing the effective memory and network bandwidth, since fewer bits of data need to be stored and transmitted.  

The unveiling of ChatGPT and the numerous other large language models (LLMs) announced over the past 12 months has transformed artificial intelligence (AI) from a relatively niche topic to a globe-spanning endeavor that promises to reshape not just what we do with computers, but how we relate to them. It might be easier to make a list of the professions that won’t eventually be impacted by AI rather than trying to list the ones that will be.

Developers occupy a unique position with respect to AI. Software development, like many other professions, is expected to change as AI capabilities become more ubiquitous. Unlike most other vocations, however, developers don’t just interface with AI as end users. They’re also responsible for building new AI applications and integrating AI into existing software. Evaluating how AI is likely to impact software development requires considering its effects on both of these roles.