AMD

TL;DR AMD is a significant force in AI hardware, building high-performance GPUs, custom accelerators, and software ecosystems that power training, inference, and large-scale enterprise AI workloads.

AMD is one of the most important companies in the global AI hardware ecosystem, developing high-performance GPUs and specialized accelerators for training and running modern machine learning models. Through its Radeon Instinct line, MI-series accelerators, and the ROCm open software stack, AMD provides a competitive and increasingly influential alternative to NVIDIA in AI compute. As AI demand worldwide surges, AMD’s focus on open tooling, energy-efficient architecture, and enterprise-grade performance has positioned the company as a central pillar of AI infrastructure.

AMD (Advanced Micro Devices) designs and manufactures CPUs, GPUs, and AI accelerators used across data centers, cloud environments, high-performance computing, and edge devices. Its AI strategy centers on delivering scalable compute and open software ecosystems that allow researchers and enterprises to build and deploy advanced AI models at lower cost and with greater flexibility.

MI-Series AI Accelerators

AMD’s MI200 and MI300 accelerator families are designed for large-scale model training and inference.
Key features include:

• massive matrix compute throughput

• high-bandwidth memory (HBM)

• multi-chip module architecture

• energy-efficient design for data centers

The MI300X has become a major competitor in the large-scale LLM training market, capable of supporting massive model sizes thanks to its exceptional memory capacity.

ROCm: Open AI Software Stack

ROCm (Radeon Open Compute) is AMD’s open platform for GPU computing, supporting Python ML frameworks and optimized libraries for AI workloads.
ROCm gives developers:

• PyTorch and TensorFlow compatibility

• open kernels and drivers

• ability to deploy AI models without closed proprietary stacks

This openness is a major differentiator in the AI hardware landscape.

AI in Consumer and Edge Devices

AMD integrates NPUs (neural processing units) into its Ryzen processors to support on-device AI tasks, including generative features, media enhancement, vision, speech, and low-latency inference.
This aligns with the growing trend of edge AI and local inference.

Partnerships and Industry Role

AMD collaborates with hyperscalers, cloud providers, and enterprise vendors to supply compute for AI, HPC, and LLM workloads. As demand for AI accelerators grows exponentially, AMD has become a primary alternative to NVIDIA in large-scale deployments.

• Developed the MI300X, one of the most capable AI accelerators for training and running large language models.

• Built ROCm, a fully open software ecosystem for AI compute, supporting PyTorch and other major frameworks.

• Became a major supplier of GPUs for data centers, high-performance computing, and cloud AI workloads.

• Integrated NPUs into consumer processors to enable efficient on-device AI.

• Advanced multi-chip GPU architecture, pushing the frontier of high-bandwidth, high-capacity compute designs.

• Established strong partnerships across cloud, enterprise, and research institutions for AI model training.

• Provided a critical alternative to NVIDIA’s CUDA ecosystem, expanding hardware choice across the AI industry.