Inside AMD’s Open Approach to Industrial AI Innovation. Discover how diverse solutions are reshaping the edge-to-cloud landscape.

In this episode, I sit down with Jens Stapelfeldt, Global AI Lead at AMD's University Program, to explore how AMD is challenging the status quo in AI hardware. We dive into the evolution from proprietary ecosystems to AMD's open, enterprise-ready platforms, discussing what this means for industrial AI applications and decision makers. Jens shares insights on AMD’s broad AI portfolio, from GPUs to edge solutions, and how strategic collaborations are accelerating innovation. We also examine the significance of open-source principles and the impact of diverse hardware options on industrial use cases. Join me as we uncover why AMD positions itself as the most versatile player in the AI space, from edge devices all the way to the cloud.

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AMD

https://www.amd.com/en/technologies/artificial-intelligence

Xilinx

https://www.xilinx.com/applications/artificial-intelligence.html

FPGA (Field Programmable Gate Array)

https://en.wikipedia.org/wiki/Field-programmablegatearray

CUDA (Compute Unified Device Architecture)

https://developer.nvidia.com/cuda-zone

ROCm (Radeon Open Compute)

https://rocm.docs.amd.com/en/latest/

PyTorch

https://pytorch.org/

VLLM

https://vllm.ai/

Lamini

https://www.lamini.ai/

Silo AI

https://silo.ai/

Meta

https://ai.facebook.com/

Microsoft

https://www.microsoft.com/en-us/ai

Oracle

https://www.oracle.com/artificial-intelligence/

Ryzen AI

https://www.amd.com/en/products/ryzen-ai

AMD Instinct

https://www.amd.com/en/products/instinct-accelerators

Vertex (AMD/Xilinx Vertex devices)

https://www.xilinx.com/products/silicon-devices/fpga/virtex.html