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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We thank our partner SIEMENS
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