
transcript
show notes
The change makes sense once we examine what NVIDIA learned from nearly dying with NV1, spending years searching for CUDA’s market, and watching researchers discover deep learning on gaming GPUs.
In this episode, we follow that strategy from NV1 and CUDA to NVIDIA’s reported $12.9 billion acquisition of Hugging Face, and ask whether the company has found the most profitable model for open-source AI.
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Attention Span is here to explain the technical and business choices shaping AI.
Links:
NVIDIA FY2026 Form 10-K https://www.sec.gov/Archives/edgar/data/1045810/000104581026000021/nvda-20260125.htm
Interview with Spencer Huang (Nvidia) https://www.youtube.com/watch?v=NEv9EnD7JVU&t=1231
Interview with Clem Delangue (Hugging Face) https://www.youtube.com/watch?v=DfJV722V1WY
NVIDIA Open Source https://opensource.nvidia.com/en-us
NVIDIA on Hugging Face https://huggingface.co/nvidia
Reuters on the reported $12.9B agreement https://www.reuters.com/technology/nvidia-talks-acquire-hugging-face-13-billion-deal-business-insider-reports-2026-08-27/
NVIDIA Open GPU Kernel Modules https://github.com/NVIDIA/open-gpu-kernel-modules
Turing Post’s history of computer vision and AlexNet https://www.turingpost.com/p/cvhistory6
#NVIDIA #OpenSourceAI #HuggingFace #AI #GitHub