~/talk

Keynote: Build Accelerated LLM Applications with Open Source Tools from NVIDIA

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NVIDIA claims 500 open-source projects and says over 100 million RTX PCs exist to run them, then demos concrete tools: RAPIDS accelerator runs existing pandas scripts unmodified on GPU, Megatron-LM scales Transformer training across thousands of GPUs, MRAW is a sparse mixture of experts 47B→13B per token for efficiency, Triton serves models on GPU/CPU with many backends, RAFT provides GPU-accelerated vector search, and NeMo Guardrails enforces safety rules in deployed LLM apps.

AI-written summary · about

  1. 0:00Introduction
  2. 0:47Nvidia has over 500 open source projects
  3. 1:30The LLM Stack
  4. 2:34Open Source Tools
  5. 2:56AI Foundations Models
  6. 4:06Data Processing
  7. 5:18Rapid
  8. 5:37Spark
  9. 5:51Megatron LM
  10. 7:07Nemo Toolkit
  11. 7:41Triton
  12. 8:21Backends
  13. 8:55Rag
  14. 9:26Raft
  15. 10:46Rails
  16. 11:15Outro
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