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wfalcon

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  1. LitServe: Build custom AI inference engines (github.com)
    1 points 0
  2. Build your own AI model inference engines (github.com)
    1 points 0
  3. 1 points 0
  4. 1 points 0
  5. 1 points 0
  6. 1 points 0
  7. 1 points 0
  8. Agent sandbox: safe, persistent cloud environments for agents (lightning.ai)
    2 points 1
  9. 1 points 0
  10. 1 points 1
  11. Lightning AI hub: Production AI in your cloud in minutes (lightning.ai)
    16 points 0
  12. Deploy dedicated DeepSeek 32B on L40 GPUs ($8/hour) (lightning.ai)
    19 points 6
  13. I'm crazy: I deployed DeepSeek in my company VPC in <24 hours without Kubernetes (lightning.ai)
    5 points 2
  14. Deploy a custom Llama 3 API in 15 lines of code (lightning.ai)
    1 points 0
  15. Thunder – A new compiler for PyTorch that can use many device executors at once (github.com)
    11 points 1
  16. Remote GPU development with VSCode [video] (youtube.com)
    1 points 0
  17. 1 points 0
  18. We scaled minGPT to 45B parameters with PyTorch Lightning (medium.com)
    1 points 0
  19. Reengineering Facebook AI’s deep learning platforms for interoperability (ai.facebook.com)
    1 points 0
  20. Sharded training – How to double the size of PyTorch models (towardsdatascience.com)
    1 points 0
  21. Interview with Facebook AI SWAV first author, (SOTA in Self-supervised learning) (youtube.com)
    1 points 0
  22. 5-Minute deep dive into multi-GPU training (youtube.com)
    1 points 0
  23. Grid AI (from the maker of PyTorch Lightning), launches with an $18.6m Series A (techcrunch.com)
    20 points 4
  24. How to Trick a Neural Network (towardsdatascience.com)
    1 points 0
  25. How PyTorch Lightning became the first ML framework to run CI on TPUs (medium.com)
    3 points 0