gemini-code-assist[bot] commented on PR #120:
URL: https://github.com/apache/tvm-ffi/pull/120#issuecomment-3403333198

   ## Summary of Changes
   
   Hello @tqchen, I'm Gemini Code Assist[^1]! I'm currently reviewing this pull 
request and will post my feedback shortly. In the meantime, here's a summary to 
help you and other reviewers quickly get up to speed!
   
   This pull request focuses on enhancing the clarity and comprehensiveness of 
the `README.md` file. The updates aim to provide a more precise overview of the 
Apache TVM FFI's design philosophy and technical capabilities, particularly by 
detailing its support for DLPack and refining descriptions of its application 
areas and multi-language features.
   
   ### Highlights
   
   * **Clarified Kernel DSLs scope**: The description for 'Kernel DSLs' was 
updated to be more concise, removing 'machine learning systems' for broader 
applicability.
   * **Refined ML Infrastructure description**: The 'ML infrastructure' point 
now explicitly includes 'DSLs' as part of its cross-language support, enhancing 
clarity.
   * **Added DLPack compatibility**: New technical features were added, 
specifically highlighting DLPack-compatible Tensor data ABI for seamless 
framework support.
   * **Introduced compact calling conventions**: A new feature detailing 
compact value and function calling conventions for common machine learning data 
types was added.
   * **Streamlined multi-language support**: The description for 
'Out-of-the-box multi-language support' was rephrased for better clarity, 
changing 'future compatibility to other languages that bind to the ABI' to 
'future path for other languages'.
   * **Removed redundant feature**: The point about 'First class support for 
PyTorch, JAX, and other array libraries' was removed, as its essence is now 
covered by the more specific DLPack compatibility feature.
   
   
   
   
   
   
   
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