Thanks @antonia0912 for the comprehensive summary. Allow me to provide some additional insights:
Based on the input received from participants and the local community, there are several shared areas of interest: 1. There is a growing interest in TVM Unity, particularly due to its adaptability and dynamic shape support. While the MLC-LLM project has laid a solid foundation, the community is seeking a more efficient, extensively documented, and user-friendly codebase. We are actively working towards fulfilling these requirements. 2. Emphasizing a Pythonic programming approach is crucial for ensuring a seamless user experience, regardless of whether individuals are utilizing TVM or other technical frameworks. 3. Heterogeneous computing is rapidly gaining importance, and machine learning compilation plays a pivotal role in this context. --- [Visit Topic](https://discuss.tvm.apache.org/t/recap-meetup-in-beijing-gathering-more-than-140-attendees/15193/3) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/b8e963553819931d2064f3b712c245ab8bdbea345cb626d11ccc0dc686d88eb0).
