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@ai4smartlife

AI4SmartLife

We research: (1) AutonoML, (2) Transparent/Explainable AI, (3) Smart Adaptive Systems, (4) LLMs and MultiModal GenAI, and (5) Smart Apps
README.md

Hi there 👋

Welcome to the collaborative space for research of the AI4SmartLife group.

Our Key Research Themes include:

  • Fundamental Generative AI – Development, Improvement and Retraining
  • Autonomous Machine Learning – Beyond Automated Machine Learning and towards General AI
  • Explainable and Transparent AI – Interacting with and Understanding of Natural and Artificial Complex Adaptive Systems
  • Applications of AI to Real World - Developing AI tools for various real-world projects

This research group is managed by Dr. Thanh Tung KHUAT (Personal site and Google Scholar) who has more than 10 years of experience in researching and developing machine learning algorithms and applications.

Popular repositories Loading

  1. .github .github Public

  2. tiny-training tiny-training Public

    Forked from mit-han-lab/tiny-training

    On-Device Training Under 256KB Memory [NeurIPS'22]

    Python

  3. TinyChatEngine TinyChatEngine Public

    Forked from mit-han-lab/TinyChatEngine

    TinyChatEngine: On-Device LLM Inference Library

    C++

  4. tinyengine tinyengine Public

    Forked from mit-han-lab/tinyengine

    [NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 2…

    C

  5. mllm mllm Public

    Forked from UbiquitousLearning/mllm

    Fast Multimodal LLM on Mobile Devices

    C++

  6. KG-filter KG-filter Public

    TypeScript

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