AI Interior Design

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Collov AI is a cutting-edge technology company located in Silicon Valley, USA, specializing in developing and deploying content generation engines and intelligent base models for visual design based on the next-generation AI technology framework. The company has successfully deployed AI-generated content (AIGC) technology for over 200 home brand enterprises in more than 60 countries, producing over 20 million design renderings. Collov's technology is capable of performing the visual understanding, reasoning, and generation tasks of human designers. Its finely controlled generation technology serves areas such as home decoration and architecture, effectively replacing the manual processes of traditional designers. Financially, Collov has completed two rounds of financing at the ten-million-dollar level, with investors including Matrix Partners, Ameba Capital, and MindWorks Capital, etc, with over $20M USD total investment. To date, it has served over a hundred commercial institutions, and the company currently has a turnover of several million dollars. These achievements mark Collov's leadership position in the AI visual design field and its ongoing drive for industry innovation.

Home Decoration & Vertical AI: The Path of AI Visual Design

Collov AI Design Path

  • (Home Decoration & Vertical Design World Model) Understanding Encoder -> Transformer
    The understanding of the visual world leads to qualitative improvements in subsequent generation flaws, aesthetics, space, coherence, and other metrics.
  • (Collov have) Generative Decoder
    Based on Collov's universal, vertical, symbiotic datasets, continuously train and optimize the base generation model to ensure generated content meets commercial needs with high aesthetic quality and controllability.
  • (Collov have) Generative Decoder Post-training -> Finetune + Control
    Based on commercial needs, modify and train the base model to achieve controllability in structure, physical integration, style, etc.



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  • Name:
    Xiao Zhang
  • Type of entry:
    Team members:
    • Casey Zhou
    • Mark Tong
  • Patent status: