OpenAI and Microsoft are being sued by news agencies for copyright infringement. Multimodal large models are becoming the mainstream trend in the field of large models. OpenAI is reportedly actively negotiating with publishers on AI policies while high-quality dataset copyright issues are receiving attention. CITIC Publishing collaborates with large model companies for language training, and Visual China holds a core advantage in the era of AIGC.

Kuaishou has launched a new AI strategy, developing large models and multimodal large models exceeding a scale of 100 billion. Kuaishou has introduced a text-to-image large model called 'Ke Tu', which can generate detailed and diverse styles of artwork. Kuaishou is accelerating the application of large models in various scenarios, providing more multimodal AI-generated content services. Kuaishou's products possess multiple AI-generated creative capabilities, assisting creators in easily producing content in different styles. Kuaishou is committed to maintaining its leading position in the domestic market to respond to potential upcoming technological breakthroughs.

The Ma Yi team proposed the EMT framework to evaluate the catastrophic forgetting of fine-tuned Multimodal Large Models (MLLMs). Experiments showed that while fine-tuning MLLMs improves performance on the fine-tuning dataset, it also leads to a decline in performance on other datasets. During the fine-tuning process, MLLMs generate hallucinated text related to the fine-tuning dataset, ignoring the original problem. This research provides a framework and benchmarks for future work, but the design and training techniques of the model still need further optimization. The Ma Yi team systematically assessed the issue of catastrophic forgetting in MLLMs for the first time, balancing different capabilities.