Against the backdrop of the global generative AI wave in 2022, YuanShi Intelligence (RWKV) completed tens of millions of RMB in angel round financing in December 2023, with investment from Tianji Capital. Following this financing, the company’s valuation doubled, and the funds will be used for team expansion, new architecture development, and product commercialization. The emergence of RWKV presents a strong challenge to the traditional Transformer architecture. With the advancement of large language models (LLMs), although the parameter scale of models is becoming increasingly large, issues like hallucination and accuracy persist.

Yuanshi Intelligence Co., Ltd. in Shenzhen recently announced that it has completed tens of millions of RMB in angel round financing on December 25, 2024, with Tianji Capital as the investor. This financing will accelerate Yuanshi Intelligence's efforts in ecological development, strengthening technological capabilities, and launching AI applications targeting end consumers. Founded in June 2023, Yuanshi Intelligence is a high-tech enterprise focusing on the research and development of large model architectures and AI applications. With its innovative technology and clear development strategy, the company has continuously attracted the favor of the capital markets. Prior to this financing, Yuanshi Intelligence had

Recently, the RWKV team announced the launch of the 'AI Novel Model' specifically designed for Chinese novel creation — the RWKV-6-ChnNovel series. This model demonstrates exceptional performance in novel continuation and expansion, and significantly outperforms the RWKV-World series when used in role-playing tasks.

DeepSeek has open-sourced the RWKV-CLIP model, a visual-language representation learner that combines the strengths of both Transformer and RNN architectures. The model has significantly enhanced performance on vision and language tasks by pre-training on image-text pairs sourced from web data, expanding its dataset with information obtained from various websites.To address the issue of noisy data and improve data quality, the research team introduced a diverse description generation framework.

2024年7月19日, RWKV开源基金会全球开源了其最新最强的稠密纯RNN大语言模型RWKV-6-World14B。此模型在性能测试中体现出与拥有213亿个参数的Llama相当的英文性能，并在100多种语言与代码上表现出显著的多语言优越性，支持全球100种以上的语言和代码。RWKV-6-World14B通过基准测试显示了出众的性能，特别是在Uncheatable Eval评测中超越了Llama213B和Qwen1.514B。优点在于，该模型在训练过程中未受特殊优化困扰，基于从RWKV-4到RWKV-6的架构改进。在当前的评价排名中，该模型不仅展示了强大的实际能力，还能够在包括arXiv论文、新闻、ao3小说和GitHub代码等实时数据上进行评估，表明了其在模型能力和泛化能力上的真实性。提供下载的平台有Hugging Face、ModelScope和WiseModel等，不支持safetensor（.st）格式的Ai00用户则可以下载都在Ai00HF仓库中转换的版本。部署所需显存约为10G至28G。此款模型在多个领域展现出潜力，涉及自然语言处理、文学创作、代码处理、学术建议以及教育指令的自动化等复杂的实际应用，并且所有开源的RWKV模型在指令与对话方面有所提供，但尚无专门针对特定任务的优化训练。