OpenAI's paid business segment has reached a significant milestone, with the number of paid commercial users for its ChatGPT Enterprise, Team, and Edu products surpassing one million, marking a substantial increase since April. This reflects strong market demand for generative AI technology. Survey data indicates that enterprise users have achieved notable improvements in productivity, time savings, and innovation, particularly in areas such as research gathering, content drafting and editing, and creative brainstorming. Additionally, user growth has been particularly rapid in international markets such as Germany, Japan, and the United Kingdom.

One of the major highlights of MiniCPM-Llama3-V2.5 is its efficient energy consumption. When running on mobile devices, it requires only 8GB of VRAM in combination with the NVIDIA GeForce RTX 4070 graphics card to achieve rapid inference and extremely fast operation speed. Additionally, the image encoding speed has been improved by 150 times, marking the first realization of system-level multimodal acceleration on the edge. Even more impressive, this model supports over 30 languages, providing robust support for multilingual environments.

Stability AI has officially launched a commercial membership plan to charge for the commercial use of AI models. The membership plan includes three tiers: free, $20 per month, and enterprise version. Stability AI aims to support future research and development through the paid membership plan. Users have expressed confusion about the concept of commercial use, while the company emphasizes its commitment to releasing open-source models.

YuanXiang announced the open-source high-performance large model XVERSE-65B-Chat edition, which is unconditionally free for commercial use. XVERSE-65B ranks first in the national open-source total score in the SuperCLUE comprehensive benchmark assessment for Chinese general large models. XVERSE-65B has stronger understanding, generation, logic, and memory capabilities, capable of handling more diverse and challenging tasks. YuanXiang has open-sourced three large models with 7 billion, 13 billion, and 65 billion parameters, among which XVERSE-65B is one.

Deep Exploration has released a large model of 67B, named DeepSeekLLM67B. This model is fully open-source and can be accessed at chat.deepseek.com. DeepSeekLLM67B has performed well on public evaluation leaderboards, exhibiting excellent reasoning, mathematical, and programming capabilities. DeepSeek has also open-sourced models in two sizes, 7B and 67B, and provided 9 model checkpoints from mid-training.

["Orion Star has released the open source OrionStar-Yi-34B-Chat model based on the Zero One Thousand Things initiative, available for free commercial use.","The model performs excellently on the C-Eval and C-MMLU Chinese evaluation benchmarks.","OrionStar-Yi-34B-Chat is one of the outstanding open source alternatives to ChatGPT.","The model boasts high performance, is fully open-source, and is free for commercial use.","Orion Star is a provider of AI service-oriented solutions."]

Yuanxiang Information Technology announces the launch of multiple high-performance models of the Yuanxiang large model, all open-sourced and free for commercial use. This fills the gap in the Chinese large model open-source ecosystem and provides technical services to help achieve industry-leading capabilities in excellent Chinese creation, logical reasoning, and task execution.

LG CNS has launched DAP GenAI, a generative artificial intelligence platform designed for commercial purposes, offering product recommendations, document summarization, and data-driven reports. The platform allows the selection of large language models such as OpenAI's ChatGPT and Google's PaLM2, and also supports the creation of AI services for product recommendations. DAP GenAI additionally provides two features, AI Prompt and LLMOps, to deliver accurate answers and optimize the LLM scope, tailored for specific businesses.

Yuanxiang open sources the 70 billion parameter general model XVERSE-7B, fully open source and free for commercial use, supporting over 40 languages. XVERSE-7B can run inference on a single consumer-grade GPU with a minimum of only 6GB of VRAM after quantization.