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Google announced the global launch of its latest video generation model, Veo3. This long-anticipated release has generated great excitement among users, as Veo3 is now available to Gemini users in over 159 countries, offering a new video creation experience. The key feature of the Veo3 video generation model is its ability to generate videos up to eight seconds long based on simple text prompts. According to Google, this technology is designed for creative users, especially those on social media who increasingly demand short-form content.

Large Language Models (LLMs) have achieved significant progress in complex reasoning tasks by combining task prompts with large-scale reinforcement learning (RL), as demonstrated by models like Deepseek-R1-Zero, which directly apply reinforcement learning to base models, showcasing strong reasoning capabilities. However, this success is difficult to replicate across different base model families, especially within the Llama series. This raises a core question: what factors lead to inconsistent performance of different base models during reinforcement learning? How does reinforcement learning perform in

Recently, a speech synthesis model called Qwen-TTS has made new progress, with its latest version update completed through the Qwen API, bringing users a richer speech synthesis experience. In this update, Qwen-TTS added support for three Chinese dialects: Beijing dialect, Shanghai dialect, and Sichuan dialect, further expanding its application scenarios. The model is trained on a large-scale corpus of more than 3 million hours, achieving naturalness and expressiveness at a human level. Qwen-TTS can not only accurately

Welcome to the AIbase [AI Daily Report] section! Spend three minutes a day to learn about the latest AI events, helping you understand AI industry trends and innovative AI product applications. For more AI news, visit: https://www.aibase.com/zh1. Baidu officially releases the WENXIN Large Model 4.5 series and fully opens it to the public, featuring ten new models with various parameter configurations. These models are trained and inferred using the PaddlePaddle framework, achieving a FLOPs utilization rate of 47%, and perform well in multi-modal text tasks.

On June 30, Huawei officially announced the open sourcing of the Pangu dense model with 7 billion parameters, the PanguPro MoE model with 72 billion parameters, and the model inference technology based on Ascend. This open-source initiative is a key step in Huawei's strategy to build an Ascend ecosystem, aiming to promote research and innovation in large model technology, accelerate the application of artificial intelligence across industries, and create value.

Recently, the Qwen VLo multimodal large model was officially released, achieving significant advancements in image content understanding and generation, offering users a brand-new visual creation experience. According to the introduction, Qwen VLo has been comprehensively upgraded based on the advantages of the original Qwen-VL series models. The model not only can accurately understand the "world", but also can perform high-quality re-creation based on understanding, truly achieving the transition from perception to generation. Users can now access Qwen Chat (chat.qwen.ai)

Welcome to AIbase's [AI Daily Report]! Spend three minutes every day to learn about the latest AI news, helping you understand AI industry trends and innovative AI product applications. For more AI updates, visit: https://www.aibase.com/zh1. Tencent open-sources the lightweight Huyuan-A13B model, which can be deployed with just one mid-range GPU card. Tencent has released a new member of the Huyuan large model family, the Huyuan-A13B model, which uses a mixture of experts (MoE) architecture, with a total parameter scale of 80 billion and an activated parameter count of 13 billion, large

Tencent officially launched and open-sourced a new member of the Hypermix large model family - the Hypermix-A13B model. The model adopts an expert mixture (MoE) architecture, with a total parameter scale of 80 billion and an activated parameter count of 13 billion. It maintains the performance of top-tier open-source models while significantly reducing inference latency and computational costs, providing a more cost-effective AI solution for individual developers and small and medium-sized enterprises.

OpenAI announced the official opening of API access to its deep research models, providing developers with a powerful set of tools including automatic web search, data analysis, MCP (Model Communication Protocol), and code execution. The models opened include the deep research versions of o3 and o4-mini, which have already been used in ChatGPT. Now, developers can directly call these models via API. These models are particularly suitable for complex tasks that require obtaining the latest information and performing advanced reasoning. In terms of function expansion, o3,