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Only 20% of German employees received AI training, with 70% never trained, risking EU AI Act violations. Bitkom warns firms must ensure AI skills for all workers, as AI boosts efficiency but needs proper use. 14% fear job loss to AI, 1/3 see AI replacing bosses.....

Tencent launched Hunyuan3D-PolyGen, the industry's first art-grade 3D generation model, using self-developed BPT technology to enhance wiring quality and complex object modeling. It generates high-precision geometric models, supports multiple surface types, and boosts gaming pipeline efficiency by 70+%.....

Ziyuan's robot Lingxi X2-N features dual-mode design: wheeled for mobility and legged for obstacle-crossing, carrying 6kg. It adapts to complex terrains with excellent balance and load capacity.....

Tencent open-sourced 'Hunyuan-A13B', an 80B-parameter MoE model with dynamic inference (130B active params). Supports 256K context, trained on 20T tokens. Achieves 87.3% on AIME2024 math, but comparisons show version disparities.....

Bilibili focuses on video podcasting, launching 'Project H' AI tool for audio-to-video conversion. Support includes traffic boost, free recording spaces, and AI tools. The tool converts 1k words to video in 6 mins (target: 3 mins), with positive test feedback.....

B站开源AniSora V3动漫视频生成模型，提升质量与流畅度，支持多种风格。基于CogVideoX-5B/Wan2.1-14B，优化时空掩码，新增华为NPU加速20%。扩展千万片段数据集，增强多任务处理，达到顶尖角色一致性。....

On July 4, 2025, Kunlun Xiwang continued to open-source the second-generation reward model Skywork-Reward-V2 series. This series includes 8 reward models based on different foundation models, with parameter sizes ranging from 600 million to 8 billion. Upon its release, it won all seven major reward model evaluation rankings, becoming a focus in the open-source reward model field. Reward models play a key role in the reinforcement learning from human feedback (RLHF) process. To build the next generation of reward models, Kunlun Xiwang has constructed a dataset containing 40 million

According to KPMG China's recent report, "The First 50 Health Tech Companies," China accounts for more than 70% of the global release volume of medical large models. This data not only demonstrates China's rapid development in the field of intelligent healthcare, but also reflects the wide application of large language models in the healthcare industry. The report points out that about 65% of the currently released medical large models are large language models. These models can process and generate natural language, playing a significant supporting role in the analysis of medical data, patient communication, and scientific research.

A recent report titled "Health Tech 50 - The First Edition" released by KPMG China reveals that China has taken a leading position in the field of medical large models globally. The report indicates that the number of medical large models launched in China accounts for more than 70% of the global total, far surpassing other countries and regions. In terms of model categories, large language models (LLMs) are the most numerous, accounting for nearly 65%. Moreover, the report also highlights the strong growth momentum of the intelligent medical devices market in China. It is expected that by 2025, the scale of the intelligent medical devices market in China will reach 24.23 billion yuan, and it will continue to grow.

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

In the media Q&A session after today's Honor Magic V5 and AI Terminal Ecosystem Launch, Honor CEO Li Jian, CFO Peng Qiuen, and Product Line President Fang Fei had in-depth discussions with the media. During the event, Honor officially announced support for the MCP and A2A protocols, and revealed that it will collaborate deeply with partners such as Alibaba, BYD, and Midea in the fields of intelligent service ecosystem, smart vehicle networking, and smart home. Honor CEO Li Jian emphasized in the conversation that 'openness' is the core philosophy of Honor. He pointed out...

Artificial intelligence once again stirs up the field of drug development! Chai Discovery recently launched a new AI model called Chai-2, which has drawn widespread attention with its breakthrough technology in molecular design. Chai-2 achieves zero-shot antibody design with a success rate of 16%-20%, hundreds of times higher than traditional methods, shortening the drug development cycle from months or even years to just two weeks. Zero-shot antibody design breaks through traditional bottlenecks. Chai-2 is a multi-modal generative AI model developed by Chai Discovery, specifically designed for...

Recently, Meta Platforms is facing a major decision, possibly abandoning its self-developed Llama AI model and adopting artificial intelligence systems from competitors such as OpenAI and Anthropic. This change reflects a significant adjustment in Meta's open-source AI strategy and also shows the company's dissatisfaction with its own product performance. The turning point occurred at the Llama 4 launch event in April, where the product was presented at Meta's Llama