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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.....

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

On June 26, 2025, ByteDance officially launched its latest image synthesis technology - XVerse, aimed at providing a high-precision multi-subject image generation solution. This innovative technology enables users to independently and precisely control multiple individuals, greatly enhancing the ability to generate personalized and complex scenes. The core of XVerse lies in its unique DiT modulation method, which allows control over the identity and semantic attributes of each subject without affecting the overall latent features of the image. By converting reference images into specific characteristics...

The plan's advancement has triggered dissatisfaction among developers. According to VentureBeat, OpenAI's current API deprecation involves the GPT-4.5 Preview version, which is an intermediary model launched between GPT-4 and GPT-5. Multiple developers have stated that this sudden change has disrupted their development plans, forcing significant adjustments to applications already built based on this API. A developer who wished to remain anonymous commented: We understand the necessity of technological iteration, but the lack of sufficient buffer time in the schedule has brought additional pressure to development teams.

Earth System Models are crucial tools for predicting environmental changes, helping us better prepare for the future. However, these models have extremely high computational demands, limiting their operation at fine enough resolutions. Currently, most models operate at a resolution of approximately 100 kilometers, equivalent to the size of Hawaii, making accurate predictions for specific regions difficult. Nevertheless, for practical applications such as agriculture, water resource planning, and disaster response, city-scale prediction accuracy around 10 kilometers is vital. Therefore, improving the resolution of these models is essential for better protection.

Recently, the Windows version of Sogou Input Method has undergone a major upgrade with the launch of the new AI Wanzai Quick Search function, providing users with a more efficient and convenient office and study experience. The AI Wanzai Quick Search function is characterized by its one-click trigger and fast response. Users no longer need to follow the traditional three-step search process of opening a browser👉🏻search engine👉🏻input content. They can directly type on any spot on the desktop or use the shortcut key Ctrl+Shift+Space”, which can summon the All-Purpose Quick Search” function within 0.5 seconds, allowing for faster information retrieval.

Recently, the DeepSeek team released a technical paper about their latest model, DeepSeek-V3, focusing on the challenges of scaling in large AI model training and related considerations of hardware architecture. This 14-page paper not only summarizes the experiences and lessons learned during the development of V3 by DeepSeek but also provides deep insights for future hardware design. Notably, CEO of DeepSeek, Liang Wenfeng, also participated in writing the paper.