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ByteDance's Seed Team recently released the impressive results of the 2025 full subject Gaokao test: the Dou Bao Seed1.6-Thinking model scored 683 in literature and 648 in science, meeting the admission threshold for Tsinghua and Peking University, and performed outstandingly in domestic and international AI model Gaokao tests. The test used the national new volume one and Shandong Province's independent proposition papers, with Dou Bao competing against five other top domestic and international AI models such as Google Gemini 2.5 Pro, DeepSeek R1, and OpenAI o3.

Recently, Tencent Charity officially launched the "Ask AI" function, which is the first time that large artificial intelligence models have been applied in the charity sector on this platform. This innovative feature allows users to ask questions about various projects and organizations of Tencent Charity, aiming to enhance the interaction and transparency between the public and charitable organizations. The launch of the "Ask AI" function marks another breakthrough for Tencent in the field of charity. Users only need to input their questions simply, and the system can instantly provide relevant information, helping users better understand and participate in various charitable activities. This convenient communication method...

Recently, the domestic embodied intelligent start-up "Lingyu Intelligence" announced the completion of a multimillion-dollar seed round financing. This round was led by InnoAngel Fund, with participation from Shuimu Alumni Seed Fund and Horizon Ventures. The company was co-founded by Jin Ge, an alumnus of the Department of Automation at Tsinghua University, together with his team. It is committed to creating a benchmark for embodied intelligent applications, accelerating the real-world implementation of robots in industrial and home scenarios. Lingyu Intelligence, leveraging its technical accumulation in the field of robot motion control, has built a general solution covering data collection from the human side, actuators on the machine side, to intelligent operation platforms, bridging from level L0 to L4 of intelligence.

A recent paper jointly published by Tsinghua University and Shanghai Jiao Tong University challenges the widely held belief that pure reinforcement learning (RL) enhances large model reasoning capabilities. The research found that models incorporating reinforcement learning performed worse than their original counterparts in certain tasks.

At the recently concluded 18th China Electronic Information Annual Conference, the China Electronics Society announced the winners of the 2024 Science and Technology Awards. Among them, the project "Key Technologies and Applications of Secure and Trusted Dynamic Behavior in the Internet with High-Efficiency Collaboration," jointly developed by Tsinghua University, Beijing Zhongguancun Laboratory, and Ant Group, won the first prize for scientific and technological progress. This achievement not only demonstrates the enormous potential of cutting-edge technology in the field of secure and trustworthy computing, but also provides an effective solution to address the increasingly complex network environment. With the proliferation of the internet, malicious traffic attacks and covert...

Amidst the growing prevalence of artificial intelligence, the collaboration between DeepSeek and Tsinghua University has garnered significant industry attention. DeepSeek, a Chinese startup, is renowned for its breakthroughs in low-cost inference models. This collaboration aims to further reduce the training costs of AI models, thereby enhancing operational efficiency. DeepSeek recently launched a new low-cost inference model that has generated considerable market excitement. To further optimize this model, DeepSeek's research team...

Researchers from DeepSeek and Tsinghua University recently published a new paper exploring scaling methods for reward model inference, seemingly advancing DeepSeek R2. Reinforcement learning is widely used in the large-scale post-training phase of large language models, but faces the challenge of obtaining accurate reward signals for these models. The researchers found that using pointwise generative reward modeling (GRM) improves model adaptability and scalability during inference. To this end, they propose Self-Principle Calibration Tuning (SPCT) learning.

Recently, Professor Zhai Jidong's team from the Institute of High Performance Computing at Tsinghua University, in collaboration with Tsinghua-affiliated innovative enterprise, Qingcheng Extreme Intelligence, announced the open-sourcing of Chitu, a groundbreaking large model inference engine. This innovative technology marks another significant breakthrough for China in the AI field, particularly in inference engine development. A core highlight of the Chitu engine is its ability to natively run FP8 precision models on non-Nvidia Hopper architecture GPUs and various domestic chips.

Recently, research teams from Tsinghua University, Fudan University, and Stanford University jointly released an Agent development framework called 'Eko'. This framework aims to help developers quickly build production-ready 'virtual employees' using simple code and natural language. The Eko framework can take over a user's computer and browser, performing various tedious tasks on behalf of humans. With Eko, users can achieve automated data collection, testing, and file management, among other functionalities. For instance, users can set Eko to automatically gather information from Yahoo Finance.