Search AI Products and News

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...

Baidu officially released the ERNIE Bot 4.5 series models and made them fully open source. Users can experience this latest open-source technology immediately through ERNIE Bot (https://yiyan.baidu.com). This series includes multiple parameter configurations, such as Mixture of Experts (MoE) models with activated parameters of 47B and 3B, as well as dense models designed with 0.3B parameters, totaling ten different models. In terms of training and inference, the ERNIE 4.5 series models use PaddlePaddle deep learning.

Baidu's WENXIN series large models have recently been open-sourced on its PaddlePaddle platform, including dozens of latest models such as ERNIE-4.5-VL-424B-A47B-Paddle and ERNIE-4.5-300B-A47B-Paddle. Although Baidu has not actively disclosed this open-source initiative, updates on the PaddlePaddle platform show that these actions were concentrated between June 29th and June 30th, marking its latest move. A source within the company confirmed: official

In the context of artificial intelligence becoming increasingly prominent, OpenAI's CEO Sam Altman recently issued an important warning. He pointed out that although his company's chatbot ChatGPT has gained widespread application and recognition globally, the level of user trust in it has surprised him, even caused some concern. In a recent interview, Altman emphasized that users should maintain a cautious attitude towards ChatGPT. Altman at OpenAI

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.

Amid the rapid development of the global artificial intelligence industry, the US AI startup Anthropic officially announced on June 24 that it will open its first Asia-Pacific office in Tokyo this fall. This news undoubtedly injects new vitality into the AI ecosystem in Japan and the entire Asia-Pacific region. Founded in 2020, Anthropic is committed to developing AI technologies centered around human needs, with the philosophy of building safe and controllable AI systems to better serve society through technology. The company is leading in this field.