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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

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

Recently, ERGO Innovation Lab and ECODYNAMICS conducted a study focusing on how insurance-related content is displayed in AI-driven search. The research analyzed over 33,000 AI search results and 600 websites, exploring the preferences of large language models (LLMs) such as ChatGPT when processing this content. The study found that LLMs tend to prioritize content that is easy to read, well-structured, and trustworthy, which closely aligns with traditional SEO strategies.

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.

On June 24, Faraday Future officially announced the launch of the FF AI2.0 intelligent cockpit operating system, which is the most significant cockpit upgrade since the release of the FF91 in 2023. The new system will be deployed to the FF91 2.0 model first through OTA software updates, and it is planned to be extended to the FX series in the future. FF AI2.0 features a complete restructuring of the entire AI architecture, with its biggest highlight being the deep integration with OpenAI. The system deeply integrates large language models (LLMs) into Faraday Future's software and hardware architecture.

Microsoft officially announced the release of a new device-side small language model (SLM), Mu, specifically designed for the settings application in Windows 11 to create an intelligent AI agent. This marks a significant breakthrough in localized AI technology within operating system interactions. As a compact and efficient model, Mu runs through deep optimization on the neural processing unit (NPU), providing users with a low-latency, high-privacy natural language interaction experience. AIbase has compiled the highlights and industry impact of Mu, taking you on a journey to explore its features. Mu: Designed Specifically for Windows Settings

At the theme speech of Huawei Developer Conference HDC2025 held this afternoon, Zhang Ping'an, Executive Director of Huawei and CEO of Huawei Cloud Computing, officially announced the release of PanGu 5.5, marking the comprehensive upgrade of five basic models in natural language processing (NLP), computer vision (CV), multimodal, prediction, and scientific computing.