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In the field of artificial intelligence, reward models are a critical component for aligning large language models (LLMs) with human feedback, but existing models face the issue of "reward hacking." These models often focus on superficial features, such as the length or format of responses, rather than identifying genuine quality metrics, such as factual accuracy and relevance. The root cause lies in standard training objectives failing to distinguish between spurious associations and true causal drivers present in the training data. This failure leads to fragile reward models (RMs), which generate misaligned policies.

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.

In the long-standing copyright infringement lawsuit filed by The New York Times against OpenAI, the case has made significant progress. According to Ars Technica, the federal judge presiding over the case has authorized The New York Times and its co-plaintiffs, The New York Daily News and the Investigative Reporting Center, to access OpenAI's user logs, including deleted content, to accurately determine the scope of the infringement. The New York Times believes that ChatGPT users may delete their history after bypassing the paywall, and therefore it is necessary to conduct large-scale data collection.

Recently, an AI Excel assistant called Shortcut has sparked heated discussions on social media. It enables users to effortlessly complete Excel tasks without writing complex formulas or VBA code through natural language processing (NLP) technology. The AIbase editorial team has compiled the latest information from social media to provide an in-depth analysis of Shortcut's powerful features and its potential impact on the fields of data processing and financial modeling. Shortcut: An Excel Revolution Driven by Natural Language

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

Zhipu AI officially open-sources its latest general vision model, GLM-4.1V-Thinking, based on the GLM-4V architecture, which introduces a chain-of-thought reasoning mechanism, significantly enhancing its capabilities for complex cognitive tasks. The model supports multimodal inputs such as images, videos, and documents, and excels in diverse scenarios including long video understanding, image question answering, subject problem-solving, text recognition, document interpretation, grounding, GUI Agent, and code generation, covering a wide range of industry application needs. GLM-4.1V-9B-Thinking

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.

Recently, the Qwen VLo multimodal large model was officially released, achieving significant advancements in image content understanding and generation, offering users a brand-new visual creation experience. According to the introduction, Qwen VLo has been comprehensively upgraded based on the advantages of the original Qwen-VL series models. The model not only can accurately understand the "world", but also can perform high-quality re-creation based on understanding, truly achieving the transition from perception to generation. Users can now access Qwen Chat (chat.qwen.ai)

Recently, the innovative AI company Vibemotion launched a revolutionary AI dynamic graphics platform, aiming to allow users to easily create high-quality dynamic videos through simple prompts and material input. Currently, the platform is available by invitation only, attracting widespread global attention from content creators. AIbase provides an in-depth analysis of the platform's key features and its potential impact on the creative industry. One-click generation of dynamic videos, lowering the creation threshold to a new low. The core of Vibemotion's AI dynamic graphics platform lies in its extremely simple user experience.

Google DeepMind recently published a blog post, officially introducing the new Gemini Robotics On-Device localized robot AI model. The model uses a vision-language-action (VLA) architecture, enabling precise control of physical robots without cloud support. The biggest highlight of the new model is that it runs entirely locally on the robot device, achieving low-latency response capabilities. This feature makes it particularly suitable for environments with unstable network connections, such as critical application scenarios like medical facilities.

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.