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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.

Recently, a new general intelligent agent called MiniMax Agent has been officially launched, aiming to provide efficient solutions for complex long-term tasks and has attracted widespread attention in the industry. MiniMax Agent: A breakthrough work of general intelligent agents - MiniMax Agent is an intelligent agent designed specifically to solve long-term complex tasks, featuring expert-level multi-step planning capabilities, flexible task decomposition mechanisms, and end-to-end execution efficiency. Its design concept is to make AI a reliable teammate.

A comprehensive analysis of MCP Stack's open-source marketing cloud platform functions, detailing its technical advantages in multi-channel integration, AI automated marketing, real-time data analysis, and providing implementation suggestions for enterprise-level marketing automation solutions.

In recent years, the field of artificial intelligence has undergone tremendous changes, especially with large language models (LLMs) making remarkable progress in multi-modal tasks. These models have demonstrated strong potential in their ability to understand and generate language, but most current multi-modal models still adopt auto-regressive (AR) architectures, which limit inference processes to be rather monotonous and lacking flexibility. To address this limitation, a research team from The University of Hong Kong and Huawei Noah's Ark Lab has proposed a brand new model – FUDOKI, aiming to break these constraints. The core innovation of FUDOKI is

A new study led by Apple researchers has poured cold water on the current large reasoning models (LRMs) that are highly anticipated. The research found that when solving complex tasks, reasoning models designed to simulate thinking processes, such as Claude3.7Thinking and Deepseek-R1, not only failed to show advantages but also exhibited serious problems like insufficient reasoning and performance collapse. This study tested four classic logical puzzles: the Tower of Hanoi, Checkers, River Crossing, and Block World. These puzzles allow precise control over the tasks.

The 2025 Meituan Accommodation Ecosystem Partner Conference was recently held in Qingdao, Shandong. Meituan Travel released the first domestic AI tool for hotel merchants - Meituan Ji Bai. Wang Puzhong, CEO of Meituan Core Local Business, stated that Meituan is stimulating new accommodation demand through cross-scenario integration and ecological collaboration, helping hotel merchants unlock greater growth opportunities. Data shows that the number of overnight stays for out-of-town travel accommodations increased by 14% year-over-year, while cross-sector demands such as accommodation + catering surged nearly 87%, accommodation + entertainment grew by 99%, and accommodation + air tickets increased by 36%. During this year's May Day holiday, Meituan...

In today's modern workplace, the importance of IT support cannot be overstated. Whenever employees encounter issues such as locked computers or inaccessible applications, they always hope to contact IT support promptly. However, help desk staff are often busy handling other requests, which may result in employees not receiving timely support. Image source note: The image is generated by AI and provided by Midjourney. Andrei Serban was once the product leader of the application and integration team at Rippling, and he...

Recently, the Natural Language Intelligence Team of the Tongyi Lab officially released and open-sourced VRAG-RL — a multi-modal RAG reasoning framework driven by visual perception. It aims to solve the problem of how AI can retrieve key information and conduct fine-grained reasoning from visual languages such as images, tables, design drafts, etc., in real-world business scenarios. Retrieving and reasoning about key information in complex visual document knowledge bases has always been a major challenge in the AI field. Traditional retrieval-augmented generation (RAG) methods struggle when handling visually rich information because they find it difficult to...

Recently, the MiMo-VL multi-modal model developed by Xiaomi Company has taken over the baton from MiMo-7B, showcasing powerful capabilities in multiple fields. The model significantly outperforms the same-size benchmark multi-modal model Qwen2.5-VL-7B in tasks such as general question answering and understanding inference for images, videos, and language, and its performance in GUI Grounding tasks is comparable to that of specialized models, preparing for the arrival of the Agent era.

Recently, a new evaluation benchmark - RBench-V, specifically designed to test the visual reasoning capabilities of multi-modal large models, was released by research teams from Tsinghua University, Tencent HUNYUAN, Stanford University, and Carnegie Mellon University. The introduction of this benchmark aims to fill the gap in the current evaluation system regarding the model's visual output capabilities, allowing for a more comprehensive understanding of existing model performance. The RBench-V benchmark consists of 803 questions covering multiple fields, including geometry and graph theory, mechanics and electromagnetism, multi-target recognition, and path planning.