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Recently, at Baidu's AI Open Day, Wenxin Kaima, Baidu's intelligent code assistant, achieved a major breakthrough. Its standalone AI-native development environment tool, Comate AI IDE, was officially launched. This industry's first multimodal, multi-agent collaborative AI IDE not only introduces the groundbreaking feature of converting design drafts into code with one click, but also provides efficient, intelligent, and secure programming experiences for domestic enterprises and developers.

This article provides a detailed review of the AI-driven social media management tool SchedPilot, analyzing its core functions such as cross-platform publishing and AI comment assistant, helping creators and marketing teams determine whether this tool is worth using. Understand the differentiated advantages and applicable scenarios of SchedPilot compared to other social media management tools.

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

Tomorrow, the 2025FORCE Original Power Conference will be held in grand style. During the conference, the capability upgrade of the BeanPod Large Model family will be revealed. At the same time, the highly anticipated new BeanPod Video Generation Model will also be officially released. It is reported that this new model has multiple excellent features. In terms of multi-camera narration, through efficient model structure design, as well as multimodal positional encoding and multitask unified modeling technology, the model can seamlessly support unique and stable multi-camera expression, making video narration more smooth and natural.

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.

OpenAI announced significant updates to its image generation API (Responses API), adding new features such as streaming transmission, multi-round editing, and integration with Model Context Protocol (MCP) tools and real-time web data search. These new features not only improve the efficiency of image generation but also provide developers with more flexible creation methods, marking a new stage for AI-driven visual content creation. AIbase has compiled the core highlights of this update and its far-reaching impact on the industry.

China National Petroleum Corporation has officially released its latest Kunlun large model, with a parameter count as high as 300 billion. This milestone advancement marks an important step forward for China National Petroleum Corporation in the field of AI. The development of this large model was jointly created by four major giants: China National Petroleum Corporation, China Mobile, Huawei, and iFlytek. It is expected to complete formal filing by August 2024 and become the first approved large model in the energy and chemical industry. It is worth noting that the launch of the Kunlun large model was not accidental. As early as August 28 last year, China National Petroleum Corporation had launched a 33 billion parameter model.

Recently, several leading technology companies in the industry announced their joint investment to build a super-large artificial intelligence (AI) computing center called "Stargate UAE". This project is led by G42 Company of the UAE and jointly developed with international giants such as OpenAI, Oracle, NVIDIA, SoftBank, and Cisco, aiming to promote AI technology innovation and application in the Middle East region and even globally.

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.