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The TEN Agent team recently announced that its core models **TEN Voice Activity Detection (VAD)** and **TEN Turn Detection** are now open source, providing powerful technical support for building real-time, multimodal speech AI agents. This move marks a significant advancement in the TEN framework's efforts to promote the democratization and open-source collaboration of speech interaction technology. The following is the latest information compiled by AIbase, offering an in-depth analysis of these two core models.

Recently, Meta Platforms is facing a major decision, possibly abandoning its self-developed Llama AI model and adopting artificial intelligence systems from competitors such as OpenAI and Anthropic. This change reflects a significant adjustment in Meta's open-source AI strategy and also shows the company's dissatisfaction with its own product performance. The turning point occurred at the Llama 4 launch event in April, where the product was presented at Meta's Llama

On June 29, 2025, the Alibaba International AI Team officially released the new multi-modal large model **Ovis-U1**, marking another major breakthrough in the field of multi-modal artificial intelligence. As the latest masterpiece of the Ovis series, Ovis-U1 integrates multi-modal understanding, image generation, and image editing functions, demonstrating powerful cross-modal processing capabilities, providing new possibilities for developers, researchers, and industry applications. This is a detailed report on Ovis-U1 by AIbase. Ovis-U1

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.