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Recently, a speech synthesis model called Qwen-TTS has made new progress, with its latest version update completed through the Qwen API, bringing users a richer speech synthesis experience. In this update, Qwen-TTS added support for three Chinese dialects: Beijing dialect, Shanghai dialect, and Sichuan dialect, further expanding its application scenarios. The model is trained on a large-scale corpus of more than 3 million hours, achieving naturalness and expressiveness at a human level. Qwen-TTS can not only accurately

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, an open-source RAG (Retrieval-Augmented Generation) engine called RAGFlow has attracted significant attention in the industry. This enterprise-level AI tool, based on deep document understanding, provides companies with a brand-new solution for processing complex documents and achieving precise question answering through its powerful multimodal data processing capabilities and efficient workflows. RAGFlow: The Pioneer of Deep Document Understanding RAGFlow is a fully open-source RAG engine that focuses on deep document understanding, aiming to help businesses and individuals extract valuable information from massive amounts of unstructured data.

The Meta AI research team has made another breakthrough in the artificial intelligence field, officially releasing the new video understanding model V-JEPA2 (Video Joint Embedding Predictive Architecture2) on June 11, 2025. Led by Meta's chief AI scientist Yann LeCun, this model has opened up new possibilities in video understanding and physical world modeling with its innovative self-supervised learning technology and zero-shot robot control capabilities.

Global renowned open-source AI platform Hugging Face recently released the open-weight model contributor ranking. Chinese teams Qwen and DeepSeek successfully ranked in the top 15, showcasing China's technical strength and influence in the global open-source AI field. This ranking honors the teams that provide high-quality model weights to the open-source community, with their models widely applied in academic and industrial innovation. The Qwen team supported by Alibaba Cloud Intelligence Group has gained favor from the community due to the excellent performance of its Qwen3 series models in tasks such as instruction following and code generation.

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

In the recent Fiction.Live benchmark test, Gemini2.5Pro performed excellently in understanding and reproducing complex stories and backgrounds, leading ahead of OpenAI's o3 model. This test goes far beyond traditional "needle-in-a-haystack" tasks, focusing on a model's ability to handle deep semantics and context-dependent information within large contexts. According to the test data, when the context window length reaches 192,000 tokens (approximately 144,000 words), the performance of the o3 model drops sharply, while

Recently, the Beijing Academy of Artificial Intelligence (BAEI), in collaboration with Shanghai Jiao Tong University and other institutions, officially released a new generation of ultra-long video understanding model - Video-XL-2. The introduction of this model represents a significant breakthrough in the field of open-source ultra-long video understanding technology, injecting new vitality into the development of multimodal large models for understanding long video content. In terms of technical architecture, Video-XL-2 mainly consists of three core components: a visual encoder, the Dynamic Token Synthesis (DTS) module, and a large language model (LLM). The model adopts

Recently, Hume AI officially released its third-generation voice interaction model, EVI3. This new voice AI has drawn extensive attention in the industry due to its outstanding emotion understanding capabilities and personalized interaction experience. EVI3 can accurately identify emotions in users' voices and generate specific styles of sound and personality based on user preferences, marking a significant breakthrough in the field of emotional interaction and natural communication. Below is the latest information and in-depth analysis about EVI3 from AIbase. Experience it at: https://demo.

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.

According to Reuters, citing three sources familiar with the matter, Nvidia will launch a new AI chip designed specifically for the Chinese market in June. The pricing is expected to be between $6,500 and $8,000, which is significantly lower than the current H20 series priced around $10,000 to $12,000. The new chip is based on the latest Blackwell architecture and adopts the RTX Pro6000D design framework. To bypass US export restrictions on advanced chips to China, this GPU deliberately avoids TSMC's advanced packaging processes and instead uses standard GDDR7.