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Microsoft Edge browser introduces a revolutionary Copilot mode, integrating AI features to deliver a smart browsing experience. Key highlights include: 1) Multi-Tab RAG technology that analyzes content from multiple tabs and automatically summarizes key information; 2) Copilot Vision can analyze screen content in real time and provide voice interaction suggestions; 3) New AI video summaries and intelligent tab grouping features. This mode transforms the browser from a passive tool into an active assistant, significantly improving information processing efficiency, marking the beginning of the AI-driven browsing era.

Doubao App has made a major upgrade in the field of visual reasoning. Its image analysis feature now supports a deep thinking mode, offering users an unprecedented intelligent experience. Users just need to take or upload a picture while in deep thinking mode, and Doubao can quickly perform fine adjustments such as zooming and cropping, and supports image search functionality, enabling users to think and search simultaneously, thereby further improving the accuracy of search results.

Netflix has for the first time extensively applied AI technology in the Argentine science fiction series 'Eternals,' using AI to assist with special effects scenes such as building collapses, significantly increasing production efficiency by ten times. The company's CEO, Reed Hastings, emphasized that AI can enhance creative quality, not just reduce costs. The series includes 2000 visual effects shots, and AI technology allows projects with smaller budgets to achieve high-level special effects. Despite industry controversy over AI (such as the Hollywood strike opposing its use), Netflix continues to explore the application of AI in pre-visualization and shot planning. In addition to special effects,

VLM2Vec-V2, a multimodal embedding framework developed by Salesforce Research and other institutions, breaks through the limitations of traditional models. Based on the Qwen2-VL architecture, this framework innovatively unifies image, video, and visual document retrieval tasks. It adds five new evaluation tasks to expand the MMEB dataset. With key technologies such as dynamic resolution and M-RoPE, it achieved an average score of 58.0 across 78 datasets, leading in performance, especially in video tasks. Although its document retrieval is slightly behind ColPali, it

Anthropic's AI service Claude has formed a deep collaboration with the design platform Canva, launching a text-to-visual design feature. After users upload written content, the system can automatically identify and generate visual works that match the brand style, offering multiple template choices. This feature significantly lowers the design barrier, helping individual bloggers and corporate marketers quickly create professional visual content and enhance their communication effectiveness. This collaboration marks a new breakthrough in AI within the creative field, and it is expected to bring more innovative design experiences in the future.

Yang Jianchao, the head of ByteDance's Visual Large Model team, announced a temporary leave due to family reasons, with Zhou Chang, former technical leader of Alibaba's Tongyi Qianwen, taking over. This personnel change occurred during a period of adjustment in ByteDance's AI department, sparking concerns about the stability of the technical roadmap. Yang Jianchao's work information remains in the internal system, and Zhou Chang will lead the global Seed team to continue research on visual multimodal generation. The company emphasized its continued investment in basic research and hopes that the new leader will bring innovative energy. This change highlights the importance of balancing work and health in the fast-paced tech industry.

ByteDance's visual AI head Yang Jianchao steps down due to workload and family reasons, succeeded by ex-Alibaba M6 lead Zhou Chang. ByteDance reassures stability in Seed visual model team's global R&D.....

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, 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.

The British Film Institute (BFI) recently released a重磅 report indicating that generative AI is quietly reshaping the UK's film, television, and gaming industries. The technology has been widely used backstage to enhance production efficiency and spur new creative approaches and business models. The report shows that generative AI has been utilized to accelerate scriptwriting, character modeling, visual effects creation, and more, significantly saving time and costs. Some works have even employed AI assistance for pre-production conceptualization and editing decisions, empowering creativity while allowing small and medium-sized production companies to benefit.

The AI visual generation platform Higgsfield has launched another major feature - "Speak", bringing unprecedented convenience to digital human content creators. Users only need three steps: select preset actions, upload custom roles, and input voice text, to generate digital human videos with lip-sync and natural actions. The Speak feature supports precise lip-sync technology, ensuring that the character's pronunciation is natural and synchronized, along with 16 built-in scene types covering diversified content styles such as interviews, explanations, advertisements, and short plays, greatly enhancing creation.

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, 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...