同时核心是你可以添加任意的上下文，上传文件也行，选择你的 Notion 指定数据库也可以，还能 添加多个 Notion 数据库。 Notion 应该是传统互联网工具产品 AI 转型最成功的一个。 昨晚，他们更新了 Notion 3.0，现在的 Notion 可以看作一个你有所有上下文的通用 Agent 产品， 而且你可以在这里用所有顶尖模型完成任务。 我早上研究了一下，发现这玩意会相当强大，所以顺便写一篇内容介绍一下现在的 Notion AI 能 力。 首先是基础的 AI 能力，你可以在Notion左侧的 Notion AI 看到一个跟其他 AI 产品差不多的页面。 支持选择所有现在的顶尖模型，比如 GPT-5 或者 Claude 4.1。 如果你觉得上面给 AI 的上下文还不够的话你还可以选择通过 Notion 链接很多其他软件获取上下 文，比如海外常用的 Gmail、开发协作的 Github 和 Linear 等。 而且现在的 Notion AI 不知可以回答问题和写作也可以帮你生成和修改你需要的数据库表格格式， 比如我这里查询了一下未打款内容，他在查完之后还问我要不要帮我创建一个逾期的视图。 比如我这里 ...

Core Viewpoint - Lovart has rapidly integrated the Seedream 4.0 model, offering significant promotional activities to attract users, emphasizing that providing benefits to users is an effective marketing strategy [2][3]. Group 1: Product Features and Innovations - Lovart and Seedream 4.0 allow users to convert long texts and documents into visually appealing images suitable for platforms like Xiaohongshu, enhancing content creation efficiency [3][6]. - The Seedream 4.0 model can generate modern, flat design infographics based on academic papers, providing a structured visual representation of the content [9][10]. - Users can adjust prompts to optimize the output, with Lovart's system automatically refining requests to improve results [12][14]. Group 2: User Experience and Customization - The Magic Canvas feature enables users to provide feedback directly on generated images, allowing for real-time modifications and improvements [16][18]. - Users can create visually consistent and engaging content quickly, significantly reducing the time required for traditional design processes [21][22]. Group 3: Educational Applications - Lovart's capabilities extend to generating educational materials, such as visual representations of classical Chinese literature, aiding in student comprehension [24][25]. - The platform can also compile information on historical figures, like Su Shi, into a series of informative cards, showcasing key life events and contributions [29][32]. Group 4: Creative Content Generation - Lovart allows for the creation of themed content, such as transforming scientific biographies into a fantasy narrative style, appealing to diverse audience interests [34][36]. - The platform supports various content styles and themes, enabling users to mix and match elements for unique outputs [38][39].

Core Viewpoint - The article discusses the launch of Seedream 4.0 by Huoshan Engine, a versatile image creation model that supports image generation, continuous image editing, and multi-image referencing, highlighting its capabilities for high-quality aesthetic output and user customization [2][3]. Group 1: Product Features - Seedream 4.0 offers advanced image generation capabilities, including the ability to produce 4K images, excellent aesthetic performance, and precise editing features, making it a top-tier model for Chinese users [2][3]. - The model allows users to customize generation ratios and supports seamless integration into the Huoshan Engine MaaS platform for enterprise clients [3]. - Personal users can access Seedream 4.0 through the Doubao and Jimeng apps, with the 4K version available for public use [3]. Group 2: Use Cases and Applications - Users can utilize Seedream 4.0 for various creative applications, such as generating personalized avatars, creating thematic mouse pads, and transforming photos into artistic representations [51][56]. - The model can generate continuous storyboard images for characters, maintaining facial identity across multiple frames, which is beneficial for content creators [22][27]. - It allows for the transformation of any photo into a glass-like icon, enhancing social media sharing [46]. Group 3: User Interaction and Customization - Users can input simple prompts to modify images, such as adjusting lighting effects or applying filters, showcasing the model's intuitive design [5][8]. - The model can respond to detailed makeup and hairstyle prompts, demonstrating its capability to handle intricate requests [11][17]. - Users can create diary-style images by uploading photos and providing context, allowing for personalized storytelling [73][76]. Group 4: Market Potential and Trends - The introduction of Seedream 4.0 is expected to lower the barriers for creating beauty applications, enabling users to explore new business opportunities [20]. - The model's ability to generate high-quality images and videos has the potential to disrupt the AI PPT industry, offering a new way to create visually appealing presentations [45][107]. - The article emphasizes the shift towards using everyday fragments of life as creative inputs, suggesting a new paradigm in content creation where personal experiences can be transformed into marketable products [109][110].

Core Insights - The article discusses the rising popularity of Nano Banana, highlighting its widespread use and the innovative applications being explored by users [1][3]. Group 1: AI Applications - The article introduces the concept of creating AI-generated dance videos using calligraphy as a reference, showcasing the creative potential of Nano Banana [4][10]. - It details the process of converting architectural floor plans into 3D renderings, emphasizing the versatility of Nano Banana in architectural visualization [17][20]. - The article explains how to generate exaggerated visual effects for video thumbnails, enhancing engagement through creative imagery [33][35]. Group 2: User Engagement and Community - The article notes the significant increase in user engagement across platforms like Twitter, Xiaohongshu, and Douyin, indicating a growing community around Nano Banana [1]. - It highlights the collaborative nature of the community, where users share tutorials and innovative uses of Nano Banana, fostering a culture of creativity and experimentation [1][3]. Group 3: Technical Guidance - The article provides detailed instructions on generating videos using specific AI models, emphasizing the importance of prompt engineering for desired outcomes [12][16]. - It outlines the steps for creating 3D models from 2D images, showcasing the technical capabilities of Nano Banana in transforming visual content [24][30]. - The article discusses the integration of various software tools to enhance the functionality of Nano Banana, indicating a trend towards multi-software workflows in creative projects [28][32].

Core Viewpoint - The article discusses a method to solve the issue of aspect ratio control in images generated by Nano Banana, allowing users to modify existing images to fit desired proportions [2][4][12]. Group 1: Problem Identification - Users of Nano Banana face two main issues: low resolution of generated images and uncontrollable aspect ratios, making it difficult to use images in production [2][4]. - The output image's aspect ratio is determined by one of the input images, leading to inconsistency when multiple images are used [4][12]. Group 2: Proposed Solution - The solution involves using a reference image to control the aspect ratio of the generated images, allowing for modifications to both new and existing images [4][8]. - Users need two images: the original generated image and a reference image that defines the desired aspect ratio [6][16]. Group 3: Implementation Steps - The process requires inputting a specific prompt to instruct Nano Banana to redraw the content of the original image onto the reference image while maintaining the aspect ratio [13][15]. - The order of images is crucial: the image to be modified should be first, followed by the reference image to avoid errors [16]. Group 4: Additional Insights - The article mentions that using the Gemini2.5 Pro model in the Gemini APP yields better results compared to AI Studio when calling Nano Banana [15]. - A link is provided for users to download various aspect ratio templates for convenience [18].

Core Viewpoint - The article discusses the capabilities and applications of the Nano Banana model integrated with Lovart, highlighting its potential in creative design and automation tasks. Group 1: Nano Banana and Lovart Integration - Nano Banana was quickly integrated into Lovart, showcasing its adaptability and speed in deployment [1] - A weekend free trial was initiated for users to explore Nano Banana without consuming any credits [1] - Users are advised to select only the Nano Banana model to avoid unintended credit deductions [2] Group 2: Functional Capabilities - Nano Banana can interpret maps and recognize landmarks, enhancing its utility in design tasks [3] - Users can interact with Lovart to generate images based on specific prompts, demonstrating the model's ability to create detailed visuals [4][6] - The model allows for the replacement and generation of multiple objects in a single image while maintaining consistency [8] Group 3: Practical Applications - Users can create realistic home design visuals by simply sketching furniture placements and using Nano Banana to generate the final image [10] - The integration of Nano Banana with other models in Lovart enables the creation of complex video content from simple prompts [12] - Users can generate cooking recipe images and videos by inputting images of ingredients, showcasing the model's versatility in culinary applications [21][30] Group 4: Creative Expression - The article encourages users to utilize Nano Banana for creative projects they may have previously abandoned due to design challenges [30] - It emphasizes the importance of creative expression over mere tool usage, suggesting that technology should enhance human creativity rather than replace it [31][32]

Core Viewpoint - The article introduces the image editing model Nano Banana, highlighting its capabilities to simplify complex editing tasks and outperform traditional software like Adobe, making it accessible for users to enhance their photos effortlessly [2][4]. Group 1: Usage of Nano Banana - Users are encouraged to utilize Nano Banana on Google AI Studio for free and efficient image editing [4]. - The model allows for various editing tasks such as acne removal, body slimming, and outfit showcasing, transforming ordinary photos into high-quality images [5][15]. - Users can upload multiple images and input specific editing requests, with the model supporting continuous editing, although performance may decline after several iterations [7][9]. Group 2: Features and Capabilities - The upgraded model significantly enhances facial ID consistency, allowing for natural language commands to modify images, such as slimming faces or improving skin quality [19]. - Users can create flat lay photographs to showcase clothing items and try on outfits shared by other influencers with high accuracy [22][25]. - The model supports advanced editing techniques, including marking areas for modification and generating interactive images based on user-drawn sketches [28][34]. Group 3: Applications in Various Fields - Nano Banana can generate stickers from photos, providing a fun and creative way to produce personalized gifts [40]. - The model can add AR descriptions to images of famous landmarks, enhancing the educational experience [43]. - It shows promise in e-commerce by improving product image modifications, addressing issues like proportion discrepancies [46]. Group 4: Overall Impact - The article concludes that Nano Banana's capabilities can revolutionize various industries, including e-commerce, education, and media, by meeting the growing demand for visual expression [50].

Core Viewpoint - The article provides a tutorial on how to use the Nano Banana model in LM Arena for creating character figures and enhancing images, particularly focusing on the game "Black Myth: Zhong Kui" [1][3]. Group 1: Tutorial Steps - Users need to access LM Arena and select the image modality to trigger the image model [3]. - After uploading an image, users can input prompt words to modify the image, such as adding a character riding a tiger and including game-related elements [3][4]. - The platform generates two images at a time, allowing users to select the best result, which may require multiple attempts to find the Nano Banana model [7]. Group 2: Enhancements and Effects - The article discusses transforming the generated images into videos to enhance visual appeal, using specific prompt words to create dynamic effects [10]. - A detailed description of the visual transformation process is provided, illustrating how the character figure transitions from a physical model to a CG representation [10]. - The final output can be further edited with music and original CG footage to create a more engaging experience [12]. Group 3: Results and Engagement - The article encourages users to experiment with the tutorial and share their results, fostering community engagement [13].

Core Viewpoint - The article emphasizes the capabilities of the Keling 2.1 model in generating first and last frame videos, particularly focusing on image generation and prompt creation, which are crucial for producing high-quality content [1][7]. Summary by Sections Image Acquisition Methods - Three primary methods for obtaining suitable images for first and last frame video generation are discussed: same prompt card drawing, modified prompt card drawing, and using image editing models like FLUX Kontext [8]. - Using the same prompt for card drawing often yields highly similar images, making it ideal for showcase-type videos [9]. - Modifying prompt card drawing allows for the movement or disappearance of main characters or objects by changing parts of the prompt after generating the initial image [12]. - Image editing models enable precise control over images through natural language, allowing for various effects to be added [15]. Prompt Generation for First and Last Frame Videos - The prompts used for generating first and last frame videos are entirely AI-generated, leveraging the enhanced understanding and adherence capabilities of the Keling 2.1 model [27]. - A structured approach to prompt creation is outlined, focusing on analyzing differences between the starting and ending frames and selecting appropriate transition strategies [28][29]. - The article details how to construct specific changes in the visuals, including object transformations, environmental changes, and stylistic variations [37]. Value Creation and Narrative Enhancement - The article suggests that the true value lies in solidifying the process into a template for future projects, enhancing productivity significantly [39]. - It emphasizes the importance of elevating effects into narratives, transforming the approach from mere visual transitions to storytelling, which can significantly increase the perceived value of the videos produced [41].

Core Viewpoint - The article highlights the independence and enhanced functionality of Feishu's multi-dimensional table, which can now be used without downloading or registering for Feishu, allowing for seamless integration with other IM systems and enabling businesses to create customized systems with zero coding [1][4][6]. Group 1: Product Independence and Accessibility - Feishu's multi-dimensional table can now function as a standalone product, retaining all its features while eliminating dependencies on other modules within Feishu [4][6]. - Users can access the multi-dimensional table directly through a browser, making it easier for businesses to adopt the tool without the need for additional software [4][21]. Group 2: Key Advantages - Users can enjoy professional-grade features of the multi-dimensional table for free without needing to become Feishu users, which lowers digital transformation costs for enterprises [8]. - The integration of AI capabilities into the multi-dimensional table allows users to leverage AI functionalities with minimal effort, making it accessible to those familiar with spreadsheets [11]. - The tool offers advanced data analysis capabilities comparable to professional BI software, enabling users to create dashboards effortlessly by simply dragging data into the interface [13]. - With a high-performance database foundation, the multi-dimensional table can support complex core business operations, ensuring stability and scalability [15]. - The platform allows users from various industries to build their own business tools without programming knowledge, facilitating innovation and efficiency [17]. Group 3: Real-World Applications - The multi-dimensional table has been successfully implemented in well-known companies such as Aeon, Recomm, Haidilao, Yadea, and Ivfory X Coty, demonstrating its capability to handle large data volumes and complex business logic [17]. - For instance, Aeon replaced a self-developed employee management system worth hundreds of millions with the multi-dimensional table, streamlining management processes [17].