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Create.",{"title":182,"list":183},"OPENAI",[184,191,199,206],{"id":185,"publish_date":167,"is_original":23,"collection":186,"cover_url":187,"cover_url_1_1":188,"title":189,"summary":190,"author":28},619,"#OpenAI #AI Image Generator #4o #MMM #AR Transformer","article_res/cover/2faffc97fcecf3151552cb0fd3206d89.jpeg","article_res/cover/1133cb4948af44cee2e7fbe79efb69e5.jpeg","The native image function of GPT-4o is officially launched","Introducing 4o Image Generation",{"id":192,"publish_date":193,"is_original":4,"collection":194,"cover_url":195,"cover_url_1_1":196,"title":197,"summary":198,"author":28},434,"2023-07-15","#Anthropic #OpenAI #Google #AI Code Generator #Claude","article_res/cover/e1b6f600a2b9f262a4392684e5f2ce25.jpeg","article_res/cover/6e1772e83f78f9a351ab23d3e414adee.jpeg","Latest Updates on Google Bard /Anthropic Claude2 / ChatGPT Code Interpreter","We want our models to use their programming skills to provide more natural interfaces to the basic functions of our computers.  \n - OpenAI",{"id":200,"publish_date":201,"is_original":4,"collection":146,"cover_url":202,"cover_url_1_1":203,"title":204,"summary":205,"author":28},417,"2023-08-24","article_res/cover/bccf897d50a88b18364e35f7466387e0.jpeg","article_res/cover/2f871085c1073717c1703ae86e18056f.jpeg","The GPT-3.5 Turbo fine-tuning (fine-tuning function) has been released～","Developers can now bring their own data to customize GPT-3.5 Turbo for their use cases.",{"id":207,"publish_date":208,"is_original":4,"collection":209,"cover_url":210,"cover_url_1_1":211,"title":212,"summary":213,"author":28},407,"2023-09-22","#OpenAI #AI Image Generator","article_res/cover/c59005e903d35cfc32346e2756e2728a.jpeg","article_res/cover/ba011d265e6d84b5c8cb6fd6b757b6cc.jpeg","Dall-E 3","DALL·E 3 understands significantly more nuance and detail, allowing you to easily translate your ideas into 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Researcher #AI Science #HKU #Google #AI Agent","article_res/cover/21fadf906067714bb0db31ae13a77c15.jpeg","article_res/cover/2697999a72bd26b22e85f0e92936d3ed.jpeg","AI-Researcher: LLM-driven全自动 scientific research assistant","AI-Researcher: Fully-Automated Scientific Discovery with LLM Agents  \nOpen-Sourced Alternative to Google AI Co-Scientist",{"id":235,"publish_date":236,"is_original":23,"collection":73,"cover_url":237,"cover_url_1_1":238,"title":239,"summary":240,"author":28},463,"2023-05-09","article_res/cover/89800f207723acdb55fc53bf999ebdc9.jpeg","article_res/cover/5764f369b4accd8f83e94aa4c077a175.jpeg","The Smallville sandbox world - A town with 25 virtual residents","Believable proxies of human behavior can empower interactive apps: Immersive environment, Rehearsal space, Prototyping tool",{"title":242,"list":243},"NVIDIA",[],true,{"code":4,"msg":5,"data":246},{"id":247,"publish_date":248,"is_original":23,"collection":249,"articles_id":250,"cover_url":251,"cover_url_1_1":252,"title":253,"summary":254,"author":28,"content":255,"popular":256,"list":321,"category":371,"tag":372},202,"2024-08-07","#Alibaba #Tencent","47M38dH8h9MIkJy41jm5yg","article_res/cover/90569daee53869375d14b41488ca77e2.jpeg","article_res/cover/d7d31ad93a5792845baa325fc4693fe6.jpeg","Alibaba's Tora vs Tencent's MotionCtrl - Controlling object trajectories in generated videos","Motion Controller for Video Generation","\u003Cdiv class=\"rich_media_content js_underline_content\n                       autoTypeSetting24psection\n            \" id=\"js_content\">\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>Compared with Tora from Alibaba and MotionCtrl from Tencent, both are used to generate video for controlling the trajectory of objects.\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: Tencent's MotionCtrl was open-sourced at the end of last year.\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: The relevant paper on Alibaba's Tora was just released last week and has not yet been open-sourced.\u003C/section>\u003C/li>\u003C/ul>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>Effect comparison:\u003C/strong>\u003C/strong>\u003C/strong>\u003C/p>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>Tora\u003C/strong>\u003C/strong>\u003C/p>\u003Csection>\u003Cdiv style=\"height: 508px; background: rgb(0, 0, 0); border-radius: 4px; overflow: hidden; margin-bottom: 12px;\">\u003Cvideo src=\"./assets/17423802989150.6662796697853539.mp4\" poster=\"./assets/17423802989090.3250551794738936.jpeg\" controls=\"\" style=\"width: 100%;height: 100%;\">\u003C/video>\u003C/div>\u003C/section>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>MotionCtrl\u003C/strong>\u003C/strong>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100006211\" data-ratio=\"0.25\" data-s=\"300,640\" data-type=\"gif\" data-w=\"640\" style=\"\" src=\"./assets/17423802990780.7389792523069858.gif\">\u003C/strong>\u003C/strong>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cstrong style='color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;cursor: pointer;background-image: none;background-position: 0% 0%;background-size: auto;background-repeat: no-repeat;background-attachment: scroll;background-origin: padding-box;background-clip: border-box;width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;'>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100006212\" data-ratio=\"0.25\" data-s=\"300,640\" data-type=\"gif\" data-w=\"640\" style=\"\" src=\"./assets/17423802991180.07395468558402563.gif\">\u003C/strong>\u003C/strong>\u003C/strong>\u003C/p>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Method comparison:\u003C/strong>\u003C/p>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">Overview of Tora architecture\u003C/strong>：\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100006210\" data-ratio=\"0.49537037037037035\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423802990840.9584401710320472.png\">\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">To achieve trajectory control in video generation based on DiT, Tora introduces two new modules: the Trajectory Extractor and the Motion-guidance Fuser.\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: Uses a 3D motion VAE to embed trajectory vectors into the same latent space as the video clips, effectively maintaining motion information across consecutive frames. Subsequently, hierarchical motion features are extracted by stacking convolutional layers.\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: Utilizes adaptive normalization layers to seamlessly inject these multi-level motion conditions into the corresponding DiT modules, ensuring that the generated videos consistently follow the defined trajectories.\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">Tora’s method aligns with the scalability of DiT, capable of creating high-resolution, motion-controllable long-duration videos.\u003C/section>\u003C/li>\u003C/ul>\u003Cp style='margin-bottom: 0px;cursor: pointer;color: rgb(0, 0, 0);font-size: 16px;line-height: 1.8em;letter-spacing: normal;text-align: left;padding-top: 8px;padding-bottom: 8px;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;text-wrap: wrap;background-color: rgb(255, 255, 255);'>\u003Cstrong style=\"cursor: pointer;background: none 0% 0% / auto no-repeat scroll padding-box border-box rgba(0, 0, 0, 0);width: auto;height: auto;border-style: none;border-width: 3px;border-color: rgba(0, 0, 0, 0.4);border-radius: 0px;\">MotionCtrl architecture\u003C/strong>：\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100006209\" data-ratio=\"0.4601851851851852\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423802991020.3101864132598462.png\">\u003C/p>\u003Cul style='margin-top: 8px;margin-bottom: 8px;cursor: pointer;padding-left: 25px;color: rgb(0, 0, 0);font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">MotionCtrl extends the denoising U-Net structure of LVDM, adding a Camera Motion Control Module (CMCM) and an Object Motion Control Module (OMCM).\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: Integrates the camera pose sequence (RT) with LVDM’s time transformer, appending RT to the input of the second self-attention module and applying a custom lightweight fully connected layer to extract camera pose features for subsequent processing.\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"cursor: pointer;margin-top: 5px;margin-bottom: 5px;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">: Derives multi-scale features from Trajs using convolutional layers and downsampling, which are spatially integrated into LVDM’s convolutional layers to guide object motion. Furthermore, given a text prompt, LVDM generates video corresponding to the prompt from noise, where background and object motions reflect the specified camera poses and trajectories.\u003C/section>\u003C/li>\u003C/ul>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"3\">\u003C/mp-style-type>\u003C/p>\u003C/div>",[257,265,273,281,289,297,305,313],{"id":258,"title_md5":259,"publish_date":260,"author_md5":261,"is_original":4,"collection":146,"summary_md5":262,"cover_url":263,"cover_url_1_1":264},397,"3f5055bf7b0b21c1374f00e2e98b0454","2023-10-10","bc27fa490c4d0d525bac812fc0793534","a2b9db8d26b79a4b83a7ff91d4410ffb","article_res/cover/1e166a499ebea0d928f41aa4bc3b03a3.jpeg","article_res/cover/61fcb5764abf995d88c0693a254c2d97.jpeg",{"id":266,"title_md5":267,"publish_date":268,"author_md5":261,"is_original":23,"collection":269,"summary_md5":270,"cover_url":271,"cover_url_1_1":272},13,"f3176791f4c6b499f882a6c342c1b8ec","2025-03-08","#Startup #Therapy","7ef7cf04fa489baf8e55e011fa4e3fb4","article_res/cover/5d6fce282c79fc71c6708831b4ab43b7.jpeg","article_res/cover/3b8b2e1ddb63a965674e407ecd5abb5c.jpeg",{"id":274,"title_md5":275,"publish_date":276,"author_md5":261,"is_original":23,"collection":277,"summary_md5":278,"cover_url":279,"cover_url_1_1":280},205,"68cfbb38bc5bc0fe0de8a3449522ba3a","2024-08-03","#Prompt Engineering #Nature #Research","65714bda1cad1a317992c3ad58f0f1fe","article_res/cover/2cc284608cd4a665b016ef5a48a21194.jpeg","article_res/cover/43f34dc7688b84136e5db6fde3662937.jpeg",{"id":282,"title_md5":283,"publish_date":284,"author_md5":261,"is_original":23,"collection":285,"summary_md5":286,"cover_url":287,"cover_url_1_1":288},71,"abab3f4c199d6939a0a31a47028570bb","2025-01-14","#Nvidia #World Foundation Model #Cosmos #Physical AI #Embodied AI","836488ec8e21615f50c0bb6a05f3e04b","article_res/cover/feddf8c832dfb45d28804291f6a42a9e.jpeg","article_res/cover/d6bc2f1186d96b78228c2283a17a3645.jpeg",{"id":290,"title_md5":291,"publish_date":292,"author_md5":261,"is_original":4,"collection":293,"summary_md5":294,"cover_url":295,"cover_url_1_1":296},293,"4bf7706e6bec5625ff61010043ce19bc","2024-04-25","#AI Index Report 2024 #DeepMind","bee0ac9f16a23f15d34b145b7d52e465","article_res/cover/abb722c0344e8169eb00f955f19af5c2.jpeg","article_res/cover/4c4f53f25ac4796997ce8f7d2ba01d5a.jpeg",{"id":298,"title_md5":299,"publish_date":300,"author_md5":301,"is_original":4,"collection":5,"summary_md5":302,"cover_url":303,"cover_url_1_1":304},530,"da032245150c1918d7303b320f288717","2022-05-26","8b3607d0f4181a3cb6ffdccf7185f09b","e2b45dcb478ccd0da9aaaac07a5d7bcc","article_res/cover/e6e7dfa9f1e4212e965aca0b1d570902.jpeg","article_res/cover/b0fa742d86b2b9f3815a0fd1e0cffb08.jpeg",{"id":306,"title_md5":307,"publish_date":308,"author_md5":261,"is_original":23,"collection":309,"summary_md5":310,"cover_url":311,"cover_url_1_1":312},273,"01c9f5a7034c2ed05d294fb640f8643c","2024-05-17","#OpenAI #AGI","cfd1ca994811c9fa46eb66fb4119ad11","article_res/cover/1297ca63669cf0f285f25b76f9095aec.jpeg","article_res/cover/e4deb05321f4f67bf1c4cbf193e86c07.jpeg",{"id":314,"title_md5":315,"publish_date":316,"author_md5":317,"is_original":4,"collection":5,"summary_md5":318,"cover_url":319,"cover_url_1_1":320},607,"4b128adf270889fe696f8a430b6eab5d","2022-03-10","311a46cfdaa3afda544e9285644f70d7","b40c5b282fba23450605baf436289fa1","article_res/cover/45e47d1f2bd97ea83773a8250da38e0e.jpeg","article_res/cover/e68da0da35ad8c14b37e94d666ed5e32.jpeg",{"related":322,"small":356},[323,331,339,340,348],{"id":324,"publish_date":325,"is_original":23,"collection":326,"cover_url":327,"cover_url_1_1":328,"title":329,"summary":330,"author":28},402,"2023-09-30","#Langchain","article_res/cover/c346c32dee9ee54a3af9917281b40c3c.jpeg","article_res/cover/40decc2f760a3389f1514504aee08862.jpeg","Langchain uses Select by Maximal Marginal Relevance (MMR)","This results in a selection of keywords that maximize their diversity within the context of the document.",{"id":332,"publish_date":333,"is_original":4,"collection":334,"cover_url":335,"cover_url_1_1":336,"title":337,"summary":338,"author":28},129,"2024-11-12","#OpenAI #AI Code Generator #LLM #o1","article_res/cover/6654db2a98aadeea109fc3364da389c7.jpeg","article_res/cover/b1e5e6d6a62fb9b205ac09b16c6a25da.jpeg","OnBoard! Podcast Notes - EP 62: OpenAI o1 and the New Paradigm of LLM + Reinforcement Learning (1)","EP 62. A deep interpretation of Google Deepmind and LLM researchers on OpenAI o1 and the new paradigm of LLM + reinforcement learning",{"id":21,"publish_date":22,"is_original":23,"collection":5,"cover_url":24,"cover_url_1_1":25,"title":26,"summary":27,"author":28},{"id":341,"publish_date":342,"is_original":23,"collection":343,"cover_url":344,"cover_url_1_1":345,"title":346,"summary":347,"author":28},207,"2024-08-01","#Buffett","article_res/cover/1aa0c688a3c0c88bdbe206fef021d450.jpeg","article_res/cover/22e9be4de3802e882c2d274130d477d5.jpeg","Buffett's Letter to Shareholders 1963","我不能保证结果，但我可以承诺一个共同的命运。",{"id":349,"publish_date":350,"is_original":23,"collection":351,"cover_url":352,"cover_url_1_1":353,"title":354,"summary":355,"author":28},5,"2025-03-15","#Meta #AI Video Generator","article_res/cover/6d289c936dcfa91f777ce3f553b01382.jpeg","article_res/cover/49d1007ac1b4cc08a3fa19c40455d915.jpeg","Meta's latest released video generation model VideoJAM","VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models",[357,363,369],{"title":10,"list":358},[359,360,361,362],{"id":96,"publish_date":97,"is_original":23,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":28},{"id":104,"publish_date":105,"is_original":23,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":28},{"id":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"title":222,"list":364},[365,366,367,368],{"id":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"id":227,"publish_date":228,"is_original":23,"collection":229,"cover_url":230,"cover_url_1_1":231,"title":232,"summary":233,"author":28},{"id":235,"publish_date":236,"is_original":23,"collection":73,"cover_url":237,"cover_url_1_1":238,"title":239,"summary":240,"author":28},{"title":242,"list":370},[],[8,9,10],[8,12,13,14,9,10,15,16,17,18],["Reactive",245],1754646417190]