[{"data":1,"prerenderedAt":206},["ShallowReactive",2],{"DlFXI4Eibt_Bn9lrEZz1TYbHCWFZj3IvqwHQSEW-Exc":3,"zQpjO3g02FovUZpEJ8k_bq_R6FU1Cq0aQQBCKiGILcA":194},{"code":4,"msg":5,"data":6},0,"",{"category":7,"tag":11,"hot":39,"new":78,"banner":118,"data":143,"cache":193},[8,9,10],"Agent","OpenAI","LLM",[12,14,17,20,23,25,27,30,33,36],{"title":8,"total":13},39,{"title":15,"total":16},"Google",44,{"title":18,"total":19},"Nvidia",13,{"title":21,"total":22},"Claude",11,{"title":9,"total":24},35,{"title":10,"total":26},85,{"title":28,"total":29},"DeepSeek",9,{"title":31,"total":32},"OCR",1,{"title":34,"total":35},"Chat",7,{"title":37,"total":38},"Generator",116,[40,48,55,64,71],{"id":41,"publish_date":42,"is_original":4,"collection":5,"cover_url":43,"cover_url_1_1":44,"title":45,"summary":46,"author":47},557,"2022-04-29","article_res/cover/7a9b1375ed9bb298154981bae42b794d.jpeg","article_res/cover/afa281dd52bc0454e6735daa8e6b0706.jpeg","Translation and summary of Messari Report [2.8 Kristin Smith, Blockchain Association and Katie Haun, a16z]","We need unity and speed right now.","Translation",{"id":49,"publish_date":50,"is_original":4,"collection":5,"cover_url":51,"cover_url_1_1":52,"title":53,"summary":54,"author":47},531,"2022-05-25","article_res/cover/e8362057f8fa189594c60afdfaaeb6e5.jpeg","article_res/cover/8ea08d0d6fa7eee6b57ed4ec61b61ad6.jpeg","Decentralized Society: Finding Web3’s Soul / Decentralized Society: Finding the Soul of Web3 -7","Decentralization through Pluralism When analyzing ecosystems, it's desirable to measure how decentralized it is.",{"id":56,"publish_date":57,"is_original":32,"collection":58,"cover_url":59,"cover_url_1_1":60,"title":61,"summary":62,"author":63},127,"2024-11-14","#Google #AI Game #World Model #AI Story","article_res/cover/0233a875b7ec2debf59779e311547569.jpeg","article_res/cover/6ffddb6ae4914b3c699493311aa9f198.jpeg","Google Launches \"Unbounded\": A Generative Infinite Character Life Simulation Game","Unbounded: A Generative Infinite Game of Character Life Simulation","Renee's Entrepreneurial Journey",{"id":13,"publish_date":65,"is_original":32,"collection":66,"cover_url":67,"cover_url_1_1":68,"title":69,"summary":70,"author":63},"2025-02-14","#Deep Dive into LLMs #Andrej Karpathy #LLM #Tool Use #Hallucination","article_res/cover/11e858ad6b74dfa80f923d549b62855c.jpeg","article_res/cover/615e1b320f1fc163edc1d2d154a6de33.jpeg","Andrej Karpathy's in-depth explanation of LLM (Part 4): Hallucinations","hallucinations, tool use, knowledge/working memory",{"id":72,"publish_date":73,"is_original":4,"collection":5,"cover_url":74,"cover_url_1_1":75,"title":76,"summary":77,"author":47},579,"2022-04-07","article_res/cover/39387376ba28447af1eb40576b9df215.jpeg","article_res/cover/02727ede8551ed49901d0abe6d6305b7.jpeg","Messari Report Translation and Summary 【1-7 Surviving the Winter】","I’d be more cautious here: 10 year and 10 hour thinking only.",[79,87,95,103,111],{"id":80,"publish_date":81,"is_original":32,"collection":82,"cover_url":83,"cover_url_1_1":84,"title":85,"summary":86,"author":63},627,"2025-03-20","#AI Avatar #AI Video Generation","article_res/cover/d95481358f73924989f8c4ee9c75d1c8.jpeg","article_res/cover/b74bc0fab01f8b6a6aa87696c0c3ed8b.jpeg","DisPose: Generating Animated Videos by Driving Video with Reference Images","DisPose is a controllable human image animation method that enhances video generation.",{"id":88,"publish_date":89,"is_original":32,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":63},626,"2025-03-21","#Deep Dive into LLMs #LLM #RL #Andrej Karpathy #AlphaGo","article_res/cover/446553a5c8f8f2f07d97b20eaee84e56.jpeg","article_res/cover/e6c2823409c9b34624064b9acbaca6f1.jpeg","AlphaGo and the Power of Reinforcement Learning - Andrej Karpathy's Deep Dive on LLMs (Part 9)","Simply learning from humans will never surpass human capabilities.",{"id":96,"publish_date":97,"is_original":32,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":63},625,"2025-03-22","#Deep Dive into LLMs #LLM #RL #RLHF #Andrej Karpathy","article_res/cover/8da81d38b1e5cf558a164710fd8a5389.jpeg","article_res/cover/96f028d76c362a99a0dd56389e8f7a9b.jpeg","Reinforcement Learning from Human Feedback (RLHF) - Andrej Karpathy's Deep Dive on LLMs (Part 10)","Fine-Tuning Language Models from Human Preferences",{"id":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},624,"2025-03-23","#Deep Dive into LLMs #LLM #Andrej Karpathy #AI Agent #MMM","article_res/cover/a5e7c3d48bb09109684d6513287c661d.jpeg","article_res/cover/d3f22b7c0ab8d82fd2da457a299e0773.jpeg","The Future of Large Language Models - Andrej Karpathy's In-Depth Explanation of LLM (Part 11)","preview of things to come",{"id":112,"publish_date":105,"is_original":32,"collection":113,"cover_url":114,"cover_url_1_1":115,"title":116,"summary":117,"author":63},623,"#Google #Voe #AI Video Generation","article_res/cover/c44062fea0f336c2b96b3928292392c2.jpeg","article_res/cover/a041041c69092ad3db191c5bf3ff981b.jpeg","Trial of Google's video generation model VOE2","Our state-of-the-art video generation model",[119,127,135],{"id":120,"publish_date":121,"is_original":32,"collection":122,"cover_url":123,"cover_url_1_1":124,"title":125,"summary":126,"author":63},160,"2024-10-04","#Philosophy","article_res/cover/496990c49211e8b7f996b7d39c18168e.jpeg","article_res/cover/14dbaa1ade9cb4316d5829423a900362.jpeg","Time","The fungus of the morning does not know the waxing and waning of the moon, and the cicada does not know the seasons; this is a short life. To the south of the state of Chu there is a dark spirit which regards five hundred years as spring and five hundred years as autumn. In ancient times there was a great tree called the Ming which regarded eight thousand years as spring and eight thousand years as autumn; this is a long life.",{"id":128,"publish_date":129,"is_original":32,"collection":130,"cover_url":131,"cover_url_1_1":132,"title":133,"summary":134,"author":63},98,"2024-12-17","#AI Video Generator #Sora #Pika","article_res/cover/3b86e85d03fff4f356a3e4cf2bb329c9.jpeg","article_res/cover/5fa5c20ad0b40f8f544d257c0ef02938.jpeg","Pika 2.0 video generation officially released: effect comparison with Sora","今天，我们推出了Pika 2.0模型。卓越的文字对齐效果。惊人的视觉表现。还有✨场景成分✨",{"id":136,"publish_date":137,"is_original":32,"collection":138,"cover_url":139,"cover_url_1_1":140,"title":141,"summary":142,"author":63},71,"2025-01-14","#Nvidia #World Foundation Model #Cosmos #Physical AI #Embodied AI","article_res/cover/feddf8c832dfb45d28804291f6a42a9e.jpeg","article_res/cover/d6bc2f1186d96b78228c2283a17a3645.jpeg","NVIDIA's Cosmos World Model","Cosmos World Foundation Model Platform for Physical AI",[144,163,188],{"title":8,"items":145},[146,147,155],{"id":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},{"id":148,"publish_date":149,"is_original":32,"collection":150,"cover_url":151,"cover_url_1_1":152,"title":153,"summary":154,"author":63},622,"2025-03-24","#OWL #AI Agent #MAS #MCP #CUA","article_res/cover/cb50ca7f2bf4d1ed50202d7406e1c19a.jpeg","article_res/cover/4aa7aa3badfacf3cc84121334f1050dd.jpeg","OWL: Multi-agent collaboration","OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation",{"id":156,"publish_date":157,"is_original":32,"collection":158,"cover_url":159,"cover_url_1_1":160,"title":161,"summary":162,"author":63},620,"2025-03-26","#LLM #Google #Gemini #AI Agent","article_res/cover/53751a6dbbe990b1eb0b63f3b062aed4.jpeg","article_res/cover/031344981f0a212ff82d1f3a64aa5756.jpeg","Gemini 2.5 Pro, claimed to be far ahead of the competition, has been released with great fanfare: comprehensively surpassing other LLMs and topping the global rankings","Gemini 2.5: Our most intelligent AI model",{"title":9,"items":164},[165,172,180],{"id":166,"publish_date":157,"is_original":32,"collection":167,"cover_url":168,"cover_url_1_1":169,"title":170,"summary":171,"author":63},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":173,"publish_date":174,"is_original":4,"collection":175,"cover_url":176,"cover_url_1_1":177,"title":178,"summary":179,"author":63},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":181,"publish_date":182,"is_original":4,"collection":183,"cover_url":184,"cover_url_1_1":185,"title":186,"summary":187,"author":63},417,"2023-08-24","#OpenAI","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.",{"title":10,"items":189},[190,191,192],{"id":88,"publish_date":89,"is_original":32,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":63},{"id":96,"publish_date":97,"is_original":32,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":63},{"id":104,"publish_date":105,"is_original":32,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":63},true,{"code":4,"msg":5,"data":195},{"id":196,"publish_date":197,"is_original":4,"collection":198,"articles_id":199,"cover_url":200,"cover_url_1_1":201,"title":202,"summary":203,"author":204,"content":205},424,"2023-08-05","#Stable Diffusion #AI Image Generator #Tencent #ControlNet","2G95LteElvBxD5VRd8Y73g","article_res/cover/df9e0e269868add9a42b2a15ea30c74b.jpeg","article_res/cover/b064c9157c194fb1ba6d8631e9f56364.jpeg","Controlnet and T2I-Adapter","T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models","--","\u003Cdiv class=\"rich_media_content js_underline_content\n                       defaultNoSetting\n            \" id=\"js_content\">\u003Csection data-tool=\"markdown编辑器\" data-website=\"https://markdown.com.cn/editor\" style='font-size: 16px;font-style: normal;font-variant-caps: normal;font-weight: 400;letter-spacing: 0px;orphans: auto;text-indent: 0px;text-transform: none;white-space: normal;widows: auto;word-spacing: 0px;-webkit-tap-highlight-color: rgba(26, 26, 26, 0.3);-webkit-text-size-adjust: auto;-webkit-text-stroke-width: 0px;text-decoration: none;color: black;padding: 25px 30px;line-height: 1.6;word-break: break-word;overflow-wrap: break-word;text-align: justify;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;margin-top: -10px;'>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">T2I-Adapter is an adapter for text-to-image generation developed by Tencent's ARC team. The paper was released in February this year, and the code has been open-sourced on GitHub.\u003C/p>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"0.6219205630970337\" data-type=\"jpg\" data-w=\"1989\" src=\"https://res.cooltool.vip/article_res/assets/17434959819880.9064000142453892.jpeg\">\u003C/section>​\u003C/section>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Paper address: https://arxiv.org/pdf/2302.08453.pdf\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Code address: https://github.com/TencentARC/T2I-Adapter\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">It is a small model that can be attached to any large text-to-image diffusion model to enhance its controllability. T2I-Adapter works by learning to align textual prompts with the internal states of image generators. This allows users to more finely control the generated images by adjusting the textual prompts.\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Some advantages of T2I-Adapter mentioned in the official paper:\u003C/p>\u003Cul data-tool=\"markdown.com.cn编辑器\" style=\"margin-top: 8px;margin-bottom: 8px;padding-left: 25px;color: black;list-style-type: disc;\">\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">Plug-and-play. Does not affect the original network topology or generative capabilities.\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">Simple and compact. Approximately 77M parameters and about 300M storage.\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">Flexible. Suitable for various adapters under different control conditions.\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">Combinable. Multiple adapters can be used to achieve multi-condition control.\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">Universal. Can be directly applied to custom models.\u003C/section>\u003C/li>\u003C/ul>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Both ControlNet and today’s T2I-Adapter are technologies used for text-to-image generation. They both use small models to control the generation of large diffusion models. However, there are some differences between them:\u003C/p>\u003Cul data-tool=\"markdown.com.cn编辑器\" style=\"margin-top: 8px;margin-bottom: 8px;padding-left: 25px;color: black;list-style-type: disc;\">\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">ControlNet uses a multimodal transformer model, while T2I-Adapter uses a simple linear model. (This may not be entirely accurate—it was derived from unknown sources by Google Bard.)\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">ControlNet can provide finer control over the generated images, whereas T2I-Adapter is more lightweight.\u003C/section>\u003C/li>\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;line-height: 26px;text-align: left;color: rgb(1, 1, 1);font-weight: 500;\">ControlNet requires more training data and computational resources, while T2I-Adapter is easier to train.\u003C/section>\u003C/li>\u003C/ul>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">The author of ControlNet, Lvmin Zhang, is a PhD student in Stanford University's CS department since 2022. He graduated from Soochow University in 2021 with a Bachelor's degree in Engineering. His research areas include computational art and design, interactive content creation, computer graphics, image and video processing, as well as anime. He organized a special interest research group called Style2Paints Research and also developed an anime drawing software named Style2Paints.\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Under the extensions section of the Stable Diffusion webUI, there are models for both ControlNet and T2I-Adapter.\u003C/p>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"1.4126778783958602\" data-type=\"jpg\" data-w=\"773\" src=\"https://res.cooltool.vip/article_res/assets/17434959819430.6741569161585368.jpeg\">\u003C/section>​\u003C/section>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"1.3225806451612903\" data-type=\"jpg\" data-w=\"837\" src=\"https://res.cooltool.vip/article_res/assets/17434959819970.7558578275090457.jpeg\">\u003C/section>​\u003C/section>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">In terms of effect comparison, theoretically ControlNet should perform better, but many netizens have found that there is no significant difference in output quality. However, T2I-Adapter generates images approximately three times faster than ControlNet.\u003C/p>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"0.5138954309938766\" data-type=\"jpg\" data-w=\"2123\" src=\"https://res.cooltool.vip/article_res/assets/17434959817400.7738846806927846.jpeg\">\u003C/section>​\u003C/section>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"0.4558758314855876\" data-type=\"jpg\" data-w=\"2255\" src=\"https://res.cooltool.vip/article_res/assets/17434959818210.44986612600536247.jpeg\">\u003C/section>​\u003C/section>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Previously, it was said that T2I-Adapter had fewer model types, but recently, more T2I-Adapter models have appeared on C station: https://civitai.com/models/17220?modelVersionId=20330\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">You can install according to the instructions on the website based on your needs.\u003C/p>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">Of course, ControlNet and T2I-Adapter can also be used together.\u003C/p>\u003Csection>\u003Csection style=\"display: inline-block;\">\u003Cimg data-ratio=\"0.5039370078740157\" data-type=\"jpg\" data-w=\"2540\" src=\"https://res.cooltool.vip/article_res/assets/17434959821140.3140911427879063.jpeg\">\u003C/section>​\u003C/section>\u003Cp data-tool=\"markdown.com.cn编辑器\" style=\"font-size: 16px;padding-top: 8px;padding-bottom: 8px;margin: 0px;line-height: 26px;color: black;\">\u003Cbr>\u003C/p>\u003C/section>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"10000\">\u003C/mp-style-type>\u003C/p>\u003C/div>",1752585436458]