[{"data":1,"prerenderedAt":378},["ShallowReactive",2],{"$fgukOamtKU1RtUiMFsqdObttmqPPQz0uc7bl_gj_LyX0":3,"$fdbwpmXqQI8U9UibzZ6ZTsOirtY2srHZ2Px2KQm53Lkk":245,"article-40":377},{"code":4,"msg":5,"data":6},0,"",{"category":7,"tag":11,"popular":19,"latest":86,"banner":126,"list":151,"cache":244},[8,9,10],"Agent","OpenAI","LLM",[8,12,13,14,9,10,15,16,17,18],"Google","Nvidia","Claude","DeepSeek","OCR","Chat","Generator",[20,29,37,45,54,62,70,79],{"id":21,"publish_date":22,"is_original":23,"collection":5,"cover_url":24,"cover_url_1_1":25,"title":26,"summary":27,"author":28},411,"2023-09-10",1,"article_res/cover/451ef50c225a8dc61c4336506794d13b.jpeg","article_res/cover/3ba9dc7a72f87d40b20fc2d225289ee3.jpeg","Idealism","Reality is created by the mind, we can change our reality by changing our mind. - Plato","Renee's Entrepreneurial Journey",{"id":30,"publish_date":31,"is_original":23,"collection":32,"cover_url":33,"cover_url_1_1":34,"title":35,"summary":36,"author":28},108,"2024-12-07","#LLM #AGI #AI Agent","article_res/cover/0039044422e4ec9f61c18e8ee1693bb0.jpeg","article_res/cover/4220971b108a91d21407d87bb02fbaa6.jpeg","Freysa.ai: The World's First Adversarial AI Agent Game","说服 Freysa 把钱包里的钱都拿出来",{"id":38,"publish_date":39,"is_original":23,"collection":40,"cover_url":41,"cover_url_1_1":42,"title":43,"summary":44,"author":28},12,"2025-03-09","#Oxford #Reasoning #LLM #Tool Use","article_res/cover/d448e9b3617a0b5302e1bd10c438bca9.jpeg","article_res/cover/864a468f9cc4c9317efadb3811909888.jpeg","Agentic Reasoning Framework - Significantly enhance the reasoning ability of LLMs through the integration of external tools using agents","Agentic Reasoning: Reasoning LLMs with Tools for Deep Research",{"id":46,"publish_date":47,"is_original":4,"collection":48,"cover_url":49,"cover_url_1_1":50,"title":51,"summary":52,"author":53},480,"2023-04-14","#Stable Diffusion","article_res/cover/0bdbe7cb1de4a78e54536e5d9afa7ec9.jpeg","article_res/cover/b3d6ffec0608dcfaf18c5a69906d1490.jpeg","【AIGC Learning】Generate Prompts Using Word Graphs - Stable Diffusion Web UI Series 13","AI will become a powerful tool in education, transforming the way we learn and deliver instruction.  \n- Reid Hoffman","--",{"id":55,"publish_date":56,"is_original":4,"collection":57,"cover_url":58,"cover_url_1_1":59,"title":60,"summary":61,"author":28},413,"2023-09-08","#Neuroscience","article_res/cover/74f8302d78a23d9430f22171eae136b6.jpeg","article_res/cover/87ca08af81bb304746be5261160964c0.jpeg","Can machines be conscious?","Do we have an ethical obligation to not turn off conscious machines? 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No. I don't lose any sleep over unplugging a conscious machine.\n- Jeff Hawkins, \"A Thousand Brains\"",{"id":63,"publish_date":64,"is_original":23,"collection":65,"cover_url":66,"cover_url_1_1":67,"title":68,"summary":69,"author":28},178,"2024-09-09","#Entrepreneurship","article_res/cover/a7224f025b55d1820408085faef63079.jpeg","article_res/cover/11a9995b096cbf64465ef01b8673b154.jpeg","37signals company","This damn sense of relaxation",{"id":71,"publish_date":72,"is_original":4,"collection":73,"cover_url":74,"cover_url_1_1":75,"title":76,"summary":77,"author":78},460,"2023-05-12","#Google","article_res/cover/b970687b12faa52da976f91248c2aa7b.jpeg","article_res/cover/d1e71b52cfd2c63bc6e71f3e85ff135c.jpeg","Learn what BRC-20 and Ordinals are using Google Bard","Ordinals - a new protocol that allows users to store arbitrary data on the Bitcoin blockchain","Google Bard mainly writes",{"id":80,"publish_date":81,"is_original":23,"collection":5,"cover_url":82,"cover_url_1_1":83,"title":84,"summary":85,"author":28},309,"2024-03-26","article_res/cover/9877f95894ee88532d0e6012c23a2df3.jpeg","article_res/cover/20092164ddc109ce6ae56b1984246751.jpeg","Learning the Cancun Upgrade with lepton and perplexity","Building a quick conversation-based search demo with Lepton AI.",[87,95,103,111,119],{"id":88,"publish_date":89,"is_original":23,"collection":90,"cover_url":91,"cover_url_1_1":92,"title":93,"summary":94,"author":28},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":96,"publish_date":97,"is_original":23,"collection":98,"cover_url":99,"cover_url_1_1":100,"title":101,"summary":102,"author":28},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":104,"publish_date":105,"is_original":23,"collection":106,"cover_url":107,"cover_url_1_1":108,"title":109,"summary":110,"author":28},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":112,"publish_date":113,"is_original":23,"collection":114,"cover_url":115,"cover_url_1_1":116,"title":117,"summary":118,"author":28},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":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},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",[127,135,143],{"id":128,"publish_date":129,"is_original":23,"collection":130,"cover_url":131,"cover_url_1_1":132,"title":133,"summary":134,"author":28},300,"2024-04-16","#AI in Science #AGI","article_res/cover/6bf01e793e0f33e848572412eebdf9b0.jpeg","article_res/cover/91a5ee21dafecb914fabeb9430d46ec1.jpeg","Would Einstein lose his job - AI and Quantum Computing: A Glimpse into the Near Future","So Einstein's job is still safe.",{"id":136,"publish_date":137,"is_original":23,"collection":138,"cover_url":139,"cover_url_1_1":140,"title":141,"summary":142,"author":28},101,"2024-12-14","#Nvidia #AI 3D Generator","article_res/cover/693e07c85980c5c0c8fde3f037733f23.jpeg","article_res/cover/9ea8edff2d5d303ff3fffff3f6f9c3d9.jpeg","NVIDIA's open-source 3D project LLaMA-Mesh","LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models",{"id":144,"publish_date":145,"is_original":23,"collection":146,"cover_url":147,"cover_url_1_1":148,"title":149,"summary":150,"author":28},131,"2024-11-10","#OpenAI","article_res/cover/87f8ed353ce39f31960e7cdfaf075a35.jpeg","article_res/cover/f597a63935f5cd32e484b4aadd6019e8.jpeg","ChatGPT has launched the Search function","Get fast, timely answers with links to relevant web sources.",{"big":152,"small":214},[153,181],{"title":154,"list":155},"AGENT",[156,157,165,173],{"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":158,"publish_date":159,"is_original":23,"collection":160,"cover_url":161,"cover_url_1_1":162,"title":163,"summary":164,"author":28},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":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},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",{"id":174,"publish_date":175,"is_original":23,"collection":176,"cover_url":177,"cover_url_1_1":178,"title":179,"summary":180,"author":28},616,"2025-03-29","#MAS #AI Agent #AI Coder #MetaGPT #MGX","article_res/cover/9dcd702ad2035902e5e77967c34a1f1e.jpeg","article_res/cover/0a97fc4a922753c8f46ff38792020df8.jpeg","MGX - An automated website-building platform composed of multiple AI Agents","Your 24/7 AI Team | Dream, Chat, 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 images.",[215,221,241],{"title":10,"list":216},[217,218,219,220],{"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":223},"GOOGLE",[224,225,226,234],{"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},615,"2025-03-30","#AI 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":318,"category":375,"tag":376},40,"2025-02-13","#Deep Dive into LLMs #Andrej Karpathy #LLM #Post-Training #RL","9xRr53Ufpn9oJLXwv_2RNA","article_res/cover/c6cfc6a4197d7baa00c15ce4e733a323.jpeg","article_res/cover/869e5f1a234304b1692e651635cfbea8.jpeg","Andrej Karpathy Deep Dive on LLM (Part 3): Post-Training","pretraining to post-training  \npost-training data (conversations)","\u003Cdiv class=\"rich_media_content js_underline_content\n                       autoTypeSetting24psection\n            \" id=\"js_content\">\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cstrong>\u003Cspan leaf=\"\" style='color:rgba(0, 0, 0, 0.9);font-size:17px;font-family:\"mp-quote\", -apple-system-font, BlinkMacSystemFont, \"Helvetica Neue\", \"PingFang SC\", \"Hiragino Sans GB\", \"Microsoft YaHei UI\", \"Microsoft YaHei\", Arial, sans-serif;line-height:1.6;letter-spacing:0.034em;font-style:normal;font-weight:normal;'>The training of LLMs (Large Language Models) is divided into two main stages:\u003C/span>\u003C/strong>\u003C/h3>\u003Col 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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Pretraining\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Training the Base Model.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Post-training\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Fine-tuning the Base Model into an interactive Assistant Model.\u003C/span>\u003C/section>\u003C/li>\u003C/ol>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">1. Pretraining\u003C/span>\u003C/strong>\u003C/span>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010134\" data-ratio=\"0.562962962962963\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" src=\"./assets/17423770733100.7188976875675281.png\">\u003C/section>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003C/strong>\u003C/span>\u003C/h3>\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;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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cspan leaf=\"\">The core goal of the pretraining stage is to\u003C/span>\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;\">\u003Cspan leaf=\"\">learn the statistical patterns of internet text\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, which is essentially a\u003C/span>\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;\">\u003Cspan leaf=\"\">Token prediction task\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" 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;\">\u003Cspan leaf=\"\">By training the model on massive amounts of internet data, it learns how to predict Token sequences.\u003C/span>\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;\">\u003Cspan leaf=\"\">The final product of the training is the\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Base Model\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, which is merely a\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Token generator\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, similar to a highly advanced\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">autocompletion system\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">。\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\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;\">\u003Cspan leaf=\"\">Deficiencies of the Base Model\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" 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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">It does not understand questions\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, but only generates text based on the statistical patterns of the training data.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">It cannot reject inappropriate questions\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, and may output unsafe or inaccurate content.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">It lacks interactivity\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, unable to engage in multi-turn conversations or perform complex tasks.\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">2. Post-training\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">To transform the Base Model into a true\u003C/span>\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;\">\u003Cspan leaf=\"\">AI assistant\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, post-training is required, which is much less costly than pretraining. Post-training mainly includes:\u003C/span>\u003C/p>\u003Col 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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Instruction Tuning\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Teaching the model to answer questions rather than just predicting Tokens.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Reward Model Training\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Defining what constitutes \"good\" and \"bad\" responses.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Reinforcement Learning with Human Feedback (RLHF)\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Using human feedback to optimize the model, making its answers more aligned with human expectations.\u003C/span>\u003C/section>\u003C/li>\u003C/ol>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">3. Key Data for Training AI Assistants: Dialogue Data\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\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;\">\u003Cspan leaf=\"\">Sources of Dialogue Data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" 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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Human Labeling\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Hiring human labelers to write\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">ideal responses\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, training the model to mimic these responses.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Existing Datasets\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Fine-tuning using data from forums, social media, etc.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Synthetic Data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Generating high-quality responses using existing LLMs, then having humans review them.\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\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;\">\u003Cspan leaf=\"\">Dialogue Examples\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"list-style-type: square;\" 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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\u003Cspan leaf=\"\">There may be thousands of dialogues like the following, very long, covering a wide range of topics.\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Csection style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010136\" data-ratio=\"0.9416498993963782\" data-s=\"300,640\" data-type=\"png\" data-w=\"994\" style='white-space-collapse: preserve;text-align: center;font-family: mp-quote, \"PingFang SC\", system-ui, -apple-system, BlinkMacSystemFont, \"Helvetica Neue\", \"Hiragino Sans GB\", \"Microsoft YaHei UI\", \"Microsoft YaHei\", Arial, sans-serif;font-size: var(--articleFontsize);letter-spacing: 0.034em;height: auto !important;' src=\"./assets/17423770734960.448095956612808.png\">\u003C/section>\u003Cul style=\"list-style-type: disc;\" class=\"list-paddingleft-1\">\u003Cli>\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;cursor: pointer;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Training Process\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\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;background-color: rgb(255, 255, 255);' class=\"list-paddingleft-1\">\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;padding-left: 25px;width: 551.867px;cursor: pointer;list-style-type: square;\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Cp>\u003Cspan leaf=\"\">Organizing some dialogues labeled by humans, and having humans provide ideal answers first.\u003C/span>\u003C/p>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Cp>\u003Cspan leaf=\"\">Marking the dialogue as a sequence of Tokens, where <im_start> is a new token that has never been trained before, created only in the post-training phase to indicate whether the dialogue initiator is the User or the Assistant.\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003C/p>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010137\" data-ratio=\"0.5018518518518519\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" src=\"./assets/17423770733160.9515934824468388.png\">\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;cursor: pointer;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cspan style=\"letter-spacing: 0em;\">\u003Cspan leaf=\"\">The neural network trains on this dialogue data, making the model mimic these responses.\u003C/span>\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;padding-left: 25px;width: 551.867px;cursor: pointer;list-style-type: square;\" class=\"list-paddingleft-1\">\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;cursor: pointer;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cspan style=\"letter-spacing: 0em;\">\u003Cspan leaf=\"\">The model mimics these responses.\u003C/span>\u003C/span>\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;cursor: pointer;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cspan style=\"letter-spacing: 0em;\">\u003Cspan leaf=\"\">The model will quickly adjust to learn the response style of the human labelers.\u003C/span>\u003C/span>\u003C/section>\u003C/li>\u003Cli style=\"cursor: pointer;\">\u003Csection style=\"margin-top: 5px;margin-bottom: 5px;cursor: pointer;color: rgb(1, 1, 1);line-height: 1.8em;letter-spacing: 0em;\">\u003Cspan style=\"letter-spacing: 0em;\">\u003Cspan leaf=\"\">During the inference stage, the model will continue to predict the next best token.\u003C/span>\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">4. Training Methods\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;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;\">\u003Cp style=\"cursor: pointer;color: rgb(0, 0, 0);line-height: 1.8em;letter-spacing: 0em;text-indent: 0em;padding-top: 8px;padding-bottom: 8px;\">\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;\">\u003Cspan leaf=\"\">Differences from Pretraining\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/p>\u003C/section>\u003C/li>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: square;padding-left: 25px;color: rgb(0, 0, 0);\" 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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Smaller Dataset Size\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">(Pretraining uses tens of trillions of Tokens, while post-training may use only millions of dialogues).\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Shorter Training Time\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">(Pretraining may take 3 months, while post-training usually takes only a few hours to days).\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Different Goals\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">(Pretraining learns Token statistical patterns, while post-training learns interactive behavior).\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">5. Instruction Tuning\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">In 2022, OpenAI released a\u003C/span>\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;\">\u003Cspan leaf=\"\">InstructGPT\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">research paper, detailing for the first time how to fine-tune a Base Model into an Assistant Model that better meets user needs through\u003C/span>\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;\">\u003Cspan leaf=\"\">dialogue data tuning\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">.\u003C/span>\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;\">\u003Cspan leaf=\"\">AI assistant (Assistant Model)\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">。\u003C/span>\u003C/p>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010138\" data-ratio=\"1.225\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" src=\"./assets/17423770733300.24509411546084214.png\">\u003C/section>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">Human-labeled data\u003C/span>\u003C/strong>\u003C/span>\u003C/h4>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">During the\u003C/span>\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;\">\u003Cspan leaf=\"\">InstructGPT\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">training process, OpenAI hired\u003C/span>\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;\">\u003Cspan leaf=\"\">human labelers\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, whose tasks were:\u003C/span>\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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Designing user inputs (Prompts)\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, such as:\u003C/span>\u003Cpre style='font-size: 1em;font-family: SFMono-Regular, Consolas, \"Liberation Mono\", Menlo, Courier, monospace;margin-top: 10px;margin-bottom: 10px;overflow: auto;cursor: pointer;border-radius: 5px;box-shadow: rgba(0, 0, 0, 0.55) 0px 2px 10px;'>\u003Ccode style=\"font-family: Consolas, Monaco, Menlo, monospace;font-size: 12px;display: -webkit-box;overflow-x: auto;padding: 15px 4px 2px;color: rgb(30, 107, 184);background: rgb(40, 44, 52);cursor: pointer;line-height: 1.8em;letter-spacing: 0em;width: auto;margin-right: 2px;margin-left: 2px;border-style: none;border-width: 3px;border-color: rgb(0, 0, 0) rgba(0, 0, 0, 0.4) rgba(0, 0, 0, 0.4);border-radius: 5px;word-break: break-all;\">\u003Cspan leaf=\"\">- How to rekindle career passion?\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003Cspan leaf=\"\">- Recommend 10 science fiction novels.\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003Cspan leaf=\"\">- Translate this sentence into Spanish.\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003C/code>\u003C/pre>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Providing ideal assistant responses\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">to ensure the quality of the model's replies.\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">Labeling Guidelines\u003C/span>\u003C/strong>\u003C/span>\u003C/h4>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">To standardize, labelers must follow\u003C/span>\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;\">\u003Cspan leaf=\"\">detailed labeling guidelines\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">(usually hundreds of pages), with core requirements:\u003C/span>\u003C/p>\u003Col 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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Helpful\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Responses should meet user needs.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Truthful\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Provide accurate information, avoiding hallucinations.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Harmless\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">: Avoid outputting unsafe or harmful content.\u003C/span>\u003C/section>\u003C/li>\u003C/ol>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">Through these guidelines, companies\u003C/span>\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;\">\u003Cspan leaf=\"\">indirectly program the behavior of AI assistants\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, ensuring their responses meet expectations.\u003C/span>\u003C/p>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">6. Existing Open-Source Attempts\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">Although OpenAI has not made the InstructGPT training data public, some open-source projects (such as\u003C/span>\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;\">\u003Cspan leaf=\"\">Open Assistant\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">) have attempted to replicate similar processes:\u003C/span>\u003C/p>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010140\" data-ratio=\"0.43796296296296294\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" src=\"./assets/17423770735360.09711850769266839.png\">\u003C/section>\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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Users contribute example dialogues\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, such as:\u003C/span>\u003Cpre style='font-size: 1em;font-family: SFMono-Regular, Consolas, \"Liberation Mono\", Menlo, Courier, monospace;margin-top: 10px;margin-bottom: 10px;overflow: auto;cursor: pointer;border-radius: 5px;box-shadow: rgba(0, 0, 0, 0.55) 0px 2px 10px;'>\u003Ccode style=\"font-family: Consolas, Monaco, Menlo, monospace;font-size: 12px;display: -webkit-box;overflow-x: auto;padding: 15px 4px 2px;color: rgb(30, 107, 184);background: rgb(40, 44, 52);cursor: pointer;line-height: 1.8em;letter-spacing: 0em;width: auto;margin-right: 2px;margin-left: 2px;border-style: none;border-width: 3px;border-color: rgb(0, 0, 0) rgba(0, 0, 0, 0.4) rgba(0, 0, 0, 0.4);border-radius: 5px;word-break: break-all;\">\u003Cspan leaf=\"\">Q: Please explain the concept of \"monopoly\" in economics and give an example.\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003Cspan leaf=\"\">A: Monopoly refers to a market with only one supplier... (specific answer)\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003C/code>\u003C/pre>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Using crowdsourcing to create high-quality training data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">and fine-tuning the model.\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003Ch3 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 20px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">7. The Role of AI-Generated Data\u003C/span>\u003C/strong>\u003C/span>\u003C/h3>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">Over the past few years, since the release of the\u003C/span>\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;\">\u003Cspan leaf=\"\">InstructGPT\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">paper,\u003C/span>\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;\">\u003Cspan leaf=\"\">the way AI assistants are trained has changed significantly\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">. Today, human labelers no longer manually write all the training data, but instead\u003C/span>\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;\">\u003Cspan leaf=\"\">use LLMs to generate part of the data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, which is then reviewed and optimized by humans.\u003C/span>\u003C/p>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">AI-assisted data creation\u003C/span>\u003C/strong>\u003C/span>\u003C/h4>\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;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;\">\u003Cspan leaf=\"\">Past: Human labelers\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">writing from scratch\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">dialogue data to provide training examples for AI assistants.\u003C/span>\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;\">\u003Cspan leaf=\"\">Present: LLMs\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">first generating responses\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, then having humans\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">review and modify\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, improving efficiency.\u003C/span>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">For example, the dataset\u003C/span>\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;\">\u003Cspan leaf=\"\">UltraChat\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">is primarily\u003C/span>\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;\">\u003Cspan leaf=\"\">AI-generated\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">but edited by humans to ensure quality. This approach significantly reduces training costs and expands the coverage of the dataset.\u003C/span>\u003C/p>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010141\" data-ratio=\"0.412962962962963\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" src=\"./assets/17423770733650.36089170879049126.png\">\u003C/section>\u003Csection 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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">Currently, these datasets contain millions of dialogues. Most are synthetic and may be edited by humans. They have a very large diversity. The figure below shows SFT Mixtures (Supervised Fine-Tuning data mixtures), during the Supervised Fine-Tuning (SFT) stage, multiple different source datasets are used for fine-tuning to improve the model's performance across various tasks.\u003C/span>\u003C/section>\u003Csection style=\"text-align: center;\" nodeleaf=\"\">\u003Cimg class=\"rich_pages wxw-img js_insertlocalimg\" data-imgfileid=\"100010143\" data-ratio=\"0.7240740740740741\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"height: auto !important;\" type=\"block\" src=\"./assets/17423770734410.48966244641500434.png\">\u003C/section>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">8. Statistical Simulation vs. True Intelligence\u003C/span>\u003C/strong>\u003C/span>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003C/strong>\u003C/span>\u003C/h4>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">When interacting with AI,\u003C/span>\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;\">\u003Cspan leaf=\"\">the model's responses are not based on real-time search\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, but rather on\u003C/span>\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;\">\u003Cspan leaf=\"\">statistical simulation\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">of the human labelers in the training data. For example:\u003C/span>\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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">If the question appears in the training data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, the AI may output a highly similar answer.\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">If the question is not in the training data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, the AI will infer possible answers based on\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">statistical patterns\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, but there may be errors.\u003C/span>\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;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;\">\u003Cspan leaf=\"\">Essentially, ChatGPT is not a truly \"understanding\" AI, but an optimized \"human labeler simulator,\"\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">similar to asking educated experts who would be hired to write these answers in relevant fields.\u003C/span>\u003C/p>\u003Ch4 style='margin-top: 30px;margin-bottom: 15px;color: rgba(0, 0, 0, 0.85);cursor: pointer;font-family: Optima, \"Microsoft YaHei\", PingFangSC-regular, serif;letter-spacing: normal;text-align: left;background-color: rgb(255, 255, 255);'>\u003Cspan style=\"cursor: pointer;font-size: 18px;color: rgb(0, 0, 0);line-height: 1.5em;letter-spacing: 0em;font-weight: bold;display: block;\">\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;\">\u003Cspan leaf=\"\">9. How AI Generates Responses\u003C/span>\u003C/strong>\u003C/span>\u003C/h4>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">When a user inputs in ChatGPT:\u003C/span>\u003C/p>\u003Cpre style='font-size: 16px;font-family: SFMono-Regular, Consolas, \"Liberation Mono\", Menlo, Courier, monospace;margin-top: 10px;margin-bottom: 10px;overflow: auto;cursor: pointer;border-radius: 5px;box-shadow: rgba(0, 0, 0, 0.55) 0px 2px 10px;text-align: left;color: rgb(0, 0, 0);letter-spacing: normal;background-color: rgb(255, 255, 255);'>\u003Ccode style=\"font-family: Consolas, Monaco, Menlo, monospace;font-size: 12px;display: -webkit-box;overflow-x: auto;padding: 15px 16px 16px;color: rgb(171, 178, 191);background: rgb(40, 44, 52);cursor: pointer;border-radius: 5px;\">\u003Cspan leaf=\"\">Recommend the top five landmarks in Paris?\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\u003C/code>\u003C/pre>\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;background-color: rgb(255, 255, 255);'>\u003Cspan leaf=\"\">The AI does not perform a real-time search, but rather:\u003C/span>\u003C/p>\u003Col 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;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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Checks if the question is in the training data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, and if so, may return a similar answer.\u003C/span>\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;\">\u003Cspan leaf=\"\">Combines a large amount of information about Paris from pretraining with the post-training dataset.\u003C/span>\u003Cspan leaf=\"\">\u003Cbr>\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">If the question is not in the training data\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">, it infers based on statistical patterns\u003C/span>\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">, guessing\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">：\u003C/span>\u003C/section>\u003C/li>\u003C/ol>\u003Cul style=\"margin-top: 8px;margin-bottom: 8px;cursor: pointer;list-style-type: disc;padding-left: 25px;color: rgb(0, 0, 0);\" 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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Frequently occurring landmarks are more likely to be recommended\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">(e.g., Eiffel Tower, Louvre).\u003C/span>\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;\">\u003Cstrong style=\"cursor: pointer;color: rgb(0, 0, 0);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;\">\u003Cspan leaf=\"\">Infrequently occurring content may be ignored or answered incorrectly.\u003C/span>\u003C/strong>\u003Cspan leaf=\"\">。\u003C/span>\u003C/section>\u003C/li>\u003C/ul>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"3\">\u003C/mp-style-type>\u003C/p>\u003C/div>",[257,265,273,281,289,296,303,311],{"id":258,"title_md5":259,"publish_date":260,"author_md5":261,"is_original":4,"collection":65,"summary_md5":262,"cover_url":263,"cover_url_1_1":264},559,"27810098e4e76d946e1d69ca515e16b6","2022-04-27","676530389d8e3e484f04abd010082682","926937fd869fb990fd5e70d49fdbd20b","article_res/cover/838866e5860d413ba612c26d877f0997.jpeg","article_res/cover/e18ed6814c52132af4db6b42cd7d83b9.jpeg",{"id":266,"title_md5":267,"publish_date":268,"author_md5":269,"is_original":23,"collection":5,"summary_md5":270,"cover_url":271,"cover_url_1_1":272},430,"a66fc661a6392a91587028e125a7b3e9","2023-07-22","bc27fa490c4d0d525bac812fc0793534","b5a87ca12712667ad2a39546c112da1f","article_res/cover/014790300fa3eae2261684ed55bf4c49.jpeg","article_res/cover/ca5250b750dfabe2b55173a5a1c31429.jpeg",{"id":274,"title_md5":275,"publish_date":276,"author_md5":269,"is_original":23,"collection":277,"summary_md5":278,"cover_url":279,"cover_url_1_1":280},226,"0cf292403dc275825546721918f6ee4a","2024-07-07","#AI Video Generator #AI Animation","c01d1cc504b314f88dc408afa77b21b8","article_res/cover/0da632cc597be863db7e82eadf492a6b.jpeg","article_res/cover/abcdbae958b5b74bf445be4352796ac9.jpeg",{"id":282,"title_md5":283,"publish_date":284,"author_md5":269,"is_original":23,"collection":285,"summary_md5":286,"cover_url":287,"cover_url_1_1":288},218,"0c69f3fbd610522b4fcad51327c6fd93","2024-07-16","#Google #AI Image Generator #AI Image Editor","acfe687cc9fb308073f436432c4ab11d","article_res/cover/87672e26d288ee3b0678dcbf32f1e4e2.jpeg","article_res/cover/4189d656ac3e42fd0926cac55198d070.jpeg",{"id":290,"title_md5":291,"publish_date":292,"author_md5":269,"is_original":23,"collection":5,"summary_md5":293,"cover_url":294,"cover_url_1_1":295},314,"577d9bb66a24cc28ba64df3dd18e9786","2024-03-16","7ac3b4869e9e8bdf2d053d10355f7901","article_res/cover/f9d727dc25194bfbd719668aabaca6f5.jpeg","article_res/cover/884e54049dfda0ef62cd4beb83757df2.jpeg",{"id":297,"title_md5":298,"publish_date":299,"author_md5":269,"is_original":4,"collection":5,"summary_md5":300,"cover_url":301,"cover_url_1_1":302},358,"22a6d6911bfa838ab56be6dfc5f99d5f","2023-12-28","06e901a23785330321da08cc550ce5ca","article_res/cover/ddca1dfc7627806c736bdb0722115f6f.jpeg","article_res/cover/4c57656ce2f8734c2020ab26c096baca.jpeg",{"id":304,"title_md5":305,"publish_date":306,"author_md5":269,"is_original":23,"collection":307,"summary_md5":308,"cover_url":309,"cover_url_1_1":310},486,"6c5e71fef51a446717ffb9c514ef8d84","2023-04-08","#Stable 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