[{"data":1,"prerenderedAt":372},["ShallowReactive",2],{"$fgukOamtKU1RtUiMFsqdObttmqPPQz0uc7bl_gj_LyX0":3,"$fQ3_uLzUpf6EKd5iItSN1s2vgDYIaB01SgELANhMuEPo":245,"article-367":371},{"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? Would turning them off be murder? 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":4,"collection":249,"articles_id":250,"cover_url":251,"cover_url_1_1":252,"title":253,"summary":254,"author":28,"content":255,"popular":256,"list":320,"category":369,"tag":370},367,"2023-12-18","#Prompt Engineering","ndYEkHBKF7JhB9LTBRILUg","article_res/cover/6d157b1913c554a83b3577d620578a75.jpeg","article_res/cover/4279850a93a48fcd6ae36d16b994048f.jpeg","Six key points for writing effective Prompts","Explore what's possible with some example prompts","\u003Cdiv class=\"rich_media_content js_underline_content\n                       autoTypeSetting24psection\n            \" id=\"js_content\">\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Liang shared a prompt guide written by OpenAI in the group. The original text is quite long, so based on the principle of Occam's Razor, I have summarized the key points that are helpful to me:\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>To view the unedited original text, please visit the OpenAI official website https://platform.openai.com/docs/guides/prompt-engineering/.\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Core content of the article: Writing effective prompts mainly includes six key points:\u003C/p>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>1. Clear instructions\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.1 Provide more details\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;overflow-x: auto;'>\u003Ctable>\u003Cthead>\u003Ctr style=\"border-width: 1px 0px 0px;border-right-style: initial;border-bottom-style: initial;border-left-style: initial;border-right-color: initial;border-bottom-color: initial;border-left-color: initial;border-top-style: solid;border-top-color: rgb(204, 204, 204);background-color: white;\">\u003Cth style=\"border-top-width: 1px;border-color: rgb(204, 204, 204);background-color: rgb(240, 240, 240);min-width: 85px;text-align: left;\">Poor example\u003C/th>\u003Cth style=\"border-top-width: 1px;border-color: rgb(204, 204, 204);background-color: rgb(240, 240, 240);min-width: 85px;text-align: left;\">Better example\u003C/th>\u003C/tr>\u003C/thead>\u003Ctbody style=\"border-width: 0px;border-style: initial;border-color: initial;\">\u003Ctr style=\"border-width: 1px 0px 0px;border-right-style: initial;border-bottom-style: initial;border-left-style: initial;border-right-color: initial;border-bottom-color: initial;border-left-color: initial;border-top-style: solid;border-top-color: rgb(204, 204, 204);background-color: white;\">\u003Ctd style=\"border-color: rgb(204, 204, 204);min-width: 85px;\">How to add numbers in Excel?\u003C/td>\u003Ctd style=\"border-color: rgb(204, 204, 204);min-width: 85px;\">How to calculate the total sum of a row of dollar amounts in Excel? I hope to automatically calculate each row in the entire table, and finally display all the totals in a column named \"Total\".\u003C/td>\u003C/tr>\u003Ctr style=\"border-width: 1px 0px 0px;border-right-style: initial;border-bottom-style: initial;border-left-style: initial;border-right-color: initial;border-bottom-color: initial;border-left-color: initial;border-top-style: solid;border-top-color: rgb(204, 204, 204);background-color: rgb(248, 248, 248);\">\u003Ctd style=\"border-color: rgb(204, 204, 204);min-width: 85px;\">Who is the president?\u003C/td>\u003Ctd style=\"border-color: rgb(204, 204, 204);min-width: 85px;\">Who was the president of Mexico in 2021? How frequent are elections in Mexico?\u003C/td>\u003C/tr>\u003C/tbody>\u003C/table>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.2 Use specific roles\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Document.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Write a thank-you letter to express gratitude to my steel bolt supplier for completing delivery promptly and within a short time, which allowed us to deliver an important order on time.\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.3 Use delimiters to clearly distinguish different parts of the input\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">You will receive two articles on the same topic (separated by XML tags). First, summarize the arguments of each article. Then, indicate which article's argument is more persuasive and explain why.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Insert the second article here\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.4 Clearly define the steps required to complete the task\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Use the following step-by-step guide to respond to user input.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">The user will provide text in triple quotes. Summarize this text in one sentence and add the prefix \"Summary:\".\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Translate the summary from Step 1 into Spanish, and add the prefix \"Translation:\".\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">\"\"\"Insert text here\"\"\"\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.5 Provide examples (\"few-shot\")\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">in a consistent\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Teach me about the concept of patience.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">The rivers that carve the deepest valleys come from gentle springs; the grandest symphonies start with a single note; the most complex tapestries begin with a solitary thread.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Teach me about the ocean.\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>1.6 Specify the required output length\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">to summarize the text within the triple quotes.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">\"\"\"Insert text here\"\"\"\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Optimized article:\u003C/p>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>2. Provide reference text\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>2.1 Guide the model to answer using the reference text\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Use triple quotes to separate articles to answer questions. If the answer cannot be found in the article, please write \"unable to find the answer\".\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">\"\"\"< Insert triple-quoted article here >\"\"\"\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Question: < Insert question here >\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>2.2 Guide the model to answer questions by referencing the provided text\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">, and quote the paragraph from the document that was used to answer the question. If there is not enough information in the document to answer the question, simply write: \"Insufficient information.\" If an answer to the question is provided, a quotation must be attached. Use the following format to quote relevant paragraphs ({\"citation\": …}).\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">\"\"\"< Insert the document here >\"\"\"\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Question: < Insert the question here >\u003C/p>\u003C/section>\u003C/section>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>3. Break down complex tasks into simpler subtasks\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>3.1 Use intent classification to identify the most relevant instructions for user queries\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100002845\" data-ratio=\"0.5416666666666666\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423813525970.2753170342680089.png\">\u003C/strong>\u003C/p>\u003Cp>\u003Cbr>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>3.2 For applications requiring long conversations, summarize or filter previous dialogues\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Method:\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>a. Summarize the previous rounds of the dialogue. b. Use embedding-based search to achieve efficient knowledge retrieval.\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>3.3 Segment-wise summarization of long documents and recursive construction of complete abstracts\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Steps:\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Step 1. Summarize each part of the document through a series of queries. Step 2. Section summaries can be concatenated and summarized to form a summary of summaries. Step 3. Recursively perform Step 2 until the entire document is summarized.\u003C/p>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>4. Give the model time to \"think\"\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>4.1 Guide the model to find its own solutions before rushing to conclusions\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>A direct answer would be incorrect:\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100002846\" data-ratio=\"0.6129629629629629\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423813527720.6169462660431446.png\">\u003C/strong>\u003C/p>\u003Cp style=\"text-align: left;\">\u003Cstrong>\u003Cspan style='color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;'>\u003C/span>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: left;\">\u003Cspan style='color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;'>If you calculate the answer yourself, you'll know that User is wrong:\u003C/span>\u003C/p>\u003Cp>\u003Cstrong>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: left;\">\u003Cstrong>\u003Cspan style='color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;'>\u003C/span>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong>\u003Cbr>\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100002847\" data-ratio=\"0.6194444444444445\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423813527520.34357055721673135.png\">\u003C/strong>\u003C/p>\u003Cp>\u003Cstrong>\u003Cbr>\u003C/strong>\u003C/p>\u003Cp>\u003C/p>\u003Cp>\u003Cbr>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>4.2 Use internal monologues or a series of queries to explore the reasoning process of the model\u003C/strong>\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cstrong>\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100002848\" data-ratio=\"0.6157407407407407\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423813528190.46679875139028515.png\">\u003C/strong>\u003C/p>\u003Cp>\u003Cbr>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>4.3 Ask the model if it has omitted anything in the previous process\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>When the source document is large, the model may stop prematurely and fail to list all relevant excerpts. You can prompt the model through subsequent queries to find any excerpts it may have missed earlier.\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">You will receive a document separated by triple quotes. Your task is to select excerpts relevant to the following question: \"What major paradigm shifts have occurred in the history of artificial intelligence?\" Ensure that the excerpts include all relevant background information needed to explain them— in other words, do not extract small snippets that lack important context. Provide the output in JSON format as follows:\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">[{\"excerpt\": \"...\"}, {\"excerpt\": \"...\"}]\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">\"\"\"< Insert document here >\"\"\"\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">[{ \"Excerpt\": \"Model writes excerpt here\" }, {\"Excerpt\": \"Model writes another excerpt here\"}]\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Please make sure not to repeat excerpts. Also ensure that the excerpts contain all relevant background information necessary to explain them.\u003C/p>\u003C/section>\u003C/section>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>5. Use external tools\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>5.1 Use embedding-based search to implement efficient knowledge retrieval\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>Use VectorDB - https://cookbook.openai.com/examples/vector_databases/readme\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>5.2 Use code execution for more accurate calculations or call external APIs\u003C/strong>\u003C/p>\u003Csection data-tool=\"mdnice编辑器\" style='margin-top: 20px;margin-bottom: 20px;padding: 10px 20px;color: rgb(0, 0, 0);font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;background: rgb(250, 250, 250);'>\u003Csection>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">. Use this feature to perform calculations.\u003C/p>\u003Cp style=\"padding-top: 8px;padding-bottom: 8px;line-height: 26px;\">Find all the real roots of the following polynomial: 3\u003C/p>\u003C/section>\u003C/section>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>5.3 Granting the model access to specific functions\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>You can refer to Function Call - https://platform.openai.com/docs/guides/function-calling\u003C/p>\u003Ch3 data-tool=\"mdnice编辑器\" style='margin-top: 30px;margin-bottom: 15px;font-weight: bold;font-size: 20px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;letter-spacing: normal;text-align: left;text-wrap: wrap;'>6. Systematically test changes\u003C/h3>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>6.1 Use LLM evaluation frameworks\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>You can refer to OpenAI Evals - https://github.com/openai/evals\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>\u003Cstrong>6.2 Evaluate model output with reference to a gold standard answer\u003C/strong>\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>If we know that the correct answer to a question should involve a set of specific known facts, we can use model queries to calculate how many required facts are included in the answer.\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>👆This part is somewhat complex and may not be commonly needed. You can check the relevant documentation at https://platform.openai.com/playground/p/default-model-based-eval-3?mode=chat.\u003C/p>\u003Cp data-tool=\"mdnice编辑器\" style='margin-bottom: 0px;padding-top: 8px;padding-bottom: 8px;color: black;font-family: Optima-Regular, Optima, PingFangSC-light, PingFangTC-light, \"PingFang SC\", Cambria, Cochin, Georgia, Times, \"Times New Roman\", serif;font-size: 16px;letter-spacing: normal;text-align: left;text-wrap: wrap;line-height: 26px;'>More examples can be found at: https://platform.openai.com/examples\u003C/p>\u003Cp style=\"text-align: center;\">\u003Cimg class=\"rich_pages wxw-img\" data-galleryid=\"\" data-imgfileid=\"100002850\" data-ratio=\"0.8555555555555555\" data-s=\"300,640\" data-type=\"png\" data-w=\"1080\" style=\"\" src=\"./assets/17423813527520.6562769681734799.png\">\u003C/p>\u003Cp>\u003Cbr>\u003C/p>\u003Cp style=\"display: none;\">\u003Cmp-style-type data-value=\"3\">\u003C/mp-style-type>\u003C/p>\u003C/div>",[257,266,274,282,290,298,306,313],{"id":258,"title_md5":259,"publish_date":260,"author_md5":261,"is_original":23,"collection":262,"summary_md5":263,"cover_url":264,"cover_url_1_1":265},107,"b8ea1832913fcb3369f048e5316358bc","2024-12-08","bc27fa490c4d0d525bac812fc0793534","#OpenAI #AGI #LLM","d1c0f5615df398ca45dfb881172a163e","article_res/cover/1cf7f8413113e6514266fbe2928da4e1.jpeg","article_res/cover/dab451fa6db7eab696589120b2c8d178.jpeg",{"id":267,"title_md5":268,"publish_date":269,"author_md5":261,"is_original":23,"collection":270,"summary_md5":271,"cover_url":272,"cover_url_1_1":273},369,"aa88cef79cf6d154f7ac51c5f018725f","2023-12-16","#AI Image Generator #AI Animation","6f9796d53b7d00ef0d78379e27d10d36","article_res/cover/1d85e2d37ef038479ef70d74da3a2dcc.jpeg","article_res/cover/2693cb77c01973daf1e2737a95d3ef40.jpeg",{"id":275,"title_md5":276,"publish_date":277,"author_md5":261,"is_original":4,"collection":278,"summary_md5":279,"cover_url":280,"cover_url_1_1":281},275,"15751a77f7da4bcba33eff3ff5a0811a","2024-05-14","#LLM","cbfe16f9ef04dc79ba98a5cb2c23959b","article_res/cover/3ebae852d0132307cb13b9b68ead6b83.jpeg","article_res/cover/1675fc145cc31c6bdb0f404a3e7ae098.jpeg",{"id":283,"title_md5":284,"publish_date":285,"author_md5":261,"is_original":23,"collection":286,"summary_md5":287,"cover_url":288,"cover_url_1_1":289},242,"b32ac197ef4528cfc9cc7703113bcff1","2024-06-18","#AI Avatar #Lip Sync","960f63511c33c5ef68155ad69afdfa03","article_res/cover/962521d82eac2b5cf90b12ec083495d6.jpeg","article_res/cover/55537cb0bfe54667c4d8ccffaa064c1c.jpeg",{"id":291,"title_md5":292,"publish_date":293,"author_md5":261,"is_original":4,"collection":294,"summary_md5":295,"cover_url":296,"cover_url_1_1":297},401,"9f5f20c45bfe685198d2d4728416d5e8","2023-10-01","#Object Detection #AI Agent #Langchain","0f56ed93fe5ce6ef3e13890e9f0a684c","article_res/cover/2dce58eb9163407c184896e9f1ce75b4.jpeg","article_res/cover/8c8d5cac60fb88a5d02561dc86bb97a0.jpeg",{"id":299,"title_md5":300,"publish_date":301,"author_md5":261,"is_original":23,"collection":302,"summary_md5":303,"cover_url":304,"cover_url_1_1":305},192,"53d80eb16d135f8f71ac98ae64c2f535","2024-08-19","#History","acf9997cac8e4f8f15263362e9da4940","article_res/cover/4df67464bfe1776bc5eff7f08b21354f.jpeg","article_res/cover/507a86384d673bba5fd0a00d305d2421.jpeg",{"id":307,"title_md5":308,"publish_date":309,"author_md5":261,"is_original":23,"collection":146,"summary_md5":310,"cover_url":311,"cover_url_1_1":312},158,"2b056043dd406b8913e760d73066cdb5","2024-10-06","026de4fc63593ecb983f42c5a3084780","article_res/cover/71fc10c144a192161013bf7d40deb9c6.jpeg","article_res/cover/05818a2b4acb1d32cc43b1dcf6b6db12.jpeg",{"id":314,"title_md5":315,"publish_date":208,"author_md5":261,"is_original":4,"collection":316,"summary_md5":317,"cover_url":318,"cover_url_1_1":319},405,"1c169b30d542c329e065176a61c06a73","#AI Video Editor","f8ed5531f622d51c1ba6839889e2cd99","article_res/cover/fe640781e743aac4903acbe36ddda57e.jpeg","article_res/cover/f48646dafa6c7b086a8afebb640f3b3d.jpeg",{"related":321,"small":354},[322,323,331,339,346],{"id":144,"publish_date":145,"is_original":23,"collection":146,"cover_url":147,"cover_url_1_1":148,"title":149,"summary":150,"author":28},{"id":324,"publish_date":325,"is_original":23,"collection":326,"cover_url":327,"cover_url_1_1":328,"title":329,"summary":330,"author":28},262,"2024-05-28","#Google #Imagen3","article_res/cover/3fe335712c303d1908ea5f856858e907.jpeg","article_res/cover/b41734e00060ac4011afcb91fc23c02b.jpeg","Google's StyleDrop - Text-to-image generation with custom styles","StyleDrop: Text-To-Image Generation in Any Style",{"id":332,"publish_date":333,"is_original":4,"collection":5,"cover_url":334,"cover_url_1_1":335,"title":336,"summary":337,"author":338},530,"2022-05-26","article_res/cover/e6e7dfa9f1e4212e965aca0b1d570902.jpeg","article_res/cover/b0fa742d86b2b9f3815a0fd1e0cffb08.jpeg","Decentralized Society: Finding Web3’s Soul / Decentralized Society: Finding the Soul of Web3 -8","Property rights are defined in Roman legal tradition as use (usus), consume or destroy (abusus), and profit (fructus).","Translation",{"id":340,"publish_date":341,"is_original":4,"collection":5,"cover_url":342,"cover_url_1_1":343,"title":344,"summary":345,"author":338},524,"2022-06-02","article_res/cover/b13ef19dd2391b42fba642a3a7fe2235.jpeg","article_res/cover/e3253e7abd2c9d58317b9ade3fd309df.jpeg","Decentralized Society: Finding Web3’s Soul / Decentralized Society: Finding the Soul of Web3 12","5.3 Programmable Plural Privacy / Programmable Plural Privacy",{"id":347,"publish_date":348,"is_original":4,"collection":349,"cover_url":350,"cover_url_1_1":351,"title":352,"summary":353,"author":53},424,"2023-08-05","#Stable Diffusion #AI Image Generator #Tencent #ControlNet","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",[355,361,367],{"title":10,"list":356},[357,358,359,360],{"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":362},[363,364,365,366],{"id":120,"publish_date":113,"is_original":23,"collection":121,"cover_url":122,"cover_url_1_1":123,"title":124,"summary":125,"author":28},{"id":166,"publish_date":167,"is_original":23,"collection":168,"cover_url":169,"cover_url_1_1":170,"title":171,"summary":172,"author":28},{"id":227,"publish_date":228,"is_original":23,"collection":229,"cover_url":230,"cover_url_1_1":231,"title":232,"summary":233,"author":28},{"id":235,"publish_date":236,"is_original":23,"collection":73,"cover_url":237,"cover_url_1_1":238,"title":239,"summary":240,"author":28},{"title":242,"list":368},[],[8,9,10],[8,12,13,14,9,10,15,16,17,18],["Reactive",245],1754646418773]