프롬프트 엔지니어링보다 RAG를 못하면 AI에게 제대로된 답변받을수 없습니다ㅣAI개발 유튜버 테디노트(AI 팟캐스트 #20) @teddynote

📝Summary
In this podcast, we have Teddy, and it will be great content to help you understand langchain and rag.
RAG is a technique that helps large language models (LLMs) provide higher quality answers.
If you convert your PDF document to Markdown format, GPT can easily process it.
Additionally, the performance of GPT can be improved through methods such as leveraging databases and using search algorithms.
This video shows you how to use rag and GPT.
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📌AI Utilization Peak Podcast is with @yuniquekr.
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⏰Time stamp
00:00:00 🎙️Teddy’s story about data analysis and artificial intelligence.
00:04:16 👀Sharing insights on Langchain programming and service production
00:08:01 🤖Difference in usability and development background between chat gpt and rag
00:10:02 💡Using rag in business: storing information and creating personalized GPTs.
00:12:13 💻ChatGPT upgrade and Wag system analysis
00:14:33 📄Convert PDF to Markdown format to make it easier to understand GPT.
00:17:31 🌐Website processing, natural language processing, and consideration of Korean language specialties
00:16:37 🧠Corporate data processing: PDF and word document conversion, vector DB
00:21:16 Understanding Pangyo restaurant keywords, GPT search method, and similarity search
00:26:06 ️💻Coding, AI services, language comparison: GPT vs Claude 3
00:30:19 ️📊Looking at the potential benefits of detailed corporate rag utilization and analysis.
00:37:14 ️🚘Introducing rag software that operates without coding related to autonomous driving
00:40:53 Tunable options in source text.
00:43:10 ️💻How to utilize the features and integration of automatic translation and summary services
00:47:42 💻Sampling tools using coding, prompts, LLM programs, etc.
00:50:26 🔬Prompt Engineering Methodology and the Importance of Model Optimization
00:52:36 🧩The importance of transparency, improved performance, and fine-tuning of answers using RAG
00:57:22 Coding academy registration and understanding of Prompt Engineering
01:02:04 🔍Comparison of GPT model and rag model, emphasizing the importance of experience through rag
01:03:08 🎙️YouTube trends and content strategy
01:08:05 📄The importance of utilizing Relive documents and collecting and arranging information
01:11:15 💬Importance of document summarization and similarity to human behavior
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✅Tag
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