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AI繪圖教學投影片:AI繪圖教學 x 教AI學習繪圖 / AI Image Generation in Education: From Learning to Draw to Teaching AI to Draw

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AI繪圖教學投影片:AI繪圖教學 x 教AI學習繪圖 / AI Image Generation in Education: From Learning to Draw to Teaching AI to Draw

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為了讓大家瞭解如何使用提示詞來進行AI繪圖,本次教學以Kera AI為繪圖平台,一步一步帶領大家從簡單的提示詞、提示詞的變化,到使用圖片來引導繪製圖片。最後則是介紹更進階的控制圖片技巧,希望成為大家踏入AI繪圖領域的敲門磚。

To help everyone understand how to use prompts for AI art generation, this tutorial uses Kera AI as the drawing platform and will guide you step-by-step from simple prompts, variations of prompts, to using images as references. Finally, we will introduce more advanced image control techniques, hoping to serve as a stepping stone for everyone entering the field of AI art.

Short URL: https://l.pulipuli.info/24/hsc

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雜談:弱電箱換上了MikroTik路由器 / TALK: I Placed a MikroTik Router in the Low-Voltage Wiring Box

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雜談:弱電箱換上了MikroTik路由器 / TALK: I Placed a MikroTik Router in the Low-Voltage Wiring Box

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由於放在弱電箱裡面的無線基地臺一直當機,這次索性購買了MikroTik路由器RB450Gx4來用用看。這款號稱最適合放在弱電箱裡面的路由器,究竟會是如何呢?

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LLL開發平臺「畢昇」實測:令人驚豔的溯源定位功能 / LLL Development Platform "BISHEN" Hands-On: Impressive Source Locating Function

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LLL開發平臺「畢昇」實測:令人驚豔的溯源定位功能 / LLL Development Platform "BISHEN" Hands-On: Impressive Source Locating Function

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雖然大家都知道RAG可以將檢索結果交給大型語言模型回答,不過到底交給大型語言模型的是那些檢索結果?這些檢索結果又對應到那些文件?LLM開發平臺「畢昇」在檢索功能漂亮地解決了上述的問題,應可成為RAG應用中值得參考的標杆。

While everyone knows that RAG can submit retrieval results to large language models (LLMs), what exactly are those retrieval results submitted to LLMs? And which documents do these retrieval results correspond to? The LLM development platform, BISHENG, elegantly addresses these questions in its retrieval function and can serve as a valuable benchmark for RAG applications.

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雜談:課程網頁的變遷 / TALK: Changes in Course Web Pages

雜談:課程網頁的變遷 / TALK: Changes in Course Web Pages

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我的課程網頁從Google DocGoogle Doc網頁Google Doc Publisher,到現在終於進入到Google Sites了!這篇就來講講這段期間我設置課程網頁方案的演進吧。

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演講投影片:大型語言模型在工業領域的潛力 / Slide: The Potential of Large Language Models in Industrial Fields

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演講投影片:大型語言模型在工業領域的潛力 / Slide: The Potential of Large Language Models in Industrial Fields

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大型語言模型(Large Language Model)成為AI浪潮之後下一個新的寵兒,它彷彿真人般的對談和創造力的發想對研究和教育上帶來了無數啟發。但是大型語言模型在要求精確的工業領域裡面,究竟可以扮演什麼角色呢?本次演講先講述工業5.0發展中對於大型語言模型的需求,再來講述工業領域應用大型語言模型的實例,最後介紹大型語言模型和檢索生成增強的相關技術作為結尾。如果你也想在產業應用大型語言模型的話,不妨先看看這份投影片,瞭解一下現況吧。

Large Language Models (LLMs) have become the next big thing in the wake of the AI wave, offering human-like conversation and creative brainstorming that have inspired countless research and educational endeavors.  But what role can LLMs play in demanding industrial fields that require precision? This presentation will first discuss the need for LLMs in the development of Industry 5.0, followed by examples of LLM applications in industrial settings. Finally, it will conclude with an introduction to related technologies like Retrieval-Augmented Generation. If you are also interested in applying LLMs in industry, take a look at this presentation to understand the current landscape.

Short URL: https://l.pulipuli.info/24/nkust  

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RAG簡介投影片:現況、原理、發展 / RAG Introduction Slides: Current Status, Mechanisms, and Development

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RAG簡介投影片:現況、原理、發展 / RAG Introduction Slides: Current Status, Mechanisms, and Development

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這份投影片對檢索生成增強(Retrieval-Augmented Generation, RAG)的觀念作一個容易理解的介紹,也是「資訊檢索的AI革新:從資訊檢索到檢索增強生成」這篇的簡化版本。一般說到AI大家都會想到創造力、彷彿真人的表現,但RAG本質上更接近資訊檢索的問題。把它當作資料庫就很容易理解RAG的用途了。

This presentation provides an accessible introduction to the concept of Retrieval Augmented Generation (RAG), and is a simplified version of "The AI Revolution in Information Retrieval: From Information Retrieval to Retrieval-Augmented Generation". When people talk about AI, they often think of creativity and human-like performance, but RAG is essentially closer to the problems of information retrieval. Thinking of it as a database makes it easier to understand the purpose of RAG.

Fixed Short URL: https://l.pulipuli.info/24/nccu/rag 

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希希助教的情人巧克力會送給最認真的同學喔! / TA. Sissi's Valentine's Day Chocolates Will Go to the Most Hardworking Student!

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希希助教的情人巧克力會送給最認真的同學喔! / TA. Sissi's Valentine's Day Chocolates Will Go to the Most Hardworking Student!

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你就是那位認真的同學嗎?

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