[BitOfAI] AI本質是函數 | (類)神經網路的老派浪漫(下) - The Essence of AI is a Function: The "Old-School Romance" of Neural Networks

分清「貴賓狗還炸雞」也可 f(x)嗎? 雖然當紅的是「生成式 AI」，但其核心底層始終是「(類)神經網路」，很多人會跳過神經網路，還來不及了解"傳統AI"在做什麼，就直接學習當紅酷炫的"生成式AI"理論。這就像在不穩固的地基上蓋房子，其實是有點可惜且危險的。 從基礎的「辨識」任務(例如分清貴賓狗還是炸雞！)，到先進的「生成」任務，這是一脈相承的技術演進。本影片帶大家回到原點，理解AI如何從神經網路找出完美的f(x)函數。 AI的理論世界豐富且各具風情，鼓勵大家先從簡單的神經網路扎根，在往後探索LLM或Transformer的奧秘。讓我們一起享受探索學習的樂趣吧！　：Ｄ Can Distinguishing "Poodle or Fried Chicken" be f(x), too? Neural Networks are the essential foundation of everything we see in AI today. Nowadays, it’s tempting to jump straight into the flashy world of Generative AI, but skipping the "Traditional AI" basics is like trying to build a skyscraper on a shaky foundation. The journey from "Recognition" (like telling a poodle from fried chicken!) to "Generation" (creating something brand new) is a continuous path of learning. In this video, we go back to the roots to understand how AI finds the perfect f(x) function through neural networks. AI theory is a vast and beautiful landscape with many different "flavors." I encourage everyone to master the simple basics of neural networks first before diving deeper into the wonders of LLMs and Transformers. Let’s explore this amazing world of learning together! #genai #ai #neuralnetworks #function #fofx #llm #crazybitwithyu #transformer #poodle #friedchicken -- Hosting provided by SoundOn