想知道你的文字在 AI 座標軸裡長什麼樣子？點進來，一起把語言變成超酷的數學地圖！

AI is basically a math-obsessed 3-year-old! It doesn't read words; it processes numbers.

Curious how your words look in a multi-dimensional universe? Let’s turn language into a cool mathematical map!

#tokenization , #WordEmbedding #dotproduct #transformer #Word2Vec. #AI #人工智慧 #Token#分詞 #維度 #內積 #注意力機制 #nlp #AIVernacular #AI白話文 #電腦如何理解語言

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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

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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

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很多人說 LLM只是文字接龍，你覺得呢?

我只是想要被理解，如果是的話我該怎麼辦?

RNN(循環神經網路)作為神經網路三大巨頭之一，他也有不行的時候。

因此Transformer發下狂語說: 「All you need is attention.」那些RNN不能解決的就交給我吧。

Many people say that LLMs are just doing text continuation.

What do you think?

Sometimes a sentence like this appears:“I just want to be understood. If that’s the case, what should I do?”

Even RNNs (Recurrent Neural Networks) — one of the three major types of neural networks — have situations where they struggle.

Then Transformer came along and boldly declared:“All you need is attention.”

The problems that RNNs cannot solve? Leave them to me.

#llm #ai #transformer #selfattention #neuralnetworks #rnn #largelanguagemodels #crazybitwithyu

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很多人會說 有了AI的幫忙，技術不再是問題，但我不知道主題要做什麼啊?

確實技術不再是問題了，但必須在一開始就做好發想的準備和練習，好好地創造，想清楚why and what，天馬行空的瘋狂想像一番，有計畫的制定每個步驟，創意和想法才是最重要的第一步。

If AI makes a mistake, call it a 'Beta test'; if you make a mistake, call it an 'Artistic choice'.

Keep dreaming big and stay legendary! :)

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