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字幕列表 影片播放

  • The main video is talking about a genetic breeding model

    主影片是在探討遺傳育種模型

  • of how to make machines learn.

    如何使機器學習

  • This method is simpler to explain or just show.

    這種演算法比較容易解釋與呈現

  • Here is a machine learning to walk or play Mario or jump really high.

    這裡有小機器人學著走路 或學玩瑪莉歐 或學跳高高

  • A genetic code is an older code but it still checks out

    遺傳算法已經過時 但仍有用

  • and I personally suspect in the future genetic models will have a resurgence as

    而且我個人認為將來遺傳算法將會崛起

  • compute power approaches crazy pants.

    一旦電腦計算能力接近嚇死人的地步

  • However, the current hotness is deep learning and recursive neural networks and

    然而 現今最熱門的技術是深度學習和遞歸神經網絡

  • that is where the linear algebra really increases

    這也是為什麼線性代數的重要性不斷提升

  • and explainability in a brief video really decreases.

    而用簡短的影片來解釋的可行性愈來愈低

  • But if I had to kind of explain how they work

    但要我用小影片來稍微解釋它們如何運作的

  • in a footnote, just for the record, it's like this:

    只是為了點明 那會像這樣:

  • No infinite warehouse. Just one student.

    沒有無限大的教室 只有一個學生

  • Teacher Bot has the same test, but this time Builder Bot is 'Dial Adjustment Bot'

    教師演算法的考卷不變 但現在「打造者演算法」是「調節員演算法」

  • where each dial is how sensitive one connection in the student bot's head is.

    每一個旋鈕決定學生演算法腦中 每個神經連結的敏感度

  • There's a lot of connections in its head so a lot of dials.

    在它腦中有非常多神經連結 所以有非常多旋鈕

  • A LOT, a lot.

    超級 超級多

  • Teacher Bot shows Student Bot a photo and Dial Adjustment Bot adjusts that dial

    教師給學生一張圖片 同時調節員調整旋鈕

  • stronger or weaker to get Student Bot closer to the answer.

    使之更強或更弱 讓學生更接近正確答案

  • It's a bit like adjusting the dial on a radio. Is that still a thing? Do cars have radios still?

    很像是在調整收音機的頻率

  • I don't know, anyway. You might not know the exact frequency of the station

    現在還有收音機嗎? 汽車還有這東西嗎?

  • but you can tell if your getting closer or further away.

    我不知道 算了

  • It's like that but with a hundred thousand dials and a lot of math,

    你應該不知道你要聽的電台的準確頻率

  • and that's just for one test question.

    但你能夠分辨出是否接近要聽的電台

  • When Teacher Bot introduces the next photo,

    這點和這種演算法很像 但有十萬以上的旋鈕 跟一大堆數學

  • Dial Adjustment Bot needs to adjust all the dials so that Student Bot can answer both questions.

    再者 這只是針對一個問題而已

  • As the test gets longer,

    當教師拿出下一張圖片

  • this becomes an insane amount of math and fine tuning for Dial Adjustment Bot.

    調節員必須去調整所有的旋鈕 使學生能給出兩個問題的答案

  • But when it's done there's a student bot who

    隨著測試愈來愈長

  • can do a pretty good job at recognizing new photos,

    數學運算量和微調次數愈來愈龐大

  • though still suffers from some of the problems mentioned in the main video.

    但當完成時 學生演算法

  • Anyway, that the most babies' first introduction to neural networks you will ever hear.

    就能將未見過的圖片辨識得非常好

  • If it sounds interesting to you and you like math and code,

    雖然仍會遭遇一些問題 在主影片有提到

  • go dig into the details;

    總之 這是你能聽到最簡單的神經網絡之簡介

  • machines that learn are the future of everything.

    如果你很感興趣 而且你喜歡數學跟寫程式

  • Maybe, quite literally, the future of everything,

    去挖掘更多知識吧

  • and given what we've put them through, may the bots have mercy on us all.

    可以學習的機器是未來的一切

The main video is talking about a genetic breeding model

主影片是在探討遺傳育種模型

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