stochastic
US /stə'kæstɪk/
・UK /stə'kæstɪk/
C2 高級
adj.形容詞隨機的
A stochastic variable, stochastic processes
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帶你回顧 2024 年電腦科學領域的重大突破 (2024's Biggest Breakthroughs in Computer Science)
10:47
- Or are the models simply repeating their training data, like so-called stochastic parrots?
或者，這些模型只是在重複它們的訓練數據，就像所謂的隨機鸚鵡？
- And so the argument is that large language models can move beyond being stochastic parents.
是以，有觀點認為，大型語言模型可以超越隨機父模型。
引力波背景終於被發現了嗎？ (Was the Gravitational Wave Background Finally Discovered?!?)
17:03
- They claim detection of the stochastic gravitational wave background, the jumbled overlap of the many many very weak but very long wavelength gravitational waves that must originate from across the known universe.
他們聲稱探測到了隨機引力波背景，即許多非常微弱但波長很長的引力波的雜亂重疊，這些引力波一定來自整個已知宇宙。
- This is similar to what the stochastic gravitational wave background should look like if it's caused by binary supermassive black holes.
這類似於如果隨機引力波背景是由雙超大品質黑洞引起的，那麼它應該是什麼樣子。
吉姆-凱瑞和柯南討論量子物理學 - "深夜與柯南-奧布萊恩"。 (Jim Carrey & Conan Discuss Quantum Physics - "Late Night With Conan O'Brien")
04:24
- incredible paper on the Stochastic phase shifting
關於隨機相移的不可思議的論文。
技術人員だけど質問ある？ | 技術支持 | WIRED.jp (統計学者だけど質問ある？ | Tech Support | WIRED.jp)
16:50
- Notice what is a stochastic process really?
注意到什麼是真正的隨機過程？
- So stochastic is just another word for random.
是以，隨機性只是隨機的另一個詞。
但人工智能影像和視頻究竟是如何工作的？| 韋爾奇實驗室特邀視頻 (But how do AI images and videos actually work? | Guest video by Welch Labs)
37:20
- The DDPM image generation process we've been looking at can be expressed using a special type of differential equation known as a stochastic differential equation.
我們一直在研究的 DDPM 影像生成過程可以用一種特殊的微分方程來表示，這種微分方程被稱為隨機微分方程。
- From here, we can consider how the distribution of all of our points evolves over time, where the motion of each point is governed by this stochastic differential equation.
由此，我們可以考慮所有點的分佈如何隨時間演變，其中每個點的運動都受這個隨機微分方程的控制。
赫爾-懷特模式 (The Hull-White model)
18:03
- We can see the stochastic differential equation that summarizes the whole wide model in this slide.
我們可以在這張幻燈片中看到總結整個廣義模型的隨機微分方程。
- And as we extrapolate, something happens to this rate and it follows some sort of behavior that is stochastic in nature.
隨著我們的推斷，這個比率會發生一些變化，並遵循某種隨機性質的行為。
Sonya Huang和Sarah Guo談人工智能的下一步發展 | Mercury Spheres (Sonya Huang and Sarah Guo on what's next in AI | Mercury Spheres)
39:21
- And so if you think about what makes large language models very different, they're stochastic in nature.
是以，如果你考慮一下大型語言模型的不同之處，它們在本質上是隨機的。
