augment
US /ɔɡˈmɛnt/
・UK /ɔ:ɡ'ment/
B2 中高級多益
v.t.及物動詞增加 ； 增大 ； 附加接頭母音字母
We need to augment our business plan
影片字幕
第02章--《孫子兵法》--發動戰爭。 (Chapter 02 - The Art of War by Sun Tzu - Waging War)
06:22
- to augment one's own strength.
18。这就是所谓的，被征服的敌人使用
孫子兵法 (The Art of War Audiobook by Sun Tzu)
49:03
- 18. This is called, using the conquered foe to augment one's own strength.
18。这就是所谓的，用征服敌人，以增强自己的实力。
英雄聯盟 Champion Spotlight: Karma, the Enlightened One LOL
06:23
- Karma players will have to carefully utilize her ultimate, Mantra, to augment her basic abilities and make clutch offensive or defensive plays.
卡瑪玩家要小心翼翼地利用她的終極技能 "咒語 "來增強她的基本能力，並做出關鍵的進攻或防守動作。
擺盤為什麼很重要？眼睛所見如何影響食物風味 (Visual Illusions That Could Trick Our Taste Buds And Persuade Us To Eat Healthier)
05:34
- Sound can augment our perception of flavor and taste.
聲音能夠擴增我們對風味與味覺的感知。
所以，你想成為一名放射科醫生[Ep. 16]。 (So You Want to Be a RADIOLOGIST [Ep. 16])
13:06![所以，你想成為一名放射科醫生[Ep. 16]。 (So You Want to Be a RADIOLOGIST [Ep. 16])](https://thumbnail.voicetube.com/w/480/h/270/DzpjRBLnKEM.jpg)
- it will likely augment and make their job easier rather than outright replace them.
它很可能會增強並使他們的工作更容易，而不是完全取代他們。
人工智能工程：初學者的現實路線圖 (AI Engineering: A Realistic Roadmap for Beginners)
15:53
- And you need to understand what embeddings are, how you store data in, for example, a vector database, how you retrieve that data and how retrieval augmented generation works within an LLM or within some kind of AI system to put it simply, this means kind of extracting relevant information and passing it to an LLM to augment the information that it has.
你需要了解什麼是嵌入，如何在矢量數據庫中存儲數據，如何檢索數據，以及如何在 LLM 或某種人工智能系統中進行檢索增強生成，簡單地說，這意味著提取相關資訊並將其傳遞給 LLM 以增強其所擁有的資訊。
AI 架構是什麼？LLM、RAG 和 AI 硬體一次搞懂！ (What Is an AI Stack? LLMs, RAG, & AI Hardware)
09:06
- Also known as RAG vector databases is the step where that external data is actually vectorized into embeddings that are saved so your model can retrieve that context more quickly and augment it with this additional knowledge that the base model does not have.
向量資料庫，也就是 RAG，這個步驟會將外部資料向量化成嵌入式，然後儲存起來，這樣你的模型就能更快地檢索到這些內容，並用模型本身沒有的這些額外知識來增強它。