Tuesday Morning: AI & Machine Learning Vocabulary 🌅

Good morning! Tuesday’s theme is AI & Machine Learning — the vocabulary you need when you’re explaining an LLM feature to a non-technical stakeholder, debugging a RAG pipeline out loud with a teammate, or just talking about your work at a meetup. Today’s word is one every engineer says a dozen times a day but rarely says clearly: inference.

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🌟 Word of the Day: Inference

IPA Pronunciation: /ˈɪnfərəns/

Vietnamese: quá trình model đưa ra dự đoán/kết quả từ input (khác với training — lúc này model không học thêm, chỉ áp dụng những gì đã học)

3 Example Sentences:

1. “Training this model took three days, but inference only takes 200 milliseconds per request.”
2. “We moved inference to a smaller quantized model to cut our GPU costs in half.”
3. “The latency spike wasn’t in the network layer — it was inference time on the larger model.”

Learn more:

• Cambridge Dictionary — inference
• YouGlish — hear “inference” in real videos
• What is Inference? — IBM Technology (YouTube)

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📚 Vocabulary Table: AI & Machine Learning

Phrase	Vietnamese	Example
hallucinate	model tạo ra thông tin sai nhưng nghe có vẻ đúng	“The model hallucinated a function that doesn’t exist in our codebase — always verify generated code before merging.”
fine-tune	huấn luyện thêm một model có sẵn trên dữ liệu chuyên biệt	“We fine-tuned the base model on our support tickets so it understands our product terminology.”
latency	độ trễ, thời gian chờ giữa request và response	“Users start noticing latency above 300 milliseconds — that’s our budget for the whole pipeline.”
retrieval	truy xuất thông tin liên quan trước khi model tạo câu trả lời (phần “R” trong RAG)	“Retrieval quality matters more than prompt engineering — if you fetch the wrong documents, no prompt will save you.”
context window	giới hạn lượng văn bản model có thể “nhìn thấy” cùng lúc	“We hit the context window limit, so we had to summarize the earlier conversation before continuing.”

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🗣️ Pronunciation Guide

Let’s break down inference /ˈɪnfərəns/ syllable by syllable:

• in- → /ɪn/ — short “i,” like in “bin”
• -fer- → /fər/ — unstressed, almost swallowed — sounds like “fer” in “offer”
• -ence → /əns/ — soft ending, don’t over-pronounce the final “e”

⚠️ Common mistake: Vietnamese speakers often stress the second syllable (“in-FER-ence”) — but native speakers put the stress on the first syllable: “IN-fer-ence.” The rest trails off quickly.

Practice sentence — read this out loud 3 times:

“Our inference latency dropped after we fine-tuned a smaller model for retrieval.”

Say it slowly the first time, focus on stress the second time, then read it at natural speed the third time.

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✍️ Exercises

Exercise 1: Fill in the blank

1. “The chatbot ______ a customer’s account number — it just made it up.” (hallucinated)
2. “We need to ______ this model on our internal documentation before launch.” (fine-tune)
3. “Our ______ pipeline fetches the top 5 documents before the model generates an answer.” (retrieval)

Show Answers

1. hallucinated
2. fine-tune
3. retrieval

Exercise 2: Translate to English

1. “Việc training mất ba ngày, nhưng inference chỉ mất vài trăm mili giây.”
2. “Model bị hallucinate khi chúng tôi hỏi về một tính năng chưa tồn tại.”
3. “Chúng tôi đã fine-tune model để giảm độ trễ (latency).”

Show Answers

1. “Training took three days, but inference only takes a few hundred milliseconds.”
2. “The model hallucinated when we asked about a feature that doesn’t exist.”
3. “We fine-tuned the model to reduce latency.”

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💬 Idiom of the Day: “Under the hood”

Vietnamese meaning: bên trong, cơ chế vận hành thực sự (thường dùng khi nói về phần kỹ thuật ẩn sau một giao diện đơn giản)

Examples:

1. “The chatbot looks simple to users, but under the hood it’s running retrieval, reranking, and three separate model calls.”
2. “Don’t worry about what’s under the hood for this demo — just show the product manager the final output.”

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📺 Recommended Watching

• IBM Technology — Inference vs. Training explained (YouTube)
• YouGlish: “inference” in real tech talks
• 3Blue1Brown — How LLMs actually work (YouTube)

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🎯 Today’s Challenge

Next time you talk about an AI feature at work — in standup, in a PR description, anywhere — say “inference” and “latency” out loud instead of writing them silently. Stress the first syllable of inference: “IN-fer-ence.” Speaking technical words before you type them is one of the fastest ways to make pronunciation stick.

See you this evening for practice! 🚀