Computer Terms in Plain Language: What TTS, STT, API, RAG, and Agent Really Mean

Tue, 12 May 2026 22:15:34 +0800

Computer science has many terms that sound advanced the first time you hear them. But once translated into plain language, many of them describe everyday actions.

For example, when AI can speak, it is called TTS; when AI can listen to you, it is called STT. It sounds like a complex system, but the simple version is “read text aloud” and “write down speech.”

Reference link: https://www.zhihu.com/question/267978646/answer/2035405228460201515

This article strings together several common terms from that angle: keep the terms themselves, but explain them in plain language.

TTS and STT: Converting Between Text and Speech

TTS means Text-to-Speech. It converts a piece of text into playable audio. Navigation announcements, audiobook reading, AI customer service voices, and voice assistants all use this kind of capability.

STT means Speech-to-Text. It does the reverse: it turns spoken audio into text, then passes that text to the next program. Voice input, meeting transcription, automatic subtitles, and smart speakers all rely on STT.

Many voice AI products are basically this pipeline:

STT: convert what you said into text.
LLM: generate a reply from that text.
TTS: read the reply aloud.

So it may feel like a natural conversation, but underneath, several modules are handing work to one another.

OCR: Copying Text Out of Images

OCR means Optical Character Recognition.

In plain language, it copies text out of images. Taking a photo of an invoice, scanning a page from a book, or reading a name and ID number from an identity document are all OCR tasks.

Early OCR was closer to “guess the character shape.” Modern OCR uses deep learning and is more tolerant of messy backgrounds, tilted text, handwriting, and blurry images. But the core question remains simple: what words are in the image?

NLP and LLM: Letting Machines Handle Human Language

NLP means Natural Language Processing. It deals with human language: tokenization, translation, summarization, sentiment analysis, question answering, classification, and more.

LLM means Large Language Model. It can understand and generate text, so many NLP tasks today are handled by LLMs.

Plain-language version:

NLP: make machines process what people say and write.
LLM: a larger text model that can handle many language tasks.

When you ask AI to summarize an article, write an email, polish a title, or explain code, it all belongs to this broad direction.

API and SDK: One Is an Interface, the Other Is a Toolkit

API means Application Programming Interface.

In plain language, someone exposes an entry point for you to call a capability. A weather API takes a city and returns weather; a payment API takes an order and returns a payment result.

SDK means Software Development Kit.

In plain language, the official team packages common code, types, examples, and tools so you can call the API more easily. An API is like the restaurant counter; an SDK is like the ordering app. You can talk to the counter directly, or use the app to make ordering easier.

CRUD: Create, Read, Update, Delete

CRUD means Create, Read, Update, and Delete.

In plain language: add, view, edit, and delete.

Many admin systems, management systems, and database operations revolve around CRUD. User management, article management, order management, and inventory management may look like different businesses, but underneath they are often forms plus create/read/update/delete operations.

That is why programmers say they wrote “another CRUD.” It is not necessarily dismissive; it is simply very common.

Cache: Keep a Copy So You Do Not Recompute Every Time

Cache means caching.

In plain language, keep frequently used things close by so you can grab them directly next time instead of searching, computing, or requesting them again.

Web pages can cache images and scripts; slow database queries can put hot results in Redis; expensive model inference can cache answers to repeated questions.

The hard part of caching is not “keeping a copy,” but “knowing when to update it.” If the data changes but the cache does not, users see stale data. That is the root of many cache problems.

Queue: Line Up Tasks and Process Them Slowly

Queue means a queue.

In plain language: too many things are happening, so put them in line and process them one by one.

For example, after a user uploads a video, transcoding may not finish immediately. The system can put the job into a queue and let a background service process it later. Sending SMS messages, emails, reports, and order callbacks also commonly use queues.

Queues solve the problem of not blocking the current request with every slow task. The user gets a response first, and time-consuming work happens later.

Index: A Table of Contents for the Database

Index means an index.

A database index is like a table of contents in a book. Without it, you may need to scan from the first page to the last page; with it, you can locate content much faster.

But more indexes are not always better. Queries may become faster, while writes and updates may become slower, because the index also needs to be maintained when data changes.

That is why database optimization often starts with indexes. But when creating one, you still need to consider query conditions, sorting fields, data volume, and write frequency.

RPC, REST, and Webhook: How Systems Talk to Each Other

RPC means Remote Procedure Call.

In plain language, it lets you call a function on another machine as if it were a local function.

REST is common in Web APIs. It uses URLs and HTTP methods to describe operations on resources, such as GET /users to query users and POST /orders to create orders.

Webhook is a callback in the opposite direction. Instead of constantly asking “is it done?”, the other side calls your URL when something happens.

Simple memory aid:

RPC: call a remote function.
REST: manage resources with HTTP.
Webhook: notify you when something happens.

CDN means Content Delivery Network.

In plain language, put static resources on nodes closer to users. When users access images, videos, CSS, or JS, they do not always have to reach the origin server.

Load Balancing means load balancing.

In plain language, when traffic is too high, do not make one server carry everything; distribute requests across multiple machines.

One is about being closer to users; the other is about not exhausting one machine. Large websites usually use both.

Docker, Container, and Kubernetes: Package, Run, and Schedule

Docker is a common container tool, and Container means container.

In plain language, package the program together with its runtime environment so it can run similarly on another machine. This reduces “it works on my computer but not on the server” problems.

Kubernetes, often written as K8s, is a container orchestration system.

In plain language, when there are many containers, it decides where they run, how to restart them if they fail, how to route traffic, and how to roll out versions.

If you only have one small service, Docker may be enough. If you have many services, machines, and replicas, K8s becomes more useful.

CI/CD: Automated Build and Deployment

CI means Continuous Integration.

In plain language, whenever code is submitted, the system automatically pulls the code, runs tests, and builds it to catch problems early.

CD can mean Continuous Delivery or Continuous Deployment.

In plain language, after the build passes, the code is delivered to testing or production environments in a more stable and automated way.

It does not solve “how to write code”; it solves “how to ship code with fewer mistakes.”

Serialization: Pack Objects Into a Transmittable Format

Serialization means turning objects inside a program into a format that can be saved or transmitted, such as JSON, XML, or Protobuf.

The reverse, Deserialization, turns those formats back into objects the program can use.

When frontend and backend exchange JSON, or services exchange Protobuf, serialization is involved.

Token, Embedding, and Vector DB: Turning Text Into Forms Models Can Process

In large models, Token usually refers to the basic units that text is split into. It is not necessarily one Chinese character or one English word; it is more like the model’s internal granularity for processing text.

Embedding means an embedding vector.

In plain language, it turns text, images, or other content into a sequence of numbers so models can compare similarity.

Vector DB means vector database.

In plain language, it stores those vectors and can quickly find content with similar meaning.

For example, if you ask “how do I reset my router?”, the system may search the vector database for content about “factory reset,” “forgot Wi-Fi password,” or “admin login failure,” then pass related materials back to the model.

RAG: Search First, Then Answer

RAG means Retrieval-Augmented Generation.

In plain language, before the model answers, it first searches a knowledge base and then answers with those materials.

It addresses the problem that large models may make things up from memory. By connecting enterprise documents, knowledge bases, product manuals, or code snippets, the model can refer to your latest materials instead of relying only on training memory.

A typical flow is:

The user asks a question.
The system turns the question into an Embedding.
It searches related documents in a Vector DB.
It sends the document snippets and the question to an LLM.
The model generates an answer.

So RAG sounds advanced, but the essence is: look up the materials first, then organize the answer.

Agent: An Automated Flow That Can Break Down Tasks

In AI contexts, Agent often means an intelligent agent.

In plain language, it does not just answer one message. It can break a goal into steps, call tools, observe results, and decide the next action.

For example, if you ask it to analyze why tests fail in a repository, a regular chat model may only give suggestions. An Agent may read files, run tests, inspect errors, edit code, and run tests again.

Of course, Agent does not mean guaranteed reliability. It is essentially “model + tool calling + state loop.” Whether it works well depends on tool permissions, task boundaries, error handling, and human confirmation.

Summary

Many computer terms sound impressive because they are wrapped in acronyms, architecture diagrams, and product copy. Once unpacked, many describe very simple actions:

TTS: read text aloud.
STT: write down speech.
OCR: copy text out of images.
API: expose a calling entry point.
SDK: package calling tools.
CRUD: create, read, update, delete.
Cache: keep a copy of common results.
Queue: line tasks up for later processing.
Index: add a table of contents to data.
CDN: put content closer to users.
Load Balancing: distribute requests.
Docker: package the runtime environment.
CI/CD: automate testing and deployment.
Embedding: turn content into numeric vectors.
RAG: search first, then answer.
Agent: let a model use tools step by step.

The terms should be preserved because they make searching, communication, and documentation easier. But you do not need to be intimidated by them. Translate them into plain language first, then return to the technical details; many concepts become much clearer.

Reference

Zhihu answer: https://www.zhihu.com/question/267978646/answer/2035405228460201515

Computer Terms on KnightLi Blog