AI & Tech Full Forms — AI, ML, API, CPU, GPU Explained

Last updated: Sep 2026

Artificial Intelligence and modern technology have introduced dozens of new abbreviations. Here's a comprehensive guide to AI, machine learning, cloud computing, and IoT terms that everyone should understand.

Full List of AI & Technology Terms

Abbreviation	Full Form	Meaning
AI	Artificial Intelligence	Computer systems that mimic human intelligence
API	Application Programming Interface	Tools allowing different software to communicate
AR	Augmented Reality	Technology overlaying digital content on real world (Pokemon Go)
AWS	Amazon Web Services	Cloud computing platform
BERT	Bidirectional Encoder Representations from Transformers	Google's AI model for language understanding
BIOS	Basic Input/Output System	Firmware that starts up computers
CDN	Content Delivery Network	System of servers delivering content efficiently
CSS	Cascading Style Sheets	Language for styling web pages
CSV	Comma-Separated Values	File format for data/spreadsheets
CV	Computer Vision	AI field allowing computers to "see" and interpret images
DL	Deep Learning	Advanced machine learning using neural networks
DOM	Document Object Model	Programming interface for web documents
ETL	Extract, Transform, Load	Process for data management
GPU	Graphics Processing Unit	Processor optimized for graphics and parallel processing
GUI	Graphical User Interface	Visual interface for users to interact with computers
HTML	HyperText Markup Language	Language for creating web pages
HTTP	HyperText Transfer Protocol	Protocol for transferring web pages (unsecured)
HTTPS	HyperText Transfer Protocol Secure	Encrypted version of HTTP (secure)
IoT	Internet of Things	Network of physical devices connected to internet (smart homes)
JSON	JavaScript Object Notation	Format for data exchange between applications
LLM	Large Language Model	AI trained on massive text data (ChatGPT, Claude)
ML	Machine Learning	AI that learns from data without explicit programming
MVP	Minimum Viable Product	Basic version of product to test with users
NLP	Natural Language Processing	AI field processing human language understanding
NoSQL	Not Only SQL	Database type flexible with data structure
ORM	Object-Relational Mapping	Programming technique bridging object-oriented code and databases
REST	Representational State Transfer	Architecture style for web APIs
RNN	Recurrent Neural Network	Type of neural network for sequential data
SaaS	Software as a Service	Cloud-based software accessed via internet (Google Docs, Slack)
SQL	Structured Query Language	Language for managing databases
SSL	Secure Sockets Layer	Security protocol for encrypted connections
TensorFlow	Open-source ML Library	Google's framework for machine learning
TLS	Transport Layer Security	Updated version of SSL for secure connections
VR	Virtual Reality	Immersive digital environment (VR headsets)
WebGL	Web Graphics Library	JavaScript API for 3D graphics in browsers
XML	Extensible Markup Language	Language for storing and transporting data

Frequently Asked Questions

Q: What is the difference between AI and Machine Learning?

A: AI (Artificial Intelligence) is the broad field of creating smart machines. Machine Learning (ML) is a subset of AI where systems learn from data without being explicitly programmed.

Q: What are Large Language Models (LLMs)?

A: LLMs are AI systems trained on massive amounts of text data. They can understand and generate human language (examples: ChatGPT, Claude, Bard).

Q: What is the difference between HTTP and HTTPS?

A: HTTP transfers data unencrypted (unsafe for sensitive data). HTTPS encrypts data (safe for passwords, financial info). Always use HTTPS for sensitive websites.

Q: What is an API and why is it important?

A: APIs allow different software applications to communicate and share data. Example: Weather app uses weather API to get current conditions.

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