# AI Terms You Need to Know: Agents, RAG, ASI & More

Here are a few AI terms that everyone that designs solutions using AI should know.

## Agentic AI

Here's a Copilot-provided answer to what this is - "Agentic AI is artificial intelligence that can set goals, make decisions, and take actions autonomously with minimal human input."

## Large reasoning model

An AI system trained to solve complex problems by breaking them down into logical steps, often mimicking human-like reasoning to produce more accurate and explainable results.

## Vector database

A vector is essentially a long list of numbers which captures the semantic meaning of the context.

A picture can be broken down to a vector.  A semantic search to search for a picture would be to match the semantic details of the vector.

## RAG

Retrieval-augmented-generation makes use of vector databases.

```prompt > retriever > embedding model > similiarity search in vector database > return results to user```

## MCP - Model Context Protocol

To make LLM connect to a database or a code repo, or any external system, MCP makes the connection standardized.

```LLM > MCP server > database / code repo / email server```

## MoE - Mixture of Experts

Provides LLMs, specialized neural subnetworks routed to expert agents which then return results back from the multiple experts.

## ASI - Artificial Super Intelligence

Purely theoretical, ASI would potentially and recursively improve itself.  Nobody knows if this will ever exist.

## AGI - Artificial General Inteligence

A type of AI that can perform any intellectual task a human can do—with equal or greater proficiency.