AI 360

How does AI know what the word “it” refers to in a sentence?

That’s where the Attention mechanism comes in.

Each token creates a Query, Key, and Value. The model compares them to calculate which words are most relevant to each other.

In this example, Attention helps the model connect “it” back to “battery” and understand the sentence correctly.

This simple idea is one of the foundations of modern Transformers and Large Language Models.

Should I visualize Multi-Head Attention next?

#AttentionMechanism #Transformers #ArtificialIntelligence

3 weeks ago | [YT] | 0

AI 360

How can an AI answer questions about documents it was never trained on?

The answer is RAG — Retrieval-Augmented Generation.

Instead of relying only on its memory, the AI searches a collection of documents, converts your question into vectors, retrieves the most relevant context, and gives that information to the LLM.

The result is a more relevant, grounded, and traceable answer.

Which part should I visualize next: embeddings, vector databases, or document chunking?

#RAG #AIAgents #LLM

3 weeks ago | [YT] | 0

AI 360

Ever wondered what actually happens after you give an AI agent a prompt? 👀

It doesn’t jump straight to the final answer.

First, it understands your request. Then it pulls useful context from memory, decides which tools to use, runs the task, and verifies the result before responding.

That’s the basic idea behind modern AI agent architecture:

Observe → Plan → Act → Verify → Repeat.

Which part should I explain next: AI memory, tool use, or multi-agent systems?

#AIAgents #ArtificialIntelligence #LLM

3 weeks ago | [YT] | 0