AI Concepts Explained

How AI Actually Works
No PhD Required

Understanding the magic behind ReplyHub's lightning-fast AI responses. Explained like you're talking to a friend, not reading a textbook.

Chunking: Breaking Down Knowledge
How we slice your documents into bite-sized pieces for AI consumption
Think of chunking like making a smoothie. You can't throw a whole apple into a blender - you need to cut it into pieces first. Same with AI and documents. When you upload a 50-page research paper, we can't feed the entire thing to the AI at once. Instead, we: 1. **Split it into chunks** - Usually 500-1000 words each 2. **Keep related content together** - We don't randomly chop sentences 3. **Add context clues** - Each chunk remembers where it came from **Why does this matter?** - 🎯 **Accuracy**: Smaller chunks = more precise answers - ⚡ **Speed**: Less text to process = faster responses - 💰 **Cost**: Only send relevant chunks, not entire documents **The Tradeoff:** - More chunks = slower but more accurate - Fewer chunks = faster but might miss details Think of it like asking a librarian vs. reading the whole library yourself.
Real Example

When you ask "What are the side effects of aspirin?", we don't send your AI a 100-page medical textbook. We send just the 3-4 chunks about aspirin side effects.

ReplyHub Edge

Our smart chunking keeps related sentences together, so you get complete thoughts, not random fragments.

Speed Impact

5 chunks = ~200ms response | 25 chunks = ~800ms response

Time to First Token (TTFT): The "Typing" Speed
How fast the AI starts "typing" its response
API Lag: The Network Journey
How long your request takes to travel through the internet
RAG: Giving AI a Memory
How we make AI experts in your specific knowledge
Embeddings: Teaching AI to "Understand" Text
How we convert words into numbers that AI can search through

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