Vector Simulator
Visualize how semantic search works. See text embeddings projected to 2D and find similar documents.
Embedding Space
Similar texts appear closer together
Similarity Search
Documents (10)
Machine learning is a subset of artificial intelligence
Deep learning uses neural networks with many layers
Natural language processing helps computers understand text
Computer vision enables machines to interpret images
Reinforcement learning trains agents through rewards
The weather today is sunny and warm
I love cooking Italian pasta dishes
Basketball is an exciting team sport
Python is a popular programming language
Data science combines statistics and programming
How It Works
This simulator demonstrates how vector similarity search works. In production, text is converted to high-dimensional vectors (embeddings) using models like OpenAI's text-embedding-ada-002.
- • Similar concepts cluster together in the embedding space
- • Cosine similarity measures how related two texts are
- • This visualization uses a simplified hash-based projection
- • Real embeddings have 1536+ dimensions