Vector
A list of numbers representing data in multi-dimensional space. In AI, vectors (embeddings) encode semantic meaning of text or other data.
In-Depth Explanation
In AI, a vector is an ordered list of numbers that represents data in a mathematical space. Vectors are fundamental to how AI systems process, compare, and reason about information.
Vector concepts:
- Components: Individual numbers in the vector
- Dimensions: How many numbers (length of the list)
- Magnitude: Length of the vector (distance from origin)
- Direction: Orientation in space
Vectors in AI:
- Embeddings: Text/images converted to vectors
- Features: Input characteristics as vectors
- Hidden states: Internal model representations
- Gradients: Direction of improvement during training
Vector operations:
- Addition: Combining vectors
- Dot product: Measure of alignment
- Cosine similarity: Angle-based comparison
- Distance: How far apart vectors are
Why vectors matter:
- Enable mathematical operations on text/images
- Support similarity comparisons
- Foundation for semantic search
- Allow efficient storage and retrieval
Business Context
Vectors enable semantic operations - comparing, searching, and clustering content by meaning rather than exact matches.
How Clever Ops Uses This
Vectors underpin all our RAG and semantic search implementations for Australian businesses. Understanding vectors helps explain how AI finds related content.
Example Use Case
"A sentence converted to a 1536-dimensional vector for semantic search, enabling finding similar content by meaning."