Tag: vector

Foundation Model

Posted on by lechuck park

From Claude with some prompting
This image depicts a high-level overview of a foundation model architecture. It consists of various components including a knowledge base, weight database (parameters), vector database (relative data), tuning module for making answers, inference module for generating answers, prompt tools, and an evaluation component for benchmarking.

The knowledge base stores structured information, while the weight and vector databases hold learnable parameters and relative data representations, respectively. The tuning and inference modules utilize these components to generate responses or make predictions. Prompt tools assist in forming inputs, and the evaluation component assesses the model’s performance.

This architectural diagram illustrates the core building blocks and data flow of a foundation model system, likely used for language modeling, knowledge representation, or other AI applications that require integrating diverse data sources and capabilities.

Scalar, Vector, Matrix, Tensor

Posted on by lechuck park

From DALL-E with some prompting
This image appears to be a diagram explaining the concepts of scalar, vector, matrix, and tensor in the context of dimensions and data structures:

Scalar: Represented as a zero-dimensional entity and is simply a single value that exists.
Vector: Shown as one-dimensional, it is depicted as an arrow, indicating a feature or a point with direction and magnitude.
Matrix: Illustrated as two-dimensional, like a grid, representing connected data points.
Tensor: Described with ‘N dimension’, suggesting a complex structure where all elements are interconnected, like a network of points extending beyond two dimensions. This progression shows how data structures become more complex and capable of representing more intricate relationships as the number of dimensions increases.