Tokenizer
A tokenizer splits text into units that an AI model can process.
Category
These terms cover the basic pipeline from tokenizing text to shaping model behavior.
Words for turning text into features and adapting models.
In a daily board, this category groups terms by their shared role. Look for four cards that describe the same mechanism, risk area, or workflow rather than four words that merely sound similar.
These entries are vocabulary notes for learning. They are not project endorsements, token recommendations, exchange rankings, or trading signals.
A tokenizer splits text into units that an AI model can process.
An embedding is a numeric vector that captures meaning or similarity for text, images, or other data.
Attention is a model mechanism that weighs which input parts matter most for each output step.
Fine-tuning updates a pretrained model on a narrower dataset to better fit a specific task.