AI BriefingCursor's New Model (1 min read)
Key point
Explains the concept and role of Model Weights, a core component of LLMs, through an analogy.
Details
Model Weights, one of the core components of an LLM, are values that quantify how much influence each input has on the result.
For example, when predicting the probability of arriving at the airport on time, there are various inputs such as traffic volume, departure time, and distance to the airport. Here, the Importance that determines how much each factor affects the result is exactly the weight.
In LLMs, these weights consist of numbers in Float form and are stored as a single file. This file containing the numerical data is itself the Model, and the structure works by loading the weights into memory and then inputting tokens to produce an output.
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