AI Dictionary › AI Models
Livello di input
The input layer is the first layer of a neural network, the one that receives the raw data to be processed and presents it to the rest of the network in a numerical form suited to subsequent computation. It does not perform learned transformations like other layers: its job is to organize incoming data, for example the pixels of an image or the token identifiers of a text, into the numerical structure expected by the following layers.
The shape of the input layer depends on the type of data the model must process: in a network working on images, each input neuron may correspond to the value of a single pixel or color channel; in a language model, the input is not directly numerical but first passes through an embedding layer that converts token identifiers into dense vectors. In this second case, the embedding layer can be considered the network's true numerical entry point.
It is present in every neural network and is the mandatory starting point of every computation: it defines how much and what kind of data the model can receive in a single pass, and its size is constrained by the nature of the problem, for example the resolution of images or the maximum length of a text sequence the model can handle.
The term describes its function directly: it is the layer through which information enters (input) the network, the point from which every subsequent transformation carried out by the hidden layers and the output layer begins.
From our network
Magellano GPS: Fleet Tracking Made Simple
Real-time GPS tracking, remote engine lock, fuel and CO₂ reporting for your fleet.
Visit magellanogps.com →From the Agora Intelligence blog
📱 Download the Android app (beta) iOS coming soon
Say what you mean. Get what you need.
Grace Certified, the AI coach that trains and certifies your prompt engineering, by Agora Intelligence.