Artificial intelligence big model refers to a large-scale neural network model constructed by deep learning technology. These models have hundreds of millions of parameters and can train a large amount of data, thus showing strong language understanding, generation and reasoning ability in various tasks and fields.

The main feature of artificial intelligence model is that it has extensive language knowledge and understanding ability through pre-training large-scale data sets. Then, these models can be fine-tuned for specific tasks to meet specific application requirements. They can usually automatically extract features from input data, learn semantic relations, and generate outputs with logical and contextual consistency.

Model characteristics

These large models are widely used in natural language processing, dialogue system, machine translation, abstract generation, problem solving, text classification and other fields, providing users with powerful language interaction and intelligent services. However, building and training these large-scale models need a lot of computing resources and data, so they are usually developed and maintained by large research institutions or companies.

These models learn language patterns and laws by pre-training massive data. They can automatically extract features from input data and generate relevant output. Usually based on Transformer architecture, self-attention mechanism is used to process sequential data, such as text or voice. The self-attention mechanism enables the model to pay attention to different parts of the input sequence and establish the correlation between contexts.