A model that sets the state-of-the-art results for any of the tasks that compose the General Language Understanding Evaluation (GLUE) benchmark.

Any model trained on vast quantities of data at scale whose goal is to serve as a starter that can be adapted to a variety of downstream tasks.

Any model validated by the artificial intelligence safety institute as the foundation for building transformed-based applications.

Any model based on the foundation paper “Attention is all you need”, that uses recurrent neural networks and convolution layers.

To enhance the model’s ability to generalize to new data.

To compress the model size for efficient storage.

To stabilize the learning process by adjusting the inputs across the features.

To encode positional information within the sequence.

To increase the throughput of the model.

To represent the order of elements in a sequence.

To prevent overfitting of the model.

To reduce the dimensionality of the input data.

A branch of artificial intelligence that focuses on creating models that can generate new and original data.

A branch of artificial intelligence that focuses on auto generation of models for classification.

A branch of artificial intelligence that focuses on improving the efficiency of existing models.

A branch of artificial intelligence that focuses on analyzing and interpreting existing data.

Sigmoid function

K-means clustering function

Mean Squared Error function

Diffusion function