10 terms
Showing all terms starting with B
A standardised test or dataset used to evaluate and compare the performance of AI models across specific tasks.
Bidirectional Encoder Representations from Transformers - a Google language model that reads text in both directions, excelling at understanding context.
Systematic errors in model outputs caused by skewed training data or flawed design, leading to unfair or inaccurate results.
An AI system whose internal decision-making process is opaque or not interpretable, even to its developers.
The algorithm used to train neural networks by calculating gradients of the loss function and propagating them backward through the network layers.
A training technique that normalises the inputs of each layer to speed up training and improve the stability of deep neural networks.
The number of training samples processed together in one forward and backward pass during model training, affecting speed and convergence.
A decoding algorithm used in text generation that maintains the top-k most probable sequences at each step to find a near-optimal output.
A probabilistic approach for hyperparameter tuning that uses past evaluation results to intelligently choose the next set of parameters to try.
A tokenisation algorithm that iteratively merges the most frequent character pairs, used in GPT and other LLMs to build their vocabulary.
