Recently, Google Research introduced a new sparse attention mechanism that improves performance on a multitude of tasks that require long contexts known as BigBird. The researchers took inspiration from the graph sparsification methods.

They understood where the proof for the expressiveness of Transformers breaks down when full-attention is relaxed to form the proposed attention pattern. They stated, “This understanding helped us develop BigBird, which is theoretically as expressive and also empirically useful.”

Why is BigBird Important?
Bidirectional Encoder Representations from Transformers or BERT, a neural network-based technique for natural language processing (NLP) pre-training has gained immense popularity in the last two years. This technology enables anyone to train their own state-of-the-art question answering system.

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