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Transformer Architecture Dominance

77% of businesses using NLP expect to increase their investment in NLP.[64] The transformer architecture has continued to be the backbone of most state-of-the-art NLP models:

• Improved Attention Mechanisms: Researchers have developed more efficient attention mechanisms, allowing for processing of longer sequences and better handling of contextual information.[65]

• Sparse Transformers: These models have gained traction, offering comparable performance to dense transformers while requiring less computational resources.[66]