Which NLP breakthrough significantly improved retail AI assistants' ability to understand customer intent across multiple languages and dialects?

Modern retail AI assistants analyze customer language patterns to provide personalized shopping experiences. These systems must process various linguistic elements including dialect variations, slang, and contextual cues. This poll explores a key technological advancement that revolutionized natural language understanding in retail consumer behavior analysis. Test your knowledge about how language processing technology has evolved to better serve retail customers across different linguistic backgrounds.

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Transformer models with attention mechanisms (like BERT and GPT)
Hidden Markov Models (HMMs)
Rule-based parsing systems
Simple recurrent neural networks (RNNs)