Technical deep dive of NLU 3.0: Modular, multi-headed, with advanced synthetic training

NLU 3.0 introduces significant advancements in natural language understanding by addressing limitations of previous versions and enhancing the system's agility and accuracy in detecting threats. The update employs synthetic data augmentation using generative AI to anticipate diverse phishing tactics and includes a unified multi-head architecture that processes multiple tasks simultaneously, such as intent classification, named entity recognition, and topic modeling. This approach leverages shared context and improves computational efficiency, enabling faster iterations and expansions of NLU capabilities without retraining entire models. The modular design allows for the rapid addition of new functionalities, thereby maintaining a proactive stance against evolving threats.