Text-to-Text NLP applications, driven by models like BERT and Transformer, enable faster decision-making through summarization, global communication via translation, and precise business support via context-aware question answering.
Speech-to-Text technology, powered by ASR systems and NLP, offers automated transcription services for conference calls and enables voice-activated assistants for hands-free operations and customer interactions in various industries.
Image-to-Text technology uses CNNs and RNNs/Transformers to convert images to text, while OCR involves pre-processing and machine learning classifiers. For businesses, this means auto-tagging visual content for SEO and automating tasks like invoice sorting.
Code Generation with LLMs accelerates software development with predicted code snippets and improves bug fixing using static analysis and machine learning for robust business applications.
Chatbots in business use decision trees, LSTM networks, and advanced models like GPT, trained on historical interactions for contextual issue-solving. They handle tasks from lead generation to cost-saving automated upselling beyond customer support.
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