Natural Language Processing
NLP
The branch of AI focused on enabling computers to understand, interpret, and generate human language. Powers chatbots, translation, sentiment analysis, and more.
In-Depth Explanation
Natural Language Processing (NLP) is the AI field enabling machines to work with human language. Modern NLP has been transformed by deep learning and large language models.
Core NLP tasks:
- Text classification: Categorising documents (sentiment, topic, intent)
- Named Entity Recognition: Identifying people, places, organisations
- Machine translation: Converting between languages
- Question answering: Finding answers in text
- Summarisation: Condensing long documents
- Text generation: Creating human-like text
NLP evolution:
- Rule-based: Hand-crafted patterns and dictionaries
- Statistical: Probabilistic models, word frequencies
- Deep learning: Neural networks, word embeddings
- Transformers: Attention mechanisms, pre-trained models
- LLMs: Massive models with emergent capabilities
Key concepts:
- Tokenisation, embeddings, attention
- Pre-training and fine-tuning
- Zero-shot and few-shot learning
Business Context
NLP automates tasks like email classification, customer feedback analysis, document processing, and conversational AI - core capabilities for modern business automation.
How Clever Ops Uses This
We implement NLP solutions across the full spectrum for Australian businesses - from simple classification to advanced conversational AI and document understanding.
Example Use Case
"Automatically extracting key information from contracts - parties, dates, obligations, amounts - saving hours of manual review."