NLP (Natural Language Processing) is the branch of AI focused on enabling computers to understand, interpret, and generate human language. It powers search engines, translation, chatbots, and large language models.

What is the difference between NLP and LLMs?

NLP is the broader field; LLMs are the dominant current approach. Traditional NLP used statistical models and rule-based systems. Modern NLP largely uses large transformer-based language models trained on massive text corpora.

What are the most common NLP tasks?

Common NLP tasks include text classification, named entity recognition (NER), sentiment analysis, machine translation, summarisation, question answering, and text generation.

Techniques

Natural Language Processing (NLP)

Natural Language Processing (NLP) is the branch of AI that deals with the interaction between computers and human language. NLP systems can read, understand, interpret, translate, and generate text and speech. Modern NLP is largely powered by transformer-based language models.

How NLP Works

Classical NLP used rule-based parsing, n-gram statistics, and hand-crafted features. Modern NLP is dominated by pre-trained transformers (BERT, GPT, T5) that learn rich language representations from large corpora, then can be fine-tuned for specific tasks with minimal labelled data. Key NLP tasks include tokenisation, embedding, named entity recognition, sentiment analysis, machine translation, and text generation.

Key Use Cases

Search engines and question answering
Machine translation (Google Translate, DeepL)
Sentiment analysis for brand monitoring
Document classification and routing
Chatbots and virtual assistants
Contract analysis and legal discovery
Clinical note processing in healthcare

Frequently Asked Questions

What is NLP in AI?: NLP (Natural Language Processing) is the branch of AI focused on enabling computers to understand, interpret, and generate human language. It powers search engines, translation, chatbots, and large language models.
What is the difference between NLP and LLMs?: NLP is the broader field; LLMs are the dominant current approach. Traditional NLP used statistical models and rule-based systems. Modern NLP largely uses large transformer-based language models trained on massive text corpora.
What are the most common NLP tasks?: Common NLP tasks include text classification, named entity recognition (NER), sentiment analysis, machine translation, summarisation, question answering, and text generation.