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ChatGPT

As explained in Elasticsearch in Action, Second Edition

ChatGPT is a conversational artificial-intelligence system that generates human-like text in response to user prompts.

ChatGPT is a conversational agent built on the GPT architecture. It generates human-like text from user prompts and aims to produce safe, relevant content through meaningful dialogue. section 1.6

The system learns from large collections of internet text by predicting the next word. This training gives it knowledge of grammar, punctuation, syntax, facts, and some reasoning ability; task-specific datasets can further fine-tune it. section 1.6

Useful prompt-driven applications include:

  • Create a travel itinerary, such as a summer trip to Athens. section 1.6
  • Summarize a legal document in plain language or develop a self-help plan. section 1.6
  • Analyze code for security and performance bugs or design application data models. section 1.6
  • Compare technologies for a use case or draft a complaint letter. section 1.6

Prompt-driven assistance

A user can ask ChatGPT to compare technologies for a specific use case, then continue the dialogue to refine the result. section 1.6

How Elasticsearch in Action, Second Edition covers it

How deep it goes
Explains conversational behavior and next-word prediction, but stops short of describing transformer internals or deployment details.
Examples
Uses travel itineraries, legal summaries, self-help plans, code analysis, data models, technology comparisons, and complaint letters.
What you can do after
Apply it via conversational prompts to generate text and support varied planning, analysis, summarization, and writing tasks.
How it connects
Connects generative AI, large language models, natural language processing, GPT architecture, fine-tuning, and AI-backed search.

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This explainer was generated by Manning's knowledge graph from the text of Elasticsearch in Action, Second Edition. The section links point to the parts of the book it draws on.