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ChatGPT

As explained in Grokking AI Applications

ChatGPT is a conversational AI system built on generative language models and trained to respond to human users.

ChatGPT is a conversational AI system built around GPT, a generative language model that predicts likely next words. Multiple training stages refine this sentence-completion ability into meaningful human conversations. section 1.5

ChatGPT’s capabilities develop through three learning phases:

  • Unsupervised learning trains GPT to find language patterns and predict the next word. section 1.5
  • Supervised learning refines initial outputs using human-guided examples. section 1.5
  • Reinforcement learning further improves conversational responses through trial, feedback, and adjustment. section 1.5
  • Applications surrounding the model can add memory, external data, and tools, making interactions appear less stateless and knowledge more expandable. section 1.3
Figure 1.6 The learning stages of ChatGPT

Trace the learning stages that transform GPT’s language prediction into conversational behavior. section 1.5

How Grokking AI Applications covers it

How deep it goes
Explains three training stages and application-level extensions, but stops short of detailed model internals.
Examples
Uses GPT sentence completion, human-guided refinement, reinforcement learning, and chatbot conversations as teaching examples.
What it assumes
Requires no mastery of model internals and introduces machine learning categories through accessible analogies.
What you can do after
Evaluate ChatGPT as a layered system rather than as an isolated language model.
How it connects
Connects generative language models with unsupervised learning, supervised learning, reinforcement learning, memory, external data, and tools.

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This explainer was generated by Manning's knowledge graph from the text of Grokking AI Applications. The section links point to the parts of the book it draws on.