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GPT model

As explained in Inside AI

GPT-3 is a generative language model developed by OpenAI for processing and generating human-language text.

GPT-3 is a generative language model developed by OpenAI. It was trained on a diverse dataset from online resources and has 175 billion parameters. section 5.2

GPT-3 can perform language tasks such as translation, question answering, summarization, and conversation. It can also assist with coding and handle examples such as word unscrambling or three-digit arithmetic. section 5.2 section 5.3

Choosing a model variant

Davinci is described as the most capable GPT-3 model, suited to creative writing or summarizing content for a particular audience. It is also slower and more resource-intensive than Curie, Babbage, and ADA. section 5.3

Coherent, human-like conversation helped fuel excitement about GPT-3, but sensational reporting also amplified fears about AI. Impressive language performance should not be confused with evidence of human-like intelligence or the claims made in alarmist headlines. section 5.2

How Inside AI covers it

How deep it goes
Describes GPT-3's parameter count, training data, task range, and variants without detailing model implementation.
Examples
Uses Python code generation, document summarization, translation, question answering, and three-digit arithmetic as examples.
What you can do after
Evaluate GPT-3 variants for language tasks by weighing their stated capabilities against differences in speed and resource demands.
How it connects
Connects GPT-3 with large language models, natural language processing, ChatGPT, BERT, T5, and OPT.

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