GPT-4
GPT-4 is a generative large language model developed by OpenAI for understanding and generating text and other supported inputs and outputs.
Introduction to Generative AI, Second Edition
GPT-4 is an OpenAI GPT language model released in 2023 and capable of performing a range of language and coding tasks.
- How it is used
- Supports language, coding, examination, multimodal, and healthcare-administration tasks.
- How deep it goes
- Demonstrates capabilities through benchmarks and cases but stops short of explaining implementation internals or guaranteeing autonomous professional performance.
- Examples
- Uses professional exams, LeetCode problems, an insurance appeal, clinical scripts, patient communications, and medical paperwork.
- What you can do after
- Evaluate/understand GPT-4's useful applications while distinguishing benchmark success and draft generation from reliable independent expertise.
Read how Introduction to Generative AI, Second Edition explains GPT-4 →
Data Analysis with LLMs
GPT-4 is a GPT language model version capable of generating and understanding text, including complex code.
- How it is used
- Deploys GPT-4 for demanding text-processing tasks, including review classification and complex data-processing code.
- How deep it goes
- Explains capabilities, token pricing, model comparison, and task evaluation, but stops short of model internals.
- Examples
- Uses product-review classification, HELM comparisons, token-cost calculations, and a GPT-4 API invocation.
- What you can do after
- Evaluate GPT-4 against cheaper models on representative data while weighing accuracy, token use, and price.
Elasticsearch in Action, Second Edition
GPT-4 is a generative pretrained transformer language model developed by OpenAI.
- How it is used
- Supports conversational search by interpreting natural-language queries, context, and intent.
- How deep it goes
- Explains training scale, knowledge cutoff, and internet-access limits without detailing model internals.
- Examples
- Uses conversational questions and training material drawn from books, articles, papers, and blogs.
- What you can do after
- Evaluate GPT-4’s role in conversational search and its limitations for real-time information retrieval.
Read how Elasticsearch in Action, Second Edition explains GPT-4 →
AI for Everyday IT
GPT is OpenAI's family of generative pre-trained transformer language models.
- How it is used
- Supports text generation and IT-support work such as documentation lookup, troubleshooting, onboarding, and customer-service assistance.
- How deep it goes
- Defines GPT as a generative language model and shows workplace uses, but avoids model internals and formal theory.
- Examples
- Uses technical documentation, troubleshooting, customer responses, and account-comparison tables as practical examples.
- What you can do after
- Apply GPTs to documentation-based support tasks while checking generated answers against authoritative product information.
The AI Pocket Book
An OpenAI large language model used as an example tokenizer and reference for token counts.
- How it is used
- Uses GPT-4o to illustrate when code generation helps and when an established library is the better choice.
- How deep it goes
- Shows generated code and compares its complexity with library usage, but does not explain model internals or tokenization.
- Examples
- Uses animated dropdown generation and Python sun-position calculation as contrasting code-generation examples.
- What you can do after
- Evaluate whether generated code or an existing library is the more practical solution for a task.
Related concepts
- multimodalkind of · A multimodal model is a model that processes, generates, or relates information represented in two or more data modalities, such as text, images, audio, or video.
- ChatGPTused by · ChatGPT is OpenAI’s conversational AI service, which lets users interact with generative AI models and related tools through natural-language prompts.
- autoregressive modelkind of · An autoregressive model represents or predicts each value in a sequence based on preceding values in that sequence.
- language modelkind of · A language model is a computational model that represents patterns in linguistic tokens to estimate sequence probabilities and predict or generate language from context.
- GPT modelcontrasts with · A GPT model is a generative pretrained Transformer language model that produces text autoregressively by predicting successive tokens from preceding context.
These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.