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Local ai

Local AI is artificial-intelligence computation performed by a model on a user's device or other locally controlled infrastructure rather than through a remote service.

How 2 Manning books explain it

Build Applications with Local AI Models on a Mac

Local AI is artificial intelligence whose models or computations run on a user's own device rather than on remote infrastructure.

How it is used
Keeps chatbot prompts, responses, and potentially voice input on the user’s device for private application building.
How deep it goes
Explains the local data flow and tradeoffs, then extends them to an offline test; does not detail model internals.
Examples
Uses a local voice chatbot, an airplane-mode test, and confidential legal drafting as concrete cases.
What you can do after
Build it from scratch as a local voice-enabled chatbot using Ollama, MLX Whisper, Python, and Streamlit.

Read how Build Applications with Local AI Models on a Mac explains local ai →

Hugging Face in Action

A local model is a machine learning model executed on the user's own machine rather than accessed through a remote service.

How it is used
Supports private-document and structured-data querying without sending content to a hosted model.
How deep it goes
Demonstrates model loading, prompt construction, LangChain invocation, and DataFrame queries, but reports imperfect generated responses.
Examples
Uses GPT4All for private text and PDF data, then Mistral 7B for questions over famous-people JSON.
What you can do after
Build it from scratch with GPT4All and LangChain to query local documents or generate DataFrame statements.

Read how Hugging Face in Action explains local ai →

Related concepts

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.