Large language model
A large language model is a machine-learning model, typically neural, trained on extensive text data to process and generate language.
Financial AI in Practice
A large language model is a language model with many learned parameters, typically trained on extensive text data to process or generate language.
- How it is used
- Uses LLMs to interpret financial language and structured signals for research, explanations, investigations, and human-reviewed decisions.
- How deep it goes
- Explains probabilistic generation and develops retrieval, constrained-output, and oversight workflows rather than model-training internals.
- Examples
- Illustrates wrong revenue extraction, fraud-complaint detection, credit explanations, and macroeconomic interpretation.
- What you can do after
- Apply it via RAG and constrained prompts to produce grounded analysis or recommendations for human review, not autonomous decisions.
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Build Applications with Local AI Models on a Mac
A machine-learning model trained on large amounts of text to process and generate language.
- How it is used
- Powers a private local assistant that turns prompts, including voice transcripts, into responses.
- How deep it goes
- Explains training patterns, sequential prediction, hallucinations, stateless calls, and context limits without detailing model internals.
- Examples
- Uses “Once upon a ...” to illustrate prediction and an Ollama chat call to show how conversation history is supplied.
- What you can do after
- Build it from scratch as a local voice-enabled chatbot, then compare models and manage chat history.
Read how Build Applications with Local AI Models on a Mac explains large language model →
Related concepts
- Ollamaused by · Ollama is software for downloading, running, and serving language models locally.
- memorycontrasts with · Memory is a storage resource or mechanism that retains data or computational state for access during computation or later use.
- multiplication ruleuses · The multiplication rule determines a combined count or probability by multiplying the numbers of choices or the relevant probabilities at successive stages.
- artificial intelligencekind of · Artificial intelligence is the field concerned with creating computational systems that perform tasks associated with human intelligence, such as learning, reasoning, perception, or decision-making.
- structured datauses · Structured data is information organized according to an explicit schema or predictable fields, types, records, or relationships for consistent machine processing.
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