Parallel Function Calling
The ability of an LLM to invoke multiple tool calls simultaneously in a single response, rather than sequentially. This enables faster task completion for independent operations.
Why It Matters
Parallel function calling can reduce agent task completion time by 50-80% when multiple independent operations are needed.
Example
An AI agent simultaneously calling weather API, calendar API, and email API to plan your day — three calls at once instead of waiting for each one sequentially.
Think of it like...
Like a chef who starts boiling water, preheating the oven, and chopping vegetables all at once rather than waiting to finish each step before starting the next.
Related Terms
Function Calling
A capability where an LLM can generate structured output to invoke specific functions or APIs. The model decides which function to call and what parameters to pass based on the user's request.
Tool Use
The ability of an AI model to interact with external tools, APIs, and systems to accomplish tasks beyond text generation. Tools extend the model's capabilities to include search, calculation, code execution, and more.
AI Agent
An AI system that can autonomously plan, reason, and take actions to accomplish goals. Unlike simple chatbots, agents can use tools, make decisions, execute multi-step workflows, and adapt their approach based on results.
Latency
The time delay between sending a request to an AI model and receiving the response. In ML systems, latency includes data preprocessing, model inference, and network transmission time.