Your function documentation is the new API for AI. Learn how to build agents that can discover and correctly use your code.
#1about 5 minutes
Controlling PowerShell with natural language commands
A live demo shows how a large language model can translate human language into executable PowerShell commands to manage system processes.
#2about 4 minutes
How large language models process text using tokens
Models break down text into numerical tokens for efficient processing, which is a fundamental concept for performance and cost calculation.
#3about 8 minutes
Calculating semantic similarity with embeddings and vectors
Text is converted into numerical vectors (embeddings) to calculate semantic similarity using cosine similarity, enabling features like recommendations and search.
#4about 5 minutes
How completion models generate text probabilistically
LLMs generate text by probabilistically selecting the next token, and the temperature parameter controls the creativity versus determinism of the output.
#5about 3 minutes
Implementing function calling with Semantic Kernel agents
An AI agent uses embeddings to understand user intent and trigger the correct external function or plugin from a library of available tools.
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