Damir

GenAI Unpacked: Beyond Basic

Your function documentation is the new API for AI. Learn how to build agents that can discover and correctly use your code.

GenAI Unpacked: Beyond Basic
#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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Machine Learning Engineer

Picnic Technologies B.V.

Picnic Technologies B.V.
Amsterdam, Netherlands

Intermediate
Senior
Python
Structured Query Language (SQL)
+1

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