Damir

Best practices: Building Enterprise Applications that leverage GenAI

How do you build enterprise AI apps that use your private data without expensive retraining?

Best practices: Building Enterprise Applications that leverage GenAI
#1about 6 minutes

Demonstrating the future of software with natural language

A live demo shows how Semantic Kernel enables a multi-lingual, chat-based interface to control devices like lights, illustrating the concept of "Software V2".

#2about 3 minutes

Building a natural language interface for PowerShell

An application translates plain English queries into PowerShell commands to retrieve system information like running processes and IP addresses.

#3about 2 minutes

Understanding the role of embeddings and vector databases

Embeddings provide a semantic, multi-dimensional representation of text tokens, which are stored and queried in vector databases to find semantic similarity.

#4about 2 minutes

Exploring native vector search in SQL Server 2025

A preview of SQL Server 2025 shows the new native vector data type and distance function, but also highlights potential linear performance scaling issues.

#5about 7 minutes

Using RAG to extend LLM knowledge without retraining

A C# code walkthrough demonstrates how Retrieval-Augmented Generation (RAG) injects new information into a model's context to override its base knowledge.

#6about 4 minutes

Implementing function calling to connect LLMs to tools

Learn how function calling enables an LLM to execute external code by mapping natural language prompts to specific functions and their arguments.

#7about 1 minute

Key takeaways for building enterprise GenAI applications

A summary emphasizes that mastering embeddings, vector databases, and function calling is essential for solving real-world problems with GenAI.

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Matching moments

GenAI applications and emerging professional roles
18:03 MIN

GenAI applications and emerging professional roles

Enter the Brave New World of GenAI with Vector Search

Moving beyond hype with real-world generative AI
00:05 MIN

Moving beyond hype with real-world generative AI

Semantic AI: Why Embeddings Might Matter More Than LLMs

Understanding the core components of a GenAI stack
14:43 MIN

Understanding the core components of a GenAI stack

Building Products in the era of GenAI

Understanding the fundamental shift to generative AI
01:42 MIN

Understanding the fundamental shift to generative AI

Your Next AI Needs 10,000 GPUs. Now What?

Using AI to reimagine the developer experience
03:18 MIN

Using AI to reimagine the developer experience

AI Pair Programming with GitHub Copilot at SAP: Looking Back, Looking Forward!

Shifting from traditional code to AI-powered logic
09:55 MIN

Shifting from traditional code to AI-powered logic

WWC24 - Ankit Patel - Unlocking the Future Breakthrough Application Performance and Capabilities with NVIDIA

How GenAI unblocks features but introduces new challenges
28:51 MIN

How GenAI unblocks features but introduces new challenges

Lessons Learned Building a GenAI Powered App

Advanced patterns for building sophisticated AI applications
21:06 MIN

Advanced patterns for building sophisticated AI applications

Java Meets AI: Empowering Spring Developers to Build Intelligent Apps

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Jobs that call for the skills explored in this talk.