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How to Build Secure AI Without Ever Exporting Your Data

Kunal Kushwaha via YouTube

Overview

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Learn to eliminate the costly and insecure practice of moving data between databases and AI systems by implementing AI models and agents directly within your database infrastructure. Discover the fundamental problems with traditional AI architectures that create latency, increase costs, and pose security risks through constant data movement. Explore the concept of AI-native databases and see Oracle's 26AI platform in action through a comprehensive demonstration. Master techniques for running AI agents inside databases to achieve zero-latency performance and understand how self-tuning data systems use AI to optimize performance autonomously. Replace traditional vector databases with built-in vector search capabilities and prepare for the future AI ecosystem featuring GPU clusters and supercomputing integration. Gain practical knowledge of multi-cloud AI deployment strategies across AWS, Azure, and Google Cloud Platform, and get hands-on experience with free tools and resources to implement these solutions immediately.

Syllabus

The "Data Shuffle" Problem in AI
Why Traditional AI Architectures are Slow & Expensive
What is an AI-Native Database? Meet 26AI
Full Demo: Running AI Agents inside the Database
How to Eliminate Latency with In-Database AI
Self-Tuning Data: AI-Driven Performance & Autonomy
Replacing Vector DBs with Built-In Vector Search
The 2026 AI Ecosystem: GPU Clusters & Supercomputing
Multi-Cloud AI: Deploying on AWS, Azure, and GCP
How to Get Started for Free

Taught by

Kunal Kushwaha

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