Rajesh - Securing Retrieval-Augmented Generation | PyData Seattle 2025
Modern LLM applications rely heavily on embeddings and vector databases for retrieval-augmented generation (RAG). But in 2025, researchers and OWASP flagged vector databases as a new attack surface — from embedding inversion (recovering sensitive training text) to poisoned vectors that hijack prompts. This talk demystifies these threats for practitioners and shows how to secure your RAG pipeline with real-world techniques like encrypted stores, anomaly detection, and retrieval validation. Attendees will leave with a practical security checklist for keeping embeddings safe while still unlocking the power of retrieval. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVi...

Kristopher Reese

Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker

BSIDES Bangalore 2026: The Biggest Cybersecurity Event You Probably Missed |@newsfirstprime

OWASP's Top 10 Ways to Attack LLMs: AI Vulnerabilities Exposed

Creator of C++: Bell Labs, Negative Overhead Abstraction, Mistakes | Bjarne Stroustrup

Everything about RAG (Retrieval Augmented Generation) - Simple Explanation with Examples

Zig 2026: No-AI Policy, $670K Foundation, Left GitHub & Why Zig Isn’t 1.0 - Andrew Kelley Explains

The World's Most Important Machine

Is AI Hiding Its Full Power? With Geoffrey Hinton

Trump Gives Medical Assessment of Graham's Death, Backs Down on Strait of Hormuz Toll: A Closer Look

Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026

What rebuilding AlphaGo teaches us about self-play, RL, and future of LLMs - Eric Jang

RAG Crash Course for Beginners

China Is About To Pop The AI Bubble

Shor's Algorithm for Quantum Computing - Computerphile

Keynote: Josh Starmer - Communicating Concepts, Clearly Explained!!! | PyData Seattle 2025

How ASML Makes Chips Faster With Its New $400 Million High NA Machine

He Risked Everything To Warn You: No One Is Ready For What's Coming, And The AI Companies Know It!

Harnesses in AI: A Deep Dive — Tejas Kumar, IBM

