The Shifting Privacy Left Podcast

S2E30: "LLMs, Knowledge Graphs, & GenAI Architectural Considerations" with Shashank Tiwari (Uno)

Oct 3, 2023

Shashank Tiwari discusses ML/AI, temporal knowledge graphs, and Generative AI's impact on privacy. He emphasizes the need for architectural privacy considerations when using Generative AI and predicts enterprise adoption. The conversation delves into the benefits of temporal knowledge graphs and LLMs in creating causal discovery inference models to prevent privacy issues.

01:00:19

Episode guests

Shashank Tiwari

AI Summary

AI Chapters

Episode notes

Podcast summary created with Snipd AI

Quick takeaways

Protect sensitive data by hosting private LLMs, use temporal knowledge graphs for causal discovery inference models.

Cross-reference and validate data with explainable AI, supplement AI insights with human judgment for accuracy.

Stay cautious of AI attack vectors, address security challenges with comprehensive understanding and proactive measures.

Deep dives

Recommendation for Architectural Approach to Data Privacy

Avoid putting any confidential data on public LLMs and consider hosting private LLMs to protect sensitive information. Abstract data sets, anonymize, and obfuscate to prevent data leaks and enhance privacy.

Introduction

3min

Exploration of Security, Privacy, and AI Journey Leading to Uno's Inception

3min

Temporal Knowledge Graphs and LLMs in Causal Discovery for Privacy

15min

Navigating Challenges in Implementing Generative AI

2min

Protecting Highly Confidential Data Sets

29min

Implications of Regulatory Influence on AI Development

4min

Importance of Standards in Generative AI Tech Stacks

4min

This week's guest is Shashank Tiwari, a seasoned engineer and product leader who started with algorithmic systems of Wall Street before becoming Co-founder & CEO of Uno.ai, a pathbreaking autonomous security company. He started with algorithmic systems on Wall Street and then transitioned to building Silicon Valley startups, including previous stints at Nutanix, Elementum, Medallia, & StackRox. In this conversation, we discuss ML/AI, large language models (LLMs), temporal knowledge graphs, causal discovery inference models, and the Generative AI design & architectural choices that affect privacy.

Topics Covered:

Shashank describes his origin story, how he became interested in security, privacy, & AI while working on Wall Street; & what motivated him to found Uno
The benefits to using "temporal knowledge graphs," and how knowledge graphs are used with LLMs to create a "causal discovery inference model" to prevent privacy problems
The explosive growth of Generative AI, it's impact on the privacy and confidentiality of sensitive and personal data, & why a rushed approach could result in mistakes and societal harm
Architectural privacy and security considerations for: 1) leveraging Generative AI, and those to avoid certain mechanisms at all costs; 2) verifying, assuring, & testing against "trustful data" rather than "derived data;" and 3) thwarting common Generative AI attack vectors
Shashank's predictions for Enterprise adoption of Generative AI over the next several years
Shashank's thoughts on proposed and future AI-related legislation may affect the Generative AI market overall and Enterprise adoption more specifically
Shashank's thoughts on the development of AI standards across tech stacks

Resources Mentioned:

Check out episode S2E29: Synthetic Data in AI: Challenges, Techniques & Use Cases with Andrew Clark and Sid Mangalik (Monitaur.ai)

Guest Info:

Connect with Shashank on LinkedIn
Learn more about Uno.ai

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The Shifting Privacy Left Podcast

S2E30: "LLMs, Knowledge Graphs, & GenAI Architectural Considerations" with Shashank Tiwari (Uno)

Episode guests

Podcast summary created with Snipd AI

Quick takeaways

Deep dives

Recommendation for Architectural Approach to Data Privacy

Enhancing Trust in AI through Source Verification and Remifications Analysis

Controlling Trustful Data in the Growing World of AI

Challenges of AI Attack Vectors

Enterprise Adoption of Generative AI

Remember Everything You Learn from Podcasts