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 UnoThe benefits to using "temporal knowledge graphs," and how knowledge graphs are used with LLMs to create a "causal discovery inference model" to prevent privacy problemsThe 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 vectorsShashank's predictions for Enterprise adoption of Generative AI over the next several yearsShashank's thoughts on proposed and future AI-related legislation may affect the Generative AI market overall and Enterprise adoption more specificallyShashank's thoughts on the development of AI standards across tech stacksResources 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 LinkedInLearn more about Uno.aiSend a text Privado.aiPrivacy assurance at the speed of product development. Get instant visibility w/ privacy code scans.Shifting Privacy Left MediaWhere privacy engineers gather, share, & learnDisclaimer: This post contains affiliate links. If you make a purchase, I may receive a commission at no extra cost to you.Copyright © 2022 - 2024 Principled LLC. All rights reserved.

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