A Decade of AI Safety and Trust // Petar Tsankov // MLOps Podcast #218

Mar 12, 2024

The podcast delves into AI safety and trust over the past decade, emphasizing the importance of reliability and transparency in deploying models. It explores the contrasting educational environments in the US and Switzerland, highlighting the journey of the speaker. Discussions cover challenges in ensuring trust in AI models, the impact of generative AI, and the need for comprehensive testing post-deployment to build trust.

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Introduction

00:00 • 3min

Strategic Expansion and AI Partnerships in Eastern Europe

03:05 • 2min

Contrasting Environments: US Chaos vs Swiss Orderliness in Education and Innovation

05:11 • 2min

Evolution of AI Safety and Trust

07:00 • 10min

Navigating Trust and Safety in AI Models

16:45 • 21min

Ensuring AI Model Safety and Trust

37:18 • 17min

Exploring the Challenges and Advancements in AI Safety and Trust

54:11 • 4min

Huge thank you to LatticeFlow AI for sponsoring this episode. LatticeFlow AI - https://latticeflow.ai/.Dr. Petar Tsankov is a researcher and entrepreneur in the field of Computer Science and Artificial Intelligence. MLOps podcast #218 with Petar Tsankov, Co-Founder and CEO at LatticeFlow AI, A Decade of AI Safety and Trust. // Abstract // Bio Co-founder & CEO at LatticeFlow AI, building the world's first product enabling organizations to build performant, safe, and trustworthy AI systems. Before starting LatticeFlow AI, Petar was a senior researcher at ETH Zurich working on the security and reliability of modern systems, including deep learning models, smart contracts, and programmable networks. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Website: https://latticeflow.ai/ ERAN, the world's first scalable verifier for deep neural networks: https://github.com/eth-sri/eran VerX, the world's first fully automated verifier for smart contracts: https://verx.ch Securify, the first scalable security scanner for Ethereum smart contracts: https://securify.ch DeGuard, de-obfuscates Android binaries: http://apk-deguard.com SyNET, the first scalable network-wide configuration synthesis tool: https://synet.ethz.ch --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Petar on LinkedIn: https://www.linkedin.com/in/petartsankov/ Timestamps: [00:00] Petar's preferred coffee [00:29] Takeaways [03:15] Shout out to LatticeFlow for sponsoring this episode! [03:22] Please like, share, leave a review, and subscribe to our MLOps channels! [03:42] Expansion [05:16] Zurich ETH [07:06] AI Safety [09:24] Optimizing one metric, no fixed data sets [12:19] Trust life-changing issues [14:59] So much interest in GenAI [16:45] Explosion of GenAI Trust and Safety [21:14] Red Teaming [25:22] Trustworthy AI in Industry [27:43] DataOps Challenges [33:42] Trusting Third-Party Models [37:00] Testing Open Source Models [41:41] Specialized ML for Leasing [43:04] Regulation and Financial Incentives [45:30] Regulations Drive Innovation Balance [47:23] Regulations vs Certification: Voluntary Prove [52:24] Workflow Transparency: Trust & Efficiency [53:20] Engineers Balance Compliance Risks [54:53] Pushing Deep Learning Limits [57:31] Wrap up