Shownotes Transcript
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.
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// 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
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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