This week, Anna Rose and Tarun Chitra dive back into the topic of ZK ML with guests Yi Sun, co-founder of Axiom, and Daniel Kang, Assistant Professor of computer science at UIUC. They discuss Yi and Daniel’s previous academic work and what led them to get interested in ZK topics and specifically ZK ML. They then dive into a discussion about 2 recent papers which examine the use of ZK within Machine Learning architectures. Here are some additional links for this episode:Episode 246: Adversarial Machine Learning Research with Florian Tramèr Trustless Verification of Machine LearningEfficient Verifiable Image Redacting based on zk-SNARKs ZK-IMG: Attested Images via Zero-Knowledge Proofs to Fight DisinformationScaling up Trustless DNN Inference with Zero-Knowledge ProofsYi Sun’s Profile Daniel Kang’s ProfileApply for ZK Hack Lisbon here: ZK Hack application Aleo is a new Layer-1 blockchain that achieves the programmability of Ethereum, the privacy of Zcash, and the scalability of a rollup.Interested in building private applications? Check out Aleo’s programming language called Leo by visiting http://developer.aleo.org.You can also participate in Aleo’s incentivized testnet3 by downloading and running a snarkOS node. No sign-up is necessary to participate.For questions, join their Discord at aleo.org/discord.If you like what we do:Find all our links here! @ZeroKnowledge | Linktree Subscribe to our podcast newsletterFollow us on Twitter @zeroknowledgefmJoin us on TelegramCatch us on Youtube

Daniel Kang, VP of finance at Mercury, explores the art of annual planning. He argues that if planning feels like a finance task, it’s bound to fail. Kang emphasizes collaboration across all departments and offers strategies to streamline the process. He highlights the pitfalls of over-planning and false productivity, suggesting that companies often waste time chasing big ideas instead of addressing core issues. He also discusses how planning should evolve as companies grow, ensuring goals remain actionable and aligned with organizational priorities.

In this insightful discussion, guests include Johann Rehberger, an AI/ML security researcher, and Richard Fang, who evaluates AI exploitation methods. They delve into the complexities of system vulnerabilities, highlighting how teams of large language model agents could exploit zero-day flaws. Rohan Bindu and Akul Gupta share findings on LLM capabilities in offensive security. The group also addresses the limitations of LLMs in recognizing security threats and the implications of managing identities across multi-cloud environments. Don't miss their fresh take on AI security!