In this episode, Anna Rose and Tarun Chitra chat with Miranda Christ, a computer science PhD student at Columbia University, about the intersection of cryptography and AI through watermarking techniques. Miranda shares her research on developing imperceptible ways to prove that content was created by AI models, covering everything from simple red-green word lists to sophisticated pseudorandom error-correcting codes.

The discussion explores the cryptographic properties of watermarks - including completeness, soundness, and undetectability - and how these parallel the properties we see in zero-knowledge proof systems. Miranda explains how watermarking differs from other cryptographic approaches like ZKML by only modifying the sampling process rather than the underlying model weights, making it computationally lightweight and practical for deployment.

 

Related Links
Episode 206: Distilling DeFi Primitives with Guillermo, Alex and TarunMy AI Safety Lecture for UT Effective AltruismGoogle SynthIDAmazon Public Watermark DetectorHow ChatGPT could embed a ‘watermark’ in the text it generates - New York TimesWall Street Journal on OpenAI not Deploying WatermarksA Watermark for Large Language ModelsUndetectable Watermarks for Language ModelsWatermarks in the Sand: Impossibility of Strong Watermarking for Generative ModelsPseudorandom Error-Correcting CodesIdeal Pseudorandom Codes
 



 

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