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 Tarun
My AI Safety Lecture for UT Effective Altruism
Google SynthID
Amazon Public Watermark Detector
How ChatGPT could embed a ‘watermark’ in the text it generates - New York Times
Wall Street Journal on OpenAI not Deploying Watermarks
A Watermark for Large Language Models
Undetectable Watermarks for Language Models
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Pseudorandom Error-Correcting Codes
Ideal Pseudorandom Codes

 



 

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