"web3 with a16z" is a show about the next generation of the internet, and about how builders and users -- whether artists, coders, creators, developers, companies, organizations, or communities -- now have the ability to not just "read" (web1) + "write" (web2) but "own" (web3) pieces of the internet, unlocking a new wave of creativity and entrepreneurship. Brought to you by a16z crypto, this show is the definitive resource for understanding and going deeper on all things crypto and web3. Fro ...
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How ZK inspired AI Watermarking with Miranda Christ
MP3•Episode home
Manage episode 498638415 series 2630382
Content provided by Zero Knowledge Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Zero Knowledge Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
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:
Check out the latest jobs in ZK at the ZK Podcast Jobs Board.
**If you like what we do:** * Find all our links here! @ZeroKnowledge | Linktree * Subscribe to our podcast newsletter * Follow us on Twitter @zeroknowledgefm * Join us on Telegram * Catch us on YouTube **Support the show:** * Patreon * ETH - Donation address * BTC - Donation address * SOL - Donation address Read transcript
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- 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
Check out the latest jobs in ZK at the ZK Podcast Jobs Board.
**If you like what we do:** * Find all our links here! @ZeroKnowledge | Linktree * Subscribe to our podcast newsletter * Follow us on Twitter @zeroknowledgefm * Join us on Telegram * Catch us on YouTube **Support the show:** * Patreon * ETH - Donation address * BTC - Donation address * SOL - Donation address Read transcript
382 episodes
MP3•Episode home
Manage episode 498638415 series 2630382
Content provided by Zero Knowledge Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Zero Knowledge Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
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:
Check out the latest jobs in ZK at the ZK Podcast Jobs Board.
**If you like what we do:** * Find all our links here! @ZeroKnowledge | Linktree * Subscribe to our podcast newsletter * Follow us on Twitter @zeroknowledgefm * Join us on Telegram * Catch us on YouTube **Support the show:** * Patreon * ETH - Donation address * BTC - Donation address * SOL - Donation address Read transcript
…
continue reading
- 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
Check out the latest jobs in ZK at the ZK Podcast Jobs Board.
**If you like what we do:** * Find all our links here! @ZeroKnowledge | Linktree * Subscribe to our podcast newsletter * Follow us on Twitter @zeroknowledgefm * Join us on Telegram * Catch us on YouTube **Support the show:** * Patreon * ETH - Donation address * BTC - Donation address * SOL - Donation address Read transcript
382 episodes
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