Verifiable Inference: Don't Trust, Verify | Crypto x AI Event
The Delphi Podcast
Shownotes Transcript
In this engaging debate for Crypto x AI Month, join Luke Saunders as he moderates a conversation on Verifiable Inference—a critical technology that ensures trustless AI by verifying the correctness of outputs without revealing internal workings. He is joined by leading founders from the crypto AI space, including Colin Gagich of Inference Labs, Ryan McNutt of SphereOne, Jeremy from Aizel Network, and **Travis Good **of Ambient, to explore:
► What verifiable inference is and why it's essential in the age of AI
► How decentralized models can offer solutions to centralized AI control
► Real-world use cases of verifiable inference across blockchain and AI applications
This panel digs into the technical approaches—from ZK proofs to trusted execution environments (TEEs)—and discusses how the future of AI and crypto requires trustless verification to ensure security, transparency, and privacy.
Watch more sessions from Crypto x AI Month here: https://delphidigital.io/crypto-ai
Crypto x AI Month is the largest virtual event dedicated to the intersection of crypto and AI, featuring 40+ top builders, investors, and practitioners. Over the course of three weeks, this event brings together panels, debates, and discussions with the brightest minds in the space, presented by Delphi Digital.
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Follow the Speakers:
- Luke Saunders on Twitter/X ► https://x.com/lukedelphi
- Travis Good on Twitter/X ► https://x.com/IridiumEagle
- Jeremy on Twitter/X ► https://x.com/immorriv
- Colin Gagich on Twitter/X ► https://x.com/colingagich
- Travis Good on Twitter/X ► https://x.com/ryanmcnutty33
Chapters 00:00 Introduction to Verifiable Inference 03:46 Defining Verifiable Inference 05:13 Use Cases for Verifiable Inference 10:01 Real-World Applications and Innovations 16:38 Different Approaches to Verification 24:18 Exploring Zero-Knowledge Proofs 28:08 Proof of Logics and Its Implications 34:02 Multi-Agent Systems and Transaction Verification 37:46 Challenges in Optimistic Approaches 41:36 Determinism and Model Reproducibility 45:30 The Balance of Open and Closed Source Models 50:25 The Future of Edge Computing and Inference 57:49 Decentralization and Government Control of AI
Disclaimer All statements and/or opinions expressed in this interview are the personal opinions and responsibility of the respective guests, who may personally hold material positions in companies or assets mentioned or discussed. The content does not necessarily reflect the opinion of Delphi Citadel Partners, LLC or its affiliates (collectively, “Delphi Ventures”), which makes no representations or warranties of any kind in connection with the contained subject matter. Delphi Ventures may hold investments in assets or protocols mentioned or discussed in this interview. This content is provided for informational purposes only and should not be misconstrued for investment advice or as a recommendation to purchase or sell any token or to use any protocol.
