Our Web3 series continues with dhadrien, Founder of Sismo, a new NFT primitive for private attestations of on and off-chain data. We cover the evolution of the Web3 ethos, the purpose of Sismo and how it works, the future of Web3 identities and privacy, and more! 


Show Notes: 

(00:00:00) – Introduction.

(00:00:58) – dhadrien’s background.

(00:10:57) – How Web3 ethos has evolved over time.

(00:17:06) – What is Sismo?

(00:22:18) – Use cases of Sismo.

(00:26:46) – Preserving transparency and privacy.

(00:35:46) – What Web3 identity looks like. 

(00:39:34) – Web3 vs. Web2 identity. 

(00:49:50) – Data & business models in Web3 vs. Web2.

(00:56:16) – Closing.


Social links: 

dhadrien’s Twitter

Sismo Twitter


Resources: 

Sismo Website

Sismo Blog

What is Sismo (Part1)

Delphi Podcast Summaries


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Web3 is Cryptography for All: Dhadrien, Founder of Sismo Protocol

Conversations with Crypto Gigabrains. Hosted by Tommy, Co-Founder and Founding Partner at Delphi Ventures

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Eigenlayer is a protocol for decentralized trust, allowing anyone to build new crypto applications without worrying about the source of trust. It enables other protocols to inherit the security of Ethereum by staking ETH and running the Ethereum protocol correctly. Eigenlayer also introduces the concept of Actively Validated Services (AVS), which consume decentralized trust from the Eigenlayer ecosystem. AVSs are verifiable SaaS (Software as a Service) that provide specialized services on top of Eigenlayer. Economic security is crucial for the short-term trust in blockchain systems, while social consensus operates on a longer time scale. The conversation explores the concept of economic security and the role of institutions in managing risks. It discusses the importance of protocols having sharp measured security and the need for regularizing risks in the crypto space. The conversation also delves into the idea of open innovation and the goal of empowering better services. The second part of the conversation focuses on the interplay between objective, subjective, and intersubjective faults in blockchain systems. It explains the need to bring social truth on-chain and the mechanism of forking to determine the true version of a token. The conversation concludes by highlighting the benefits of pooling security and the importance of isolation between financial applications and forking applications. EigenLayer's core premise is to provide decentralized trust to as many different applications as possible. The Eigen token is consumed by AVSs for intersubjective false and intersubjective staking. In the event of a fault, all AVSs must decide which token to follow within a lag period. Forking occurs after the 28-day period, with each AVS switching to one of the two forks. The system ensures that faults are adjudicated by a majority vote among eigenstakers. The AVSs are compensated for any faults, and the system remains secure as long as the transaction value is less than the attributable security. The Eigen token design went through multiple iterations, with the goal of finding the right balance between order and chaos. EigenLayer's view is that decentralized trust is the raw material of the crypto economy, and trustless composability is crucial. The project aims to bridge the gap between short-term utility and long-term merit. The success of EigenLayer's ecosystem was an emergent phenomenon, driven by the principles of reducing capital costs and incentivizing adoption.


Sreeram's Twitter - https://twitter.com/sreeramkannan


Chapters


00:00 Introduction to Eigenlayer and Restaking
03:52 Verifiable SaaS: Actively Validated Services
14:31 The Importance of Economic Security
34:09 Managing Risks and Ensuring Economic Security
36:01 Open Innovation and Better Services
45:26 The Importance of Unit Matching in Economic Security
54:23 Bringing Social Truth On-Chain through Forking
01:03:53 Pooling Security and Elastic Scaling
01:07:31 Isolation: Maintaining Trust and Avoiding Centralized Influence
01:08:26 Decentralized Trust and the Eigen Token
01:09:25 Forking and Adjudication in EigenLayer
01:10:52 Balancing Order and Chaos in the Eigen Token Design
01:14:11 Bridging Short-Term Utility and Long-Term Merit in EigenLayer




Disclosures


This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.

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EigenLayer's Forkable Token System - Bringing Social Truth Onchain

In this episode of the Delphi podcast, the co-founders of Drift Protocol, Cindy Leow, along with Arthur Hayes and Kyle Samani, discuss the vision and development of Drift, as well as the future of DeFi. They highlight the importance of censorship resistance and access to financial markets for all individuals, regardless of their location. They also discuss the advantages of building on Solana and the challenges of operating an app chain. The conversation covers topics such as cross-margin and cross-collateral, the democratization of finance through DeFi, the potential of tokenizing real-world assets, and the value of meme coin derivatives. The episode concludes with a discussion on the future of Drift, including plans for faster transactions and the internalization of MEV. The conversation covers various topics related to decentralized finance (DeFi) and the current state of the crypto market. The speakers discuss the advantages and challenges of decentralized exchanges (DEXs) compared to centralized exchanges, the potential for stablecoin innovation, the growth of DeFi, and the future of the crypto market. They also touch on the upcoming token generation event (TGE) for Drift Protocol.

Cindy's Twitter - https://twitter.com/cindyleowtt
Arthur's Twitter - https://twitter.com/CryptoHayes
Kyle's Twitter - https://twitter.com/KyleSamani


Chapters


00:00 Introduction and Backgrounds
04:21 The Vision for DeFi 
08:37 The Importance of Censorship Resistance and Access to Financial Markets
12:56 The Evolution of Drift Protocol
19:03 The Rise of Meme Coin Derivatives
21:19 Exploring Faster Transactions and MEV Capture
23:42 App Chain vs Monolith: Trade-offs and Considerations
26:58 The Future of Drift: Financializing Assets and Improving User Experience
30:48 The Value of Building on an L1 like Solana
31:43 The Advantages and Challenges of DEXs
34:39 The Potential for Stablecoin Innovation
38:03 The Growth of DeFi and Improving the Trading Experience
47:23 The Future of the Crypto Market
50:46 The Impact of Token Vesting Schedules
56:30 Factors Influencing the Crypto Market




Disclosures


This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.





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Arthur Hayes, Kyle Samani and Cindy Leow: Drift Protocol and the Future of DeFi

David Johnston discusses the Morpheus project, which aims to build a free future by providing individuals with their own personal AI. The project attracted significant interest and support through a fair launch, where users could stake their ETH and contribute to the project in exchange for tokens. The Morpheus network acts as a coordination platform between personalized AIs and a global network of services. The network uses a smart agent rank algorithm to recommend the best smart agents for specific tasks based on factors like reputation and usage. The fair launch model and token economics of Morpheus have attracted attention and may inspire other projects to adopt similar approaches. Morpheus Network has different buckets for rewarding contributors, including the code bucket, compute bucket, community bucket, capital bucket, and protection fund bucket. The code and compute buckets are important for providing value to the network. The code bucket rewards those who build the platform, while the compute bucket rewards those who provide computing resources. The community bucket rewards the builders of smart agents, and the capital bucket rewards those who provide capital. The protection fund bucket is for handling audits, bounties, and recovering from attacks. The network aims to strike a balance between proof of stake and proof of work.


David's Twitter - https://twitter.com/DJohnstonEC




Chapters
00:00 Introduction to Morpheus and its Goals
03:18 The Fair Launch Model and Attracting Support
05:16 The Role of the Morpheus Network
10:29 The Smart Agent Rank Algorithm
25:53 Understanding the Reward Mechanism
31:08 Rewarding Smart Agents and Compute Providers
34:56 Directing Rewards with Morpheus Token Holders
38:45 Creating an Ecosystem for Developers
45:01 Rewarding App Builders and Preventing Centralization
46:28 The Potential of Decentralized AI Models




Disclosures
This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.






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David Johnston: Morpheus's Fair Launch Attracts $400M in stETH to Build Network of AI Agents

0G Labs is building the world's first modular AI chain that enables on-chain storage of training data, models, and the entire stack for crypto AI. Their DA layer provides high throughput and scalability, with a performance difference of 50,000 times better and 100 times cheaper than existing solutions. They aim to achieve Web2 parity on-chain for AI and promote transparency, traceability, and democratization of AI. 0G Labs is focused on making AI a public good and ensuring verifiability and alignment of models. Their roadmap includes launching the base infrastructure, introducing custom consensus, and expanding AI support and capabilities.


Michael's Twitter - https://twitter.com/mheinrich
Ming's Twitter - https://twitter.com/spark_ren
Jason's Twitter - https://twitter.com/zenghbo





Chapters

00:00 Introduction
17:42 The DA Layer: High Throughput and Scalability
29:13 Promoting Transparency and Democratization of AI
38:54 Differentiators of Zero G Labs
51:28 Roadmap and Future of Crypto AI





Disclosures
This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.




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Michael, Ming and Jason of 0G Labs: Building A Modular Chain Specifically for AI

GRASS (GetGrass.io) is a viral crypto AI project built on Solana that aims to scrape and validate internet data for AI training. The name 'GRASS' was chosen for its memeability and metaphors. The project addresses the scarcity of quality data and the control of web data by a few companies. It also tackles the unfairness of companies scraping data from residential networks without compensating users. GRASS is a network of 2 million devices that scrape and clean web data in real-time. The data collected by GRASS can be used for training specialized AI models, fine-tuning models, and real-time inference. GRASS is a web scraping protocol that aims to democratize access to public web data and enable the creation of AI models. The protocol allows users to download a browser extension or mobile app that scrapes data from websites and contributes it to the GRASS network. The data is then validated and stored on a decentralized network of nodes. GRASS aims to provide transparent and verifiable data, ensuring fairness and preventing bias in AI models. The protocol is built on the Solana blockchain for its speed, scalability, and innovation.


Andrej's Twitter - https://twitter.com/0xdrej



Chapters

00:00 - Introduction to GRASS
17:00 - Utilizing GRASS Data for AI Models and Inference
26:04 - Amassing Users and the Mission of GRASS
34:26 - Transparency and Privacy in Data Collection
44:36 - Tracking and Authenticating Data Sources
55:05 - Representing Every Region and Culture




Disclosures
This podcast is strictly informational and educational and is not investment advice or a solicitation to buy or sell any tokens or securities or to make any financial decisions. Do not trade or invest in any project, tokens, or securities based upon this podcast episode. The host and members at Delphi Ventures may personally own tokens or art that are mentioned on the podcast. Our current show features paid sponsorships which may be featured at the start, middle, and/or the end of the episode. These sponsorships are for informational purposes only and are not a solicitation to use any product, service or token.

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Web3 is Cryptography for All: Dhadrien, Founder of Sismo Protocol

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