Sei is a Layer 1 blockchain built for trading. It was co-founded by Jay, who was inspired to create a decentralized trading platform after working at Robinhood during the GameStop trading fiasco. Sei is designed to offer the best trading experience possible, with fast finality, high throughput, and specialization for its core focus.
Sei achieves its goals through a number of innovative technologies. These include frequent batch auctions, twin turbo consensus, and parallelization. Frequent batch auctions prevent front running and ensure that everyone gets the same trade price. Twin turbo consensus achieves faster time to finality and eliminates the risk of re-orgs. Parallelization increases throughput and allows for more transactions to be processed per second.
Sei is still in its early stages, but it has the potential to revolutionize the way we trade. It is a powerful new tool that could give traders more control over their assets and make the markets more fair and transparent. 
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 Jayendra Jog
  Tommy Shaughnessy

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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. Delphi’s transparency page can be viewed here.
As an additional disclosure Delphi Ventures is an investor in Sei. 

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Jayendra Jog: Robinhood's GameStop Fiasco Inspires Sei, The Layer 1 For Trading

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

Technology

Tech News

Podcasting

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Software How-To

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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Andrej Radonjic: Grass's Two Million Data Scraping Users Enabling Crypto x AI on Solana

Josh, the co-founder of Astria, discusses the journey from data availability layers to building a shared sequencer network. He explains the concept of shared sequencing and its advantages, such as amortizing the cost of engineering and providing a competitive experience for rollup developers. He also addresses the trade-offs and constraints of using a shared sequencer, including the block time and potential lock-in. Josh highlights the target market for shared sequencers and the potential value accrual in a world where multiple rollups tap into the same shared sequencer. Astria is focused on building a shared sequencer for rollups, which allows for faster and more cost-effective transactions. The market is still evaluating the cost and security trade-offs of shared sequencers versus centralized providers. The architecture of a shared sequencer relies on a distributed network, but it remains to be seen if it can be cost-competitive in the market. There is also an ideological question of where to draw the line between a developer building an app-specific rollup on a centralized sequencer and writing to a base layer. The landscape of optimistic rollups versus ZK rollups is constantly evolving, with ZK technology progressing significantly. Base sequencing refers to rollups that are purely dependent on the block producers of the L1, while shared sequencing involves a separate sequencing layer. Astria's go-to-market strategy involves vertically integrating and building their own rollups on top of the shared sequencer to demonstrate its viability.


⁠Josh's Twitter - https://twitter.com/Jskybowen



Chapters

00:00 Introduction and Background
17:14 Target Market for Shared Sequencers
25:11 Value Accrual in a World with Shared Sequencers
32:41 The Evolving Landscape of Optimistic Rollups and ZK Rollups
44:11 The Definition and Challenges of Base Sequencing
50:41 Astria's Go-to-Market Strategy: Vertically Integrating and Building Their Own Rollups



Disclosures
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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Decentralization Unleashed: The Astria Approach to Rollup Sequencing

Integral is a financial operations and accounting platform for companies with Web3 assets. It simplifies financial workflows and provides real-time access to financial information. The platform saves businesses time and frustration by automating tasks such as bookkeeping, payroll, and payments. Integral enables companies to manage their crypto assets, track transactions, and generate financial statements easily. It also facilitates global operations, complex money flows, and multiple asset classes. The platform is part of the larger transformation in capital formation and the redefinition of companies in the Web3 era. Integral is an accounting software for the future of composable Web3 companies. It aims to facilitate the operations of businesses beyond just accounting, including tax, payments, payroll, and financial planning. By providing accurate and real-time data on business finances, Integral enables founders and large corporations to make better decisions and manage their assets more effectively. The platform also offers benefits such as reducing the need for internal controllers, automating processes, and improving efficiency. Integral serves a range of clients, including startups, large brands like Nike, and VC firms. The company is also exploring the use of AI to enhance legibility and provide proactive recommendations.



 Gui's Twitter⁠
 Avi's Twitter
 Drew's Twitter



Chapters



00:00 - Introduction and Background
08:39 - Overview of Integral and its Benefits
31:25 - The Composable Nature of Integral in the Web3 Era
45:13 - Enhancing Legibility and Providing Proactive Recommendations with Integral



Disclosures


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. Delphi’s transparency page can be viewed ⁠⁠⁠⁠⁠⁠⁠⁠here⁠⁠⁠⁠⁠⁠⁠⁠.







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Jayendra Jog: Robinhood's GameStop Fiasco Inspires Sei, The Layer 1 For Trading

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