The Delphi Podcast The Delphi Podcast

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.




---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message

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.








---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message

io.net is a distributed training and inference project built on Solana. They aim to solve the problem of the GPU shortage in the AI industry by building a decentralized network that connects underutilized GPUs from multiple sources. Ionet uses clustering technology to combine GPUs from different geographic locations, allowing for more efficient and cost-effective AI compute. They are attracting both web2 and web3 customers, with a focus on inferencing, which makes up the majority of the market. The goal is to decentralize the AI ecosystem and prevent big tech companies from controlling all aspects of AI. io.net is a decentralized AI network that provides GPU compute power for AI workloads. They are focused on solving the compute aspect of decentralized AI and offer a network of choice for users to perform inference, fine-tuning, and training. The team is driven by a sense of urgency and executes quickly, following operational best practices. They have a disciplined go-to-market approach, targeting Series A to seed-generated AI companies. io.net aims to be the currency at the center of decentralized AI and is exploring the possibility of building a decentralized model marketplace and expanding into other areas like gaming and zero knowledge.




Tory's Twitter



Chapters



00:00 Introduction to Ionet

01:03 Solving the GPU Shortage

13:24 Attracting Web2 and Web3 Customers

27:51 Building a Decentralized Model Marketplace

29:47 The Role of Crypto in Incentivizing Participants

32:37 Easy Onboarding for GPU Workers

34:00 Organic Demand and Onboarding Sales Process

37:20 Choice and Flexibility in Compute Options

43:22 Conquering the Three Key Stakeholders in Decentralized AI


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.






---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message

The conversation explores the concept of Layer 3 (L3) blockchains and their potential impact on the crypto industry. L3s offer unlimited customizations with near-zero gas fees, allowing for limitless creativity and experimentation. The discussion focuses on Degen, a community built on the L3 chain, and its journey from a tipping functionality on Forecaster to launching its own L3. The founders of Syndicate, the team behind Degen's L3, explain the need for L3s and the benefits they provide to different types of applications. The conversation also touches on the future of L3s and the potential for further customization. Degen Chain, an L3 solution built on top of Ethereum, offers low gas fees and customization options for developers. The ability to customize blockchains is seen as a powerful feature, and Degen Chain aims to pull customizations from startups specializing in that space. L3s are designed for customized functionality, while L2s are for scaling. Interoperability between L3s is a vision that many in the space are pursuing, and there are different approaches to achieving it. The security and value capture of Ethereum are important considerations, but the focus should be on usage and adoption. Degen Chain is just the beginning, and there is excitement about the future development and growth of on-chain communities.




Ian's Warpcast
Will's Warpcast
Jacek's Warpcast



Chapters



00:00 Introduction and Disclosures

01:06 Understanding Layer 3 (L3) Blockchains

11:50 Benefits of L3s for Different Types of Applications

29:18 Degen Chain: Low Gas Fees and Customization

31:06 L3s vs L2s: Customized Functionality vs Scaling

32:04 Interoperability: A Vision for L3s

34:32 Usage and Adoption: The Key Metrics

36:30 The Future of On-Chain Communities



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.






---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message

In this conversation, Jeff from Nous Research discusses their work on open source models and the BitTensor subnet. They address the challenges of ranking models on platforms like Hugging Face and the need for a more reliable and commercially viable model ranking system. Nous Research has developed Nous Hermes, an open source model that can be fine-tuned to follow specific instructions. They also created the BitTensor subnet, which allows developers to submit their models and rank them against synthetic data generated by GPT-4 and Claude. The goal is to approximate the state-of-the-art models and incentivize the creation of high-quality models. The conversation explores the potential of synthetic data generation, the future of model selection, the world simulator and amorphous applications, the intersection of AI and crypto, concerns and risks in the crypto AI space, the inevitability of AGI, the role of crypto in AI, regulation and over-regulation in crypto AI, the potential interaction between AGI and centralized systems, proof of personhood and verifying authenticity, and Nous Research's mission and focus.




Jeffrey's twitter



Chapters



00:00 Introduction to Noose Research and Open Source Models

07:12 Overview of Nous Hermes and Fine-Tuning Models

26:30 Challenges with Open Source Models and the Need for BitTensor

32:10 Ranking and Reputation in BitTensor Subnet

34:27 Approaching GPT-4 with BitTensor

37:42 The Potential of Synthetic Data Generation

39:07 The Future of Model Selection

41:29 The World Simulator and Amorphous Applications

44:48 The Intersection of AI and Crypto

48:32 Concerns and Risks in the Crypto AI Space

51:17 The Inevitability of AGI

53:35 The Role of Crypto in AI

56:01 Regulation and Over-Regulation in Crypto AI

58:52 The Potential Interaction Between AGI and Centralized Systems

01:05:24 Proof of Personhood and Verifying Authenticity

01:10:04 Nous Research's Mission and Focus

01:12:26 Attracting AI Developers to Nous Research



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.


---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message

Recorded Live at ETH Denver 2024, this conversation explores the intersection of crypto and AI, discussing the need for decentralized AI models and the challenges of achieving this. The participants highlight the importance of keeping AI open and driven by people, rather than organizations. They discuss the potential of blockchain and Web3 technology to enable new business models and address the limitations of centralized AI companies. The conversation also touches on the role of incentives and tokens in driving innovation in the crypto AI space. The discussion concludes with an examination of BitTensor and the potential for future advancements in crypto AI. The conversation explores various themes related to the intersection of crypto and AI. It discusses the value of outside judgment in rating AI systems, the concept of a hive mind, and exciting use cases in the crypto and AI space. The projects AGI Guild and Morpheus are highlighted, along with the decentralized data warehouse Space and Time. The potential of utilizing unused data in DeFi protocols and the decentralized chat GPT platform MyShell.ai are also discussed. Concerns about OpenAI's dominance, the collaboration between Web2 and Web3, and the concept of zero party data are explored. The conversation also touches on the potential of data DAOs and crowdsourcing, the idea of minimum viable centralization, and the inflection point of decentralized AI and compute. Tangible innovation in ZKML and decentralized data, the importance of edge compute, and the need for decentralized inference are further examined.


Casey's Twitter
Colin Gagich
Vassilis Twitter



Chapters

00:00 Introduction and Background

01:54 The Need for Crypto and AI

06:29 Challenges of Decentralizing AI

09:18 Building Better Models with Web3

13:31 Innovation and Value in Crypto AI

19:11 BitTensor and the Future of Crypto AI

24:18 The Value of Outside Judgment

25:14 The Concept of a Hive Mind

25:43 Exciting Use Cases at the Intersection of Crypto and AI

26:33 AGI Guild and Morpheus Projects

27:32 Space and Time: Decentralized Data Warehouse

29:26 Utilizing Unused Data in DeFi Protocols

29:53 Decentralized Chat GPT with MyShell.ai

30:48 Concerns about OpenAI's Dominance

34:00 Web2 and Web3 Collaboration

35:11 The Concept of Zero Party Data

37:30 The Potential of Data DAOs and Crowdsourcing

38:06 Minimum Viable Centralization

40:29 The Inflection Point of Decentralized AI and Compute

43:45 Tangible Innovation in ZKML and Decentralized Data

45:35 The Importance of Edge Compute

46:30 The Need for Decentralized Inference

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.




---

Send in a voice message: https://podcasters.spotify.com/pod/show/the-delphi-podcast/message