The Open Podcast

00:00 Introduction

00:36 Meet Lukas: Crypto Enthusiast and Ecosystem Lead

00:48 Lucas's Journey in Crypto

09:38 Introduction to Nillion: Privacy and Data Ownership

16:44 Real-World Applications and Future Prospects

25:17 Potential of Blind Computation

27:19 Technical Aspects of Blind Computation

29:49 Future of Decentralized AI and Blind Computation

36:17 Roadmap and Ecosystem of Nillion

------RESOURCES

Lukas: https://x.com/0xlukeskywalker

Into Nillion: https://nillionlabs.com/

Into RSS3: https://rss3.io/

Into Open: https://open.network/

Co-produced by ⁠⁠⁠RSS3⁠⁠⁠.

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CHAPTERS

00:00 Intro

• Introduction to Open Podcast and the theme of today’s episode.

• Host welcomes Michel, VP of Global Partnerships at AIOZ Network.

00:29 Michel’s Journey from Web2 to Web3

• Michel shares his background, starting in traditional tech and consulting with Alibaba, then transitioning to Web3.

• His passion for decentralized technology and blockchain innovations.

• Michel’s role at AIOZ Network and his mission to drive growth in the Web3 space.

02:00 Overview of AIOZ Network

• AIOZ Network as a decentralized platform for Web3 AI, storage, and streaming.

• Discussion on how AIOZ empowers decentralized AI, providing affordable, secure, and decentralized solutions.

• The importance of decentralized storage for developers, especially for NFTs and dApps.

03:30 The Future of Decentralized Streaming

• AIOZ’s content delivery network (CDN) powered by blockchain, revolutionizing how media is streamed globally.

• Explanation of edge computing and peer-to-peer networks in content delivery.

05:00 AIOZ’s Decentralized AI Platform

• Introduction to decentralized AI through AIOZ Network.

• How AIOZ is enabling decentralized AI computation and storage.

• AI competition now accessible globally through decentralized nodes.

07:30 Collaborations with Universities and Research Institutions

• AIOZ’s partnerships with global universities, including Tsinghua University, for AI and drone research labs.

• Expanding the AI research ecosystem through decentralized infrastructure.

10:00 Building the Future of Web3 with AIOZ

• Michel’s vision of Web3 and how AIOZ aims to revolutionize AI, storage, and streaming.

• The roadmap for launching W3AI, AIOZ’s decentralized AI platform.

12:00 W3AI Platform and AI Marketplace

• Introduction to W3AI and its two-layer architecture: infrastructure for AI computation and the AI marketplace for models and dApps.

• Michel explains how W3AI allows developers to contribute and monetize AI models through the decentralized marketplace.

14:30 Incentivizing Quality in AI Models

• Discussion on the W3AI reputation system, where high-quality AI models are rewarded and poor models face penalties.

• How this system encourages niche AI development, ensuring better solutions for specific market needs.

16:30 Privacy and Decentralized Federated Learning

• How AIOZ is leveraging decentralized federated learning for AI model training while maintaining user data privacy.

• Michel introduces privacy-preserving technologies, such as homomorphic encryption, ensuring sensitive data remains protected.

18:30 Homomorphic Encryption for Data Privacy

• Explanation of homomorphic encryption and how it allows for secure AI model training using sensitive data.

• Real-world examples: medical records and financial data being used without exposing private information.

20:00 Closing Remarks and Future Plans for AIOZ

• Michel shares insights into the future of AIOZ and upcoming projects, including the launch of W3AI.

• How listeners can engage with AIOZ, including upcoming events, hackathons, and collaborations with partners like Cardano.

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Contribute to the Open Web:

https://openinformation.io/grant

In this episode, we delve into the Permaweb with Benjamin, co-founder and CEO of decent.land, which focuses on accelerating the growth of this space. Join us as we discuss decentralized information, open data, and how these new technologies ensure the preservation of digital history while offering a future of openness and security.

Co-produced by ⁠⁠RSS3⁠⁠.

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CHAPTERS

00:00 Intro

00:29 What is Permaweb

• Overview of the Permaweb, a decentralized, permanent web built on blockchain.
• Explanation of how this ensures digital history is preserved permanently and immutably.
• Spotlight on decent.land - advancing the adoption of the Permaweb.

00:55 decent.land’s Role in Decentralization

• decent.land is at the forefront of decentralized technology, building tools for the Permaweb.
• Emphasis on creating a more open, secure, and permanent web for the future.
• Personal journey of Benjamin, the co-founder of decent.land.

01:21 Culture and Developer Community of decent.land

• A high-level overview of decent.land's approach
• Brief discussion of the technical nature of the project.
• decent.land’s community-driven mission and how developers are attracted to its values.
• Milady avatars.

08:21 Radical Composability

• Radical composability refers to the idea of modular, interoperable systems within Web3.
• This philosophy drives product development, particularly in creating open, scalable infrastructures.
• Explanation of WeaveVM and its role in decentralized storage and data availability.

10:26 Challenges Addressed by WeaveVM

• WeaveVM addresses the storage bottlenecks in traditional blockchain systems.
• Enables more efficient storage solutions that bypass the high costs of data storage on-chain.
• Ensures data permanence, making decentralized apps more scalable and reliable.

12:02 Data Permanence and Privacy Concerns

• Encryption can be used to protect sensitive data, but once stored, it’s hard to remove.
• The responsibility lies with gateway operators, who determine what content to serve.
• Like Web2 issues, once something is stored online, it’s challenging to erase it completely.

26:00 The Importance of Open Data

• Open data must be permanent and accessible.
• Discussion on how ensuring the permanence of data helps preserve valuable information for future generations.
• decent.land is committed to building the infrastructure for scalable, open data storage.

30:00 Future Plans for decent.land

• Announcement of upcoming testnet launches and ecosystem grants for developers.
• Plans to enhance the WeaveVM platform and attract more developers to build on the Permaweb.
• Exciting collaborations with partners in archiving and decentralized data storage.

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Contribute to the Open Web:

⁠⁠https://openinformation.io/grant

In this episode, we sit down with Michael Yung, a strategic advisor at Google Cloud, to explore the latest advancements in AI and Web3 technologies. Tune in to hear about how Google Cloud supports AI & Web3 applications, the integration of AI in various industries, and Michael's personal journey from early cryptocurrency adoption to developing innovative applications using Google Cloud's AI, Gemini.

Co-produced by ⁠RSS3⁠.

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CHAPTERS

00:00 Intro

00:29 Current Focus At Google Cloud

• Currently focusing on AI and Web3 technologies, advising projects on how these technologies impact business strategies.
• Conducting workshops and collaborating with colleagues for technology implementation.

01:49 Personal Journey and Experience

• Been in the tech industry since 2012
• Early crypto trading experiences
• Also an indie developer - built an app using Gemini for travel journaling

04:35 Google Cloud and Gemini

• Google Cloud’s robust infrastructure supports a variety of products
• Gemini is highly capable and provides multimodal support for text, images, videos, and audio, with a large token context window for extensive data processing

08:14 Existing Integrations

• Financial institutions using AI for data analysis and training tools
• Insurance companies using video analysis for claims
• Web2 companies transitioning to Web3 with smart contracts

12:50 Traditional Tech VS Web3 Industry

• Discusses the risk-averse nature of Web2 companies and the new use cases and benefits offered by Web3 technologies
• Emphasizes the role of Google Cloud in bridging these technologies

14:42 Future of the AI and Web3 Integration

• The potential of using spare GPU capacities for AI model training and the concept of AI agents performing different tasks
• The use of tokens for rewarding AI agents and the benefits of combining AI and Web3

17:43 Advice for Developers

• Using Gemini’s tools like the chatbot and AI studio for testing
• Exploring different AI models from the Model Garden, which includes over 150 models, to fit specific business cases
• Starting with Google Cloud Console for testing various features

20:56 Google Cloud Model Garden

• Various models specific to healthcare, security, and text-based applications
• The potential for Web3 native models and the contribution of community models to Google Cloud

23:30 Working At Google

25:50 Closing Comments

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Contribute to the Open Web:

⁠https://openinformation.io/grant

Join the discussion on Web3+AI with Altan Tutar, Senior Tech BD from Near Protocol, Clemens Wan, Global Solutions Architect / Lead AI Evangelist from Consensys, Henry Wang, CTO of RSS3, João Fiadeiro, Chief Product Officer of Catena Labs, and Ben Jones, CMO of LazAI & P1X Labs.

How can AI be adapted to the decentralized environment? What are the benefits and challenges? What do the existing and future innovations stand on?

Tune in to hear from leaders on the cutting edge of AI and Web3 technologies.

Co-produced by RSS3.

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CHAPTERS

0:00 Intro

4:12 Adapting AI to Web3 & Existing Innovations

• zkML (zero-knowledge markup language) for verifiable machine learning in DeFi and games.
• AI agents operating on-chain with verifiable outputs and permissionless goal achievement.
• The OpenAgent framework for Web3 native use cases.
• Optimistic ML using off-the-shelf models with zk proofs for partial verifiability.

14:35 Benefits from the Web3+AI Integration

• Potential for fairer access and reduced costs compared to centralized AI providers.
• Increased transparency and trust through verifiable computation and agent actions.
• Fostering user ownership and control over AI models and data.

21:06 Challenges in the Decentralized Environment

Scalability and Compute:

• Decentralized systems are inherently expensive due to the distributed nature of computation and storage, and it can be difficult to scale blockchains efficiently.

• Maintaining consistency and ensuring minimal latency & reliable connections are difficult but crucial.

Data Management:

• Storing, referencing, and training data in a decentralized system presents architectural and logistical challenges.
• Balancing data privacy with accessibility for training and inference is crucial.

Economic Incentives:

• It is essential to attract and incentivize GPU owners to contribute their resources to decentralized AI systems.
• Developing a sustainable economic model to compensate node and agent operators for their contributions remains a work in progress.

Other:

• Gather focus beyond the crypto bubble and address the broader societal implications of AI.

26:35 Risks and Concerns

• Web3 technologies actually help with data privacy issues for AI rather than threats due to their decentralization nature.
• Emerging local models are bringing lots of opportunities.
• Unpredictable outputs can be concerning.
• AI can create inequality as its performance is directly related to the resources put into the training.
• Autonomous agents capable of on-chain operations, e.g., token transfers, can be tricky.
• Large models are mostly withheld by big corporations and not open-sourced, and access to them can be restricted easily.

32:50 What to Expect for the Future of Decentralized AI

• More zk technology to enable more verifiable methods of model evaluations
• Next-gen hardware and DePINS for AI.
• More open-sourced models.
• AI games.
• Better aligned and tuned private AI agent.

42:57 Tips for Building in AI+Web3

Focus on User Needs:

• Build solutions that address real problems and have a clear target audience. Don't just chase trends or build "vaporware."
• Partner with established players and communities to gain feedback and traction.
• Utilize resources like grants and collaboration opportunities offered by various projects.

Technical Considerations:

• Understand inherent challenges like scalability, latency, and data management.
• Explore innovative solutions like zkML for verifiable machine learning and agent frameworks for distributed tasks.
• Consider the economic aspects of incentivizing participation in a decentralized AI system.

Additional Tips:

• Be open to wearing different hats and entrepreneurial opportunities beyond coding.
• Leverage AI agents to assist with tasks like customer service.
• Understand the technical foundations of LLMs and the limitations of the current web2 infrastructure.

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Contribute to the Open Web:

https://openinformation.io/grant