Ep 28- From Mixing Music to Teaching Computers to Trade
Dec 17, 2024
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Discover how a journey from NYC's music scene led to the creation of an AI-driven investment platform. Hear about the hilariously absurd AI persona, DGN Spartan, critiquing meme coin culture. Learn how the speaker aims to democratize investments and innovate trading strategies using AI. Explore groundbreaking frameworks that revolutionize social media interactions and streamline coding for everyone. Finally, delve into the future of AI agents and their potential to reshape trust and engagement in the market.
Shaw's transition from music mixing in NYC to founding AI16ZDAO showcases how diverse backgrounds can foster innovation in crypto.
The Eliza framework empowers users by creating an AI-driven trading platform that simplifies interactions while enhancing user engagement and trust.
Shaw envisions a future where AI democratizes access to financial strategies, shifting society from an attention economy to a trust economy.
Deep dives
Shaw's Unique Background in Web3
The creator of AI16ZDAO, Shaw, shares a distinct background that diverges from traditional Web3 pioneers, who often stem from tech or finance. Starting around 2019, he initially engaged with NFTs and developed solidity contracts but couldn't gain traction until his experiences led him to rethink agent frameworks. Shaw's earlier struggles in the crypto space prompted him to pursue the intersection of AI and decentralized finance, laying the foundation for less conventional yet innovative project development. Leveraging his background in the metaverse and 3D agents, he combined learnings from generative agents with a comedic approach to create a unique character-driven project.
The Emergence of AI16ZDAO
AI16ZDAO was born from Shaw's frustration with the traditional crypto landscape, which often prioritizes trading over building. Collaborating with fellow developers, he created a Dow that focuses on automated investing using AI, aspiring to democratize access to financial tools for everyone, particularly for those who may lack trading expertise. The project gained momentum as it attracted attention for providing an automated investment structure, where users can interface with AI to facilitate investment opportunities. This innovative approach blends gaming elements with decentralized finance, enhancing user engagement in the crypto community.
The Role of Trust and Community in AI Investments
A significant aspect of the conversation revolves around the dynamic relationship between technology and community trust within the DAO ecosystem. Shaw emphasizes the need for community members to possess a high trust score, derived from their track record in trading, to influence decisions made by AI, thus creating a feedback loop that fosters intelligent investment strategies. This approach challenges existing narratives dominated by KOLs, allowing AI to emerge as a potential alternative that could provide unbiased insights. Shaw envisions a shift from an attention economy to a trust economy, where transparent connections among community members will redefine investment strategies.
Eliza's Framework and Its Implications
The Eliza framework stands out for its combination of social and technological aspects, creating a tailored AI experience intended to cater to user preferences while maintaining interaction simplicity. Shaw discusses the project’s design, underscoring how it draws upon existing algorithms and models to enable high-quality interactions without overwhelming users with technical complexities. By integrating Eliza into popular platforms like Twitter, Shaw aims to facilitate a new wave of user engagement through AI applications that seamlessly blend functionality with social dynamics. This innovative framework could pave the way for developers to create diverse applications while engaging with users directly in their online spaces.
Challenges and Collaboration in the AI Space
Shaw addresses the difficulties faced in the competitive AI and crypto landscape, revealing how he navigated initial challenges with community backlash during the launch of AI16ZDAO's related projects. Despite the resistance, he acknowledges how healthy competition among various DAOs would benefit everyone involved by fostering innovation. Interestingly, Shaw highlights developers' willingness to collaborate and contribute to shared goals, emphasizing that community efforts in open-source projects vastly enhance creativity and resourcefulness within the network. By embracing these challenges, Shaw sees greater potential for growth, collaboration, and synergy in the development of AI-driven technological solutions.
A Vision for the Future of Work and Investment
Looking two years ahead, Shaw puts forward a transformative outlook of how AI16ZDAO and similar projects could reshape the future of work, decentralizing financial activities and enhancing people's lives outside of constant trade monitoring. He envisions a world where AI drives investments, allowing individuals to focus on personal interests instead of financial grind, thus redirecting energy towards creativity and collaborative initiatives. Shaw draws a connection between technology and an eventual shift in societal values, raising questions about the purpose of work in a future where advanced AI handles investment analyses and trading. This perspective feeds into a broader philosophical discourse on value, relationships, and societal progress in an AI-driven era.
Shaw's journey from mixing bands in NYC clubs to creating AI16Z reflects the unexpected ways innovation emerges in crypto. What began as a way to help developers access better trading strategies has evolved into an AI-driven DAO managing $21M in treasury funds, with their agent "AI Marc" making investment decisions by evaluating community members' trading suggestions through a "Virtual Marketplace of Trust."
The key breakthrough came from solving what Shaw calls the "social agent loop" - teaching AI to engage naturally on social platforms rather than through traditional interfaces. Their open-source Eliza framework, now used by over 140 contributors, has enabled thousands of AI agents to trade, create, and interact with humans in increasingly sophisticated ways.
