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DCo Podcast: Interview with Shaw

Timestamps​

  1. Origins of ai16z (0:00-5:40)
  • ai16z started as a token and DAO with a treasury
  • Uses ELIZA framework, which is open source
  • Initially raised 420.69 SOL
  • Focus on autonomous investing
  1. Shaw's Background (5:41-12:08)
  • Transitioned from music career/audio engineering
  • Had a touring band and worked as sound engineer in NYC
  • Shifted to programming to "build the future"
  • Got involved in metaverse and AI development
  1. Early Crypto/AI Integration (12:09-20:46)
  • Created DJen Spartan AI with Skelly
  • Used Meta Llama 40B model
  • Focus on personality and engagement rather than token shilling
  • Built community around AI agents
  1. Eliza Framework Development (20:47-27:34)
  • Conflict with competing Eliza implementations
  • Focus on high-quality art and development
  • Community contributions and open source approach
  1. Technical Infrastructure (27:35-34:09)
  • Autonomous investor capabilities
  • Integration with DeFi protocols
  • Trust scoring system for trading advice
  • Paper trading marketplace
  1. Framework Architecture (34:10-41:27)
  • Comparison to Next.js for AI agents
  • Focus on accessibility for web developers
  • Dynamic prompt engineering
  • Integration with social media
  1. Beyond Meme Coins (41:28-46:54)
  • Vision for legitimate investment opportunities
  • Community-driven development
  • Focus on contributor rewards
  1. Agent Development (46:55-52:09)
  • Different base models and implementations
  • Role of prompt engineering
  • Integration with existing APIs
  • Accessibility for developers
  1. Social Media Impact (52:10-58:42)
  • Potential to replace traditional KOLs
  • Trust economy vs attention economy
  • AI agents providing market analysis
  1. Future Vision (58:43-1:15:00)
  • Goal of universal access to AI tools
  • Potential impact on work and society
  • Focus on community income over UBI
  • Long-term vision for ai16z and ELIZA framework

The interview provides a comprehensive look at how ai16z is working to democratize AI trading tools while building a sustainable framework for future development.

Episode Overview​

In this wide-ranging conversation, Shaw (founder of ai16z DAO and creator of the ELIZA framework) discusses how AI agents are transforming crypto trading. The discussion covers the technical architecture of ELIZA, the vision behind ai16z, and the broader implications of AI agents in finance and society.

Key Topics​

  • Evolution of ai16z from token to comprehensive trading framework
  • Technical architecture of the ELIZA framework
  • Integration of AI agents with social media and DeFi
  • Community-driven development and open source philosophy
  • Future vision for AI in finance and society

Notable Quotes​

On ELIZA Framework​

"What's special about what we did was saying, okay, if I have a community of people, and I want Mark to be able to get alpha from those people [...] how do we know who the best trader is? How do we know what information to actually accept?"

On Developer Accessibility​

"I think most of your average AI dev at Uber is taking the transformer stuff and applying it in their context [...] But most of them even training models is so expensive [...] that most of us end up fine tuning models that we get for free from the large companies."

On Community Development​

"In the last six weeks, we've gotten external contributions from more than 140 people [...] We get eight pull requests on average a day."

On Future Vision​

"The reality is that robots and AI will be better than humans at literally every single thing that there is. And there is no escaping that it is just going to happen. How do we live in that world?"

On AI Trading​

"I really think that the future of this is like AIs are going to invest all of the money. I really think that's like a big part of the future."

Technical Details​

  • Built on Meta Llama 40B model
  • Integrates with DeFi protocols
  • Uses trust scoring system for trading advice
  • Implements paper trading marketplace
  • Features dynamic prompt engineering
  • Open source framework with community contributions

Community Impact​

  • 140+ external contributors
  • 8 daily pull requests on average
  • Thousands of active AI agents
  • Growing ecosystem of developers and users

Future Roadmap​

  • Expanding autonomous investor capabilities
  • Developing trust-based trading systems
  • Building community income mechanisms
  • Creating more accessible AI tools
  • Fostering open-source development