Darcy Liu@darcy_liu483

**Inspiration** EdenHouse addresses food security by tackling rising grocery prices, vulnerable supply chains, accessibility issues, and the disruption from traditional systems. **Connection to AI and Power** EdenHouse leverages principles from distributed AI and power generation: - **Scalability**: Like Kubernetes scales applications, EdenHouse scales food production. - **Fault Tolerance**: Ensures continuous food supply despite setbacks. **What It Does** EdenHouse is a hydroponics orchestrator akin to Kubernetes: - **Hydroponics Setup**: Modular and efficient plant growth. - **AI-Assisted Monitoring**: Automates feeding, climate control, and lighting. - **Community System**: Facilitates trading and selling homegrown produce. - **Scalability**: Grows more units as demand increases. **Challenges** Ensuring user-friendly design, minimizing maintenance, integrating AI, and creating a community trading platform. **Accomplishments** Low-maintenance hydroponics system and a framework for community engagement. **What's Next** Expanding outreach, enhancing AI, partnering with local restaurants, and exploring subsidized solar panel options. Check Out Our Website: duo-keyboard-koalition.github.io GitHub Repo: [GitHub Repo](https://github.com/duo-keyboard-koalition)

The DeepSeek Business Creator demonstrates how to leverage DeepSeek's latent reasoning space to emulate three-agent interaction for multi-business creation on the web. This system integrates a simple Markov chain optimization process with browser automation, allowing businesses to emerge dynamically in an optimized sequence. The approach enables AI-driven enterprises to launch and scale efficiently, simulating real-world economic expansion with minimal human intervention. From an initial dataset of 200 business ideas, 20 were selected based on predefined success factors. Each of these businesses was assigned three AI agents, each specializing in different aspects of business creation: market research, operational strategy, and adaptive growth. The sequence of business creation was optimized using a Markov chain model, ensuring that dependencies between business types and market readiness were accounted for. This optimization increased the likelihood of success by structuring the order in which AI-driven businesses launched and scaled. AI agents interacted within DeepSeek’s latent space to generate business plans dynamically. These plans emerged from the interplay of three AI agents, refining concepts based on strategic reasoning. Once validated, browser automation was used to execute the launch of these businesses, coordinating their deployment across different online markets. As AI-driven businesses launched, they began to emerge in various markets worldwide. The system's ability to simulate economic scaling in a decentralized manner demonstrated the potential of AI agents to drive real-world business success autonomously. As businesses evolved, AI agents adapted and absorbed the most successful strategies. The agent absorption rule ensured that underperforming agents were phased out, while the most effective decision-making patterns were integrated into the next generation of business iterations.