🛣️Roadmap

Phase 1: Project Initiation and Infrastructure Development

• Token Launch

• Introducing GPU infrastructure: To improve AI processing capacity, introduce GPU-accelerated computing capabilities.

• Creating AI agents: Use AI agents to help AI models make intelligent decisions and behave adaptively.

• Integration of the AI Layer1 DAG blockchain: To build a highly scalable and effective blockchain for AI applications, introduce the AI Layer1 DAG blockchain, which combines components of BitTensor and KASPA.

• Deployment of decentralized AI nodes: To enable GPU-accelerated computation and AI agents, extend the network of distributed AI nodes.

Phase 2: Platform Expansion and Integrations

• AI marketplace launch: Create a marketplace for developers to utilize, commercialize, and distribute AI models and algorithms to consumers.

• AI-as-a-Service (AIaaS): Provide users with AI-as-a-Service options so they are able to pay for the resources used and get AI capabilities whenever they need them.

• Increased usage cases: Examine novel decentralized AI application cases in sectors, such as finance, healthcare, and smart cities.

• Improved compatibility: Boost communication between internal and external networks and systems to provide easy integration with current cloud infrastructure and AI frameworks.

Phase 3: Community Building and Engagement

• Community-driven governance: Put in place decentralized governance systems to enable stakeholders to take part in the formulation and application of AI-related policies.

• Outreach to developers and support: Offer information, guidelines, and assistance to developers that want to use the DeCloud platform to create AI applications.

• Education and awareness campaigns: Start educational programs to inform users and developers about the possibilities of cloud computing and decentralized AI and building on DeCloud.

• Strategic partnerships: To promote development and innovation in the decentralized AI and cloud computing area, create alliances and partnerships with other initiatives and platforms.

Phase 4: Scaling and Optimization

• Infrastructure scalability: To meet rising demand and workload needs, expand GPU infrastructure and decentralized AI nodes.

• Algorithm optimization: To increase accuracy, efficiency, and performance, AI algorithms and models should be continuously improved.

• Research & development: Make investments in this area to investigate novel AI methods, tools, and uses.

• Iterate and enhance the DeCloud platform continuously, taking into account user input, industry trends, and technology improvements.