DeepcometAI Master Roadmap
A multi-phase strategy to achieve Vertical AI Integration.
Phase 1: Aurelia Foundation In Progress
Alpha compiler, Lexer, Parser, and MLIR Integration.
Key Milestones
- Implement core lexer and parser in Rust.
- Define AST and intermediate representation.
- Integrate with MLIR for initial code generation.
- Release v0.1.0-alpha to early adopters.
Phase 2: Zenith Kernel
Probabilistic scheduling and AI-Watchdog immune system.
Key Milestones
- Develop probabilistic task scheduler.
- Implement AI-Watchdog for zero-day exploit detection.
- Establish secure IPC mechanisms.
- Initial boot on reference NPU hardware.
Phase 3: SkyOS & Generative UI
Large Action Models (LAM) and Semantic File System.
Key Milestones
- Integrate Large Action Models into the core OS.
- Develop the Semantic File System for context-aware storage.
- Create the Generative UI framework for dynamic interfaces.
- Developer preview release of SkyOS.
Phase 4: DeepComet Model Family
Deployment of Prime, Zenith, Code, and Mobile tiers.
Key Milestones
- Train and release DeepComet-Prime (Trillion-parameter).
- Optimize DeepComet-Zenith for kernel-level operations.
- Release DeepComet-Code for Aurelia synthesis.
- Deploy DeepComet-Mobile for edge devices.
Phase 5: SkyCloud Infrastructure
Decentralized cloud network sharing idle NPU power.
Key Milestones
- Design peer-to-peer NPU sharing protocol.
- Implement secure execution enclaves for shared workloads.
- Launch SkyCloud tokenomics and incentive structure.
- Global network beta testing.