WHY HROS.dev?
1.
Professional Development Program for HARSH Robotics Innovation
2.
Swarm Revolution: Smaller, Lighter, Swarms Of Autonomous Systems To Transform Agriculture
3.
MLIR Performance Reqmts For Harsh Environments
4.
MLIR Compiler Fold Mechanisms
5.
Swarm Robotic Mgmt Systems -- Small Multi-Species Livestock Grazing Agroforestry Understory
6.
Virtual Fence Collars for Livestock: A Potential Swarm Robotics Application
7.
Develop Locally, Deploy To The Cloud
7.1.
Section 1: Foundations of Local Development for ML/AI
7.2.
Section 2: Hardware Optimization Strategies
7.3.
Section 3: Local Development Environment Setup
7.4.
Section 4: Model Optimization Techniques
7.5.
Section 5: MLOps Integration and Workflows
7.6.
Section 6: Cloud Deployment Strategies
7.6.1.
Specialized GPU Cloud Providers for Cost Savings
7.7.
Section 7: Real-World Case Studies
7.8.
Section 8: Miscellaneous "Develop Locally, DEPLOY TO THE CLOUD" Content
8.
50-Day Study Plan
8.1.
Day 1-2 Rust/Tauri
8.2.
Day 3-4 LLMs and LLMops
8.3.
Day 5-6 Ingesting APIs
8.4.
Day 7-8 Data Wrangling
8.5.
Day 9-10 Vector Databases
8.6.
Day 11-12 Jujutsu & GitHub
8.7.
Day 13-14 arXiv API
8.8.
Day 15-16 HuggingFace API
8.9.
Day 17-19 Patent APIs
8.10.
Day 20-22 FinNews APIs
8.11.
Day 23-25 Email APIs
8.12.
Day 26-28 Anthropic MCP
8.13.
Day 29-31 Google A2A
8.14.
Day 32-34 Agent Orchestration
8.15.
Day 35-37 Info Summarization
8.16.
Day 38-40 Learning Preferences
8.17.
Day 41-43 Data Persistence
8.18.
Day 44-46 Adv Email w/AI
8.19.
Day 47-48 Refactor UI
8.20.
Day 49-50 Deploy/Test
8.21.
Milestones
8.22.
Daily Workflow
8.23.
Autodidacticism
8.24.
Communities
8.25.
Papers
8.26.
Documentation
8.27.
References
9.
Blogifying The Plan
9.1.
Rust Dev Fundamentals
9.2.
Tauri Development
9.2.1.
Tauri vs Electron
9.2.2.
Svelte With Tauri
9.3.
ML/AI Development
9.4.
ML/AIOps System Design
9.5.
Personal Assistant Agentic Systems (PAAS)
9.6.
Multi-Agent Systems and Architecture
9.7.
Data Storage and Processing Technologies
9.8.
Creative Process Flow For Development
9.9.
Philosophy/Principles
9.10.
Cross-Platform
10.
ML/AI Ops Study Notes
10.1.
Rust Language
10.2.
Tauri
10.3.
Cargo
10.4.
crates.io
11.
Information Autonomy
11.1.
Philosophical Foundations
11.2.
Technical Foundations
11.3.
Adv Observability Enrg
11.4.
Data Pipeline Architecture
11.5.
Knowledge Engineering
11.6.
Unobtrusive AI Assistance
11.7.
Architecture Integration
11.8.
Compute Resources
11.9.
Implementation Roadmap
11.10.
Application, Adjustment
11.11.
Future Directions
11.12.
Conclusion
Light
Rust
Coal
Navy
Ayu
HARSH (Hazardous, Austere, Remote, Severe, and Hostile) Robotic Operating System Development
References Pertinent To Our Intelligence Gathering System
Cloud Compute
RunPod
ThunderCompute
VAST.ai
Languages
Go
Python
Rust
Rust Package Mgmt
crates.io
Cargo
Tauri
Typescript
Libraries/Platforms for LLMs and ML/AI
HuggingFace
Kaggle
Ollama
OpenAI
Papers With Code
DVCS
Git
Jujutsu