AI Power Progress iA
Human-first
Clear learning outcomes, real project scaffolds, and safety-aware guidance.
Definition + mission
Augmented Intelligence (iA)
Augmented Intelligence is AI designed to amplify people: learning faster, building better, and making safer decisions.
AI Power Progress iA (also written “PowerProgress”) is an open hub for artificial intelligence, LLMs, and modern engineering—from zero knowledge to leading contributor.
What makes iA different
Open inputs
Open-source courses + open data are the default. Every resource gets a fallback path when possible.
Real operations
Local-first LLMs, embeddings, and cluster ops: learn the systems that power modern AI.
Start here (zero → contributor)
Day 1
Pick a track and the “foundation” stage. Learn fundamentals (math, stats, programming, CS).
Week 1
Build one small project end-to-end: data → model → evaluation → deployment → documentation.
Month 1+
Specialize: RAG, vector DBs, multimodal, robotics, embedded, cybersecurity, quantum, or neuroscience.
Local AI + automation
If you want a smarter local AI, prioritize grounded retrieval (RAG), high-quality datasets, and measurable evals—then scale out with a cluster when needed.
Local LLMs
Run models locally (Ollama + OpenAI-compatible serving patterns) and pick role-specific models (fast, general, code, tutor, embeddings, vision).
RAG + vector DBs
Index your code + docs, refresh embeddings, and keep a clean corpus so automation stays reliable.
Continuous improvement
Use strict data governance: filter sources, log provenance, and validate with eval suites before training or fine-tuning.