Project Genesis: AI on the Verge of Self-Directed Learning
Project Genesis explores AI systems that generate their own curriculum: they sketch plans, simulate outcomes, score the best behaviors, and compress them into reusable skills. The emphasis is on safe exploration, energy-aware strategies, and cross-task transfer — so what a model learns in one sandbox helps everywhere else. With lightweight guardrails (telemetry, red-team checks, ability caps), Genesis pushes rapid iteration without letting models drift off-mission. The goal is simple: smarter agents that learn faster, waste less compute, and adapt cleanly from text workflows to physical robots.
From tokens to transformer: a practical view of how large models are built — a good foundation for understanding how Genesis adds self-directed training on top.
Neural networks 101: visual intuition for representation learning — the bedrock for skill discovery and transfer.