josh d7d77238b9 Redesign model lifecycle: upfront SFT/alignment, multi-size families, point releases, quantization-only variants ...

Training pipeline now requires SFT specializations and alignment method configured at start — no more
mid-training configuration step. Model families support multiple size tiers (Nano/Small/Medium/Large/Flagship)
trained independently, mimicking real AI company model families. Point releases iterate on deployed models
with 40% training time and 8% capability gain. Distillation and fine-tuning variants removed — players
train smaller size tiers or configure SFT during initial training instead. Only quantization remains as
a variant type.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

2026-04-25 11:00:38 -04:00

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src

Redesign model lifecycle: upfront SFT/alignment, multi-size families, point releases, quantization-only variants

2026-04-25 11:00:38 -04:00

package.json

Add Docker and Gitea Actions CI/CD pipeline

2026-04-24 18:27:07 -04:00

tsconfig.json

Initial scaffold: AI Tycoon monorepo with core game loop

2026-04-24 16:53:46 -04:00