export function StatsSection() { const stats = [ { value: "124M", label: "Parameters", sub: "GPT-2 base" }, { value: "988", label: "MB Model Size", sub: "Full precision" }, { value: "37,500", label: "Total Steps", sub: "Target" }, { value: "2,000", label: "Steps Completed", sub: "5.3% done" }, { value: "50+", label: "Hours Training", sub: "On a phone" }, { value: "$0", label: "Total Cost", sub: "Zero cloud" }, { value: "~86s", label: "Per Step", sub: "Snapdragon 685" }, { value: "+146%", label: "Quality Gain", sub: "CP-1400 to CP-2000" }, ] const timeline = [ { step: "Phase 1", title: "Foundation", status: "complete", items: [ "Training pipeline on mobile", "Custom tokenizer", "Checkpoint system", "Evaluation framework", ], }, { step: "Phase 2", title: "Current", status: "active", items: [ "Continued pre-training", "Language expansion", "YUY CLI tool (Rust)", "YUY-Chat TUI interface", ], }, { step: "Phase 3", title: "Upcoming", status: "planned", items: [ "Yuuki v0.1 full release", "Research paper publication", "Native model (from scratch)", "Community model hub", ], }, ] return (
Numbers

Progress is Real

Every metric is measurable and reproducible. Trained at zero cost with consistent improvements across checkpoints.

{/* Stats grid */}
{stats.map((stat) => (
{stat.value}
{stat.label}
{stat.sub}
))}
{/* Roadmap / Timeline */}
{timeline.map((phase) => (
{phase.step}

{phase.title}

    {phase.items.map((item) => (
  • {item}
  • ))}
))}
{/* Why it matters */}

Why This Matters

Accessibility

Students without GPU access can experiment with ML training. No cloud account, no credit card, no barriers.

Democratization

Proves that meaningful ML research can happen anywhere in the world, with just a phone and determination.

Edge ML

Explores the limits of what is possible with mobile hardware, pushing edge ML training into new territory.

) }