Overhaul model system with multi-stage training, variants, benchmarks, and eval

Replace the single-stage training + flat capability score with a realistic AI
development pipeline: pre-training with Chinchilla scaling laws, SFT with
specializations, alignment with safety/capability tradeoffs (RLHF/DPO/Constitutional),
model families with distillation/fine-tuning/quantization variants, named benchmark
suite with compute-costing eval jobs, and segment-specific market quality.

Phases 1-6 of the model rework plan: new types, engine rewrite, save migration,
training events/risk system, concurrent training, variant creation, benchmark
evaluation with leaderboard, and market integration.

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

apps/web/src/pages/DashboardPage.tsx

@@ -13,8 +13,8 @@ export function DashboardPage() {
   const expensesPerTick = useGameStore((s) => s.economy.expensesPerTick);
   const totalFlops = useGameStore((s) => s.infrastructure.totalFlops);
   const totalDCs = useGameStore((s) => s.infrastructure.totalDataCenterCount);
-  const trainedModels = useGameStore((s) => s.models.trainedModels);
-  const activeTraining = useGameStore((s) => s.models.activeTraining);
+  const baseModels = useGameStore((s) => s.models.baseModels);
+  const activePipelines = useGameStore((s) => s.models.activeTrainingPipelines);
   const subscribers = useGameStore((s) => s.market.consumers.totalSubscribers);
   const reputation = useGameStore((s) => s.reputation.score);
   const inferenceUtil = useGameStore((s) => s.compute.inferenceUtilization);
@@ -33,13 +33,13 @@ export function DashboardPage() {
         </TutorialHint>
       )}
 
-      {totalDCs > 0 && trainedModels.length === 0 && !activeTraining && (
+      {totalDCs > 0 && baseModels.length === 0 && activePipelines.length === 0 && (
         <TutorialHint id="train-first-model">
           You have compute available! Head to the Models tab to allocate compute for training and start your first model.
         </TutorialHint>
       )}
 
-      {trainedModels.length > 0 && !trainedModels.some(m => m.isDeployed) && (
+      {baseModels.length > 0 && !baseModels.some(m => m.isDeployed) && (
         <TutorialHint id="deploy-model">
           Your model is trained! Deploy it from the Models tab to start serving customers and earning revenue.
         </TutorialHint>
@@ -66,8 +66,8 @@ export function DashboardPage() {
         <StatCard
           icon={Brain}
           label="Models"
-          value={trainedModels.length.toString()}
-          subValue={activeTraining ? `Training: ${Math.floor((activeTraining.progressTicks / activeTraining.totalTicks) * 100)}%` : 'Idle'}
+          value={baseModels.length.toString()}
+          subValue={activePipelines.filter(p => p.status === 'active').length > 0 ? `Training: ${activePipelines.filter(p => p.status === 'active').length} active` : 'Idle'}
           color="text-purple-400"
           onClick={() => useGameStore.getState().setActivePage('models')}
         />