Fix compute utilization bug and add subscriber saturation cap
CI / build-and-push (push) Successful in 34s
CI / build-and-push (push) Successful in 34s
Three intertwined fixes: 1. Zero-capacity utilization: when inference allocation was 0%, the guard clause returned 0% utilization instead of 100%, so the market system never penalized satisfaction and subscribers never churned. 2. Stale compute in market: restructured tick order so capacity is computed before market runs, giving satisfaction calculations current-tick demand/capacity ratio instead of previous tick's. 3. Subscriber growth: replaced pure compound growth (reached billions in minutes) with logistic saturation curve. Era-based market caps: startup 10K, scaleup 1M, bigtech 20M, agi 100M. Quality and reputation expand the effective cap. Also tuned FLOPS-to-tokens multiplier (10 → 26) for balanced demand/capacity feel across all eras, and added market saturation indicator to the Market page. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
@@ -1,5 +1,8 @@
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import { useGameStore } from '@/store';
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import { useGameStore } from '@/store';
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import { formatNumber, formatMoney, formatPercent } from '@ai-tycoon/shared';
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import {
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formatNumber, formatMoney, formatPercent,
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MARKET_SIZE_CAP, MARKET_CAP_QUALITY_BONUS, MARKET_CAP_REPUTATION_BONUS,
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} from '@ai-tycoon/shared';
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import { Users, Zap, Shield, TrendingUp, Settings2 } from 'lucide-react';
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import { Users, Zap, Shield, TrendingUp, Settings2 } from 'lucide-react';
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export function MarketPage() {
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export function MarketPage() {
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@@ -10,9 +13,21 @@ export function MarketPage() {
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const inferenceUtil = useGameStore((s) => s.compute.inferenceUtilization);
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const inferenceUtil = useGameStore((s) => s.compute.inferenceUtilization);
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const tokensCapacity = useGameStore((s) => s.compute.tokensPerSecondCapacity);
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const tokensCapacity = useGameStore((s) => s.compute.tokensPerSecondCapacity);
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const tokensDemand = useGameStore((s) => s.compute.tokensPerSecondDemand);
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const tokensDemand = useGameStore((s) => s.compute.tokensPerSecondDemand);
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const currentEra = useGameStore((s) => s.meta.currentEra);
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const reputationScore = useGameStore((s) => s.reputation.score);
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const deployedModels = useGameStore((s) => s.models.trainedModels.filter(m => m.isDeployed));
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const setProductPricing = useGameStore((s) => s.setProductPricing);
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const setProductPricing = useGameStore((s) => s.setProductPricing);
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const setOverloadPolicy = useGameStore((s) => s.setOverloadPolicy);
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const setOverloadPolicy = useGameStore((s) => s.setOverloadPolicy);
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const bestQuality = deployedModels.length > 0
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? Math.max(...deployedModels.map(m => m.benchmarkScore)) / 100
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: 0;
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const eraCapBase = MARKET_SIZE_CAP[currentEra] ?? 100_000_000;
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const effectiveCap = eraCapBase
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* (1 + bestQuality * MARKET_CAP_QUALITY_BONUS)
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* (1 + (reputationScore / 100) * MARKET_CAP_REPUTATION_BONUS);
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const saturation = effectiveCap > 0 ? consumers.totalSubscribers / effectiveCap : 0;
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const chatProduct = productLines.find(p => p.type === 'chat-product');
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const chatProduct = productLines.find(p => p.type === 'chat-product');
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const textApi = productLines.find(p => p.type === 'text-api');
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const textApi = productLines.find(p => p.type === 'text-api');
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@@ -20,7 +35,7 @@ export function MarketPage() {
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<div className="space-y-6">
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<div className="space-y-6">
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<h2 className="text-2xl font-bold">Market</h2>
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<h2 className="text-2xl font-bold">Market</h2>
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<div className="grid grid-cols-3 gap-4">
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<div className="grid grid-cols-4 gap-4">
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<div className="bg-surface-900 border border-surface-700 rounded-xl p-4">
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<div className="bg-surface-900 border border-surface-700 rounded-xl p-4">
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<div className="flex items-center gap-2 mb-2">
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<div className="flex items-center gap-2 mb-2">
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<Users size={16} className="text-orange-400" />
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<Users size={16} className="text-orange-400" />
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@@ -55,6 +70,22 @@ export function MarketPage() {
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{formatNumber(tokensDemand)} / {formatNumber(tokensCapacity)} tok/s
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{formatNumber(tokensDemand)} / {formatNumber(tokensCapacity)} tok/s
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</div>
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</div>
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</div>
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</div>
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<div className="bg-surface-900 border border-surface-700 rounded-xl p-4">
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<div className="flex items-center gap-2 mb-2">
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<TrendingUp size={16} className="text-purple-400" />
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<span className="text-xs text-surface-400 uppercase">Market Saturation</span>
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</div>
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<div className="text-2xl font-bold font-mono">{formatPercent(saturation)}</div>
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<div className="text-xs text-surface-400 mt-1">
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Cap: {formatNumber(effectiveCap)} ({currentEra})
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</div>
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<div className="h-1.5 bg-surface-800 rounded-full mt-2 overflow-hidden">
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<div
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className={`h-full rounded-full ${saturation > 0.9 ? 'bg-danger' : saturation > 0.7 ? 'bg-warning' : 'bg-accent'}`}
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style={{ width: `${Math.min(100, saturation * 100)}%` }}
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/>
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</div>
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</div>
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</div>
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</div>
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<div className="grid grid-cols-2 gap-4">
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<div className="grid grid-cols-2 gap-4">
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@@ -1,24 +1,36 @@
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import type { GameState, ComputeState, InfrastructureState } from '@ai-tycoon/shared';
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import type { GameState, ComputeState, InfrastructureState } from '@ai-tycoon/shared';
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import { FLOPS_TO_TOKENS_MULTIPLIER } from '@ai-tycoon/shared';
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export function processCompute(state: GameState, infrastructure: InfrastructureState): ComputeState {
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export interface CapacityResult {
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totalFlops: number;
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trainingAllocation: number;
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inferenceAllocation: number;
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tokensPerSecondCapacity: number;
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}
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export function computeCapacity(state: GameState, infrastructure: InfrastructureState): CapacityResult {
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const totalFlops = infrastructure.totalFlops;
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const totalFlops = infrastructure.totalFlops;
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const trainingAllocation = state.compute.trainingAllocation;
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const trainingAllocation = state.compute.trainingAllocation;
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const inferenceAllocation = 1 - trainingAllocation;
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const inferenceAllocation = 1 - trainingAllocation;
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const inferenceFlops = totalFlops * inferenceAllocation;
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const inferenceFlops = totalFlops * inferenceAllocation;
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const tokensPerSecondCapacity = inferenceFlops * 10;
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const tokensPerSecondCapacity = inferenceFlops * FLOPS_TO_TOKENS_MULTIPLIER;
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const tokensPerSecondDemand = state.compute.tokensPerSecondDemand;
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return { totalFlops, trainingAllocation, inferenceAllocation, tokensPerSecondCapacity };
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const inferenceUtilization = tokensPerSecondCapacity > 0
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}
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? Math.min(1, tokensPerSecondDemand / tokensPerSecondCapacity)
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: 0;
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export function finalizeCompute(capacity: CapacityResult, totalTokenDemand: number): ComputeState {
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const inferenceUtilization = capacity.tokensPerSecondCapacity > 0
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? Math.min(1, totalTokenDemand / capacity.tokensPerSecondCapacity)
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: (totalTokenDemand > 0 ? 1 : 0);
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return {
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return {
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totalFlops,
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...capacity,
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trainingAllocation,
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tokensPerSecondDemand: totalTokenDemand,
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inferenceAllocation,
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inferenceUtilization,
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inferenceUtilization,
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tokensPerSecondCapacity,
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tokensPerSecondDemand,
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};
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};
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}
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}
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export function processCompute(state: GameState, infrastructure: InfrastructureState): ComputeState {
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const cap = computeCapacity(state, infrastructure);
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return finalizeCompute(cap, state.compute.tokensPerSecondDemand);
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}
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@@ -1,11 +1,16 @@
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import type { GameState, MarketState, ComputeState } from '@ai-tycoon/shared';
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import type { GameState, MarketState } from '@ai-tycoon/shared';
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import {
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import {
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CONSUMER_BASE_GROWTH,
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CONSUMER_BASE_GROWTH,
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CONSUMER_QUALITY_GROWTH_MULTIPLIER,
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CONSUMER_QUALITY_GROWTH_MULTIPLIER,
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CONSUMER_BASE_CHURN,
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CONSUMER_BASE_CHURN,
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CONSUMER_TOKENS_PER_SUBSCRIBER,
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API_TOKENS_PER_REQUEST,
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API_TOKENS_PER_REQUEST,
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OPEN_SOURCE_REVENUE_PENALTY,
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OPEN_SOURCE_REVENUE_PENALTY,
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OPEN_SOURCE_TALENT_ATTRACTION,
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OPEN_SOURCE_TALENT_ATTRACTION,
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MARKET_SIZE_CAP,
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MARKET_CAP_QUALITY_BONUS,
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MARKET_CAP_REPUTATION_BONUS,
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OVERLOAD_PENALTY_EXPONENT,
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} from '@ai-tycoon/shared';
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} from '@ai-tycoon/shared';
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export interface MarketTickResult {
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export interface MarketTickResult {
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@@ -15,7 +20,7 @@ export interface MarketTickResult {
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totalTokenDemand: number;
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totalTokenDemand: number;
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}
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}
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export function processMarket(state: GameState, compute: ComputeState): MarketTickResult {
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export function processMarket(state: GameState, currentTickCapacity: number): MarketTickResult {
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const bestModel = state.models.trainedModels
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const bestModel = state.models.trainedModels
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.filter(m => m.isDeployed)
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.filter(m => m.isDeployed)
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.sort((a, b) => b.benchmarkScore - a.benchmarkScore)[0];
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.sort((a, b) => b.benchmarkScore - a.benchmarkScore)[0];
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@@ -33,7 +38,17 @@ export function processMarket(state: GameState, compute: ComputeState): MarketTi
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const fairPrice = 20 + modelQuality * 80;
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const fairPrice = 20 + modelQuality * 80;
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const priceRatio = price / Math.max(1, fairPrice);
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const priceRatio = price / Math.max(1, fairPrice);
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const priceAttractiveness = Math.max(0, Math.min(1, 1 - (priceRatio - 1) * 0.8));
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const priceAttractiveness = Math.max(0, Math.min(1, 1 - (priceRatio - 1) * 0.8));
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const growthRate = (CONSUMER_BASE_GROWTH + modelQuality * CONSUMER_QUALITY_GROWTH_MULTIPLIER) * priceAttractiveness;
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// --- Logistic growth with era-based market cap ---
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const eraCapBase = MARKET_SIZE_CAP[state.meta.currentEra] ?? 100_000_000;
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const effectiveCap = eraCapBase
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* (1 + modelQuality * MARKET_CAP_QUALITY_BONUS)
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* (1 + (state.reputation.score / 100) * MARKET_CAP_REPUTATION_BONUS);
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const saturationFactor = Math.max(0, 1 - consumers.totalSubscribers / effectiveCap);
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const growthRate = (CONSUMER_BASE_GROWTH + modelQuality * CONSUMER_QUALITY_GROWTH_MULTIPLIER)
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* priceAttractiveness * saturationFactor;
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const priceChurnMultiplier = priceRatio > 1 ? 1 + (priceRatio - 1) * 3 : 1;
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const priceChurnMultiplier = priceRatio > 1 ? 1 + (priceRatio - 1) * 3 : 1;
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const churnRate = CONSUMER_BASE_CHURN * (1 + (1 - consumers.satisfaction) * 2) * priceChurnMultiplier;
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const churnRate = CONSUMER_BASE_CHURN * (1 + (1 - consumers.satisfaction) * 2) * priceChurnMultiplier;
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@@ -42,25 +57,51 @@ export function processMarket(state: GameState, compute: ComputeState): MarketTi
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const newSubs = consumers.totalSubscribers * growthRate;
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const newSubs = consumers.totalSubscribers * growthRate;
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const lostSubs = consumers.totalSubscribers * churnRate;
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const lostSubs = consumers.totalSubscribers * churnRate;
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consumers.totalSubscribers = Math.max(0, consumers.totalSubscribers + newSubs - lostSubs);
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consumers.totalSubscribers = Math.max(0, Math.min(
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effectiveCap,
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consumers.totalSubscribers + newSubs - lostSubs,
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));
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if (consumers.totalSubscribers < 100 && modelQuality > 0.1 && priceRatio < 3) {
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if (consumers.totalSubscribers < 100 && modelQuality > 0.1 && priceRatio < 3) {
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consumers.totalSubscribers += 5 + modelQuality * 20;
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consumers.totalSubscribers += 5 + modelQuality * 20;
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}
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}
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const loadPenalty = compute.inferenceUtilization > 0.9
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// --- Satisfaction from demand/capacity ratio (current tick) ---
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? (compute.inferenceUtilization - 0.9) * 5
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const consumerDemand = consumers.totalSubscribers * CONSUMER_TOKENS_PER_SUBSCRIBER;
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: 0;
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let demandCapacityRatio: number;
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if (currentTickCapacity > 0) {
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demandCapacityRatio = consumerDemand / currentTickCapacity;
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} else {
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demandCapacityRatio = consumerDemand > 0 ? 10 : 0;
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}
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let headroomBonus = 0;
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let overloadPenalty = 0;
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if (demandCapacityRatio <= 1) {
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headroomBonus = (1 - demandCapacityRatio) * 0.2;
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} else {
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overloadPenalty = Math.min(1, Math.pow(demandCapacityRatio - 1, OVERLOAD_PENALTY_EXPONENT));
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}
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consumers.satisfaction = Math.min(1, Math.max(0,
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consumers.satisfaction = Math.min(1, Math.max(0,
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0.3 + modelQuality * 0.5 + (1 - Math.min(1, compute.inferenceUtilization)) * 0.2 - loadPenalty,
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0.3 + modelQuality * 0.5 + headroomBonus - overloadPenalty,
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));
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));
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consumers.viralCoefficient = modelQuality > 0.5 ? 1 + (modelQuality - 0.5) * 2 : 0;
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consumers.viralCoefficient = modelQuality > 0.5 ? 1 + (modelQuality - 0.5) * 2 : 0;
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subscriptionRevenue = consumers.totalSubscribers * (chatProduct.pricing.subscriptionPrice / 86400);
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subscriptionRevenue = consumers.totalSubscribers * (chatProduct.pricing.subscriptionPrice / 86400);
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// --- Overload policy ---
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const policy = state.market.overloadPolicy;
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if (policy.degradeQualityUnderLoad && demandCapacityRatio > 0.85) {
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consumers.satisfaction = Math.max(0, consumers.satisfaction - 0.02);
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}
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if (policy.prioritizeEnterprise && demandCapacityRatio > 0.9) {
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consumers.satisfaction = Math.max(0, consumers.satisfaction - 0.01);
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}
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}
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}
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// --- B2B API market (organic demand based on model quality + reputation) ---
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// --- B2B API market ---
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const enterprise = { ...state.market.enterprise };
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const enterprise = { ...state.market.enterprise };
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let apiRevenue = 0;
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let apiRevenue = 0;
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let organicApiTokens = 0;
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let organicApiTokens = 0;
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@@ -80,29 +121,26 @@ export function processMarket(state: GameState, compute: ComputeState): MarketTi
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apiRevenue += (contract.tokensPerTick / 1_000_000) * contract.pricePerMToken;
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apiRevenue += (contract.tokensPerTick / 1_000_000) * contract.pricePerMToken;
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}
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}
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const totalApiTokens = organicApiTokens + contractTokens;
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apiRevenue += (organicApiTokens / 1_000_000) * textApi.pricing.outputTokenPrice;
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apiRevenue += (organicApiTokens / 1_000_000) * textApi.pricing.outputTokenPrice;
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enterprise.totalApiCallsPerTick = (organicApiTokens + contractTokens) / API_TOKENS_PER_REQUEST;
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enterprise.totalApiCallsPerTick = totalApiTokens / API_TOKENS_PER_REQUEST;
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}
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}
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const totalTokenDemand = organicApiTokens +
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const totalTokenDemand = organicApiTokens +
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consumers.totalSubscribers * 0.5 +
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consumers.totalSubscribers * CONSUMER_TOKENS_PER_SUBSCRIBER +
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enterprise.activeContracts.reduce((s, c) => s + c.tokensPerTick, 0);
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enterprise.activeContracts.reduce((s, c) => s + c.tokensPerTick, 0);
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// --- Open source effects ---
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const openSourceCount = state.market.openSourcedModels.length;
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const openSourceCount = state.market.openSourcedModels.length;
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if (openSourceCount > 0) {
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if (openSourceCount > 0) {
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const growthBoost = 1 + openSourceCount * OPEN_SOURCE_TALENT_ATTRACTION;
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const growthBoost = 1 + openSourceCount * OPEN_SOURCE_TALENT_ATTRACTION;
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consumers.totalSubscribers *= growthBoost > 1 ? 1 + (growthBoost - 1) * 0.01 : 1;
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consumers.totalSubscribers *= growthBoost > 1 ? 1 + (growthBoost - 1) * 0.01 : 1;
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apiRevenue *= 1 - openSourceCount * OPEN_SOURCE_REVENUE_PENALTY * 0.3;
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apiRevenue *= 1 - openSourceCount * OPEN_SOURCE_REVENUE_PENALTY * 0.3;
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}
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const policy = state.market.overloadPolicy;
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const eraCapBase = MARKET_SIZE_CAP[state.meta.currentEra] ?? 100_000_000;
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if (policy.degradeQualityUnderLoad && compute.inferenceUtilization > 0.85) {
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const effectiveCap = eraCapBase
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consumers.satisfaction = Math.max(0, consumers.satisfaction - 0.02);
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* (1 + modelQuality * MARKET_CAP_QUALITY_BONUS)
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}
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* (1 + (state.reputation.score / 100) * MARKET_CAP_REPUTATION_BONUS);
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if (policy.prioritizeEnterprise && compute.inferenceUtilization > 0.9) {
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consumers.totalSubscribers = Math.min(effectiveCap, consumers.totalSubscribers);
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consumers.satisfaction = Math.max(0, consumers.satisfaction - 0.01);
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}
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}
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const subscriberHistory = [...(state.market.subscriberHistory || [])];
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const subscriberHistory = [...(state.market.subscriberHistory || [])];
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@@ -1,7 +1,7 @@
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import type { GameState, AchievementDefinition } from '@ai-tycoon/shared';
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import type { GameState, AchievementDefinition } from '@ai-tycoon/shared';
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import { processEconomy } from './systems/economySystem';
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import { processEconomy } from './systems/economySystem';
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import { processInfrastructure } from './systems/infrastructureSystem';
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import { processInfrastructure } from './systems/infrastructureSystem';
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import { processCompute } from './systems/computeSystem';
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import { computeCapacity, finalizeCompute } from './systems/computeSystem';
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import { processResearch } from './systems/researchSystem';
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import { processResearch } from './systems/researchSystem';
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import { processModels } from './systems/modelSystem';
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import { processModels } from './systems/modelSystem';
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import { processMarket } from './systems/marketSystem';
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import { processMarket } from './systems/marketSystem';
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@@ -49,13 +49,10 @@ export function processTick(state: GameState): Partial<GameState> {
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}
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}
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const stateWithModels = { ...stateWithInfra, models: modelResult.modelsState };
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const stateWithModels = { ...stateWithInfra, models: modelResult.modelsState };
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const market = processMarket(stateWithModels, state.compute);
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const compute = processCompute(state, infrastructure);
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const capacity = computeCapacity(state, infrastructure);
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compute.tokensPerSecondDemand = market.totalTokenDemand;
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const market = processMarket(stateWithModels, capacity.tokensPerSecondCapacity);
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compute.inferenceUtilization = compute.tokensPerSecondCapacity > 0
|
const compute = finalizeCompute(capacity, market.totalTokenDemand);
|
||||||
? Math.min(1, market.totalTokenDemand / compute.tokensPerSecondCapacity)
|
|
||||||
: 0;
|
|
||||||
|
|
||||||
const talent = processTalent(stateWithModels);
|
const talent = processTalent(stateWithModels);
|
||||||
const stateWithTalent = { ...stateWithModels, talent };
|
const stateWithTalent = { ...stateWithModels, talent };
|
||||||
|
|||||||
@@ -28,9 +28,24 @@ export const CONSUMER_QUALITY_GROWTH_MULTIPLIER = 0.01;
|
|||||||
export const CONSUMER_PRICE_ELASTICITY = -0.5;
|
export const CONSUMER_PRICE_ELASTICITY = -0.5;
|
||||||
export const CONSUMER_BASE_CHURN = 0.001;
|
export const CONSUMER_BASE_CHURN = 0.001;
|
||||||
|
|
||||||
|
export const CONSUMER_TOKENS_PER_SUBSCRIBER = 0.5;
|
||||||
|
|
||||||
export const API_TOKENS_PER_REQUEST = 500;
|
export const API_TOKENS_PER_REQUEST = 500;
|
||||||
export const API_REVENUE_PER_MTOK = 1.0;
|
export const API_REVENUE_PER_MTOK = 1.0;
|
||||||
|
|
||||||
|
export const MARKET_SIZE_CAP: Record<string, number> = {
|
||||||
|
startup: 10_000,
|
||||||
|
scaleup: 1_000_000,
|
||||||
|
bigtech: 20_000_000,
|
||||||
|
agi: 100_000_000,
|
||||||
|
};
|
||||||
|
export const MARKET_CAP_QUALITY_BONUS = 0.3;
|
||||||
|
export const MARKET_CAP_REPUTATION_BONUS = 0.2;
|
||||||
|
|
||||||
|
export const FLOPS_TO_TOKENS_MULTIPLIER = 26;
|
||||||
|
|
||||||
|
export const OVERLOAD_PENALTY_EXPONENT = 1.5;
|
||||||
|
|
||||||
export const ERA_THRESHOLDS = {
|
export const ERA_THRESHOLDS = {
|
||||||
scaleup: { revenue: 10_000, capability: 15, reputation: 30 },
|
scaleup: { revenue: 10_000, capability: 15, reputation: 30 },
|
||||||
bigtech: { revenue: 1_000_000, capability: 50, reputation: 60 },
|
bigtech: { revenue: 1_000_000, capability: 50, reputation: 60 },
|
||||||
|
|||||||
Reference in New Issue
Block a user