PHPMem v2.0.1

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1.6.45
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llm:abc820ef4c00f4f9781d4756518472d988d5043681cfde12ffff58126e4e6c7a
TTL 7 hours 12 minutes 21 seconds Size 1,37KB Export
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{
    "action": "tool_call",
    "reasoning": "I have good evidence about the geographic distribution and concentration of compute power. The most striking pattern so far is that China has 175 systems (36% of all systems) but only 109,411 H100 equivalents (7% of total compute), while the US has 118 systems (24% of systems) but 1,250,989 H100 equivalents (79% of total compute). This suggests a massive disparity in scale per system. To make this finding more concrete and surprising, I should calculate the average system size for China vs US and show the magnitude of difference.",
    "tool": "query_sql",
    "args": {
        "sql": "SELECT Country, COUNT(*) as system_count, SUM(\"H100 equivalents\") as total_compute, AVG(\"H100 equivalents\") as avg_h100_per_system, SUM(\"H100 equivalents\") / (SELECT SUM(\"H100 equivalents\") FROM raw.ai_supercomputers WHERE \"H100 equivalents\" IS NOT NULL) * 100 as pct_global_compute FROM raw.ai_supercomputers WHERE \"H100 equivalents\" IS NOT NULL AND Country IN ('China', 'United States of America') GROUP BY Country ORDER BY total_compute DESC",
        "purpose": "Calculate the stark contrast in average system size between China and US to quantify the counterintuitive finding that China has more systems but vastly smaller scale",
        "source": "raw"
    }
}