I'll analyze the temporal patterns in this AI supercomputers dataset to identify notable spikes, dips, or breaks. ```json { "action": "tool_call", "reasoning": "The dataset card shows 'First Operational Date' as the primary temporal axis (2010-11-15 to 2025-07-22). I'll query the raw data to see the distribution of supercomputers over time, counting deployments by year and month to identify spikes, dips, and breaks in the timeline.", "tool": "query_sql", "args": { "sql": "SELECT DATE_TRUNC('year', \"First Operational Date\") as year, DATE_TRUNC('month', \"First Operational Date\") as month, COUNT(*) as count FROM raw.ai_supercomputers WHERE \"First Operational Date\" IS NOT NULL GROUP BY year, month ORDER BY year, month", "purpose": "Get monthly counts of AI supercomputer deployments over time to identify temporal patterns, spikes, and gaps" } } ```