I can see from the evidence that there is a clear time dimension (publication year) and I have the yearly model counts. Let me get the complete time series to identify all notable patterns. ```json { "action": "tool_call", "reasoning": "The result was truncated at 50 rows (ending at 2010), but the dataset spans 1950-2026 according to the card. I need the complete time series to identify spikes, dips, and breaks across the full range, especially the recent years which likely contain the most dramatic changes.", "tool": "query_sql", "args": { "sql": "SELECT EXTRACT(YEAR FROM \"Publication date\") as year, COUNT(*) as model_count FROM raw.all_ai_models WHERE \"Publication date\" IS NOT NULL GROUP BY EXTRACT(YEAR FROM \"Publication date\") ORDER BY year", "purpose": "Get complete yearly model publication counts from 1950-2026 to identify all spikes, dips, and breaks", "source": "raw" } } ```