I need to explore the temporal dimensions in this dataset to identify notable spikes, dips, or breaks. Let me start by examining the time-related columns. ```json { "action": "tool_call", "reasoning": "The card shows three temporal axes: Publication date (1950-2026), Training time (hours), and Last modified (2025-2026). I'll query the Publication date column to see the distribution of AI models over time and identify any notable patterns, spikes, or dips.", "tool": "query_sql", "args": { "sql": "SELECT DATE_TRUNC('year', \"Publication date\") as year, COUNT(*) as model_count FROM raw.all_ai_models WHERE \"Publication date\" IS NOT NULL GROUP BY year ORDER BY year", "purpose": "Get yearly distribution of AI model publications to identify temporal patterns", "source": "raw" } } ```