unit

etl/steps/data/garden/artificial_intelligence/2025-02-27/epoch_price_reduction.meta.yml

@@ -2,6 +2,8 @@
 definitions:
   common:
     processing_level: minor
+    unit: "reduction in price per year"
+    short_unit: "x per year"
     presentation:
       topic_tags:
         - Artificial Intelligence
@@ -17,19 +19,13 @@ tables:
     variables:
       gpqa_diamond:
         title: Scientific questions
-        unit: "reduction in price per year"
       humaneval:
         title: Coding
-        unit: "reduction in price per year"
       lmsys_chatbot_arena_elo:
         title: Chatbot arena
-        unit: "reduction in price per year"
       math_5:
         title: Math (easier)
-        unit: "reduction in price per year"
       math_500:
         title: Math (harder)
-        unit: "reduction in price per year"
       mmlu:
         title: General language understanding
-        unit: "reduction in price per year"

etl/steps/data/garden/artificial_intelligence/2025-02-27/epoch_price_reduction.py

@@ -30,6 +30,7 @@ def run(dest_dir: str) -> None:
     tb_pivot.columns = [str(col) for col in tb_pivot.columns]
 
     tb_pivot = tb_pivot.rename(columns={"threshold_model": "country"})
+    print(tb_pivot)
 
     tb_pivot = tb_pivot.format(["country", "year"])
 

etl/steps/data/meadow/artificial_intelligence/2025-02-27/epoch_price_reduction.py

@@ -26,12 +26,6 @@ def run(dest_dir: str) -> None:
     #
     tb = tb[["bench", "threshold_model", "end_date", "price_reduction_factor_per_year"]]
     tb["year"] = 2025
-    print(tb)
-    # Convert price_reduction_factor_per_year to float
-    tb["price_reduction_factor_per_year"] = tb["price_reduction_factor_per_year"].astype(float)
-    # Express price_reduction_factor_per_year in logarithmic scale
-    tb["price_reduction_factor_per_year_log"] = np.log(tb["price_reduction_factor_per_year"])
-    print(tb)
 
     tb = tb.drop(columns=["end_date"])
     tb = tb.format(["bench", "threshold_model", "year"])