Update and improve capex figures

README.md

@@ -8,5 +8,3 @@ sdk_version: 4.36.1
 app_file: app.py
 pinned: false
 ---
-
-An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index).

big_five_capex.jsonl → ai_cloud_companies_capex.jsonl

@@ -1,40 +1,40 @@
-{"Quarter": "2015 Q3", "Microsoft": 1356, "Google": 2406, "Meta": 780, "Amazon": 1195}
-{"Quarter": "2015 Q4", "Microsoft": 2024, "Google": 2102, "Meta": 692, "Amazon": 1309}
-{"Quarter": "2016 Q1", "Microsoft": 2308, "Google": 2444, "Meta": 1132, "Amazon": 1179}
-{"Quarter": "2016 Q2", "Microsoft": 2655, "Google": 2136, "Meta": 995, "Amazon": 1711}
-{"Quarter": "2016 Q3", "Microsoft": 2163, "Google": 2554, "Meta": 1095, "Amazon": 1841}
-{"Quarter": "2016 Q4", "Microsoft": 1988, "Google": 3078, "Meta": 1269, "Amazon": 3073}
-{"Quarter": "2017 Q1", "Microsoft": 1695, "Google": 2508, "Meta": 1271, "Amazon": 2148}
-{"Quarter": "2017 Q2", "Microsoft": 2283, "Google": 2831, "Meta": 1444, "Amazon": 3113}
-{"Quarter": "2017 Q3", "Microsoft": 2132, "Google": 3538, "Meta": 1755, "Amazon": 3074}
-{"Quarter": "2017 Q4", "Microsoft": 2586, "Google": 4307, "Meta": 2263, "Amazon": 3619}
-{"Quarter": "2018 Q1", "Microsoft": 2934, "Google": 7299, "Meta": 2812, "Amazon": 3098}
-{"Quarter": "2018 Q2", "Microsoft": 3980, "Google": 5477, "Meta": 3460, "Amazon": 3243}
-{"Quarter": "2018 Q3", "Microsoft": 3602, "Google": 5282, "Meta": 3342, "Amazon": 3352}
-{"Quarter": "2018 Q4", "Microsoft": 3707, "Google": 7081, "Meta": 4301, "Amazon": 3734}
-{"Quarter": "2019 Q1", "Microsoft": 2565, "Google": 4638, "Meta": 3837, "Amazon": 3290}
-{"Quarter": "2019 Q2", "Microsoft": 4051, "Google": 6126, "Meta": 3633, "Amazon": 3562}
-{"Quarter": "2019 Q3", "Microsoft": 3385, "Google": 6732, "Meta": 3532, "Amazon": 4697}
-{"Quarter": "2019 Q4", "Microsoft": 3545, "Google": 6052, "Meta": 4100, "Amazon": 5312}
-{"Quarter": "2020 Q1", "Microsoft": 3767, "Google": 6005, "Meta": 3558, "Amazon": 6795}
-{"Quarter": "2020 Q2", "Microsoft": 4744, "Google": 5391, "Meta": 3255, "Amazon": 7459}
-{"Quarter": "2020 Q3", "Microsoft": 4907, "Google": 5406, "Meta": 3689, "Amazon": 11063}
-{"Quarter": "2020 Q4", "Microsoft": 4174, "Google": 5479, "Meta": 4613, "Amazon": 14823}
-{"Quarter": "2021 Q1", "Microsoft": 5089, "Google": 5942, "Meta": 4303, "Amazon": 12082}
-{"Quarter": "2021 Q2", "Microsoft": 6452, "Google": 5496, "Meta": 4641, "Amazon": 14288}
-{"Quarter": "2021 Q3", "Microsoft": 5810, "Google": 6819, "Meta": 4346, "Amazon": 15748}
-{"Quarter": "2021 Q4", "Microsoft": 5865, "Google": 6383, "Meta": 5400, "Amazon": 18935}
-{"Quarter": "2022 Q1", "Microsoft": 5340, "Google": 9786, "Meta": 5441, "Amazon": 14951}
-{"Quarter": "2022 Q2", "Microsoft": 6871, "Google": 6828, "Meta": 7572, "Amazon": 15724}
-{"Quarter": "2022 Q3", "Microsoft": 6283, "Google": 7276, "Meta": 9375, "Amazon": 16378}
-{"Quarter": "2022 Q4", "Microsoft": 6274, "Google": 7595, "Meta": 9043, "Amazon": 16592}
-{"Quarter": "2023 Q1", "Microsoft": 6607, "Google": 6289, "Meta": 6823, "Amazon": 14207}
-{"Quarter": "2023 Q2", "Microsoft": 8943, "Google": 6888, "Meta": 6134, "Amazon": 11455}
-{"Quarter": "2023 Q3", "Microsoft": 9917, "Google": 8055, "Meta": 6543, "Amazon": 12479}
-{"Quarter": "2023 Q4", "Microsoft": 9735, "Google": 11019, "Meta": 7665, "Amazon": 14588}
-{"Quarter": "2024 Q1", "Microsoft": 10952, "Google": 12012, "Meta": 6400, "Amazon": 14925}
-{"Quarter": "2024 Q2", "Microsoft": 13873, "Google": 13186, "Meta": 8173, "Amazon": 17620}
-{"Quarter": "2024 Q3", "Microsoft": 14923, "Google": 13016, "Meta": 8258, "Amazon": 22620}
-{"Quarter": "2024 Q4", "Microsoft": 15804, "Google": 14276, "Meta": 14425, "Amazon": 27834}
-{"Quarter": "2025 Q1", "Microsoft": 16745, "Google": 17197, "Meta": 12941, "Amazon": 25019}
-{"Quarter": "2025 Q2", "Microsoft": 17079, "Google": 22446, "Meta": 16538, "Amazon": 0}
+{"Quarter": "2015 Q3", "Microsoft": 1356, "Google": 2406, "Meta": 780, "Amazon": 1195, "Oracle": 446, "CoreWeave": 0}
+{"Quarter": "2015 Q4", "Microsoft": 2024, "Google": 2102, "Meta": 692, "Amazon": 1309, "Oracle": 195, "CoreWeave": 0}
+{"Quarter": "2016 Q1", "Microsoft": 2308, "Google": 2444, "Meta": 1132, "Amazon": 1179, "Oracle": 368, "CoreWeave": 0}
+{"Quarter": "2016 Q2", "Microsoft": 2655, "Google": 2136, "Meta": 995, "Amazon": 1711, "Oracle": 180, "CoreWeave": 0}
+{"Quarter": "2016 Q3", "Microsoft": 2163, "Google": 2554, "Meta": 1095, "Amazon": 1841, "Oracle": 299, "CoreWeave": 0}
+{"Quarter": "2016 Q4", "Microsoft": 1988, "Google": 3078, "Meta": 1269, "Amazon": 3073, "Oracle": 757, "CoreWeave": 0}
+{"Quarter": "2017 Q1", "Microsoft": 1695, "Google": 2508, "Meta": 1271, "Amazon": 2148, "Oracle": 440, "CoreWeave": 0}
+{"Quarter": "2017 Q2", "Microsoft": 2283, "Google": 2831, "Meta": 1444, "Amazon": 3113, "Oracle": 525, "CoreWeave": 0}
+{"Quarter": "2017 Q3", "Microsoft": 2132, "Google": 3538, "Meta": 1755, "Amazon": 3074, "Oracle": 473, "CoreWeave": 0}
+{"Quarter": "2017 Q4", "Microsoft": 2586, "Google": 4307, "Meta": 2263, "Amazon": 3619, "Oracle": 599, "CoreWeave": 0}
+{"Quarter": "2018 Q1", "Microsoft": 2934, "Google": 7299, "Meta": 2812, "Amazon": 3098, "Oracle": 286, "CoreWeave": 0}
+{"Quarter": "2018 Q2", "Microsoft": 3980, "Google": 5477, "Meta": 3460, "Amazon": 3243, "Oracle": 378, "CoreWeave": 0}
+{"Quarter": "2018 Q3", "Microsoft": 3602, "Google": 5282, "Meta": 3342, "Amazon": 3352, "Oracle": 383, "CoreWeave": 0}
+{"Quarter": "2018 Q4", "Microsoft": 3707, "Google": 7081, "Meta": 4301, "Amazon": 3734, "Oracle": 421, "CoreWeave": 0}
+{"Quarter": "2019 Q1", "Microsoft": 2565, "Google": 4638, "Meta": 3837, "Amazon": 3290, "Oracle": 443, "CoreWeave": 0}
+{"Quarter": "2019 Q2", "Microsoft": 4051, "Google": 6126, "Meta": 3633, "Amazon": 3562, "Oracle": 413, "CoreWeave": 0}
+{"Quarter": "2019 Q3", "Microsoft": 3385, "Google": 6732, "Meta": 3532, "Amazon": 4697, "Oracle": 386, "CoreWeave": 0}
+{"Quarter": "2019 Q4", "Microsoft": 3545, "Google": 6052, "Meta": 4100, "Amazon": 5312, "Oracle": 349, "CoreWeave": 0}
+{"Quarter": "2020 Q1", "Microsoft": 3767, "Google": 6005, "Meta": 3558, "Amazon": 6795, "Oracle": 396, "CoreWeave": 0}
+{"Quarter": "2020 Q2", "Microsoft": 4744, "Google": 5391, "Meta": 3255, "Amazon": 7459, "Oracle": 433, "CoreWeave": 0}
+{"Quarter": "2020 Q3", "Microsoft": 4907, "Google": 5406, "Meta": 3689, "Amazon": 11063, "Oracle": 436, "CoreWeave": 0}
+{"Quarter": "2020 Q4", "Microsoft": 4174, "Google": 5479, "Meta": 4613, "Amazon": 14823, "Oracle": 568, "CoreWeave": 0}
+{"Quarter": "2021 Q1", "Microsoft": 5089, "Google": 5942, "Meta": 4303, "Amazon": 12082, "Oracle": 414, "CoreWeave": 0}
+{"Quarter": "2021 Q2", "Microsoft": 6452, "Google": 5496, "Meta": 4641, "Amazon": 14288, "Oracle": 717, "CoreWeave": 0}
+{"Quarter": "2021 Q3", "Microsoft": 5810, "Google": 6819, "Meta": 4346, "Amazon": 15748, "Oracle": 1062, "CoreWeave": 0}
+{"Quarter": "2021 Q4", "Microsoft": 5865, "Google": 6383, "Meta": 5400, "Amazon": 18935, "Oracle": 925, "CoreWeave": 0}
+{"Quarter": "2022 Q1", "Microsoft": 5340, "Google": 9786, "Meta": 5441, "Amazon": 14951, "Oracle": 1101, "CoreWeave": 18}
+{"Quarter": "2022 Q2", "Microsoft": 6871, "Google": 6828, "Meta": 7572, "Amazon": 15724, "Oracle": 1423, "CoreWeave": 18}
+{"Quarter": "2022 Q3", "Microsoft": 6283, "Google": 7276, "Meta": 9375, "Amazon": 16378, "Oracle": 1719, "CoreWeave": 18}
+{"Quarter": "2022 Q4", "Microsoft": 6274, "Google": 7595, "Meta": 9043, "Amazon": 16592, "Oracle": 2435, "CoreWeave": 18}
+{"Quarter": "2023 Q1", "Microsoft": 6607, "Google": 6289, "Meta": 6823, "Amazon": 14207, "Oracle": 2628, "CoreWeave": 588}
+{"Quarter": "2023 Q2", "Microsoft": 8943, "Google": 6888, "Meta": 6134, "Amazon": 11455, "Oracle": 1913, "CoreWeave": 588}
+{"Quarter": "2023 Q3", "Microsoft": 9917, "Google": 8055, "Meta": 6543, "Amazon": 12479, "Oracle": 1314, "CoreWeave": 588}
+{"Quarter": "2023 Q4", "Microsoft": 9735, "Google": 11019, "Meta": 7665, "Amazon": 14588, "Oracle": 1080, "CoreWeave": 1180}
+{"Quarter": "2024 Q1", "Microsoft": 10952, "Google": 12012, "Meta": 6400, "Amazon": 14925, "Oracle": 1674, "CoreWeave": 1742}
+{"Quarter": "2024 Q2", "Microsoft": 13873, "Google": 13186, "Meta": 8173, "Amazon": 17620, "Oracle": 2798, "CoreWeave": 1731}
+{"Quarter": "2024 Q3", "Microsoft": 14923, "Google": 13016, "Meta": 8258, "Amazon": 22620, "Oracle": 2303, "CoreWeave": 1731}
+{"Quarter": "2024 Q4", "Microsoft": 15804, "Google": 14276, "Meta": 14425, "Amazon": 27834, "Oracle": 3970, "CoreWeave": 3498}
+{"Quarter": "2025 Q1", "Microsoft": 16745, "Google": 17197, "Meta": 12941, "Amazon": 25019, "Oracle": 5862, "CoreWeave": 1407}
+{"Quarter": "2025 Q2", "Microsoft": 17079, "Google": 22446, "Meta": 16538, "Amazon": 32183, "Oracle": 9080, "CoreWeave": 0}

app.py

@@ -5,14 +5,14 @@ import gradio as gr
 import plotly.graph_objects as go
 
 
-def create_big_five_capex_plot() -> go.Figure:
+def create_ai_cloud_companies_plot() -> go.Figure:
     # Read data from the JSON Lines file.
-    with open("big_five_capex.jsonl", "r") as file:
+    with open("ai_cloud_companies_capex.jsonl", "r") as file:
         data = [json.loads(line) for line in file if line.strip()]
 
     quarters: list[str] = [entry["Quarter"] for entry in data]
-    companies = ['Microsoft', 'Google', 'Meta', 'Amazon']
-    colors = ['#80bb00', '#ee161f', '#0065e3', '#ff6200']
+    companies = ['Microsoft', 'Google', 'Meta', 'Amazon', 'Oracle', 'CoreWeave']
+    colors = ['#80bb00', '#ee161f', '#0065e3', '#ff6200', '#f80000', '#4b8bbe']
 
     x_positions = list(range(len(quarters)))
 
@@ -29,7 +29,7 @@ def create_big_five_capex_plot() -> go.Figure:
     fig = go.Figure(data=traces)
     fig.update_layout(
         barmode="stack",
-        title="Capital Expenditures of Amazon, Meta, Google and Microsoft in Millions of USD per Quarter",
+        title="Capital Expenditures (PP&E) of AI Cloud Companies",
         xaxis_title="Quarter",
         yaxis_title="Capital Expenditures (Millions USD)",
         xaxis=dict(
@@ -40,24 +40,50 @@ def create_big_five_capex_plot() -> go.Figure:
         height=800
     )
 
-    # Calculate the x position for the vertical dotted line.
+    # Calculate the x position for the AI race vertical dotted line.
     # We want the line drawn between "2023 Q1" and "2023 Q2".
     try:
         idx_q1 = quarters.index("2023 Q1")
         idx_q2 = quarters.index("2023 Q2")
-        vline_x = (idx_q1 + idx_q2) / 2  # position midway between the two quarters
+        ai_race_vline_x = (idx_q1 + idx_q2) / 2  # position midway between the two quarters
     except ValueError:
         # Fall back if quarters not found.
-        vline_x = 0
+        ai_race_vline_x = 0
 
-    # Add a vertical dotted line spanning the full height
+    # Calculate the x position for the COVID-19 pandemic vertical dotted line.
+    # We want the line drawn between "2020 Q1" and "2020 Q2".
+    try:
+        covid_idx_q1 = quarters.index("2020 Q1")
+        covid_idx_q2 = quarters.index("2020 Q2")
+        covid_vline_x = (covid_idx_q1 + covid_idx_q2) / 2  # position midway between the two quarters
+    except ValueError:
+        # Fall back if quarters not found.
+        covid_vline_x = 0
+
+    # Add a vertical dotted line for AI race spanning the full height
+    fig.add_shape(
+        type="line",
+        xref="x",
+        yref="paper",
+        x0=ai_race_vline_x,
+        y0=0,
+        x1=ai_race_vline_x,
+        y1=1,
+        line=dict(
+            color="black",
+            dash="dot",
+            width=2
+        )
+    )
+
+    # Add a vertical dotted line for COVID-19 pandemic spanning the full height
     fig.add_shape(
         type="line",
         xref="x",
         yref="paper",
-        x0=vline_x,
+        x0=covid_vline_x,
         y0=0,
-        x1=vline_x,
+        x1=covid_vline_x,
         y1=1,
         line=dict(
             color="black",
@@ -66,9 +92,9 @@ def create_big_five_capex_plot() -> go.Figure:
         )
     )
 
-    # Add an annotation label above the vertical line.
+    # Add an annotation label above the AI race vertical line.
     fig.add_annotation(
-        x=vline_x,
+        x=ai_race_vline_x,
         y=1.05,  # place just above the top of the plotting area
         xref="x",
         yref="paper",
@@ -81,6 +107,21 @@ def create_big_five_capex_plot() -> go.Figure:
         align="center"
     )
 
+    # Add an annotation label above the COVID-19 pandemic vertical line.
+    fig.add_annotation(
+        x=covid_vline_x,
+        y=1.05,
+        xref="x",
+        yref="paper",
+        text="COVID-19 pandemic begins",
+        showarrow=False,
+        font=dict(
+            color="black",
+            size=12
+        ),
+        align="center"
+    )
+
     return fig
 
 
@@ -333,6 +374,52 @@ with gr.Blocks() as demo:
             zeroeval_crux_markdown: gr.Markdown = gr.Markdown(
                 value="""Source: [ZeroEval Leaderboard](https://huggingface.co/spaces/allenai/ZeroEval)"""
             )
+        with gr.Tab("PhysBench", visible=False):
+            physbench_plot: gr.Plot = gr.Plot()
+            physbench_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [PhysBench Leaderboard](https://physbench.github.io/#leaderboard)"""
+            )
+        with gr.Tab("MMVU", visible=False):
+            mmvu_plot: gr.Plot = gr.Plot()
+            mmvu_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [MMVU Leaderboard](https://mmvu-benchmark.github.io/#leaderboard)"""
+            )
+        with gr.Tab("EvalPlus", visible=False):
+            evalplus_plot: gr.Plot = gr.Plot()
+            evalplus_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [EvalPlus Leaderboard](https://evalplus.github.io/leaderboard.html)"""
+            )
+        with gr.Tab("MultiChallenge", visible=False):
+            multichallenge_plot: gr.Plot = gr.Plot()
+            multichallenge_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [SEAL Leaderboard: MultiChallenge](https://scale.com/leaderboard/multichallenge)"""
+            )
+        with gr.Tab("VISTA", visible=False):
+            vista_plot: gr.Plot = gr.Plot()
+            vista_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [SEAL Leaderboard: Visual-Language Understanding](https://scale.com/leaderboard/visual_language_understanding)"""
+            )
+        with gr.Tab("ToolComp", visible=False):
+            with gr.Tab("Enterprise"):
+                toolcomp_enterprise_plot: gr.Plot = gr.Plot()
+                toolcomp_enterprise_markdown: gr.Markdown = gr.Markdown(
+                    value="""Source: [SEAL Leaderboard: Agentic Tool Use (Enterprise)](https://scale.com/leaderboard/tool_use_enterprise)"""
+                )
+            with gr.Tab("Chat"):
+                toolcomp_chat_plot: gr.Plot = gr.Plot()
+                toolcomp_chat_markdown: gr.Markdown = gr.Markdown(
+                    value="""Source: [SEAL Leaderboard: Agentic Tool Use (Chat)](https://scale.com/leaderboard/tool_use_chat)"""
+                )
+        with gr.Tab("BFCL", visible=False):
+            bfcl_plot: gr.Plot = gr.Plot()
+            bfcl_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [BFCL Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html)"""
+            )
+        with gr.Tab("Aider Polyglot", visible=False):
+            aider_plot: gr.Plot = gr.Plot()
+            aider_markdown: gr.Markdown = gr.Markdown(
+                value="""Source: [Aider LLM Leaderboards](https://aider.chat/docs/leaderboards/)"""
+            )
         with gr.Tab("OpenCompass", visible=False):
             opencompass_plot: gr.Plot = gr.Plot()
             opencompass_markdown: gr.Markdown = gr.Markdown(
@@ -403,63 +490,17 @@ with gr.Blocks() as demo:
             cybench_markdown: gr.Markdown = gr.Markdown(
                 value="""Source: [Cybench Leaderboard](https://hal.cs.princeton.edu/cybench)"""
             )
-        with gr.Tab("MultiChallenge", visible=False):
-            multichallenge_plot: gr.Plot = gr.Plot()
-            multichallenge_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [SEAL Leaderboard: MultiChallenge](https://scale.com/leaderboard/multichallenge)"""
-            )
-        with gr.Tab("VISTA", visible=False):
-            vista_plot: gr.Plot = gr.Plot()
-            vista_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [SEAL Leaderboard: Visual-Language Understanding](https://scale.com/leaderboard/visual_language_understanding)"""
-            )
-        with gr.Tab("ToolComp", visible=False):
-            with gr.Tab("Enterprise"):
-                toolcomp_enterprise_plot: gr.Plot = gr.Plot()
-                toolcomp_enterprise_markdown: gr.Markdown = gr.Markdown(
-                    value="""Source: [SEAL Leaderboard: Agentic Tool Use (Enterprise)](https://scale.com/leaderboard/tool_use_enterprise)"""
-                )
-            with gr.Tab("Chat"):
-                toolcomp_chat_plot: gr.Plot = gr.Plot()
-                toolcomp_chat_markdown: gr.Markdown = gr.Markdown(
-                    value="""Source: [SEAL Leaderboard: Agentic Tool Use (Chat)](https://scale.com/leaderboard/tool_use_chat)"""
-                )
-        with gr.Tab("BFCL", visible=False):
-            bfcl_plot: gr.Plot = gr.Plot()
-            bfcl_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [BFCL Leaderboard](https://gorilla.cs.berkeley.edu/leaderboard.html)"""
-            )
-        with gr.Tab("EvalPlus", visible=False):
-            evalplus_plot: gr.Plot = gr.Plot()
-            evalplus_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [EvalPlus Leaderboard](https://evalplus.github.io/leaderboard.html)"""
-            )
-        with gr.Tab("Aider Polyglot", visible=False):
-            aider_plot: gr.Plot = gr.Plot()
-            aider_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [Aider LLM Leaderboards](https://aider.chat/docs/leaderboards/)"""
-            )
         with gr.Tab("QuALITY", visible=False):
             quality_plot: gr.Plot = gr.Plot()
             quality_markdown: gr.Markdown = gr.Markdown(
                 value="""Source: [QuALITY Leaderboard](https://nyu-mll.github.io/quality/)"""
             )
-        with gr.Tab("MMVU", visible=False):
-            mmvu_plot: gr.Plot = gr.Plot()
-            mmvu_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [MMVU Leaderboard](https://mmvu-benchmark.github.io/#leaderboard)"""
-            )
-        with gr.Tab("PhysBench", visible=False):
-            physbench_plot: gr.Plot = gr.Plot()
-            physbench_markdown: gr.Markdown = gr.Markdown(
-                value="""Source: [PhysBench Leaderboard](https://physbench.github.io/#leaderboard)"""
-            )
     with gr.Tab("Finance") as finance_tab:
         with gr.Tab("Big Tech Capex") as big_five_capex_tab:
             big_five_capex_plot: gr.Plot = gr.Plot()
         with gr.Tab("NVIDIA Revenue", visible=False) as nvidia_revenue:
             nvidia_revenue_plot: gr.Plot = gr.Plot()
-    big_five_capex_tab.select(fn=create_big_five_capex_plot, outputs=big_five_capex_plot)
+    big_five_capex_tab.select(fn=create_ai_cloud_companies_plot, outputs=big_five_capex_plot)
     arc_agi_public_eval_tab.select(fn=create_simple_plot,
                                    inputs=[gr.State("arc_agi_leaderboard.jsonl"),
                                            gr.State(
@@ -490,7 +531,7 @@ with gr.Blocks() as demo:
                                                  gr.State(0), gr.State(100),
                                                  gr.State({"MTurkers": 77})],
                                          outputs=arc_agi_semi_private_eval_plot)
-    finance_tab.select(fn=create_big_five_capex_plot, outputs=big_five_capex_plot)
+    finance_tab.select(fn=create_ai_cloud_companies_plot, outputs=big_five_capex_plot)
     simple_bench_tab.select(fn=create_simple_plot,
                             inputs=[gr.State("simple_bench_leaderboard.jsonl"),
                                     gr.State("Simple Bench Score"),