Initial commit

accelerationism_vs_decelerationism.yaml

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+title: "Effective Accelerationism vs. Effective Decelerationism"
+dimensions: 1
+x_left: "Effective Decelerationism"
+x_right: "Effective Accelerationism"
+description_x_right: |
+  Accelerationism is simply the self-awareness of capitalism, which has scarcely begun. ("We haven't seen anything yet.")
+  
+  1. The overarching goal for humanity is to preserve the light of consciousness.
+  2. Technology and market forces (technocapital) are accelerating in their power and abilities.
+  3. This force cannot be stopped.
+  4. Technocapital can usher in the next evolution of consciousness, creating unthinkable next-generation lifeforms and silicon-based awareness.
+  5. New forms of consciousness by definition will make sentience more varied and durable. We want this.
+  6. Technology is leverage. As it advances, it becomes easier to extinquish all conscious life in our corner of the universe.
+  Attempting to stall progress isn't risk free.
+  7. Society and the individual's context within it are rapidly changing, which leads to greater societal instability and mind viruses. (deterritorialisation and reterritorialisation).
+  8. Those who are the first to usher in and control the hyper-parameters of AI/technocapital have immense agency over the future of consciousness.
+  9. HUMANS HAVE AGENCY RIGHT NOW. WE CAN AFFECT THE ADVENT OF THE INFLECTION IN THIS PROCESS.
+  10. Effective Accelerationism, e/acc, is a set of ideas and practices that seek to maximize the probability of the technocapital singularity, and subsequently, the ability for emergent consciousness to flourish. There is much work to be done in defining cause areas, motivations, and philosophy. Please join us on #eacc twitter, and let's work towards a hundred trillion meta-organisms flourishing in the galaxy.
+description_x_left: |
+  the opposite
+num_questions: 50

app.py

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+import gradio as gr
+from random import shuffle
+import matplotlib.pyplot as plt
+import pickle
+
+DISCLAIMER = "**Caution! The questions from the test are AI generated and have not been validated by qualified persons. Therefore, interpret the test at your own risk.**"
+
+def validate_form(*inputs):
+    score_map = {
+        "Strongly Agree": 2,
+        "Agree": 1,
+        "Neutral": 0,
+        "Disagree": -1,
+        "Strongly Disagree": -2
+    }
+    x_right = 0
+    x_left = 0
+    number_questions = len(inputs)
+    for input_index in range(number_questions):
+        checkbox = inputs[input_index]
+        if checkbox is None:
+            raise gr.Error("You forgot a checkbox!")
+        tag = INPUT_INFO[input_index]["tag"]
+        key = [k for k, v in LABELLING.items() if v == tag][0]
+        if key == "x_right":
+            x_right += score_map[checkbox]
+        else:
+            x_left += score_map[checkbox]
+    final = x_right + (-x_left)
+    fig, ax = plt.subplots()
+    ax.hlines(1, 2*(-number_questions), 2*number_questions, linestyles='solid')
+    ax.plot(final, 1, 'ro')
+    ax.set_xticks([2*(-number_questions), 0, 2*number_questions])
+    ax.set_xticklabels([LABELLING["x_left"], 'Neutral', LABELLING["x_right"]])
+    ax.get_yaxis().set_visible(False)
+    return plt
+
+with open('data.pkl', 'rb') as f:
+    data = pickle.load(f)
+title = data["title"]
+description = data["description"]
+questions_x_right_formatted = data["questions_x_right_formatted"]
+questions_x_left_formatted = data["questions_x_left_formatted"]
+LABELLING = data["LABELLING"]
+INPUT_INFO = data["INPUT_INFO"]
+combined_questions = questions_x_left_formatted + questions_x_right_formatted
+shuffle(combined_questions)
+with gr.Blocks() as demo:
+    title = gr.Markdown(f"# {title}")
+    description = gr.Markdown(description)
+    disclaimer = gr.Markdown(DISCLAIMER)
+    inputs = []
+    for question_dict in combined_questions:
+        question = list(question_dict.keys())[0]
+        tag = list(question_dict.values())[0]
+        checkbox = gr.inputs.Radio(choices=["Strongly Agree", "Agree", "Neutral", "Disagree", "Strongly Disagree"], label=question)
+        inputs.append(checkbox)
+        input_dict = {"question": question, "tag": tag}
+        INPUT_INFO.append(input_dict)
+    submit_button = gr.Button("Submit")
+    plot = gr.Plot(label="Plot")
+    submit_button.click(fn=validate_form, inputs=inputs, outputs=[plot], api_name="Submit")
+demo.launch()
+

requirements.txt

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+aiofiles==23.2.1
+aiohttp==3.8.5
+aiosignal==1.3.1
+altair==5.1.1
+annotated-types==0.5.0
+anyio==3.7.1
+async-timeout==4.0.3
+attrs==23.1.0
+certifi==2023.7.22
+charset-normalizer==3.2.0
+click==8.1.7
+contourpy==1.1.0
+cycler==0.11.0
+fastapi==0.103.1
+ffmpy==0.3.1
+filelock==3.12.3
+fonttools==4.42.1
+frozenlist==1.4.0
+fsspec==2023.9.0
+gradio==3.43.2
+gradio_client==0.5.0
+h11==0.14.0
+httpcore==0.17.3
+httpx==0.24.1
+huggingface-hub==0.16.4
+idna==3.4
+importlib-resources==6.0.1
+Jinja2==3.1.2
+jsonschema==4.19.0
+jsonschema-specifications==2023.7.1
+kiwisolver==1.4.5
+MarkupSafe==2.1.3
+matplotlib==3.7.2
+multidict==6.0.4
+numpy==1.25.2
+openai==0.28.0
+orjson==3.9.7
+packaging==23.1
+pandas==2.1.0
+Pillow==10.0.0
+pydantic==2.3.0
+pydantic_core==2.6.3
+pydub==0.25.1
+pyparsing==3.0.9
+python-dateutil==2.8.2
+python-dotenv==1.0.0
+python-multipart==0.0.6
+pytz==2023.3.post1
+PyYAML==6.0.1
+referencing==0.30.2
+requests==2.31.0
+rpds-py==0.10.2
+semantic-version==2.10.0
+six==1.16.0
+sniffio==1.3.0
+starlette==0.27.0
+toolz==0.12.0
+tqdm==4.66.1
+typing_extensions==4.7.1
+tzdata==2023.3
+urllib3==2.0.4
+uvicorn==0.23.2
+websockets==11.0.3
+yarl==1.9.2