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AI explanation

^{Show image generation prompt} Model: dalle-3
Prompt: Generate an image of a cybernetic art-style representation. It should depict a tranquil living room scene where several individuals are gathered around a large window. They are captivated by the sight of raindrops cascading against the glass outside. Outside, an assortment of vibrant, exotic birds seek refuge under a tree, attempting to evade the downpour. Additionally, in the living room, there is a tablet displaying a list of YouTube video titles from the channel Technology Connections, containing subtle and less conspicuous phrases such as "Understanding Old PC Hardware" and "Classic TV Technology Explained." The depiction should include only scenes, people, and objects, it should not include text or speech bubbles.

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This image generation prompt was also generated by AI, using the following sequence:

Model: gpt-3.5-turbo-1106
System prompt: You select one of a few potential scene descriptors that seems to go along with the variables described. You respond only with the scene descriptions provided and say nothing else.
User prompt: Here are two variables: How provocative Technology Connections YouTube video titles are and Google searches for 'where do birds go when it rains'. Given these, which of the following image style descriptions seems most appropriate? Pick the one that seems to be related to one of the variables at hand. Please respond with only one of the following potential descriptions: Symbolism Minimalism Vaporwave Voxel art Cybernetic art
ChatGPT: Cybernetic art

Model: gpt-3.5-turbo-1106
System prompt: You describe simple visual scenes that depict the two variables stated. You combine both variables into one scene.
User prompt: Please describe a visual scene that prominently depicts both How provocative Technology Connections YouTube video titles are and Google searches for 'where do birds go when it rains', in the following situation: As people became more interested in bird behavior during inclement weather, they realized that the real drama was happening outside their windows. Faced with the choice of watching a video about birds or witnessing the avian antics firsthand, viewers opted for the live-action show. So, as the fascination with rainy day bird whereabouts grew, the allure of technology-related content dwindled, ultimately leading to less provocative titles for Technology Connections YouTube videos.. Keep the description simple.
ChatGPT: A hushed living room, where several people are huddled around a large window, transfixed by the sight of raindrops pattering against the glass outside. Outside, a group of colorful birds takes refuge under a tree, seeking shelter from the downpour. The screen of a tablet in the room displays a list of YouTube video titles from Technology Connections, with subdued and less eye-catching phrases like "Understanding Old PC Hardware" and "Classic TV Technology Explained."

Model: gpt-3.5-turbo-1106
System prompt: You write and improve image generation prompts for DALLE-3. You maintain the same subjects, but enhance the visuals.
User prompt: Please respond with an image generation prompt that would be likely to create an interesting visual using DALLE-3, using the following style: [ Cybernetic art ] and depicting this scene: A hushed living room, where several people are huddled around a large window, transfixed by the sight of raindrops pattering against the glass outside. Outside, a group of colorful birds takes refuge under a tree, seeking shelter from the downpour. The screen of a tablet in the room displays a list of YouTube video titles from Technology Connections, with subdued and less eye-catching phrases like "Understanding Old PC Hardware" and "Classic TV Technology Explained." Keep the visual depiction simple. Do not include any words or speech bubbles.
ChatGPT: Generate an image of a cybernetic art-style representation. It should depict a tranquil living room scene where several individuals are gathered around a large window. They are captivated by the sight of raindrops cascading against the glass outside. Outside, an assortment of vibrant, exotic birds seek refuge under a tree, attempting to evade the downpour. Additionally, in the living room, there is a tablet displaying a list of YouTube video titles from the channel Technology Connections, containing subtle and less conspicuous phrases such as "Understanding Old PC Hardware" and "Classic TV Technology Explained."

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*Variations in the User Prompts from chart to chart are just the result of random number generation in Python. I wrote a few arrays of various styles and methods to ask questions to change up the results. Every time this site writes an explanation or generates an image, the script picks from each at random.

I sequence the requests into multiple prompts because I find GPT 3.5 to perform much better with short, well-managed contexts. Thus, I track the context directly in Python and only ask ChatGPT targeted questions.

AI academic paper

The Provocative Power of Puzzling Ponderings: The Connection Between Technology Tidbits and Tempting Twitterings The Journal of Whimsical Cyber Wonders Jan 2024 Reminder: This paper is AI-generated. Not real!

Problem variable:	Which variable has a problem? How provocative Technology Connections YouTube video titles are Google searches for 'where do birds go when it rains' Neither / both
Issue:	What is the issue? The data is incorrect The chart isn't displaying properly There is a typo The source link is incorrect A calculation is wrong Something else
Additional details: Optional
Confirm you are a human:

Data details

Why this works

1. Data dredging: I have 25,237 variables in my database. I compare all these variables against each other to find ones that randomly match up. That's 636,906,169 correlation calculations! This is called “data dredging.” Instead of starting with a hypothesis and testing it, I instead abused the data to see what correlations shake out. It’s a dangerous way to go about analysis, because any sufficiently large dataset will yield strong correlations completely at random.
2. Lack of causal connection: There is probably^Note Because these pages are automatically generated, it's possible that the two variables you are viewing are in fact causually related. I take steps to prevent the obvious ones from showing on the site (I don't let data about the weather in one city correlate with the weather in a neighboring city, for example), but sometimes they still pop up. If they are related, cool! You found a loophole.
   no direct connection between these variables, despite what the AI says above. This is exacerbated by the fact that I used "Years" as the base variable. Lots of things happen in a year that are not related to each other! Most studies would use something like "one person" in stead of "one year" to be the "thing" studied.
3. Observations not independent: For many variables, sequential years are not independent of each other. If a population of people is continuously doing something every day, there is no reason to think they would suddenly change how they are doing that thing on January 1. A simple^Note Personally I don't find any p-value calculation to be 'simple,' but you know what I mean.
   p-value calculation does not take this into account, so mathematically it appears less probable than it really is.
4. Very low n: There are not many data points included in this analysis. Even if the p-value is high, we should be suspicious of using so few datapoints in a correlation.

Try it yourself

# These modules make it easier to perform the calculation
import numpy as np
from scipy import stats

# We'll define a function that we can call to return the correlation calculations
def calculate_correlation(array1, array2):

    # Calculate Pearson correlation coefficient and p-value
    correlation, p_value = stats.pearsonr(array1, array2)

    # Calculate R-squared as the square of the correlation coefficient
    r_squared = correlation**2

    return correlation, r_squared, p_value

# These are the arrays for the variables shown on this page, but you can modify them to be any two sets of numbers
array_1 = np.array([4,3.2,3.1667,3.1316,3.25,3.3571,3.2083,3.2632,3.2,])
array_2 = np.array([3,2.08333,1.75,1.5,1.63636,1.91667,1.75,1.72727,1.88889,])
array_1_name = "How provocative Technology Connections YouTube video titles are"
array_2_name = "Google searches for 'where do birds go when it rains'"

# Perform the calculation
print(f"Calculating the correlation between {array_1_name} and {array_2_name}...")
correlation, r_squared, p_value = calculate_correlation(array_1, array_2)

# Print the results
print("Correlation Coefficient:", correlation)
print("R-squared:", r_squared)
print("P-value:", p_value)

Reuseable content

• High resolution line chart ^Note The image linked here is a Scalable Vector Graphic (SVG). It is the highest resolution that is possible to achieve. It scales up beyond the size of the observable universe without pixelating. You do not need to email me asking if I have a higher resolution image. I do not. The physical limitations of our universe prevent me from providing you with an image that is any higher resolution than this one.
  
  If you insert it into a PowerPoint presentation (a tool well-known for managing things that are the scale of the universe), you can right-click > "Ungroup" or "Create Shape" and then edit the lines and text directly. You can also change the colors this way.
  
  Alternatively you can use a tool like Inkscape.
  
• High resolution line chart, optimized for mobile
• Alternative high resolution line chart
• Scatterplot
• Portable line chart (png)
• Portable line chart (png), optimized for mobile
• Line chart for only How provocative Technology Connections YouTube video titles are
• Line chart for only Google searches for 'where do birds go when it rains'
• AI-generated correlation image
• The spurious research paper: The Provocative Power of Puzzling Ponderings: The Connection Between Technology Tidbits and Tempting Twitterings