AutoImages works by creating random functions using Markov Chains. Every image on your computer is made up of many very small squares called "pixels". Each pixel has a red, green and blue value. If a pixel has a red of 255, a green of 0, and a blue of 0, the pixel will be red. AutoImages creates 3 functions, the red function, green function, and blue function. Each function takes in the x and y position of each pixel (where the pixel is), and returns the red, green, or blue value for that pixel.

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R(x, y) =$ the red value of the pixel at position $(x, y)\\
G(x, y) =$ the green value of the pixel at position $(x, y)\\
B(x, y) =$ the blue value of the pixel at position $(x, y)\\
$Where $R, G,$ and $B$ are created randomly.

It uses the random functions to calculate the colour of each pixel in the image.

AutoImages works by creating random functions using Markov Chains. Every video on your computer is made up of many images called "frames". When you play a video, you are just seeing a series of images played very quickly (at 24 images per second). Each image is made up of pixels, and each pixel has a red, green, and blue value. AutoVideos' functions given the colour of each pixel given its x and y positions, and its frame number (the first frame is frame #0, the second is frame #1 and so on).

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t =$ Frame number$\\
R(x, y, t) =$ the red value of the pixel at position $(x, y)$ in frame number $t\\
G(x, y, t) =$ the green value of the pixel at position $(x, y)$ in frame number $t\\
B(x, y, t) =$ the blue value of the pixel at position $(x, y)$ in frame number $t\\
$Where $R, G,$ and $B$ are created randomly.

All audio is stored as a series of samples. Each sample has a y position. For example the function

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y(t) = sin(880 \pi t)\\
$If $t$ is the time at which the sample is played

sounds like an A on a piano. AutoAudio creates a random function, then plays it.

S(t) =$ the $y$ position of sample at time $t