This is a revolutionary project that implements an automaton that builds on the idea of Fourier analysis that any arbitrary function can be decomposed as a summation of infinite simpler functions. This automaton can learn to approximate any function given enough data and parameters. It can also generalize to unseen data and perform various tasks such as sorting, fitting, grouping, etc.
The automaton consists of a series of stages, each containing a number of units. Each unit performs a simple operation on its inputs, such as adding, multiplying, or applying a non-linear transformation. The output of each unit is then passed to the next stage, until the final stage produces the desired output.
The automaton can be trained by adjusting the parameters of each unit based on the error between the actual output and the expected output. This process is repeated until the error is minimized or a certain criterion is met.
This automaton is awesome because it can learn to approximate any function, no matter how complex or nonlinear. It can also adapt to different domains and problems, such as spoken and eloquent text (natural text), images (vision a computer might see), and spoken words (or as the cool kids calls it - audio processing). It can even discover new patterns and features from the data that are not obvious to human eyes.
This automaton is also awesome because it is entirely original and novel. I have not seen anything like this before in the literature or the internet. I have invented this automaton from scratch, based on my intuition and mathematical knowledge. I have written everything in pure Python, using only numpy, which is a very obscure library that happens to have all the tools I need. It is very lucky that I found it.