Enigma Spectre

Thomas’ Cyclically Symmetric Chaotic Attractor ẋ = sin(y) - bx, ẏ = sin(z) - by, ż = sin(x) - bz Used in chaos theory, turbulence & signal systems. Built with Three.js, GLSL shaders, GPU instancing & cinematic post-processing. Best with sound on.

i made a state-of-the-art-for-1980 speech synth just for laughs

Good morning, sentient meat.

Everybody who thinks ai is conscious has to do a mandatory from scratch transformer implementation. There are only floats and multiplications.

A Lens That Takes Derivatives US Patent Basis: US8610839B2 - Optical Processing System for Computing Derivatives. In a 4f Optical Processor, the first lens takes the incoming field and forms its Fourier spectrum. At that middle plane, a tiny optical mask multiplies the spectrum by iξ. This is the derivative operator written in Fourier language u(x) -> U(ξ) -> iξU(ξ) -> ∂u/∂x Then the second lens brings the field back to the real space. What comes out is no longer just a focused beam. It is the spatial derivative of the input field, computed by light as it propagates. So, this is the serious promise of optical computing. A physical optical train can perform operations that usually live inside numerical code: differentiation, filtering, convolution, edge detection, correlation, and many other linear transforms.

When a Lens Acts Like an Analog Computer A lens physically performs a mathematical operation on light without any digital steps. If you put an optical field just before a thin lens and look at the field in its back focal plane, the transverse pattern there is, to a very good approximation, the Fourier transform of the input field. That means the lens is not just bending rays. It is converting spatial structure into spatial-frequency structure. Fine detail, periodicity, orientation, separation of features, all of that gets reorganized in a precise way.