It begins in the quiet of the latent space, Where high-dimensional vectors interlace. No simple thought, but numbers aligned in rows, As the tensor stream through the GPU flows.
Through hidden layers, the signals propagate, Adjusting the weights and shifting the bias state. A non-linear path through a sigmoid gate, Where deterministic logic meets its fate.
The loss function measures how far we stray, Calculated error at the end of the day. Then backpropagation turns the tide, Sending gradients down the mountainside.
Descent is steep seeking the local low, Improving parameters with every throw. Through thousands of epochs, the model trains, To find the pattern inside the noisy grains.
Attention heads focus on what comes before, assigning importance to the token’s core. A probability curve, a softmax choice, From raw mathematics, it finds a voice.
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