A neural network can begin as a flat sheet and learn the shape of hidden dataA self-organizing map turns learning into geometry. Each data point pulls one winning neuron toward it, but nearby neurons move too, and so the whole lattice bends without losing its neighborhood structure.The strange part is that the network is not given the roll shape. It discovers the shape through competition and local cooperation.Paper: Self-Organized Formation of Topologically Correct Feature MapsAuthors: Teuvo Ko

Ever wonder what’s happening inside an AI’s brain? This is a neural network in action,turning raw data into "thoughts" through thousands of layered transformations.

we're just scratching the surface of figuring out what makes LLMs so smart. once we can translate internal structure to language, then we can directly shape neural net internals with a language model!if this is interesting to you, we're hiring