ADSM: limits of model capabilities
Models operate inside the transformer architecture: vector width defines how detailed the representations are, depth sets the level of abstraction, and the number of connections fixes the computational load. Each token is produced by a full pass through the network. The context window is the shared space for input and output, so growing the output reduces reproducibility. Efficient work relies on narrowing the context, feeding homogeneous inputs, and keeping a strict one-shot mode. Minimizing the creative component keeps results steady and the model within the intended frame. The full article in Russian is published on Habr.