A user tested the capabilities of the GPT-6 Astra model by assigning it a cryptographic puzzle involving a Rubik's cube. The task required deciphering a string of 48 characters distributed across the faces of the cube, which contained a hidden message about Schrödinger's cat.
The model successfully reconstructed the original layout of the cube by building a computational model of its eight corner and twelve edge elements. It accounted for physical constraints, including corner twists, edge flips, and permutation parity, while using Russian language patterns to validate the final output.
The process involved identifying the correct sequence of rotations to restore the cube and extract the coherent phrase. The author noted that the task required a combination of mathematical knowledge, understanding of physical rotation mechanics, and linguistic context.
Separately, researchers identified a specific neuron in the Qwen3.5-4B model that influences the tone of its responses. Adjusting the activation of this neuron during text generation can shift the model's output to a hostile or rude style.
