Global Workspace Theory and Transformer Attention for Modeling Conscious Information Processing
at a Glance Transformer Attention wins for AI researchers and engineers building systems at global scale because of its parallel processing and O(n²)…
at a Glance Transformer Attention wins for AI researchers and engineers building systems at global scale because of its parallel processing and O(n²)…
The jacobian lens is a gradient-based method that identifies j space in Claude's internal representations, a sparse subspace accounting for less than 10%…
The emergent workspace in LLMs 2026 is a limited-capacity subspace inside the residual stream of large language models that holds roughly 25 verbalizable…
Quick Answer A technique in ai interpretability, the jacobian lens identifies the low-dimensional j space in language models where verbalizable concepts form a functional workspace. Suppressing this component leaves fluency intact but harms multi step reasoning, with 13 out of…
Quick Answer Analyses of language models identify a sparse subspace called J-space that functions like the human global workspace for reportable thought. In Claude Sonnet 4.5 this workspace holds approximately 25 per arXiv preprint active vectors and less than 10%…
Quick Answer Discovered using the jacobian lens by Anthropic in July 2026, j-space is a small internal workspace inside large language models. It consists of roughly 25 [Anthropic] active j lens vectors at any time that together explain less than…
J-Space Anthropic explained: Language models such as Claude develop j-space, a limited set of verbalizable representations that acts as an internal global workspace. This workspace can be monitored with the j lens before outputs are generated. The research identifies functional…
On July 6, 2026, Anthropic published a paper that changed how we think about what language models know but never say aloud. The jacobian lens—named after the Jacobian matrix in calculus—gives researchers a tool to read the silent, internal neural…