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"A Review of Anthropic’s Global Workspace Paper" by Neel Nanda

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The below is a public review Anthropic asked me to write for their new global workspace paper. I recommend at least skimming their paper first.

TLDR:

  • I think this is a fantastic paper - it presents compelling evidence for some kind of "cognitive space" in models, that is used as a "working memory" for intermediate variables during a forward pass, shows that J-Lens is a useful technique for accessing this space. I believe these key claims.
  • I believe J-Lens will be a useful (but limited) tool in practice for model forensics, e.g. generating hypotheses about unusual model behaviour during alignment audits.
  • I discuss my mental models for why a cognitive space should exist, and first principles arguments for why J-Lens should work for accessing it
  • I assess the paper's evidence that this cognitive space exists, and the paper's evidence that J-Lens is practically useful.
  • We have replicated the core claims on Qwen 3.6 27B, and also share preliminary evidence of extending this work by finding abstract "interpretative meta-tokens", like Chinese characters for "what does this mean" that seem to activate and play a causal role on processing ambiguous sentences.
What claims is this paper making?

In my opinion this [...]

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Outline:

(01:27) What claims is this paper making?

[... 28 more sections]

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First published:
July 6th, 2026

Source:
https://www.lesswrong.com/posts/zFJ3ZdQwrTWE9jT5S/a-review-of-anthropic-s-global-workspace-paper

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Images from the article:

Diagram illustrating token concatenation and multi-layer perceptron fact lookup process for embedding names.
Graph showing Spearman correlation between J-lens and verbal outputs across neural network layers.
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Table showing J-lens analysis of top-10 tokens per layer across 50 layers.
Table showing J-lens token predictions across neural network layers with poetry-related terms highlighted in orange.
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