Ethan Mollick Jokes About Codex Composer Text Predictions

1. 12:16
   Latent Space

   Goodfire’s Nick Cammarata argues agentic analysis resolves familiar examples of neural polysemanticity

   Latent Space highlights Goodfire’s Nick Cammarata’s working theory that neural networks are already largely interpretable, with further agentic analysis resolving many familiar examples of polysemanticity and superposition. Cammarata argues that most neurons are legible, contrasting with roughly 2% in his 2023 OpenAI effort. The roundup also reports objections concerning weak activations, neuron simulation and neglected non-maximal activations, alongside a reminder that the paper itself is not yet available.

2. 11:34
   Ethan Mollick · X

   Ethan Mollick Reacts to @emollick’s Codex Composer Text Predictions Post

   @emollick posted: “Live the kind of life where the suggestions from Codex Composer Text Predictions are always wrong.” Ethan Mollick: I couldn't help myself. https://t.co/1D6DQqXvAC https://t.co/baQEzSDYII

3. 11:21
   Ethan Mollick · X

   Ethan Mollick says Codex Composer Text Predictions suggestions are always wrong

   Live the kind of life where the suggestions from Codex Composer Text Predictions are always wrong.

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