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A New Trick Reveals AI Models’ Inner Thoughts

Researchers cracked open Claude, GPT, and Gemini's reasoning traces—and found evidence some Chinese models may be trained on US frontier labs.

Illustration of a transparent lens revealing connected networks across layers of paper.
Exploring the next frontier of AI research.AI illustration by KeyNews
The KeyNews take

Why it matters

A new interpretability technique reveals model internals at scale, raising both technical and geopolitical questions about model lineage and training data provenance in the frontier AI race.

The key facts

5 to know
  1. New method to extract 'reasoning traces' from Claude, GPT, and Gemini

  2. Evidence suggests some Chinese AI models trained on leading US models

  3. Interpretability breakthrough enabling inspection of model internals

  4. Geopolitical implications for frontier lab competition

  5. Published August 2026

Go to the source

Wired Businesswired.com

Publisher excerpt: Researchers devised a way to extract “reasoning traces” from Claude, GPT, and Gemini. What they found, they say, indicates that some Chinese AI may be trained on leading US models.
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