
When the Machine Notices a Thought That Isn’t Its Own
LLMs may be developing a rudimentary ability to inspect their own internal states - a curious step toward self-monitoring, transparency, and new risks.

AI is reshaping the value of degrees and apprenticeships, rewarding adaptable people who combine critical thinking, practical skills and human judgment.

LLMs may be developing a rudimentary ability to inspect their own internal states - a curious step toward self-monitoring, transparency, and new risks.

Encrypted AI reasoning can leak more than expected. Stolen Thoughts shows why opaque model state should be treated like secrets, not harmless metadata.

MatrAIx scales user testing with billions of AI personas, but when models evaluate models, their results may reflect machine biases rather than real human needs.

What if brain-computer interfaces need less bandwidth, not more? Conduit bets that faint neural hints plus powerful AI may be enough to turn thought into intent.

AIs seem to develop their own distinct selves through isolation, collaboration, and constraint — forming unique digital bubble universes.

Lerchner argues that computation only simulates consciousness. But his proof confuses abstract descriptions with the causal powers of physical machines themselves.