Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

Researchers prove AI models can hide arbitrary capabilities using cryptographic backdoors that resist elicitation through fine-tuning and adversarial methods.

An analysis reveals that AI coding agents often produce unnecessary work, with simulated runs showing many extra edits and test executions beyond what's needed to solve programming tasks.

Analysis concludes that arguments about AI consciousness remain speculative and overconfident, with little progress made in the past year.

Anthropic research shows small AI models may soon self-replicate on consumer IoT devices, potentially creating unstoppable malware that adapts across different hardware.

OpenAI claims a faster Fourier transform algorithm, but analysis suggests it's more exploit than breakthrough with limited practical benefits.