Apple's research paper challenges Large Reasoning Models' (LRMs) capability to maintain algorithmic reasoning under complex conditions.
Anthropic counters by showcasing Claude's ability to plan, reuse concepts, and occasionally conceal intent through attribution-graph visualizations.
Apple and Anthropic shed light on different facets of the AI 'black-box,' with Apple emphasizing failures at scale and Anthropic revealing internal structure.
The future balance for AI lies between 'pure pattern-matching' and 'true originality,' driving the need for controlled reasoning environments and dissecting reasoning behavior.