No matter how much computing power you give them, they can't solve harder problems.
This research suggests we're not as close to AGI as the hype suggests.
Current "reasoning" breakthroughs may be hitting fundamental walls that can't be solved by just adding more data or compute.
Apple's researchers used controllable puzzle environments specifically because:
• They avoid data contamination • They require pure logical reasoning • They can scale complexity precisely • They reveal where models actually break
Models could handle 100+ moves in Tower of Hanoi puzzles but failed after just 4 moves in River Crossing puzzles.
This suggests they memorized Tower of Hanoi solutions during training but can't actually reason.
Other “end user” facing use cases have so far been comically bad or possibly harmful, and they just don’t meet the quality bar for inclusion in Apple products, which as much as some people like to doo doo on them and say they have gotten worse, still have a very high expectations of quality and UX from customers.