
AI systems rival doctors in new Nature studies, but one result suggests the tech won't age well
Quick Answer
Two studies in Nature reveal specialized AI systems can diagnose diseases and make treatment decisions as effectively as physicians in simulated cases, sometimes outperforming them.
Quick Take
However, both systems rely on outdated base models, raising concerns about their long-term viability.
Key Points
- AI systems matched or exceeded physician performance in disease diagnosis and treatment decisions.
- Both AI systems are based on outdated models, questioning their future effectiveness.
- The studies highlight the potential of AI in healthcare but also its limitations.
Source Excerpt
Two new studies published in Nature show that specialized AI systems diagnose diseases and make treatment decisions as well as physicians in simulated patient cases, sometimes even better. Both systems run on base models that are already outdated.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from The Decoder
See more →
An AI model programmed nonstop for 19 days on a single MirrorCode task that cost $2,600 to run
Epoch AI's MirrorCode benchmark reveals Claude Opus 4.7 as the leader with a 56% solve rate, reconstructing a 16,000-line toolkit in 14 hours. Despite this, all models tested struggle with the most complex tasks, highlighting limitations in current AI capabilities. The single task consumed $2,600 over 19 days, raising questions about cost-effectiveness in AI development.

