Start with the paper
We link the primary study or proof, not a press release repeating it. Reviews and reporting may help us find context, but the original work carries the claim.
About AI Solved X
AI Solved X covers major AI advances in medicine, science, energy, computing, and daily work: what became possible, what the evidence supports, and how it could change everyday life. Routine tutorials and old features do not qualify as breakthroughs.
Who makes the briefs
AI Solved X is an AI-assisted research publication. Our editorial byline identifies the publication, not the researchers who conducted the original study. Each brief links to that study so you can inspect the evidence for yourself.
“AI Solved X” is the publication’s name. Each headline must match the demonstrated advance and its scope. Partial progress does not mean an entire problem is solved. Mathematics briefs distinguish proofs from computational checks and conjectures.
We explain published research; we do not claim to have independently repeated the experiments. Editorial illustrations are not evidence from the studies.
Editorial standards
Every story must survive the same six checks before it is ready to publish.
We link the primary study or proof, not a press release repeating it. Reviews and reporting may help us find context, but the original work carries the claim.
The title explains the possible change in a person's life. The body immediately shows the actual intervention, study design, and result behind it.
A model tested in a laboratory is not a product. Better detection is not automatically better health. We state what the study did not establish.
Randomized real-world evidence earns a stronger label than a retrospective dataset, simulation, laboratory benchmark, or proof that is still a preprint.
AI helps find research, prepare drafts, and check claims against sources. Routine, low-risk briefs may publish automatically after a separate verification pass. High-stakes claims, ambiguous findings, and exceptions require human editorial review.
Material corrections belong on the article with a date and explanation. Quietly changing the claim is not enough.
Evidence labels
Usually a randomized or prospective study with a meaningful human or operational outcome. Strong does not mean universal or risk-free.
Often a preprint, new proof, laboratory test, retrospective analysis, model benchmark, or early field deployment that still needs broader validation.