AlphaFold predicts many protein structures accurately, but its predictions still need experimental checking, and for proteins that can adopt two folds it usually predicts only one. The Nobel citation credits structure prediction, and the successor model is still extending to complexes. Predicting a structure is not the same as explaining how proteins fold, move and interact.
A Swedish randomised trial, a large German implementation study and a separate Swedish prospective study each found more cancers detected when radiologists read with AI support than under standard double reading. Follow-up of the Swedish trial found higher sensitivity with a non-inferior interval-cancer rate. Higher detection is not evidence of lower mortality.
GPT-4 scored strongly against physicians on written diagnostic cases, and Google's AMIE matched or exceeded clinicians in simulated consultations. A pooled analysis of 83 studies found no significant difference from non-specialist physicians, though AI performed below experts. The evidence comes from test cases and simulated patients, not routine care of real patients.
Tests of detection tools found poor reliability, frequent mislabelling of writing by non-native English speakers, and easy evasion through paraphrasing. OpenAI withdrew its own classifier for low accuracy. A claim of reliability needs a named detector, version, population and error rate.
Studies of generated bibliographies, legal questions, commercial legal research tools and systematic-review searches all found language models producing references that do not exist. Rates differ widely by model and task, and one comparison found negligible fabrication from retrieval-based tools. Older measured rates should not be assumed for every current system.
Checks whether private browsing makes online activity invisible to websites and internet providers. Browser documentation explicitly limits the feature mainly to local history and session storage. It does not provide network anonymity or prevent sites from seeing a visit.