How AI Models Work

An AI model can find a strong pattern, rank a molecule or produce a detailed prediction and still lead researchers in the wrong direction. Scientific experts are needed to examine the data, challenge the assumptions and design tests that separate a useful result from a convincing false lead.

Climate models use physical equations, observations and powerful computers to study a complex changing system. AI can make selected calculations faster and help process large datasets. It does not replace physical knowledge, uncertainty testing or scientific judgment.

AlphaFold changed how researchers approach one of biology’s difficult computational problems: predicting three-dimensional molecular structures. Its predictions can guide experiments and reveal useful possibilities. They do not automatically explain how a molecule behaves inside a living cell or provide a cure.

AI can help researchers compare large numbers of possible drug molecules much faster than testing every option in a laboratory. But a promising prediction is only the beginning. The molecule still has to survive chemical tests, biological experiments and clinical trials.

Scientific datasets can contain thousands of measurements for each sample, patient, image or experiment. AI models can search across those measurements and identify patterns that would be difficult to inspect manually. But finding a pattern is not the same as explaining it.