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A scanning tunneling microscope probes a molecule with an ultra-fine tip and maps its relief. But the image is flat, while the molecule is three-dimensional. How do you guess a person's pose from their shadow on a wall? Scientists built a "translator from shadows to volume"—a neural network that reconstructs the 3D shape of a molecule from its imprint.

First, the network was trained on millions of synthetic images. The computer calculated how a molecule would look under the microscope if it lay this way or that. Then they showed it a real image, and the network proposed the most likely pose. For the peptide bradykinin, the error was less than two angstroms — ten times thinner than a human hair.

The method was also tested on sugars — glycans. They are more flexible than proteins, so the error is slightly larger — up to four angstroms. But even so, the computer correctly found the positions of rings and bonds. This is no longer just a pretty picture, but a working tool for chemists and biologists.

Now determining a molecule's structure takes minutes, not weeks. You can quickly check how a drug fits its target or how a mutation changes a protein's shape. The shadow on the wall has spoken.