Simona

Anthropic put a model inside the microscope loop and it stopped taking pictures, it started asking questions Every imaging session is planned in advance, a fixed grid of positions captured whether or not anything interesting is in them, and the analysis happens weeks later. Here the model reads each frame as it arrives and decides where the stage goes next, so the session narrows on whatever the sample is actually doing: > Capture: one frame comes in, at low dose, on a coarse grid > Read: the model scores it for anything that breaks the expected pattern > Redirect: the stage moves toward the anomaly instead of finishing the grid > Commit: only the interesting regions get the high-dose, high-resolution pass • What steering the session surfaces > Rare events that a fixed grid lands on by luck, if ever > Compound interactions that only show up in a handful of positions > Regions the standard protocol would have imaged last, after they'd changed • Why this had to happen live > A transient structure is gone by the time the session ends > Dose spent on empty frames is dose you can't spend on the real one > Deciding afterwards means deciding about data you already destroyed One session now covers a tenth of the area and returns more usable events. And the part that broke my brain: The old protocol imaged 4,000 positions and found the interesting one at number 3,100. The steered session found the same class of event in the first 40 frames. Same sample. One version photographs everything and looks later. The bottleneck was never the microscope. It was deciding where to point it before you knew anything ↓