A common fear about AI in science is that it will narrow the frontier - that models trained on existing data will herd researchers toward the familiar. This issue's stories suggest the opposite is happening.

☑️ A new analysis of nearly 250,000 protein structures shows that AlphaFold reversed a long-running decline in scientific novelty, redirecting researchers toward proteins no one had studied before.

☑️ DISCO, from Frances Arnold's lab, designed working enzymes for chemistry that no living organism has ever performed - with active sites that have no match anywhere in the known protein universe.

☑️ The OpenAI Foundation is committing over $100 million to Alzheimer's, a disease that has defeated over 100 attempts in clinical trials, using AI to map the combinatorial complexity that traditional approaches couldn't navigate.

☑️ And a new initiative is funding the datasets the field still lacks - because models have outpaced the data they need.

Far from just accelerating what scientists already do, AI is also changing what they attempt.

Let's dive in.