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In chemical manufacturing, a single breakthrough route to a molecule can be worth hundreds of millions of dollars. Deep neural networks hold tremendous promise for retrosynthesis—the key strategic phase of designing a new synthesis—by augmenting and accelerating human intuition with creative ideas.

We just hit a milestone that made us stop and reflect. Three years ago, we made an audacious bet: that you can treat automated chemistry as a learning problem — and solve it by scaling chemical data generation.