What if Jev spoke Arrow?

TypeSafe AI's new model Jev turns natural language and application state into typed decisions with scores and probabilities delivered as JSON, offering significant speed and cost improvements over general-purpose language models. The article explores how Jev could be integrated with Apache Arrow to create more efficient data pipelines by avoiding JSON conversions, designing Arrow schemas to represent Jev's three question types (Choice, Noul, and Score) as structured columns. This combination could enable fundamentally probabilistic workflows in applications where deterministic processes were previously assumed to be necessary.