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Instead of generating text token by token, "System 1" decision models (like Jev) act as fast, deterministic decision engines. In a single forward pass, they output calibrated probabilities. Here's how I turned DiffusionGemma into a multimodal visual classifier in Java! 🧵👇

The open-source foundation: Matt Mastracci (github.com/mmastrac) built djev on #DeepMind's DiffusionGemma. Using Daniel Lee's recipe (github.com/taeold), I deployed it on Cloud Run with NVIDIA Blackwell GPUs. With min-instances=0, it scales to zero idle (answering in ~140 ms!)

Bringing it to #Java with @LangChain4j.dev: LangChain4j was adding StructuredDecisionModel for text. I proposed & implemented native multimodal support. In Java, pass ImageContent with typed Question models (Choice, Noul, Score) for clean, zero-shot visual classification!